This PDF file contains the front matter associated with SPIE Proceedings Volume 12458 including the Title Page, Copyright information, Table of Contents, and Conference Committee Page.

Nitrogen is an important nutrient element that affects crop yields. The establishment of a highly applicable and stable leaf nitrogen content hyperspectral inversion model has significant significance for the development of precision agriculture. Based on the canopy spectrum and leaf nitrogen content data of the whole growth period of different nitrogen application levels, the changes of leaf nitrogen content and relative fluorescence intensity with nitrogen concentration gradient were studied, and the inversion was constructed using relative fluorescence intensity. The estimation model of leaf nitrogen content and comparison with three traditional vegetation index models (NDVI, NDRE, NDDA).The results showed that the relative fluorescence intensity and leaf nitrogen content both increased with the increase of nitrogen concentration. When the nitrogen concentration reached N3, the changes of the two were no longer obvious. Compared with the four vegetation indices, the fitting effect of relative fluorescence intensity and leaf nitrogen content is the best, R² is 0.60. The leaf nitrogen content inversion model established with the relative fluorescence intensity as a variable has the highest simulation accuracy, with R² of 0.74 and root mean square error (RMSE) of 0.24%. Solar-induced chlorophyll fluorescence provides a new idea for monitoring crop nitrogen nutrition status.

In this study, 48 rat models were established and randomly divided into experimental group (n=36) and control group (n=12). The experimental group was further divided into low-dose group, middle-dose group and high-dose group (n=12/group). the levels of transforming growth factor (TGF-β) and vascular endothelial growth factor(VEGF) were detected by enzyme-linked immunosorbent assay (ELISA) at 6 weeks,12 weeks and 18 weeks, respectively, which proved that Centella asiatica can inhibit renal tissue cytokines and extracellular matrix (ECM) produced. Compared with the control group, the level of TGF-β and VEGF in the kidney tissue of the rats in the model group was significantly increased. Compared with the model group, the level of TGF-β and VEGF in the kidney tissue of the rats in the Centella asiatica group was significantly decreased. It provides a theoretical basis for the effect of Centella asiatica on inhibiting renal fibrosis.

The ideal conditions of aluminium chloride colorimetric test affecting detection of total flavonoids from daylily extract have been established using rutin as a reference substance. Effects of AlCl₃ concentration, dosage, reaction time, and temperature on the color reaction of total flavonoids with AlCl₃ have been systematically investigated. The results indicated the optimal reaction conditions are seen as the following: adding 6 ml 3%AlCl₃ solution and reacting for 20min at 30℃ water bath temperature. Under these conditions, the regression equation between the absorbance value and the standard solution of rutin in the range of 0.0043~0.0258 mg/ml was y=25.442x-0.0097, R² =0.9997. The average recovery of the method was 100.1%, and the relative standard deviations (RSD) of stability, precision, and recovery were 0.29%, 0.08%, and 1.70%, respectively. The method is simple, rapid, and accurate, and can be used to determine total flavonoids in the daylily.

Gingivitis is a kind of oral disease caused by local inflammation. The periodontal diseases with the highest clinical incidence in adults are chronic gingivitis and periodontitis. However, most of the antibiotics used in clinical treatment of periodontal disease are those that produce bacterial resistance and interfere with the ecological balance of oral flora. Research shows that honeysuckle, forsythia, coptis and other heat-clearing and detoxifying traditional Chinese medicine can assist periodontal basic treatment has a good effect on periodontitis and can be applied for a long time. In order to study the anti-inflammatory effects of common Chinese medicines on gingivitis, 27 kinds of Chinese medicines were selected and extracted by enzymolysis and boiling method. The antibacterial effects on bacteria and fungi were detected by the AGAR plate Oxford cup method. The best antibacterial effects of rhubarb, honeysuckle, coptis chinensis, galla chinensis, liquorice, forsythia, and clove were screened, and their inhibitory effects on inflammatory factors were further detected by human gingival epithelial cells. The results showed that rhubarb, honeysuckle, coptis chinensis, galla chinensis, glycyrrhiza, forsythia suspensa, and clove could inhibit inflammatory factors.

Photoswitches are a group of molecules which can modulate biochemical features via isomerisation. Azobenzene is a prevalent structure used in photoswitches. The key feature of azobenzene is the light-stimulated interconversion between cis- and trans- forms, with diverse activity in its two forms. Owing to the various synthetic methods of azobenzene derivates and their photoswitchable features, azobenzene-based photoswitches have been promising elements in the field of life science, both for photopharmacological drugs and research tools. As photopharmacological drugs, they can interact with the traditional targets (ion channels, transporters, etc.) and be introduced as novel elements in some new technology (Proteolysis Targeting Chimeras). As research tools, they are used to regulate the conformation and activity of some biomolecules such as proteins and peptides via structural restrictions or target protein degradation. Several barriers remain, however, especially regarding these molecules’ use in vivo and clinic. This paper aims to integrate properties, mechanisms, synthetic methods, and applications of azobenzene-based photoswitches, meanwhile, providing some challenges in this field.

Capacitive Micromachined Ultrasonic Transducer (CMUT) is a type of ultrasonic transducer that can be applied in many fields like chemical and mechanical sensing, physical imaging, and bio-imaging. Sacrificial layer release is one of the fabrication methods and cavity releasing is the key part of this method. The stress of the sacrificial material is one of the causes making membranes break in this procedure. The previous studies had a phospho-silicide-glass (PSG) layer deposited between polysilicon sacrificial layer and silicon nitride membrane with LPCVD partially solved the problem. However, its processing temperature is relatively high, which makes it not compatible with CMOS integrated circuits (ICs). This work fabricated CMUTs in the sacrificial layer release process, with polysilicon as the main sacrificial layer. Utilizing chemical reaction of polysilicon in ashing process, a thin oxide was formed between the sacrificial layer and membrane while removing the remaining photoresist with ashing. The result showed that it could also help produce large membranes with a lower processing temperature, which can be more compatible with CMOS ICs. After fabrication, the impedance of an element with 100 μm diameter cells was measured to be several hundred ohms in air with 30 V bias voltage and the resonance frequency was 4.7 MHz.

In this research, microcapsule with different amount of yak butter (YB) was prepared by spray drying method. The in vitro digested behavior of the microcapsules as affected by pancreatic enzyme concentration in a pancreatin/bile salts-induced intestinal model was then investigated in terms of YB release, particle size distribution, zeta potential and microstructure. The results suggested that pancreatic enzyme concentration had significant impacts on the digestion behavior of microcapsules, especially for the low YB added samples. The hydrolysis of pancreatin, together with emulsification of bile salt and its positive effect for pancreatin hydrolysis all occurred during the incubation and affected the digested behavior in the end. This research would provide valuable information for designing and digestion of YB microcapsule.

To have a more detailed understanding of the structural characteristics, information transmission and other aspects of an organism, it can be started with the three most basic levels of cells, molecules and tissues. Cells are the most basic unit that constitutes an organism. Their structure determines its function. Observing the structure of cells is of great help to understand the function of an organism. Every strange biological phenomenon is the result of intermolecular interaction. Studying the existence significance of each molecule in a biological process can more thoroughly understand the details of the biological process. Tissue is a structure composed of a series of cells and biological macromolecules. The study of tissues can directly reflect the principle of the operation of birth objects. With its high resolution, AFM is widely used in these three levels of research. This article will introduce the screening of cancer cells by AFM at the cell level, the determination of protein-DNA/RNA interaction properties in molecular interactions and the characterization of ECM in lung tissue at the tissue level.

Melanoma is a type of skin cancer that has a substantial rate of morbidity and mortality and is a worldwide problem. Phototherapy and chemotherapy are the most popular therapies for it today. Phototherapy (PT) is a medical treatment in which natural or artificial light is used to improve a health condition. Chemotherapy is a cancer treatment in which the patient is given harmful medications to stop the cancer cells from growing. Though both therapies show efficiency towards cancer, they also display side effects. Since phototherapy needs directly light to lesion site, this therapy would pale its usefulness against disseminated tumors like liver cancer. Recently nanomaterials are popular among target drug research, this is because nano-drug delivery systems that encapsulate or adsorb pharmaceuticals on the surfaces of natural or synthetic polymer materials have the advantages of decreasing adverse drug reactions, controlling drug release rates, and targeting tumor locations. Consequently, using Chemo-photothermal therapy combination would significantly reduce the risk of side effects. This article talks about a new nanostructure of target drug: Melanoma cell membrane encapsulated with Prussian blue and paclitaxel. Prussian blue (PB) has been employed as a photothermal conversion reagent to produce heat to cause localized tumor destruction and paclitaxel is usually adopted in chemotherapy.

Wearing masks has been generally recommended to reduce the spreading of COVID-19. However, little is known about its effects on metabolic VOC changes in human body. To explore how the duration of wearing masks influences VOC metabolism in the human body, the essay used a self-developed electronic nose to analyse exhaled breath samples from 10 healthy individuals in this study. Firstly, polytetrafluoroethylene sampling bags are used to collect breath samples after volunteers wearing masks for 1h, 2h, 3h, 4h, and 5h. Secondly, data pre-processing, including baseline calibration and normalization are carried out. Thirdly, the study used LDA for dimensionality reduction on the original data to extract 4 features. Fourthly, differences in the length of time of wearing masks are analysed. Then, 4 algorithms were applied for cluster analysis based on extracted features. Moreover, 3 supervised classification algorithms were used to recognize the duration of wearing masks. Finally, multi-dimensional linear regression is used to study the possibility of predicting the duration of wearing masks based on breath signals acquired through electronic noses. As a result, the first feature extracted by LDA significantly differs from each other in the duration of wearing masks (p<0.05). Cluster analysis results show that the optimal internal parameters Adjusted Rand Index, Adjusted Mutual Information, Homogeneity and V-measure reach 80.2%, 81.5%, 83.5% and 83.7% respectively. Using 5-fold cross-validation on the K nearest neighbour classification model, the best accuracy of recognizing durations of wearing a mask reaches 88%. R-square of multi-dimensional linear regression reaches 92.5%, which shows excellent fitting performance. It can be concluded that the VOC metabolism of the human may change with the duration of wearing masks. Further, “breath prints” obtained by electronic nose may have the potential to predict the effective time and even the quality of masks.

Objective: To systematically evaluate the effectiveness and safety of propolis preparation in the treatment of aphthous ulcers in order to provide evidence-based references for its clinical treatment. Methods: Databases, such as CNKI, VIP, Wanfang, CBM, PubMed, EMbase, Cochrane Library, etc., were searched to collect the randomized controlled trials (RCT) on the propolis preparation (the treatment group) with the conventional treatments (the control group) in the treatment of aphthous ulcers. After the data of clinical studies that met the inclusion criteria were extracted by two researchers, the Cochrane risk-of-bias tool was used to evaluate the methodology quality, and RevMan 5.4 was used for Meta-analysis. Results: A total of 23 studies were included, involving 2467 participants with 1356 in the treatment group and 1111 in the control group. The overall quality of the RCTs was relatively low. Meta-analysis showed that propolis preparation for aphthous ulcers, compared with conventional Western medicines could improve the total efficacy rate (RR= 1.40, 95%CI[1.33, 1.46], P<0.00001), no incidence of adverse reactions. Conclusion: Propolis preparation has demonstrated promising therapeutic efficiency and safety in treatment of aphthous ulcers.

Currently, the therapeutic tools and therapeutic effects of melanoma are very limited, therefore, this paper designed a liposome encapsulated with indocyanine green and vincristine, modified by transferrin and polyethylene glycol, with the aim of improving new ideas for tumor treatment. This paper attempted to prepare nanoparticles by thin film evaporation ultrasonic dispersion method, and experiments were conducted on the morphology, particle size, zeta potential, drug loading rate, encapsulation rate, photothermal effect, drug in vitro release, cellular uptake and cytotoxicity of the prepared nanoparticles. The experimental results verified the good performance of the nanoparticles designed in this paper for the combined treatment of melanoma.

A novel method for treating melanoma which is a fatal skin cancer is proposed in this article. By combining chemotherapy and photodynamic therapy (PDT), it provides us a more effective and efficient way for the treatment of melanoma. The dacarbazine which is reported to be a relatively mild drug in inhibiting melanoma is combined with the indocyanine green that can be used as a photosensitizer for PDT to realize the combined therapy. Dipalmitoyl-sn-glycerol-3-phosphocholine (DPPC) and 1,2-Dioleoyl-3-trimethylammonium-propan (DOTAP) was used to synthesize the liposomes which gave it a positively charged surface for electrostatic coating with hyaluronic acid. Hyaluronic acid molecules are utilized to modify the liposomes surface to achieve the purpose of active targeting to the melanoma sites. This nanoparticle is expected to show enhanced cytotoxicity and its therapeutic effect compared with regular treatment against melanoma.

Melanoma is considered as one the deadliest tumors. There is a discovery of a rising trend of melanoma detection in developed countries. Nevertheless, early detection is currently most acknowledged method, and for effective treatment of latter melanoma, contemporary clinical treatment involving chemotherapy and photothermal therapy are often not effective in completely elimination of melanoma cell. Therefore, in this paper, we have proposed a prototype that combines chemotherapy and photothermal therapy. Temperature sensitive liposome is used as the carrier of medicine, carrying Paclitaxel and gold nano star. Paclitaxel loaded temperature sensitive liposome is prepared by film dispersion method. We have demonstrated that such prototype is biocompatible and biodegradable, possessing a promising future in assisting melanoma healing.

When a medical infusion pump is used with a disposable pump infusion set for infusion, the change in infusion precision will affect the treatment effect, which will have a greater impact on burn patients and critically ill patients. Failure to infuse fluid in time will increase the mortality rate. Therefore, the factors influencing the infusion accuracy of disposable pump infusion sets under medium and high flow rate conditions are analyzed by conducting infusion experiments with flow rates of 100 ml/h, 200 ml/h, 500 ml/h and 1000 ml/h at temperatures of 10°C, 20°C and 30°C. The degree of correlation and influence between the infusion accuracy and the influencing factors are studied, and suggestions are provided. The results show that the grey correlation degrees between temperature, time and flow rate and infusion accuracy are all greater than 0.6, with obvious correlation. The correlation between temperature and infusion accuracy is the strongest. Temperature, time and flow rate all have significant effects on infusion accuracy and temperature has the greatest impact on infusion accuracy. When infusion is carried out under the condition of medium and high flow rate, the influence of temperature on the infusion accuracy should be considered first.

Cancer is one of the leading causes of incurable death and remains a serious disease worldwide. Of all types of skin cancer, melanoma is the most aggressive malignancy. Adriamycin is one of the most commonly used and important antibiotics among anti-cancer drugs in recent years and has a significant killing effect on melanoma cells when chemotherapy is administered using adriamycin. In PTT treatment, gold nanoparticles are used as photosensitizers with the property of warming up under 808 nm near infrared light to achieve melanoma inhibition. However, neither chemotherapy nor PTT alone is a good solution to this challenge and may result in a range of complications. We have therefore taken the approach of chemically combining adriamycin with gold nanoparticles to form a new nano-drug for treatment to compensate for its shortcomings when acting singly.

Traditionally, the most common way to cure cancer is chemotherapy. Unfortunately, the cytotoxic drug that is commonly used in chemotherapy does not have selectivity towards cancer cell and highly proliferating normal cells, which would result in side effects such as emesis and hearing loss. Nanoparticles delivery system, on the other hand, is attracting interest from its ability of targeted drug delivery, tumor in situ imaging, heat production under light stimulation, carrying one or more contrast agents, etc. In this paper, I designed a mesoporous polydopamine nanoparticle (MPDA) coated with erythrocyte membrane, and loaded with tirapazamine. Particularly, the red blood cell membrane (RBC membrane) can make MPDA achieve long circulation in the human body by camouflaging the MPDA and the macrophage would not uptake MPDA. Besides, the RBC membrane can insert AS1411 to target the tumor more successfully and more accurately. In addition, MPDA and RBC membrane have biodegradability and they would not harm human tissue after the drug delivery is complete. This nanoparticle drug delivery system is formulated by MPDA as the triapazamine carrier and coated by RBC membrane with the insert of AS1411. Thus, it is expected that the combined therapy in the nanoparticle drug delivery system can realize the combined treatment of phototherapy and chemotherapy.

Mirabilis jalapa L. has strong environmental adaptability and reproductive ability, and is distributed all over the country. The use of ornamental plants for phytoremediation of polluted soil can not only remove pollutants in the environment, but also green, beautify and purify the environment. The germination rate of M. jalapa seeds decreased significantly with the prolongation of storage time, and the seeds germinated satisfactorily within 9 months. The germination rate was reach peak at the sixth day. The plant height and root length of M. jalapa grown on different soil substrates has shown different trend. The fleshy root propagation survival rate of M. jalapa was significantly higher than that of seed and stem cutting propagation. The main enrichment of Cd was in root. The survival rate of fleshy root reproduction was no significant effect in different growth substrates. Therefore, fleshy root propagation was the best way for M. jalapa to grow on different substrates. And the application prospects of M. jalapa as a remediation plant should be further studied.

The main ingredients of the Western diet are highly processed and refined foods, and high in sugar., salt, fat, and protein from red meat. In the past few decades, the Western diet has been an important factor in the rise of obesity rates. Individuals who are overweight or obese have a higher chance of developing comorbidities such as diabetes, cancer, cardiovascular disease Several studies have shown significant changes in the intestinal flora of obese people both in composition, and that this dysfunction of the intestinal flora is one of the major contributors to the western diet-induced obesity. This review addresses recent progress in the understanding of the association of the Western-style diet with obesity, dysbiosis of intestinal flora plays an important role in obesity. And possible therapeutic interventions by targeting gut microbiota are also discussed, aiming to tackle and prevent this current pandemic.

Among several different lethal tumours, the mortality of pancreatic cancer with poor efficiency after surgery is the highest. Late diagnosis and lack of symptoms contribute to pancreatic cancer's horrific mortality rate, and a growing body of research is trying to find a solution to the problem. With a deeper understanding and more research in signal pathways, many new target proteins come into sight. The downstream target of pancreatic cancer also become a significant hotspot for many researchers, in this review, it will analyze the main target in pancreatic cancer and try to illustrate the treatment by the target.

PCR combined with ITS sequence analysis were used to identify the type of trematode metacercariae in Channa gachus living in Jinghong City. By targeting the specific type, local health departments can prevent and control fish-borne fluke disease scientifically and reduce the risk of human infection more effectively. The Channa gachus were collected from the Jinghong city in Kunming, and metacercariaes were then extracted using artificial digestion method. DNA of different morphological cysts were extracted, PCR amplification, and sequencing analysis was conducted. Classification was performed based on morphological features of different species. Morphological identification showed that Haplorchis pumilio was found in the cheeks, fins and muscles of the snakehead, Metorchis orientalis Tanabe, Clonorchis sinensis, Centrocestus formosanus, Haplorchis pumilio and other metacercariaes. Unknown bladder worms were also present. ITS Sequence analysis results identified Haplorchis pumilio flukes. A variety of trematode metacercariaes have been detected in Channa gachus in Jinghong City. There are certain defects in the identification of trematode metacercariaes pecies only by morphological characteristics. The species can be determined by combining with ITS sequence analysis.

Cancer and reactive oxygen species (ROS) are two of the health threats faced by modern humans. In this research paper, polydopamine nanoparticles (PDA NP) are proposed as a potential material for the treatment of the two health issues. Experiments were carried out to illustrate the photo-thermal properties of PDA NP as well as its ability to eliminate perhydrol in vitro. Finally, the biocompatibility test was performed and the results proved that PDA NP is safe for human red blood cells.

Background: Glutamine synthetases are considered to be an important enzyme class for microbial adaptation to extreme environments, and studying the Antarctic sea ice bacterial glutamine synthetases can be used to explore the molecular mechanisms of psychrophilic microorganisms. Objective: This work use bioinformatics tools to predict structure and function of Glutamine synthetase (GS) from Pseudoalteromonas sp., and to provide a theoretical basis for further study. Methods: Open reading frame (ORF) of GS sequence from Pseudoalteromonas sp. was obtained by ORF finder and was translated into amino acid residue. The structure domain was analyzed by Blast. By the method of analysis tools: Protparam, ProtScale, SignalP-4.0, TMHMM, SOPMA, SWISS-MODEL, NCBI SMART-BLAST and MAGA 7.0, the structure and function of the protein were predicted and analyzed. Results: The results showed that the sequence was GS with 468 amino acid residues, theoretical molecular weight was 51986.64 Da. The protein has the closest evolutionary status with Shewanella oneidensis. Then it had no signal peptide site and transmembrane domain. Secondary structure of GS contained 35.04% α-helix, 16.67% Extended chain, 5.34% β-turn, 42.95% RandomCoil. Conclusions: This GS was a variety of biological functions of protein that may be used as a molecular samples of microbial nitrogen metabolism in extreme environments.

In order to explore the effects of temperature on microbial community diversity on activated sludge, winter and summer activated sludge in the same sewage treatment system were selected for comparison. The experimental results show that in winter, when the activated sludge is prone to expansion and the activated sludge expands, the bacterial phyla with the largest relative abundance is Chloroflexi, while the largest phyla in the normal activated sludge is Proteobacteria, and the abundance of Actinobacteria and Bacteroidota in the other two sludges is also very different. Through the analysis of environmental factors, it was judged that under the environmental stress of low temperature and low dissolved oxygen, the proliferation of Chloroflexi and Bacteroidota in the activated sludge was determined, which inhibited the growth of Proteobacteria and Actinobacteria and triggered sludge expansion. In addition, the related microorganisms in the winter sludge have a strong metabolic capacity for carbohydrates and proteins, indicating that under long-term extreme conditions, the microbial community can form a rapid metabolic pattern for carbohydrates and proteins to maintain the optimal removal effect of activated sludge on pollutants. By reducing the organic load of sludge and increasing the concentration of dissolved oxygen in the water, it is found that the sedimentation of sludge has been improved, the efficiency of wastewater treatment has been improved, and the activated sludge system tends to be stable.

To clarify the genetic diversity among typical drought tolerant flax varieties, in this study, the Single-nucleotide polymorphism sites (SNPs) of 29 drought tolerant flax varieties were identified by whole-genome resequencing, and their SNP characteristics and genetic relationships were analyzed. The results showed that 1069106 SNP sites were obtained from the genome of the 29 drought tolerant flax varieties, among which the variety with the largest number of SNP was Zhangya 2 (1027658) and the least was Shache flax (801300). Among the types of SNP variation that occurred, the number of transitions (671103) was higher than transversions(398003). Phylogenetic analysis divided all 29 flax varieties into three groups, each with a wide range of sources, and some flax originating from the same region were located in the same group, indicating a rich genetic diversity of these 29 flax varieties. PCA (Principal component analysis) also divided all the flax varieties into three groups, which showed similarity to the phylogenetic tree grouping, which provides evidence for the results of the phylogenetic analysis. Among them, five varieties, Linxiabai, Gaolanbai, Lingtaizhuangna, Shache flax and Shache precocious red, showed evidently close genetic relationship both in phylogenetic analysis and PCA. This study can prove that the 29 drought tolerant flax varieties have rich genetic diversity, which lays the foundation for the genetic breeding of drought tolerant flax, the development of specific molecular markers, and the identification of germplasm resources.

Flax (Linum usitatissimum L.) is an annual herb that can be divided into oilseed flax and fibre flax during evolution. In order to clarify the genetic relationship of typical drought tolerant flax cultivars we systematically studied the genetic diversity of 29 drought-resistant flax cultivars by SSR molecular markers. The results showed that 30 pairs of SSR primers amplified 330 bands from 29 drought-resistant flax cultivars, of which 307 bands were polymorphic, with a polymorphism ratio of 93.01%. Each pair of primers had an average of 10.2 polymorphic loci, and the average polymorphism information content (PIC) of primers was 0.9254. The effective alleles (Ne) ranged from 1.2622 to 1.6399, the Nei's index (H) ranged from 0.1833 to 0.3777, and Shannon's index (I) ranged from 0.3146 to 0.5612. UPGMA clustering analysis showed that 29 drought-resistant flax cultivars were divided into A and B categories at the genetic similarity coefficient of 0.41. The results of population structure analysis show that when K=2, 29 drought-resistant flax cultivars can be divided into 2 subgroups. The results of principal coordinate analysis showed that the two populations are relatively far apart on axis PCoA1 and can be significantly separated. The population structure analysis, cluster analysis and principal coordinate analysis results were highly consistent, and it was concluded that the drought-resistant flax varieties had a high degree of genetic diversity, and it was most appropriate to divide the 29 drought-resistant flax varieties into 2 subgroups according to the analysis results.

This paper mainly summarizes the comparison between the prevalent covid-19 virus and the previous influenza virus, distinguishing their advantages and disadvantages by the type of vaccine and the efficacy of booster shots. Inactivated vaccines, attenuated vaccines, and influenza vaccines all aim to boost the body's immunity against bacteria. By comparison, it is found that the covid-19 vaccine is more effective than the influenza vaccine but requires 2-3 injections and booster injections to consolidate. In addition, this article also considers the development of vaccines in the future. If the future vaccines have multiple effects in one shot, it will reduce the risk of future spread of the epidemic and the pressure on hospitals. In conclusion, the epidemic has brought many troubles to our lives. Vaccines, as the result of scientific and technological development, can eliminate most of the threats, but the virus will also mutate the corresponding vaccines. Therefore, for future consideration, developing a more efficient vaccine with fewer side effects to fight the virus is a guarantee for human safety.

Rhodopsin is a binding protein consisting of retinal and seven transmembrane proteins which can absorb light and cause a series of light-induced reactions within any organism. This kind of protein is not only discovered in animals' eyes, but also found in a wide range of microbes in recent years. Microbial rhodopsin is further divided into different categories that carry out different functions, including proton pump, ion pump, and optical driver. Past research has hypothesized the existence of certa in connections between animal and microbial rhodopsin. Therefore, this research collects information about various kinds of microbial rhodopsin (BR, HR, SRI, SRII) as well as animal rhodopsin sequences and explores their evolutionary relationship through the phylogenetic tree and transmembrane domain analysis. The results show that both HR and SR evolved from BR. As for the evolutionary relationship between microbial and animal rhodopsin, this research agrees with the conclusion of preexisting research: though they share conservative structures, their evolutionary relationship is still not supported by solid evidence.

Temozolomide (TMZ) and indocyanine green (ICG) are relatively effective drugs for cancer treatment. TMZ can effectively cross the barrier between blood and brain, while ICG has a high thermal conversion rate, but they also have disadvantages such as easy decomposition in vivo and poor targeting. In order to address the shortcomings of these two drugs and to improve their stability and targeting in vivo, as well as to further enhance their efficacy, I will use PAMAM nanoparticles to encapsulate TMZ and ICG and target the tumour-targeting peptide cRGDyk as a synergistic therapy, and conduct relevant experimental validation.

In a protein primary structure, a type of amino acids is usually clustered together rather than homogenously distributes. What advantage of such distribution and how to measure different distributions are rarely addressed. In the current communication, we apply the distribution probability to investigate the mutations/variants from monoamine oxidases A and B. The results reveal the rationale of clustering distribution of amino acids in the full-length sequence and in functional regions of the monoamine oxidases, and how the mutations/variants affect the distribution probability. Thus, we can quantitatively measure and compare not only the amino-acid distributions across different monoamine oxidases, but also the effect of mutations/variants on the enzymatic function.

Site-directed mutagenesis (SDM) is an important tool in molecular biology, especially in genetics and protein engineering. It can alter specific amino acid residues by changing the codons of a gene, thus allowing to explore the role of specific amino acid residues in the structure and function of the aim protein. Here, we developed a method for constructing SDM of the Saccharomyces cerevisiae genome based on homologous recombination in vivo using mismatch PCR product. In this method, mutations were designed in the PCR primers. After transforming the mismatch PCR product into yeast, positive colonies were screened via colony PCR with a verification primer whose 3' end were the mutated bases. To avoid false positive results in the screening, the annealing temperature of the colony PCR was optimized via temperature gradient PCR. This method was applied to the Exo70 subunit of the tethering complex exocyst, which is an effector of Rho3 and critical for localization of exocyst to the cell membrane. Finally, we successfully introduced the desired mutations in Exo70 within three days, showing that this method is simple, fast and feasible for SDM of yeast genome.

Ajania purpurea Shih is a plant of the genus Ajania endemic to Tibet. As an ornamental plant, it has not been investigated for its pharmacological activity. In this study, HPLC analysis of 70% ethanol extracts of A. purpurea (EAPS) identified two major compounds, chlorogenic acid and piperine. We evaluated the cytoprotective activity and antioxidant effects of EAPS by examining the production of oxidative-stress-related mediators, including ROS, superoxide dismutase, and catalase, in glutamate-induced HT22 cells. JC-1 and TUNEL staining revealed that EAPS attenuated intracellular mitochondrial depolarization and subsequent apoptotic protein expression. Most importantly, EAPS promoted the nuclear translocation of Nrf2 and deliverance of HO-1 in HT22 cells. EAPS also inhibited glutamate-induced cytotoxicity and ROS production, which was partly changed by siRNA HO-1. These results intimate the effective cytoprotective and neuroprotective vitality of A. purpurea, peradventure via the adjustment of the Nrf2/HO-1 signaling pathway.

Neonicotinoid insecticides occupy the highest market share in the world. Their wide usage has led to the emergence of insect resistance and bee toxicity problem. Insect nicotinic acetylcholine receptors (nAChRs) are the molecular targets of these insecticides. Acetylcholine binding proteins (AChBPs) share a similar homologous pentameric structure with extramembrane ligand-binding domains of nAChRs. Therefore, AChBPs are used as an alternative tool for studying the ligand binding properties of nAChRs. Recently, the AChBP identified from Pardosa pseudoannulata, Pp-AChBP, was proven to be more similar to insect nAChRs in terms of the binding properties of known nAChR-targeting insecticides. Meanwhile, a spider peptides toxin, Hv1a (ω-hexatoxin-Hv1a), has been found to selectively bind to insect nAChRs, but the binding pocket is different from traditional neonicotinoid insecticides. The purpose of this study is to reveal the molecular mechanism of spider toxin Hv1a binding to Pp- AChBP. Hv1a gene was cloned and expressed in Escherichia coli. Pp-AChBP gene was cloned and expressed in Sf9 insect cells. We explored the strategies to achieve a high level of expression of both proteins. The pull-down assay result showed that Pp-AChBP do not bind with Hv1a, the possible reasons of which were discussed. This study provided a theoretical basis for the regulation mechanism of Hv1a.

Florfenicol (FFC) is a novel form of specific antibiotic for animals, but because of its low water solubility, it has a lot of challenges in veterinary therapeutic use. A new form of amphiphilic chitosan derivative nano-material—HPCH-SA nano-micelle—was produced in this research to address the problem of FFC's poor water solubility. TEM was used to examine the nano-micelles. Taking particle size, Zeta potential and critical micelle concentration (CMC) as evaluation criteria, the properties of FFC/HPCH-SA nano-micelles were studied by stability investigation. The pharmacokinetics of FFC/HPCH-SAnano-micelles was studied in SD rats by oral administration. The results showed that the FFC/HPCH-SA nano-micelles were spherical with a smooth surface and good distribution. The particle size was 246.13±2.99 nm, the electric potential was 32.4±1.92 mV. Florfenicol must be stored in a dry location. In rats, FFC had a quick absorption rate, wide distribution, moderate elimination rate, and long half-life. It had a high oral bioavailability and could be kept in rats for a long time. This study found that an amphiphilic chitosan derivative nano-micelle, HPCH-SA, might efficiently increase the water solubility and bioavailability of hydrophobic medicines, and that it had a wide range of applications.

Anaphase Promoting Complex/Cyclosome (APC/C) is a kind of E3 ubiquitin ligase involved in a variety of biological processes including mitosis, senescence, apoptosis, and tumor cell formation. Its structural changes and major functions are closely related to the cell cycle progression. APC/C is a large complex consisting of multiple subunits, and the catalytic core exhibits the typical characteristics of the cullin-Ring E3 ligase. The function of the APC/C was modulated by the binding and separation of its co-activators and inhibitors and the corresponding conformational changes of APC/C itself. Ubiquitination is realized through the interaction with UBE2C and UBE2S E2 enzymes and substrates. Therefore, studying the structural changes of APC/C in the cell cycle species is helpful to understand the progression, the specific process of ubiquitination of E3 ubiquitin ligase, and how macromolecular components regulate activity through structural and conformational changes, which is conducive to the development of molecular biology, cell biology, pharmacology, oncology, and other fields. This paper will focus on APC/C’s molecular structure changes and biological functions in different processes of the cell cycle from the perspective of cell cycle progression.

Tacrolimus (FK506) is a novel macrolide antibiotic derived from the broth medium of soil fungi, which has a strong immune inhibitory effect, but its adverse reactions toxic side effects cannot be ignored. The side effects of tacrolimus may cause other clinical symptoms that directly or indirectly harm the patient. Under- standing the toxic side effects and adverse effects can provide valuable reference for clinical applications. The purpose of this article is to outline and summarize the potential side effects of tacrolimus toxicity, and briefly analyses the factors that lead to their creation. This work can provide a basis for clinical and follow-up studies.

In recent years, nanomaterials, as an emerging material, have attracted extensive concern because of their special structure and function. Polymer-based nanomaterials (PBNs) refer to a class of nanomaterials with polymer molecules as matrix and a nanoscale structure after special treatments such as embedding and adsorption. Due to the properties of polymers are determined by a series of factors such as monomers and polymeric structures, PBNs have a variety of applications, especially in therapy. Current investigations have already demonstrated that PBNs have significant roles as delivery carrier and vaccine adjuvants, nanoparticle-based drug delivery systems and antibacterial materials. However, because of the wide variety of organic molecules, diverse synthesis methods and complex structures, the researches on PBNs stay at the surface stage, which means only a small part of PBNs have been experimentally tested. In this research, the applications of PBNs in therapy field are briefly introduced from the above three aspects including the advantages of PBNs compared with traditional materials, some findings that have been investigated and some researches that are in progress. Safety, nontoxicity, targeting, good stability and other prominent properties are the main reasons that PBNs are suitable for vaccine therapy and drug delivery, showing a great development prospect. The objective of this paper is to summarize some existing examples to prove that PBNs have a very high adaptability in the applications of vaccine treatment and drug delivery, and provide case references and suggestions for future research and investigation.

Nanobiomedicine is a biomedical application based on nanotechnology. It is an emerging interdisciplinary subject and has become an important scientific research direction. Based on the PubMed literature database and using the citexs data analysis platform, this paper conducts literature analysis and big data mining on nano-silver research from 2012-01 to 2021-12, sorts out the development process of this field, and analyzes the application of nano-silver in the field of biomedicine. Research status, development trends, research hotspots, and multi-dimensional analysis and discussion on the research status and progress of nano-silver in biomedicine. In the past ten years, the number of nano-silver papers in the field of biomedicine has grown rapidly, indicating that nano-biomedicine has been closely related to our life, medical treatment and other aspects. Therefore, statistics on the number of nano-silver papers published and the frequency of hot words have certain reference significance for the development and in-depth research in the field of nano-biomedicine.

Although lots of studies take analysis on sports performance between running surfaces, the mechanism of underlying this performance on human body is still unclear. The purpose of this study was to explore a whether there was consistent sport loading at 75% VO2max sports intensity and sports time. Methods: 10 health male runners participated in this study. The running speed (RS), the running distance (RD), the body composition and muscle conditioning data in knee and ankle joints were capture while subjects run at given sports intensity and sports time on treadmill and over-ground surfaces. A paired T-test was applicated to analyse the difference between parameters. Results: (1) RS and RD on RO (RD, 6.85±1.41km; RS, 13.69±0.28km/h; P=0.732) were relatively higher than RT (RD, 7.4±1.41km; RS, 14.80±2.83km/h; P=0.732), but no significant differences were found; (2) the variations of protein and fat volume on RT were significantly lower than RO and the variations of the fat-free weight, body moisture, intracellular fluid and extracellular fluid were significantly higher than RO;(3) Total watt of muscle extensor in knee joint at 120o/s (Pre,1138.7±274.11; Post, 827.4±207.41; P=0.02) after RT was significantly lower related to TO (Pre, 738.1±82.54; Post, 782.67±107.70; P=0.02). Conclusions: under given sports intensity and sports time, RT could bring the relatively higher sports loading on subject`s body than RO; this difference in sports loading may take the potential risk injury, and the relative practitioner should also pay attention to this negative influence to avoid the unnecessary risk.

In this paper, for the purpose of exploring the preparation technology of Codonopsis pilosula soft sweets, Codonopsis pilosula polysaccharide extracted by water extraction and alcohol precipitation method is used as raw material. On the basis of single factor experiment, an orthogonal experiment of four factors and three levels is designed, and the sensory evaluation is used as the index to optimize the technological formula of Codonopsis pilosula soft sweets, aiming at developing a soft candy which is easy for consumers to accept, can improve immunity and contains traditional Chinese medicine ingredients. Through the analysis of a large number of experimental data, it was found that the best scheme of preparing Codonopsis pilosula soft sweets by orthogonal test was A3B1C1D1, that is, the best raw material formula was citric acid 0.9%, Codonopsis pilosula polysaccharide 0.6%, gelatin 6% and white sugar 10%. Codonopsis pilosula soft sweets prepared by this formula not only have edible value, but also have the efficacy of prevention and health care, and are suitable for consumers to eat.

Hollow manganese dioxide (H-MnO₂) has been a popular nano-platform in widespread applications, and the extraordinary properties of H-MnO₂ include the high capacity for drug loading and the unique ability to adjust hypoxic tumor microenvironment (TME), which plays a significant role in treating the tumor. Herein, the H-MnO₂ structure was prepared by using the silica as a template. The H-MnO₂ would then be co-loaded with a chemotherapy drug temozolomide (TMZ) and a photodynamic agent IR780. In addition, the H-MnO₂ was coated with polyethylene glycol (PEG) and modified with RGD peptide sequence (ACDCRGDCFCG) to achieve high stabilization and targeting therapy. In short, the resulted TMZ/IR780/H-MnO2@PEG-RGD would be a promising nanoparticle to treat melanoma through the combined chemo-photodynamic therapy and adjustment to hypoxic TME.

In recent years, the number of people with autism increases gradually, and they get more social attention. But the current attention is mainly focused on children with autism, most of the autistic children can receive compulsory education, but they are seldom concerned once they graduate from school as the growth of the age. The rehabilitation of older autistic is in the vacuum state after they leaving school system and the family caregivers of them have huge pressure. What is more serious is that the condition of older autistic gets bad once they stop the rehabilitation training, so this paper studies and designs a rehabilitation training system for older autistic. It mainly includes the evaluation module, the general training module and the space environment module. The training system can evaluate physical condition of older autistic and then recommend rational training scheme, as well as, it can simulate various spatial environments and simple social occasions. The training system is appropriate for the family or other rehabilitation training institution when the older autistic graduate from school, it can provide good effect on the autistic.

Blepharoptosis, a drooping eyelid symptom that brings widespread vexation to millions around the globe, is commercially treated mainly by surgeries. In response to the limitations of surgery id est side effects, this review analysed different causes of blepharoptosis, provided the potential explanations for surgical side effects, and investigated other conservative treatments as possible alternatives for surgery. The realm of traditional treatments covered methodologies stemming from both Eastern and Western Iatrologies. Overall, conventional treatments indicate, though lower confidence for efficacy, fewer side effects, and together the treatments shed light on the possibility of combined usage for better results.

Breast cancer is the most common malignant tumor nowadays, which is even more common than lung cancer among human being. Fine Needle Aspiration (FNA) is the most common way to detect whether the breast mass is malignant or not. Although the rate of survive after the malignant tumor spreads is pretty low, if the tumor can be noticed at early stage, patients still hold a great chance of survive. With a low death rate in early stage comparing to other cancers, a convenient and efficient way to help diagnosing whether the breast mass is benign or malignant is crucial. However, many existing models on predicting breast cancer includes variables of the patients themselves, like weight changes and lifestyle, which requires long-term tracking survey, and that will cost a lot of precious time during the early stage of the tumor. Thus, a model which only consider the numeric variable from the FNA would save a lot of time and increase the chance of living. In this study a model is created based on the FNA data of the breast tumor patients in Wisconsin in 1995. A set of variable filtrations are employed to get the best variable combination such as AIC, ridge regression, variance inflation factor (VIF), LASSO, and cross validation. After the variable filtration a model based on General Linear Model (GLM) is created with an accuracy of 0.88.

Clinical decision support system (CDSS) is a medical artificial intelligence system based on medical knowledge and clinical data, its development now is embarrassed. There is no strong evidence to prove that CDSS is of great help to clinic, and this situation has not improved in recent 10 years According to the research, about 50% of CDSS encountered failure in clinic manifested as unexplained decision-making process, low system application rate, poor user acceptance and negative impact on clinical work flow. How to improve this dilemma has become an important issue in CDSS research. Because CDSS is constructed with medical knowledge & clinical data, and is used by clinicians, the perspective of clinicians on CDSS also plays a role in its construction and utility. In this paper, current CDSS is inspected in its technique, used knowledge, reasoning method, data management and clinical cognition with the perspective of a clinician. It is proposed that CDSS should provide useful information to meet the requirement of medical science and to follow reasoning pattern of clinicians which endows its clinical role and eligibility in healthy care service.

Helicobacter pylori is a common type of bacteria that is strongly associated with the development of gastric cancer. In this study, a case-control study was used based on an epidemiological perspective in public health. The presence of H. pylori infection was investigated in two groups of people, the healthy group and the gastric cancer group. This led to an analysis of the relationship between H. pylori and gastric cancer and methods of prevention and treatment based on epidemiological methods. It was concluded that there is a close relationship between H. pylori and gastric cancer, and that those infected with H. pylori are 13.49 times more likely to develop gastric cancer than those who are not. However, the exact mechanism needs to be further investigated.

The purpose of the present study was to identify the effects of transcranial pulsed current stimulation of the central nervous system (CNS‑TPCS) on systemic monoamine neurotransmitter changes in rats with exercise fatigue. Nine Sprague Dawley (SD) rats, of which three SD rats with CNS-TPCS, were enrolled in this pilot study. Changes in plasma dopamine (DA) and 5-hydroxytryptamine (5‑HT) levels were examined using two-way repeated measures anova at seven time points (a fixed time point after the end of the test, 7 days in a row). In the experimental group, DA levels increased significantly over time following CNS‑TPCS, and 5-HT levels increased significantly over time following CNS‑TPCS. In the observation and control groups, DA and 5-HT levels remained unchanged during the experimental. The DA levels of the control group was significantly lower than that of the experimental group and the observation group, while the 5-HT level was significantly higher than that of the experimental group and the observation group. These results suggest that the anti-fatigue properties of CNS-TPCS experimental associated with its fatigue recovery effectiveness in rats with exercise fatigue. Moreover, additional studies are essential to evaluate the potential of DA and 5-HT, and as biomarkers to evaluate the fatigue recovery response to CNS‑TPCS experimental, which could facilitate sports rehabilitation optimization.

People have found plenty of measures to better manage and cure the neuropathic pain which many people have been surfing from all over the world. According to the pain mechanism, the spinal cord stimulation is new-created treatment which is more effective than the traditional therapeutic ones with medicine. The spinal cord stimulation is a low-intensity electrical pulse on large myelinated Aβ fibers and aimed to relieve the pain based on gate control theory. However, the success rate of SCS limited and the sample of patients who experience SCS is small. In this case, it is hard for people to figure out the mechanism of SCS and make an improvement for neuropathic pain. Therefore, people are urged to investigate the effects of SCS among the subjective and objective evaluation methods. This paper aims to collect the information about the evaluation for effects of SCS and make a comparison. This may be easy for people better understand the effect of SCS and give a suggestion for the future improvement.

Neuropathic pain is a prominent illness that is often resistant to therapy and is typically accompanied with dissatisfaction among patients throughout the treatment process. Prior research has shown that medications may be beneficial in some circumstances, but there are still hurdles and risks. Numerous studies have shown that spinal cord stimulation (SCS) utilizing varying wave frequencies is a viable alternative therapy for neuropathic symptoms. This study investigates the mechanism and application scenarios of three distinct SCS protocols, as well as the evaluation and treatment of individuals with various kinds of neuropathic pain; it may serve as a practical reference for future research.

At the end of 2019, a new coronavirus suddenly broke out all over the world. To date, there is still no targeted medicine available for the treatment of this disease. Vaccine is essential for controlling the epidemic of SARS-CoV-2. But the effective of vaccine was reduced because of the SARS-CoV-2 constant mutation. It is gratifying that scientist uncover the infection mechanisms of the SARS-CoV-2. The main protease of SARS-CoV-2 is highly conserved and plays an important role of the life cycle of virus. Therefore, we executed virtual screening on the FDA-approved database and hoped to find a potential candidate against the main protease. As a result, we obtained eight available active compounds derived from the database through molecular dynamics simulations. As antiviral treatment candidates, the drugs can also be used to clinical emergencies.

Depression was common before COVID-19 and became the top 25 burdens of disease in 2019 according to the annual Global Burden of Disease Study. With the continued spreading of COVID-19, researchers predict that depression may increase larger in the future. With the development in both neuroscience and psychology, the major depressive disorder can be released by different kinds of methods. From the medical aspect, most of the antidepressants which are widely used can be divided into 4 types: Tetracyclic Antidepressants (TeCAs), Tricyclic Antidepressants (TCAs), Selective Serotonin Reuptake Inhibitors (SSRIs), and Serotonin-Norepinephrine Reuptake Inhibitors (SNRIs). The advantages of them involve high efficiency and can be absorbed easily. However, the main drawback of these medications is the side effects that they can cause ranging from somnolence to drowsiness after starting treatment. Research shows that some level of sexual dysfunction may occur in 40 to 65 percent of people who use SSRIs due to the sexual side effects. In this way, some of the psychological methods were explored including cognitive behavior therapy (CBT) and interpersonal psychotherapy (IPT) which focus on changing the mind or opinions of the patients to achieve goals. The content of this article not only focuses on different methods to treat depression but also compares their advantages and disadvantages of them. It may provide some pieces of evidence and viewpoints for clinical decision-making.

Coronavirus disease 2019 (COVID-19) has become a global pandemic, causing heavy losses to the global community. Novel Coronavirus development speed, the scope of the large, so that biomedical workers have to face together. Meanwhile COVID-19 (SARS-CoV-2) has a strong infection rate as well as certain mortality rate, which brings challenges to the treatment of the disease. Vaccination is an important means to prevent infectious diseases. At present, many research institutions around the world have launched the research as well as advance of COVID-19 vaccines. The current situation of SARS-CoV2 pandemic has triggered development and use of epidemiological vaccines in the medical community. Aiming at vaccines evolution is to acquire straight as proof of vaccines efficient in defend people from SARS-CoV-2 as well as COVID-19 in order to effective vaccine manufacture will be selectively. One vaccine candidate against COVID-19 may fight acute, disease, either contagion, or a vaccine which reduces anyone the elements may aid in disease control. This article introduces the morphological characteristics, mechanism of action, clinical utility, enhance as well as differences of COVID-19 vaccines development, In order to compare mRNA vaccine, subunit vaccine and attenuated vaccine and studied from multiple medical perspectives to promote the selection and use of vaccine in a safer way and ensure the best efficacy end points, prevent grave pathema and doom, as assessed about phase 3 clinical trials. hoping to help comprehend development as well as vaccination point at COVID-19 vaccine in the future.

The neurological condition known as autism spectrum disorder (ASD) has been the subject of extensive discussion and study since the 20^th century. It is a relatively newly discovered neurological disease, and many aspects considering ASD are still obscure. Symptoms of the disease include communication and social impairment, repetitive behaviors, and self-injury behaviors. While significant cognitive or learning difficulties are often observed in classical ASD, patients with Asperger’s syndrome (another kind of ASD) can be highly talented in a specific area. This literature review discusses the possible causes and treatments of ASD through research done in this century. It summarizes several points of the research progress and findings in the area of ASD. The treatments discussed are applied behavior analysis, intestinal microecology, treatment and education of autistic and related communication handicapped children (TEACCH), and medical treatments.

The new virus was initially defined in Wuhan, China, in 2019. Because of its quick transmission, a pandemic spread over the world. The SARS-CoV-2 virus is a subtype of the coronavirus family, the seventh virus type after SARS. The virus enters organisms’ cells and produces mRNA in the host cell through a series of processes including replication and transcription. mRNA is translated into the corresponding viral protein in the cell and released from the host cell. To stop the spread of the disease, various vaccines have been developed and put into use in a short time. This paper details the design of a newer type of mRNA vaccine against COVID-19, its advantages and disadvantages, and compares it with other types of vaccines. The comparison reveals that mRNA vaccines have apparent advantages in terms of speed of production and safety, but at the same time their delivery conditions and instability are issues that need to be addressed. If the mRNA vaccines' storage conditions are improved, such as by raising the temperature at which they are stored, extending their half-life, and lowering the stringent storage standards, in the future, mRNA vaccines will play a larger clinical role.

Opioid is one of the main components used in many pain pills, such as fentanyl. It can selectively inhibit the impulse transmission of some excitatory nerves by acting on opioid receptors in central nervous tissues and relieving pain. However, opioid is easy to be addicted. Opioid addiction has become a serious social issue. The main aim of this dissertation is to investigate the influences of Single Nucleotide Polymorphisms (SNPs) of OPRM1 on opioid addiction. In this essay, three methodologies are used to conclude whether SNPs of OPRM1 influence opioid addiction. The first method uses sample statistics to hypothesize and estimate the population by finding out the confidence interval for the difference between two population proportions by randomly choosing 500 European subjects and sequencing the OPRM1 SNPs. In the second method, an oxford nanopore is used to determine the specific sequence by creating a characteristic disruption in the electrical current. In the third method, house mice's zygotes are first developed in vitro. Then, house mice learn how to self-administer in the vapor chambers.

The resulting Covid-19 pandemic has afflicted tens of millions of people to fight COVID-19 with the mRNA vaccine, which has provided good feedback but has also brought some adverse effects and complications. This paper demonstrates the great potential of MRA vaccines in fighting new tubes by introducing the mechanism and advantages of MNA vaccines and summarizes the adverse reactions found around the world after injection of mRNA vaccines and focuses on the three types of adverse reactions to discuss and tries to analyze their causes. Our work can draw public attention to adverse reactions to the MNA vaccine and accelerate the development of related technologies.

Objective: Taking patients with vertigo as an example, to explore the effect of applying traditional Chinese medicine nursing methods on the patients. Methods: Taking the patients with vertigo in our hospital as an example (from June 2021 to June 2022), a total of 80 patients were selected. With different nursing methods as the main method, one group of 40 people used routine nursing (control group), and the other group of 40 people used traditional Chinese medicine nursing (experimental group), to compare and analyze the nursing effect under different nursing methods. Results: After nursing intervention, the scores of TCM symptom scores such as palpitations, fatigue, dizziness and headache in the experimental group were all lower than those in the control group, and there was a big difference between the two groups, P<0.05. At the same time, after nursing, the patients in the experimental group had higher nursing satisfaction and lower incidence of adverse reactions, and the diastolic and systolic blood pressure of the patients in the experimental group were lower than those in the control group. When the data were compared with the data of the control group, the difference was statistically significant, P<0.05. Conclusion: The application of traditional Chinese medicine nursing method in patients with vertigo has positive significance in improving the blood pressure level and reducing the incidence of adverse reactions in patients, and the effect is outstanding.

Objective: To systematically evaluate the efficacy of staging-acupuncture therapy on peripheral facial paralysis. Methods: The clinical trials regarding acupuncture therapy for peripheral facial paralysis published before December 31st 2021 were searched in databases of PubMed, The Cochrane Library, Web of Science, CNKI, WanFang, VIP and CBM. The information of included studies was extracted and the quality was assessed by two independent researchers. The Metaanalysis was performed by using RevMan 5.4 software. Results: A total of 8 trials were included, involving 1224 cases. The results of Meta-analysis showed that: The markedly effective rate of staging-acupuncture group was higher than of the non-staging group [RR=1.23, 95%CI(1.15,1.32), Z=6.02, P<0.01]. Conclusion: Based on the current evidence, the efficacy of staging-acupuncture therapy on facial paralysis is superior to non-staging acupuncture therapy. But for the quantity and quality of the included trials are not satisfactory, the conclusion still needs more high-quality, large-size and randomized controlled trials.

Chickenpox is an acute infectious disease caused by the primary infection of herpes zoster virus. But its misuse and side effects have led many to question the vaccine. This paper introduces in detail what chickenpox is and its characteristics by analyzing the current situation of chickenpox and the key points of its prevention. It also describes the types of vaccines currently available, describes each vaccine and its availability, and then describes how many aspects of the vaccine challenge are proposed and addressed. The latent disease caused by varicella virus and its treatment are also described. Currently, the chickenpox vaccine remains the most effective treatment for the chickenpox virus, as long as it is proven to be used correctly.

Hand function has a great influence on our daily life. It is common sense that hand rehabilitation training is of vital significance to improve the living standard of patients with neural trauma. Muscle synergy, an important research method of biomechanics, can be viewed as a useful tool to reveal the control mechanism of the central nervous system over limbs. Despite many advances in the research on muscle coordination of human hand movements, it is necessary to conduct more detailed research on different joint movements because of the characteristics of hands with multiple joints and multiple degrees of freedom. A muscle synergies analysis was made herein to study three degrees of freedom and six hand movements of the wrist for muscle coordination analysis with the results indicating that the six hand movements have the same amount of muscle synergies. In terms of synergy stability, the results showed poor consistency in the muscle synergies of external rotation and radial deviation of wrist in contrast to great consistency in the extension and ulnar deviation. This study is of great significance to the motor function rehabilitation of different degree of freedoms (DoFs) of wrist for stroke survivors.

Objective: To observe the effect of Xiaoxuming decoction combined with massage therapy in the treatment of acute cerebral infarction (ACI) with yang deficiency syndrome and hemiplegia. Methods: In this study, 70 patients with ACI combined with hemiplegia with yang deficiency syndrome were selected, and the patients in the observation group were treated with Xiaoxuming decoction combined with massage therapy and conventional western medicine treatment. The patients in the control group were treated with conventional comprehensive treatment of western medicine, and the clinical therapeutic effects of the two groups were compared. Results: Comparing the patients in the control group, it can be seen that the TCM syndrome scores, FMA scores, clinical total effective rate, and Barthel index after treatment in the observation group were significantly improved after treatment, P<0.05; TCM syndrome score, FMA score, Barthel index and adverse reactions, P<0.05. Conclusion: The effect of Xiaoxuming decoction combined with massage therapy in the treatment of patients with acute cerebral infarction (ACI) combined with hemiplegia with Yang deficiency syndrome is ideal.

Objective: To observe the effect of Huatan Tongsui Decoction in the treatment of phlegm congestion and blood stasis meridian type in hemiplegia patients with stroke. Methods: The clinical data of 58 stroke patients with phlegm congestion and blood stasis in the meridian type in hemiplegia were collected. The patients in the observation group were treated with basic therapy, rehabilitation training, and Huatan Tongsui Decoction. The patients in the control group were treated with basic treatment and rehabilitation training, and the treatment effects and related indicators of the two groups were compared. Results: Compared with the patients in the control group, it was found that the clinical symptom scores, EMG scores after treatment, upper limb motor function scores after treatment, TG after treatment, TC after treatment, and hemorheology indexes after treatment in the observation group were significantly improved , P<0.05. The clinical symptom scores, electromyography scores, upper limb motor function scores, TG, TC, and hemorheology indexes were compared between the two groups before treatment, P<0.05. Conclusion: The effect of Huatan Tongsui Decoction in the treatment of phlegm congestion and blood stasis meridian type in hemiplegic patients with stroke is ideal.

Scientific medication is of great significance to improve the therapeutic effect of diseases. The etiology of chronic diseases is complex, different patients have different responses to drugs. Analyzing the examination results and medication information of previous patients can make the treatment plan follow a regular basis. First, the existing medical data is used to visualize the examination results of previous patients and the drugs used, to find the corresponding relationship between the two, and to build new attributes based on the attributes of the original data to improve the accuracy. Then, three oversampling algorithms are used to balance the imbalanced properties of the dataset. Finally, five kinds of classifiers were used to build a drug prediction model and conduct comparative experiments. The results showed that the random forest model based on the KMeans-SMOTE showed good results in various evaluations, and the drug prediction accuracy rate reached 95.05%. The model can better predict the drugs needed by patients, and its performance is better than other established models.

Objective: To analyze the clinical effect of Buyang Huanwu Decoction combined with transcranial magnetic stimulation on cognitive dysfunction after stroke. Methods: 80 stroke patients were selected and divided into two groups. The control group was treated with transcranial magnetic stimulation, and the observation group was combined with Buyang Huanwu Decoction to evaluate the effects of different treatment methods. Results: After treatment, compared with the control group, the NIHSS scores of the observation group were lower, the MMSE and ADL scores were significantly higher, the TCM symptom scores were lower than those of the control group, the MoCA scores of all dimensions were lower than those of the control group, and the total effective rate was higher than the control group. group (P<0.05). Conclusion: In the clinical treatment of patients with cognitive impairment after stroke, dietary nursing intervention can improve the patients' swallowing disorders, reduce the incidence of complications, and the patients will also give high recognition to the dietary nursing work.

The discovery of non-coding RNAs has opened up a new field in human diseases research because of their critical role in regulating cellular processes. This review focuses on the micro-RNA biogenesis, expression, and function in cancer pathogenesis with miRNAs acting as tumour suppressors or oncogenes (oncomiRs), and the therapeutic approaches such as miRNA mimics and molecules targeting miRNAs (antimiRs).

Objective: To observe the effect of traditional Chinese medicine nursing intervention on coronary heart disease (full name coronary atherosclerotic heart disease) angina pectoris. Methods: A total of 62 patients with coronary atherosclerotic heart disease and angina pectoris were selected, and the patients in the observation group were treated with traditional Chinese medicine nursing intervention and routine nursing. The patients in the control group received routine care, and the data between the two groups were compared. Results: Compared with the patients in the control group, it can be seen that the total effective rate of nursing, the average number of angina attacks, the duration of angina pectoris, the pain score, the time in bed, the length of hospital stay, and the anxiety score of the observation group were significantly improved, P<0.05.
Conclusion: TCM nursing intervention for coronary atherosclerotic heart disease angina pectoris is effective.

Objective: To analyze the effectiveness of relaxation therapy combined with traditional Chinese medicine fumigation and washing in preventing postoperative complications of hemorrhoids. Methods: From January 2021 to January 2022, 80 patients with hemorrhoids were selected from our hospital and randomly divided into observation group and control group. There were 40 cases in each group, and the control group was implemented with routine anorectal nursing methods. The patients in the observation group were treated with relaxation therapy combined with traditional Chinese medicine fumigation and washing, and the recovery effect of the patients in the two groups was observed. Results: The total effective rate of patients in the observation group was 95.00%, and that in the control group was 80.00%. In terms of resting pressure of the anal canal, maximum systolic pressure of the anal canal, longest contraction time of the anal canal, and wound healing time, the indexes of the observation group were all significant It was better than the control group (P<0.05), the nursing satisfaction (95.00%) of the observation group was higher, and the incidence of postoperative complications (2.50%) was also lower (P<0.05). Conclusion: In the treatment of hemorrhoid patients, relaxation therapy combined with traditional Chinese medicine fumigation and washing can improve the condition and prevent postoperative complications. It has high clinical effectiveness and can be promoted.

Pulmonary disease has long been a major problem in the world medical community. Common drugs for the treatment of pulmonary diseases, such as albuterol and pirfenidone, have many side effects in clinical use. Therefore, it is of great significance to find new safe drugs to solve the clinical disadvantages of Western medicine. At present, increasing numbers of medicinal plant extracts have been testified to be effective in clinical trials of pulmonary diseases. The unique physiological structure of the lung provides convenience for aerosol inhalation therapy, and avoids adverse reactions caused by oral and injection administration. This review article aims to introduce the application of some medicinal plants in the treatment of lung diseases. The combination of medicinal plants and aerosol inhalation drug delivery system can improve the targeting, safety and effectiveness of drugs. With the development of technology and experience accumulation, aerosol inhalation treatment of medicinal plants brings hope for the treatment of pulmonary diseases.

Radioactive iodine 125 particles implantation has been widely used in the treatment of various malignant tumors, and obtained satisfactory therapeutic effects, recent studies have shown that 3D printing template auxiliary iodine 125 particles implantation can better guarantee the preoperative postoperative dose the consistency and accuracy of this article reviewed the 3D printing template auxiliary iodine 125 particles into the feasibility of the treatment of malignant tumor, The dose distribution difference of ¹²⁵I seed implantation in 3D assisted implantation and old unarmed implantation was compared, which provided a reliable method. The foundation of RISI standardization implementation assisted by 3D printing templates.

Objective: To explore the clinical effect of applying modified Maxing Shigan decoction in the treatment of children with bronchopneumonia. Methods: The research work was carried out in our hospital from June 2021 to June 2022, and a total of 100 patients were selected as the research objects. The patients were all children with bronchopneumonia, and the selected patients were divided into two groups (based on different treatment methods). Among them, 50 were treated with conventional western medicine (control group), and the other 50 were treated with modified Maxing Shigan decoction (experimental group). The clinical effects of different treatment methods were compared and analyzed. Results: The cough reduction time, the fever subsidence time and the lung rales subsidence time of the children in the experimental group were all shorter than those in the control group, and the recovery speed was faster. All data indicators were statistically different from those in the control group (P <0.05). Moreover, the scores of pulmonary function indexes such as FEV1, FEF and FVC in the experimental group after treatment were lower than those in the control group, and the difference was significant with that in the control group, P<0.05. The treatment effective rate was 98.00% in the experimental group and 84.00% in the control group. There was a significant difference in the effective rate between the two groups, P<0.05, which was statistically significant. Conclusion: The application of Modified Maxing Shigan Decoction in the treatment of children with bronchopneumonia has a significant effect, which can improve the clinical efficiency, improve the lung function of children, and promote the recovery of children, with high application value.

Objective To dig herbs and prescriptions with potential good medicinal value in ancient prescriptions of traditional Chinese medicine (TCM) based on data mining and network pharmacology. Method: Firstly, all published literature related to traditional Chinese ancient medicine prescriptions for treatment of T2DM were screen out form major Chinese databases from the beginning of establishment to June 2021, according to a formulated inclusion and exclusion criteria. Then the herbs and prescriptions among them used for treatment of T2DM were extracted and summarized and were ready to construct the data set. Python programming was used to perform frequency statistics of traditional Chinese medicines. Subsequently, Apriori algorithm was adopted to establish association rules to match high-frequency medicinal materials, in order to screen out high-scoring drug pairs. Next, systematic pharmacology methods was applied and the active ingredients and targets for each herb were searched out from TCMSP, ECTM and other traditional herb pharmacological databases. Moreover, type 2 diabetes-related target genes were screen out from Genecards, OMIM , PharmGkb and TTD databases, and the disease-related targets were obtained through Venn2.1; the pathway analysis on Kyoto Encyclopedia of Genes and Genomes (KEGG ) for each herb using R language and Bioconductor bioinformatics software package; A scoring formula was established based on the enrichment of drug target genes to disease-related genes and the scores about all selected herbs and prescriptions were calculated through the formula; the score was sorted and those herbs and prescriptions with higher scores were potential good clinical values. Results: 700 prescriptions were finally screened out and Astragalus was a high-frequency herb. The highest correlation of paired drug obtained from the correlation analysis was Astragalus membranaceus-Rehmannia glutinous. Through the KEGG pathway enrichment analysis and scoring, the highest score herb and prescription were Gorgon Fruit and Warming Yang got respectively. In addition, Astragalus membranaceous and Xiaoke formula, which are known to be commonly used in the treatment of T2DM, were ranked higher scored groups, and some top-ranked ones were not commonly used, such as herb Gorgon Fruit, and prescription Warming Yang. Conclusion: These results demonstrated that this research method has a certain value and significance for digging potential good clinical value of herbs and prescriptions from the available TCM database, which also provides a positive reference values for experimental research as well as clinical drug uses.

Objective: To observe the effect of Huoxue Tongluo Qingnao Decoction in the treatment of patients with transient cerebral ischemic attack vertigo. Methods: The author selected 60 patients with transient cerebral ischemic attack vertigo. The patients in the observation group were treated with Huoxue Tongluo Qingnao Decoction combined with conventional treatment, and the patients in the control group were treated with conventional treatment. Results: Compared with the patients in the control group, it can be concluded that the clinical total effective rate, the score of vertigo symptoms after treatment, and the score of apoplexy symptoms after treatment in the observation group were significantly improved, P<0.05; Aura symptom score, P>0.05. Conclusion: Huoxue Tongluo Qingnao Decoction is used in the treatment of transient cerebral ischemic attack vertigo, and the effect is ideal.

Objective: To observe the curative effect of Buyang Huanwu Decoction and Plum Blossom Needle percussion for hemiplegia due to cerebral infarction. Methods: The author selected 60 hemiplegic patients with cerebral infarction, and the observation group was treated with Buyang Huanwu Decoction combined with plum blossom acupuncture. The control group was treated with plum blossom acupuncture, and the curative effects of the two groups were compared. Results: Comparing the patients in the control group, it can be seen that the TCM symptom scores of the patients in the observation group decreased, and the neurological deficits of the patients in the observation group improved. The functional independence assessment results of the observation group were improved, and the serum inflammatory factors of the observation group were improved after treatment. The peripheral blood CTRP9 and SES levels of the observation group were improved after treatment, and the observation group had a higher curative effect, P<0.05; the TCM symptom scores, neurological deficits, functional independence assessment results, serum serum levels were compared between the two groups before treatment. Inflammatory factors and the levels of CTRP9 and SES in peripheral blood, P>0.05. Conclusion: Hemiplegia due to cerebral infarction is treated with Buyang Huanwu Decoction and Plum Blossom Needle, and the effect is ideal.

The COVID-19 virus is a rapidly spreading epidemic that threatens the world. Since its discovery, there have been fewer studies on the combination of COVID-19 and diabetes, and the complications of COVID-19 are closely related to diabetes. The findings showed that diabetes, high blood pressure, and cholesterol levels were significantly associated with the severity of COVID-19, i.e. people with diabetes were more likely to contract COVID-19, especially those with severe acute respiratory distress. This comorbidity has been studied to be associated with compromised innate immunity and excessive proinflammatory cytokine responses involving IL-6 and TNF-α in uncontrolled diabetes mellitus (DM). The condition worsens if there are other comorbidities, such as high blood pressure, chronic kidney disease, or coronary artery disease. These comorbidities often coexist with diabetes and are associated with more aggressive COVID-19 infections. This is because the most common complications of the new coronavirus are renal tubular necrosis and pancreatic islet B cell damage, so the treatment and prognosis of diabetes can also cause adverse reactions and worsen the condition of diabetic patients to a certain extent. A search of relevant literature and studies shows that, when treating patients with the disease, medical staff should implement early and aggressive management of diabetes to prevent adverse outcomes. In conclusion, the novel coronavirus worsens diabetes, and elevated blood sugar worsens pneumonia. Therefore, the control of diabetes and its complications should be prioritized for patients with pneumonia complicated by novel coronavirus infection, and then the disease caused by COVID-19 should be controlled and treated.

Objective: To observe the effect of Buyang Huanwu Decoction in patients with acute cerebral infarction. Methods: The author selected 50 patients with acute cerebral infarction for data research. The patients in the observation group were treated with Buyang Huanwu Decoction and conventional treatment. The patients in the control group were treated with conventional treatment, and the curative effects of the two groups were compared. Results: Comparing the patients in the control group, it can be seen that the NIHSS scores and clinical treatment effects of the patients in the observation group after treatment. After treatment, the scores of main syndromes, BI scores after treatment, breath-holding index after treatment, cerebrovascular reserve function after treatment, and increase rate of average blood flow velocity after treatment were all significantly improved, P<0.05. The NIHSS scores, main syndrome scores, BI scores, breath-holding index, cerebrovascular reserve function, and mean blood flow velocity increase rate were compared between the two groups before treatment, P<0.05. Conclusion: Patients with acute cerebral infarction were treated with Buyang Huanwu Decoction, and the clinical effect was ideal.

Medical endoscope can effectively diagnose pathological organs in patients. In the process of medical endoscope interventional diagnosis and treatment, the diagnosis and treatment results mainly rely on its design structure and imaging principle, combined with medical optoelectronics, to directly observe the body cavity and internal organ cavity In this paper, the development of medical endoscope is introduced, and the basic working principle and application of ultrasonic endoscope are briefly analyzed, and the development trend of ultrasonic endoscope in the future is envisaged.

Infant phototherapy incubator is widely used in medical institutions to reduce the concentration of bilirubin in the body of infant while maintaining the body temperature of the infant. This article presents a novel design of calibration procedure to measure the instruments’ metrological parameters such as "error of total irradiance for bilirubin after pre-ageing", "relative local distribution of total irradiance for bilirubin after pre-ageing", "uniformity of incubator temperature", "accuracy of skin temperature sensor", "relative humidity indication error" and "accuracy of oxygen sensor" in order to ensure the accuracy and reliability of infant phototherapy incubator. The experimental results show that the calibration procedure presented in this article can ensure the metrological traceability of infant phototherapy incubators in daily use.

Atomic force microscope (AFM) provides a number of significant benefits, including ultrahigh imaging resolution, a compact and non-destructive sample preparation technique, and the ability to detect materials in real time, among others. In biological and medical disciplines, AFM has been used to evaluate a variety of physical and chemical parameters, such as cell stiffness, average roughness of cell surfaces, and surface composition. The data are used to assess whether or not people have a certain disease, particularly cancer. Xu studied cellular migratory and invasiveness potential using cell surface stiffness as a biomarker. Guo used average cell surface roughness to reconstruct the dynamic changes in endothelial cell membrane structure that occur during diabetes. Under the AFM basic mode and the AM-FM visco-elastic mapping mode, González-Dominguez discovered the HIV protein capsid inside the lipid membrane. These polls present a rosy picture of medical treatment, particularly in terms of illness diagnosis.

Optical tweezers (OT) are increasingly being used in neuroscience research. Neurons are studied on a sub-molecular and molecular scale, and thus the neural network system of the brain is studied. The complex properties of the brain itself and the difficulties of operating OT deep within the brain have made the development of OT technology relatively slow compared to other biotechnologies. However, the ease with which OT can be combined with other techniques is leading to the rapid development of research into cancer and neurodegenerative diseases. In this insight, relevant OT concepts based on neuroscience are described, other types of OT related to the field of neuroscience are introduced, and experiments related to cancer and neurodegenerative diseases are described.

The ability to study fundamental processes associated with cells and single molecules has changed considerably because of technological developments, especially the optical tweezer and atomic force microscope (AFM), in the fields of chemical and biological systems. This paper investigates the subject of the application of optical tweezers and AFM for the detection of single cells and single molecular layers by collecting data from previous experiments and analysing the data statistically and graphically. Based on the collection and statistics of several experimental data, it has been shown that by using laser beams to capture and manipulate microscopic particles, optical tweezers can be used for the analysis of cancer and sickle cell diseases, and can provide insight into the way DNA is formed and characterised. In addition, AFM has yielded important results in the study of polymer transport and chemical bonding. Both are important for gaining insight into the specific recognition of biological and chemical processes at the single-molecule level.

Objective To understand the status quo of health literacy and its influencing factors of college students in Guangdong, so as to provide scientific evidence for formulating effective intervention measures and policies. Methods Stratified cluster random sampling was used to conduct a survey on health literacy among college students in Guangdong Province in 2021. Logistic regression was used to analyse the influencing factors of students' health literacy level. Results The total level of college students' health literacy is 45.3%; From the three dimensions of health literacy, 51.3% of Guangdong college students have health knowledge and conceptual literacy, 47.2% of healthy lifestyle and behaviour, and 40.8% of health skills literacy. From high to low, the awareness rates of the six types of health knowledge are scientific health concept (60.9%), prevention and control of infectious diseases (52.3%), safety and first aid (49.6%), prevention and control of chronic diseases (46.8%), basic medical care (41.4%), and health information (38.5%). And there are significant differences among students of different grades, home address, self-rated health status and whether they have taken health-related courses (P <0.05) in the aspect of health literacy. Conclusion Guangdong college students' health literacy still needs to be improved, especially in health skills, basic medical care and health information literacy. The government, families and colleges should work together to improve college students' health literacy.

To better estimate the productivity levels of terrestrial ecosystems at global and regional spatial scales, we used FLUXNET 2015 flux site data, GOME-F chlorophyll fluorescence product, ISLSCP II vegetation dataset, MODIS vegetation index product and surface reflectance product to introduce temperature stress factor, water stress factor, and solar zenith angle into the model. In addition, we also calculated fesc by approximating vegetation index, near-infrared reflectance and photosynthetically active radiation components to enhance the model accuracy. The results show that the five vegetation types have improved estimation results compared with the traditional empirical linear mode. The accuracy of the evergreen broadleaf forest type improved the most, with R² increasing to 0.7331. The improvement of model accuracy is more considerable when the influence factor of solar zenith angle is added to the model, and the model with the addition of solar zenith angle is closer to the measured values than the model without the addition of solar zenith angle. The model proposed in this paper can better estimate the vegetation production level of different vegetation types.

In classifying chest X-rays (CXR), machine learning, particularly transfer learning, has been widely implemented and has demonstrated an excellent range of accuracy. In this study, ResNet-50, ResNet-101, and VGG16, three popular transfer learning models, were compared in a CXR classification task. This study used a dataset containing CXRs of 3616 COVID- 19-positive cases, CXRs of 1345 viral pneumonia cases, CXRs of 6012 lung opacity (non-Covid lung infection) cases, as well as CXRs of 10,192 normal individuals and corresponding lung masks. The study used Keras and TensorFlow to import the pre-trained models and compare them using the exact same training sets, testing sets, and validation sets. The ResNet-50 achieves a classification accuracy of 90%, the ResNet-101 achieves a classification accuracy of 91%, and the VGG16 achieves a classification accuracy of 89%. This research reached the conclusion that ResNet-101 performs better in such image multiclassification tasks. We speculate that this is because ResNet-101 was trained based on residual learning which is easy to optimize.

Arrhythmia is a common cardiac disease. Hence the diagnosis and treatment of arrhythmia is important problem for public health in our country. For the auxiliary diagnosis of devices, the features of arrhythmia are used to recognize the cardiac disease. Therefore, how to extract the effective features of arrhythmia is the key problem. In this paper, a variation rate measure (VRM) for arrhythmia is presented. Via the quantitative index VRM, the change degree of RR intervals for arrhythmia can be described effectively. Experiment results demonstrate that the arrhythmia can be recognized and classified effectively. Hence, VRM can be as a valid feature of the arrhythmia.

Natural immunity is an important way for the human body to resist viral infection. In the process of natural immune antiviral, viral nucleic acids can be recognized by Toll-like Receptors (TLR receptors), RIG-1 Like Receptors (RLRs receptors), cytoplasmic DNA receptors and mitochondrial antiviral-signaling protein receptors (MAVS receptors) within immune cells, and then the information is transmitted to downstream signal molecules, so that immune cells generate IFN- 1 ( type 1 interferon ).In this process, ubiquitination modifications play a wide role in regulating natural immune antiviral processes, thereby maintaining stability in the human body. This paper mainly introduces the four specific receptors of TLR receptor, RLRs receptor, cytoplasmic DNA receptor and MAVS receptor, as well as the natural immune antiviral pathways mediated by these receptors, and further elaborates the role of ubiquitination modification in these pathways, aiming to lay a foundation for the study of natural immune antiviral pathways.

In clinical practice, nerve root compromise mainly refers to diseases in which the protrusion of the nucleus pulposus of the spinal cord leads to irritation or compression of the spinal cord and spinal nerve roots, causing corresponding neurological symptoms. Magnetic Resonance Imaging (MRI) of the lumbar spine is an important tool to grade the nerve root compromise. The traditional diagnosis method mainly relies on manual identification by doctors, so it is inefficient. At present, the computer aided diagnosis system based on deep learning has been widely used in the medical field, and the diagnosis accuracy of many diseases has surpassed that of clinicians. Vision Transformers have been successfully applied to several computer vision problems, achieving state-of-the-art results. These advancements in computer vision have resulted in a growing interest in Transformers in the medical image processing field. Vision Transformers can capture global context, but lack the local receptive field of CNNs and is relatively weak in modeling local spatial context. Many researchers have tried and achieved preliminary results, but there is still a long way to go before it can be widely used in the medical field like CNN. This paper aims to expand the application of visual Transformer in the field of medical image processing, using two convolution methods, atrous convolution embedding and depthwise atrous convolution projection, to improve the Swin Transformer for automatic classification of nerve root compromise in MR images of Lumbar Spine. The introduction of convolution effectively improves the performance of the Swin Transformer model, and enables the network to better take into account global and local context information. Our method achieved 0.8234 accuracy and 0.8185 F1 score on test set, which improved by 1.31% and 1.94% respectively compared to the baseline model.

Bone tissue, as an important tissue structure of human body, plays an great role. Bone defects caused by trauma, infection and tumour resection are difficult to be repaired by themselves. Traditional methods for repairing bone defects include autograft and allograft. However, these methods have some problems such as limited source and immune rejection. In recent years, bone tissue engineering has attracted much attention due to its sufficient supply and no risk of infection, and is expected to replace traditional bone grafting. In bone tissue engineering, seed cells are cultured on scaffolds and transplanted into bone defects to repair bone defects. In this paper, the research progress of the three elements of bone tissue engineering, namely seed cells, scaffold materials and growth factors, was summarized by reading the literature, aiming to further promote the development of bone repair field.

The spinal cord stimulator (SCS) is a highly effective technology for treating neurological illnesses. It is mainly composed of a pulse generator and electrode. The electrode selection is crucial because it ensures not only the proper transmission of stimulation but also the safety of the human body. This paper primarily introduces the current market electrodes, their benefits, drawbacks, and future development directions, as well as potential difficulties and biocompatibility. This paper intends to provide readers with a more thorough understanding of SCS electrodes and their problems, so that they may make more informed decisions about SCS electrode development in the future.

As a kind of neurological disease therapy without destroying nerve tissue, electrical nerve stimulation technology has significant efficacy in the treatment of chronic pain, Parkinson's disease, epilepsy, obsessive-compulsive disorder and other functional neurological diseases and mental diseases. As the result of electrical nerve stimulation technology, implantable neuro-stimulator devices thus have a wide application prospect. This paper introduces the current application of various kinds of implantable neuro-stimulator worldwide and some advances in the research of implantable neurostimulator, and also analyzes its development trend. The purpose of this paper is to help readers to have a comprehensive understanding of the basic working principle of main kinds of neural electrical stimulators, and can be a reference for the future development of this technology.

Traumatic brain injury (TBI) is a leading cause of death and disability throughout the world. Its primary and secondary damage can lead to impaired neurological function and serious complications such as post-traumatic stress disorder, cognitive or behavioural impairment, epilepsy and neurodegenerative diseases. This article outlines the main mechanisms of secondary brain injury and provides an updated direction for potential neuroprotective treatments. Among other things, current clinical studies suggest that vagus nerve stimulation (VNS) may reduce brain injury after TBI by inhibiting oxidative stress, inflammation and apoptosis, promote recovery of consciousness and cognitive function after experimental TBI, enhance motor and cognitive recovery, reduce brain oedema and inflammation, reduce blood-brain barrier disruption, and confer neuroprotection. In addition, the literature describes deep brain stimulation, gene therapy targeting the combined regeneration of stem cells and biomaterials for TB repair, novel neuroprotective drugs and nanomaterials enabling electrophysiological recording tests and biochemical modulation. Although the data suggest that these potential therapeutic approaches are beneficial for the eventual outcome of TBI, their availability for good use in clinical trials needs to be further explored.

Neuropathic pain impacts 7-10% of the general population and seriously undermines quality of life despite available medications. Although initially approved to treat chronic neuropathic pain as an alternative to conventional medical management, spinal cord stimulation (SCS) is expanding its application prospect to the treatment for an assortment of indications including ischemic pain and neurodegenerative disorders, with new stimulation modalities, techniques, and electrode materials emerging every year. Despite its proven efficacy and cost-effectiveness when compared with the long-term application of insufficiently effective and potentially harmful medications, SCS is still largely neglected by pain physicians and neurosurgeons worldwide because of the exorbitant cost of the devices and possible complications. The mechanism of action, constituents and clinical applications, and performance of SCS are here reviewed, with a special focus on five indications amenable to SCS treatment, including failed back surgery syndrome (FBSS), complex regional pain syndrome (CRPS), painful diabetic neuropathy (PDN), critical limb ischemia (CLI) and Parkinson’s disease (PD). Among all the indications, only FBSS and CRPS have a mature application scenario, and SCS treatment for PDN has just recently been approved by FDA. The clinical study of more conditions that may benefit from SCS treatment, such as CLI and PD, is still underway. Market expectations and recent developments of SCS are further discussed to provide an outlook for the future trends of spinal cord stimulation.

Objective: To explore the association between family/friend social support and mental health (cognitive and emotional well-being) in the elderly with hypertension. Methods: A total of 173 elderly patients with hypertension aged 60 to 81 years old (76 males and 97 females) were selected from community hospitals. The social support was measured with a self-prepared questionnaire. The cognitive well-being was measured with the immediate and delayed word recall, number span, verbal fluency, and backward counting tasks, while the emotional well-being measured with a 12-item affective wordlist. Results: The main results of univariate analysis showed that family support was associated with more positive affect and less negative affect (NA) (ps < 0.05); friend social support was associated with better cognitive well-being and more positive affect (PA). The result of multiple linear regression analysis showed that family support could positively predict PA and negatively predict NA (β₁ = 0.39, p₁ = 0.003; β₂ = -0.25, p₂ = 0.004); while friend support positively predict cognitive well-being (β = 0.39, p < 0.001). Conclusion: Family and friend support play different roles on the two facets of mental health of the elderly with hypertension. Family support had greater contribution on emotional well-being, while friend support contributed more to cognitive well-being.

Sars-CoV-2 is the causative agent responsible for the global pandemic of COVID-19. Bioinformatics tools are used to sequence the viral genome, identify SARS-CoV-2 from all host genomes, and detect its variants. There is no all-in-one tool that can automatically analyse complete sequences, so different bioinformatics resources are needed to work together for detection and characterisation. This paper discusses the use of next-generation sequencing for virus definition and characterization.

Autism (classical autism) is a neurodevelopmental disorder which is characterized by language delay, social impairment, repeated behaviors and hypophrenia in clinic. Recently, researches on autism have increased for the increasing prevalence of autism around the world. Genetic factors and environmental factors are considered as two main etiologies of autism. Hundreds of genes that are related to dendrite growth, synapse formation and neuronal function are identified as autism-associated genes. It is hard to totally understand the pathogenesis of autism due to the heterogeneous etiology of autism. Shank3 gene encodes an important scaffold protein which is involved in the formation of PSD. Mutations of Shank3 gene are strongly related to autism. Especially, the 22q13.3-deletion that results in the haploinsufficiency of SHANK3 leads to Phelan-McDermid syndrome. In order to find out how Shank3 mutations cause autism in molecular level, this review summarizes the relationship between SHANK3 and signaling pathways that are influenced by Shank3 mutations with current literature. In addition, possible intervening strategies towards SHANK3-related autism are collected for their potential in treating autism.

In general, healthcare spending mainly refers to medical insurance, which keeps raising from 1970 to 2020. Therefore, it is crucial to predict the costs accurately. Based on the multivariate linear regression, this paper constructs a quantitative model to investigate the cost of medical care. The data used for research were gathered from Massachusetts health insurance centre. To avoid overfitting effects and simplify the model, only parts of the variables were chosen for prediction model. In the research, the Y variable was changed into log(y), and all X variables were used to fit a linear regression model. According to the analysis, the healthcare cost has a significant relationship with smoking. These results shed light on guiding further research exploring the healthcare cost.

Individual onset prediction models for diabetes are widely recognized as an effective tool for ascertaining the risky population of diabetes and for selecting intervention programs, which can provide a basis for health management, disease prevention decisions and evaluation of intervention programs. Currently, many countries have established individual prediction models for diabetes in different populations, however, due to the lack of cohort data, it is not yet possible to predict the incidence of diabetes in different populations. Meanwhile, due to the lack of data on different populations, effective topometric models for individual risk of diabetes have not yet been established. Therefore, it is necessary to establish suitable prediction models for the onset of diabetes at the individual level in adults. In this study, regression models were developed to compare different possible causes of diabetes, and according to the individual results of the chances of getting diabetes in 768 researchers, it was found that there were more cases of high BMI, diabetic pedigree function and blood glucose levels. Because this is a new disease in developing countries, there is a potential improvement for clinical prediction models to be developed. I believe that this model can be used to generate credible predictions regarding type 2 diabetes and ultimately improve on existing preventive interventions or come up with more acceptable models to lower diabetes's incidence and expense.

As an interdisciplinary science, bioinformatics draws methods and resources from the following disciplines by extracting valuable information and patterns: computer science, which provides the hardware and software for analysis; molecular biology, which is the source of the data to be analyzed; and mathematics, where the algorithms for data analysis originate. Bioinformatics greatly benefits omics research. It improves our knowledge of biological systems and contributes to our deep understanding of the genomes, growth, and development of microorganisms, animals, and plants. Using bioinformatics, we can advance human welfare by revolutionizing breeding methods, developing new drugs, or creating novel treatments for diseases. This article outlines and theoretical underpinnings of bioinformatics, analyzes its applications in agriculture and medicine in detail, identifies its unsolved issues, and puts forwards corresponding suggestions.

Stroke is known as a disease that can cause patients’ limbs to be weak. The disease will be more serious when it is developed to Cerebral infarction. It can lead to facial numb, barylalia, blurred vision and Nausea. This article investigates the feasibility of judging whether a person will have stroke disease based on different examined factors. Specifically, the R project will be utilized to analyse a dataset by logistic regression, dummy variable analysis and Lasso regression. According to the analysis, the model of predicting stroke disease and its simplification will be presented. Based on the evaluation, main causalities of stroke will be clarified. Moreover, the percentage of right prediction of the prediction will be recorded to show the accuracy of the result. These results shed light on offering the possible causality criterions of predicting stroke, which paves simplify path to predict stroke.

According to statistics, about one-third of the world's deaths are caused by cardiovascular diseases, which have a significant health impact on modern young people. Therefore, the most critical issues in the medical field are the prevention and diagnosis of heart system diseases. Electrocardiogram (ECG) is currently one of the most common diagnostic techniques for cardiovascular diseases. This article reviews some denoising methods of ECG signals, including traditional denoising methods, wavelet transform denoising methods, based on FIR Denoising method, and elaborates the classification technology and improvement strategies of related ECG features, such as Random Forest(RF), Back Propagation(BP), and analyzes the advantages and disadvantages of various algorithms. Finally, all the preprocessing algorithms and classification methods of ECG are summarized, and future development has prospected.

Near-infrared (NIR) spectroscopy is an analytical technique characterizing molecular structure by measuring the absorption bands produced by overtones and combined excitations. Due to the advantages of the spectral analysis method, it grows fast in recent years and is widely used in the field of bioscience. The present review aims to provide an overview of NIR spectroscopy in a diverse field of bio-applications, including bioanalysis or biomedical diagnosis of body fluids, biological samples and plant medicines. Challenges and perspectives for NIR spectroscopy are also described.

Tardigrades are tiny semi-terrestrial animals with an extremely strong tolerance to stress. They are famous for their ability to enter the state of cryptobiosis, in which metabolism stops reversibly, providing tardigrades with the potential to survive conditions under extreme stress. Research into the mechanisms of stress tolerance and cryptobiosis in tardigrades has aroused wide attention, as the discoveries can bring enlightenments to different fields, such as the development of aerospace biotechnology. Due to its great importance, the review below aims to provide an insight into the new studies in stress tolerance in tardigrades, as this field still lacks an overview of the recent progress in these years. The essay begins with an introduction to cryptobiosis in tardigrades. It then describes progress in four parts on tardigrades stress tolerance, specifically the drought, radiation, ice, and hunger attacks. The final part summarizes and presents a vision for the future in tardigrades stress tolerance study. Besides having insights into the tardigrades’ strong tolerance to extreme conditions, this paper also provides a better understanding in the future application of the potential mechanism of stress tolerance in tardigrades.

With the change in people's lifestyles and the popularity of smartphones, more and more people suffer from cervical spondylosis. The change in cervical curvature is closely related to cervical spondylosis. This paper compares the existing cervical curvature measurement techniques and publishes a questionnaire through the network to explore the application of cervical curvature measurement technology in daily life, people's attention to the health of the cervical vertebra, and the willingness to consume related products. The survey results show that the existing cervical curvature measurement technology still need to be improved, people pay more attention to the health of the cervical vertebra and have a strong willingness to consume products such as cervical curvature measuring instruments. Finally, it is concluded that the research on the measurement technology of cervical curvature is of great significance at both the medical level and the health level of the whole people.

Thirty healthy college students (16 males and 14 females) at a university were recruited as study subjects. A pressure algometer was used to measure the pressure pain threshold (PPT) and pressure pain tolerance (PTO) at the brachioradialis of the arm, the lower trapezius of the back and the vastus lateralis of the thigh. Analyzed gender and measurement position differences of PPT and PTO by repeated measures variance analysis methods. Ultimately, the normal reference value range of PPT and PTO were obtained. The results showed that the PPT and PTO were significantly different between the gender (P<0.001):the PPT and PTO were lower in females than in males; the PPT and PTO were significantly different between measurement position (0.001): the PPT and PTO were lower at the brachioradialis muscle and higher at the vastus lateralis muscle. Conclusion: The measurement of the PPT and PTO is influenced by factors such as gender and measurement position, performing pain measurement and pain assessment should focus on inter- and intra-individual differences in pain thresholds.

Aging is a phenomenon that refers to the decline of the body's functions over time, and it has always been a hot topic in the scientific community. With the continuous development of life sciences, the research on aging has gone deep into the molecular level. In this paper, we review the theory of aging and its molecular mechanism, summarize the strategies for removing senescent cells and improving the aging environment, and elucidate the cutting-edge anti-aging therapies, including stem cell therapy, exosome therapy, and targeted gene therapy. Aging-related proteins are mainly involved in the aging process by interacting with metabolites to activate related pathways, regulating the expression of aging-related genes, and repairing the damage. As an important monitoring and defensive system of the body, the immune system is closely related to aging, and the special relationship between the immune system and metabolism is increasingly recognized. In this paper, we focus on summarizing and reviewing the interrelationships among metabolism, proteins, genes and the immune system, and analyzing the effects of aging-related proteins on the aging process and the role of immune metabolism in the aging mechanism, so as to provide a reference for systematically understanding the mechanism of the aging process.

Drug addiction, or substance use disorder, is caused by interference of drugs with how neurons are sent, received or process neurotransmitters to one another. The use of drugs will cause cravings, and this is due to the stimulation of the brain’s reward system. Video game addiction, or Internet gaming disorder (IGD) is a common phenomenon especially in teenagers. The symptom of video game addiction is similar to drug addiction, which is the craving behavior of the patient. To resolve this issue, researchers have come up with many different solutions. One of the possible solutions is applying low frequency of Deep brain stimulation (DBS) and SCH23990 to the patient. This is a type of treatment for drug addictions, and it can only be done to treat video game addiction if proven that video game addiction and drug addiction have the same mechanism and disordered parts of the brain.

In recent years, antibiotic resistance develops very quickly, while it is difficult to find new antibiotics. It is speculated that by 2050, the number of deaths due to antibiotic resistance will exceed the number of cancer deaths, reaching 10 million, it seems that people will return to the pre-antibiotic era. The problem of drug resistance has become so serious that some researchers looking for alternatives to antibiotics have refocused their attention on phage therapy, a method of using bacterial viruses to cleave pathogens to achieve therapeutic effects. It has the advantages of specificity, lack of cross-resistance to antibiotics, an excellent curative effect on biofilm, short research time, and relatively low development cost. At present, there are more and more successful cases of phage therapy. This paper will review the phage therapy, analyze its advantages and disadvantages so that readers can better understand phage therapy to promote the development of phage-based treatment of bacterial infection.

As an inherent physiological signal of the human body, the PPG signal contains a large amount of physiological information, but it is often interfered with by various factors during the detection, which affects the subsequent acquisition of physiological data. This paper proposed a denoising algorithm based on morphological filtering and double-density dual-tree wavelet thresholding to address interference problems such as baseline drift and high-frequency noise in PPG signal acquisition. The results of the control experiment with traditional discrete wavelets show that our algorithm can remove high-frequency noise and baseline drift more effectively in the presence of intense noise, with an average additional increase of 1.7483 in signal-to-noise ratio and an average additional increase of 38.86% in mean square error reduction, which can facilitate the subsequent signal processing and the establishment of blood component concentration models, etc. The algorithm structure is relatively simple and of low computational complexity, which can provide better technical support for real-time waveform analysis.

In acidic condition with pH=3.6, Fe³⁺ can react with potassium thiocyanate to form the red complexes of Fe(SCN)²⁺. Hydrosulfuryl(-SH) in methimazole molecule can reduce Fe³⁺ to Fe²⁺, which results in the fading of the red complexes of Fe(SCN)²⁺, and the fading degree is directly proportional to the addition of methimazole. So, the content of methimazole can be indirectly measured by measuring the decrease value of absorbance of the red complexes of Fe(SCN)²⁺. Accordingly, a new method for the fading spectrophotometric determination of methimazole using Fe(Ш)-potassium thiocyanate has been established. The method has been applied to the determination of methimazole in drugs, and the results are basically consistent with the results of pharmacopoeia.

Background: Electronic cigarettes are increasingly preferred by young people today, and most people use them to quit smoking. However, the impact of e-cigarettes on human oral health is still controversial. It is debatable whether e-cigarettes are as safe, regulated, and harmless as one might believe, and whether they have potential side effects on the human body. Objective: In this paper, we reviewed the literature related to traditional cigarettes and e-cigarettes and oral health in recent years, and investigate the impact of e-cigarettes and traditional cigarettes on oral health from four aspects: analysis of the composition of e-cigarettes and traditional cigarettes, effects on oral cells, oral flora, and clinical oral health. Conclusion: Both e-cigarettes and traditional cigarettes have an impact on a person's oral health. However, extensive experimental data is needed to prove whether e-cigarette aerosol is more harmful to the oral cavity than cigarette smoke (CS).

Objective: Through experiments and simulation calculations, this paper aims to study the influence of temperature effect on the stress distribution of human lower limbs during sand therapy, so as to provide a theoretical basis for revealing the treatment mechanism of sand therapy. Methods: A sand burial experiment was carried out in the indoor four-season sand therapy system established in the Biomechanics and Heat Transfer Laboratory of the School of Mechanical Engineering of Xinjiang University by simulating the sand therapy field of Xinjiang Turpan Uygur Hospital. The subjects were divided into two groups, each with 16 people. The initial sand burial temperature was controlled at 45℃ and 50℃ respectively, the sand burial thickness was controlled to be 10 cm. Continuous sand therapy was given for ten days, once a day and each lasting 30 minutes. Dynamic changes in pressure and temperature of the lower limb skin surface (in upper, lower, left, right test points) were continuously recorded under the two temperatures and statistically analyzed. The three-dimensional model of the human lower limbs was reconstructed and subject to finite element simulation calculations. Results: ① When the sand burial thickness is 10cm and the initial sand burial temperature is 50℃, the average surface stress of the four test points (upper, lower, left and right) on the human lower limb skin surface increased by 0.093Kpa, 0.173Kpa, 0.167Kpa, 0.169Kpa, respectively compared with those under initial temperature of 45℃. The relationship between temperature and stress is approximately hyperbolic. That is, the stress gradually increases with the decrease of temperature; ②The simulation calculation shows that the maximum equivalent stress of the lower limbs is distributed at the point where muscles contact bones. This is in line with the characteristics of statically indeterminate structure. Compared with 45℃, under the initial sand burial temperature 50℃, the maximum Von mises equivalent stress increased by 0.009Mpa, 0.017Mpa, 0.02Mpa, respectively when sand burial time was t=5min, t=15min, and t=30min. The maximum Von mises equivalent stress increased by 0.046Mpa during the 30min sand burial process. Conclusion: Experiments and simulation studies show that sand therapy temperature produces a certain effect on the lower limb stress of the human body. The temperature stress increases with the prolongation of sand burial time. The lower limb stress state of the human body changes dynamically, which facilitates the massage effect and the blood circulation of removing blood stasis. The higher the initial temperature is, the greater the temperature stress and the better the curative effect is. This carries certain guiding significance for understanding the thermal physical mechanism of sand therapy, guaranteeing the safety and comfort of patients during sand therapy and popularizing sand therapy.

Following by life and work with enormous variation, myopic incidence has increased at an incredible rate. Then, the understanding of myopia become an urgent project. In the decades of studying mechanism and treatment, it is making some progress in myopic onset and progression. After the progress, it is known that what is known about myopia is not far enough. The influencing factors can be generally divided into genetic and environmental factors. And, the treatment for myopia is composited by optics, pharmacology and surgery. This review summarized the latest progress and new presenting problems in the mechanism and treatment of myopia since the 20th century. This concise paper provides a brief blueprint for the future study of myopia.

Through the comparative test of nitrogen fertilizer, phosphate fertilizer and potassium fertilizer in the field, the effect of improving the utilization rate of nitrogen fertilizer, phosphorus fertilizer and potassium fertilizer in Luanzhou city was found out, and the zero growth of the utilization rate of chemical fertilizer was promoted in Luanzhou City.

Plant essential oils (EO) have a variety of biological activities such as anti-microbial, anti-cancer, anti-oxidant, analgesic and anti-inflammatory. EOs have shown to be effective in the treatment of neurodegenerative diseases such as Alzheimer's disease and in improving blood sugar in diabetic patients. However, the mood-regulating mechanisms of essential oils have not established. This article reviews the mood regulation mechanisms of essential oils and their applications and prospects in neurodegenerative diseases, diabetes and mood regulation.

To explore training effects of “living high-training low” on special movement quality of Men Freestyle Wrestlers. 14 excellent male wrestlers were randomly divided into two group: low-oxygen group—HiLo (n= 7) and control group—LoLo (n=7), and experiment was lasted for 4 weeks. Methods: HiLo group exposure for 10 hours in a hypoxic environment (14.2% ~ 14.8%O2) every day. The change of related indexs are separately examined before experiment, every weekend and after a week experiment, The results showed that, after the experiment (1 days) and the end of the experiment after 1 weeks, Hilo group and Lolo group athlete special strength index, the specific speed endurance index and special action speed index was improved in different degrees. compared with the after one day of test. after one week of test each special quality index of HiLo players were greatly improved. And the level of each special index of Hilo group of athletes have significant difference compared with the before test (P > 0.05) by paired T test,But there was no significant difference for the Lolo group athletes (P< 0.05).Conclusion:The immediate effect is not obvious of living high-training low (4weeks) for Men Freestyle Wrestlers pecial movement quality,But next week, effect is remarkable.

Traditional Chinese Medicine (TCM) is a unique medical system with thousands of years of history, which has been applied in various areas for diagnosing and curing diverse diseases. Though play an essential and multifarious role as TCM can in human health, it is solely defined as an alternative medical technique because of the unique medical system including; basic theory, diagnosis methods and therapy methods. Artificial Intelligence (AI), a computational embodied human intelligence, has greatly improved and made tremendous progress in various fields, which is named the force of the fourth scientific and technical revolution. After decades of study, AI technology has combined with TCM in some aspects, and achieved several valuable results. However, most results are only appropriate for special situations and databases, which cannot be used in the clinic. Thus, this article will analyze the reason why the current results of AI-assisted TCM cannot be used in clinics and state a new AI-assisted TCM diagnosis and treatment system

With the development of medical technology, there are also special databases for human understanding and data collection of various cells, and doctors' judgments on various diseases have become more accurate with the help of various technologies. This article will introduce the development of machine learning and the three stages of human development of cell recognition and the tools used to explain the importance of cell recognition. At the same time, this article will introduce the CNN model and the information retrieval CAD system to explain and find their medical response through research on the functions and working methods of the two models. The defects in use and the corresponding remedial measures, as well as discuss how to improve them, and whether the two models can be combined to make up for each other's shortcomings.

The current mainstream methods are to use 2D segmentation algorithms such as UNet and FCN to segment kidneys and tumors on a single slice of a patient, but these methods will lose more contextual information of the original image, which is not conducive to the improvement of segmentation accuracy. To solve this problem, this paper proposes an improved Res-UNet image segmentation algorithm (M-ResUNet) based on mask estimation and Res-UNet image segmentation algorithm. The algorithm first uses the mask estimation algorithm to obtain the context information and the region of interest of the image to be segmented, then uses the Res-UNet image segmentation algorithm to segment the kidney, and finally uses the image fusion algorithm to fuse the mask image and the segmented image. The algorithm makes the segmented images retain the accurate segmentation results in the segmented images to the greatest extent, and removes the inaccurate segmentation results in the segmented images. The experimental results show that the MResUNet kidney segmentation algorithm proposed in this paper has a certain improvement in the segmentation accuracy of the KITS19 kidney public dataset.

Tumor classification and diagnosis are not an easy task as novel research keeps emerging about what makes a tumor type unique. There are several ways to classify a tumor, such as molecular analysis as well as the usual ways where biopsies or physical examinations are used to diagnose cancer. Previous studies have been using DNA or messenger RNA features in tumor classification, but there are not a lot of specific studies in the area of tumor classification using microRNA (miRNA). As new investigations suggest, miRNA serves a crucial role in tumor growth and metastasis, so my investigation dives into the relationship between miRNA and tumor classification, which is still mostly unexplored. Here, using miRNA expression data from large cancer sequencing projects for over 10,000 patients, I build machine learning models to classify more than 30 different types of cancer. Two different algorithms, k-nearest neighbors and random forest are tested and benchmarked. For certain cancer types, the random forest model can be over 95% accurate. I further demonstrate that errors of the classifier come largely from tumors with similar cell-of-origin, such as digestive organ tumor stomach cancer are sometimes mislabeled as other digestive organ tumors like esophageal cancer or colon cancer. To explore how we can use the miRNA-based tumor classifier in a clinical setting, I further demonstrate that it is possible to reach near 95% accuracy with a minimal model of only 10 miRNA genes, which suggests that a small test kit for 10 miRNA genes can reach a comparable accuracy as the more expensive option of whole miRNA sequencing. Overall, this study suggests that miRNA expression can accurately predict tumor types and may be developed into clinical diagnostic kits.

In order to improve the low accuracy and poor reusability of camera parameter calibration, a camera parameter calibration optimization method based on Chaotic Sparrow Search Algorithm (SSA) is proposed. The method includes four steps: Firstly, the population is initialized by Tent chaotic sequence in order to improve the quality of the initial solution and the global search ability of the algorithm; Then, Gaussian mutation method is introduced to improve the local search ability and search accuracy; Thirdly, the Tent chaotic sequence is generated based on the search stagnation solution, and this chaotic sequence is used to carry out chaotic disturbance on some individuals trapped in local optimum, so that the algorithm jumps out of the limitation to continue searching, so as to obtain the initial estimation of the internal and external parameters of the camera, and then the operation interval of SSA is determined by the initial estimation; Finally, by establishing the average reprojection error equation and using SSA to calibrate and optimize the camera parameters in the determined interval, the smaller average reprojection error can be obtained. The experimental results show that the camera calibration parameter optimization method based on chaotic SSA has higher accuracy and better reusability, than Zhang Zhengyou calibration method and particle swarm calibration method.

With the development of information technology and the deepening of network application, the problem of network security is becoming more and more serious. The form of network security concept is also constantly sublimating and expanding. How to effectively protect important data information and improve computer network security is a problem that must be considered in modern security system and also needs to be determined. Although the security protection measures provided by database management can protect it to a certain extent, there are still loopholes. By analyzing the cause of system component failure and related security technology, a multi-layer database security model based on intrusion tolerance technology is abstracting, which can guarantee the availability, integrity and confidentiality of data under attack. In this paper, based on intrusion tolerance technology in the application of biological information analysis platform was designed, according to current situation of the development of modern computer networks and intrusion tolerance technology put forward its own understanding of existing problems, aims to accelerate intrusion tolerance technology in the application of biological information analysis platform, to further improve the construction of biological information platform.

Currently, aggressive breast cancer has become a difficult problem in the clinical treatment of breast cancer patients. Weighted Gene Co-expression Network Analysis (WGCNA) is widely used for genetic markers finding. Therefore, this paper studies the clustering method in WGCNA. In this paper, k-means clustering, maximum expectation clustering, hierarchical clustering and WGCNA commonly used in bioinformatics are selected to compare and verify the quality of clustering methods. Firstly, three clustering methods were applied in the WGCNA process. Then, the modules obtained from the three clusters were used to screen genetic markers using the centrality method. Finally, survival analysis was performed on the genetic markers obtained by each clustering method and WGCNA to verify whether the gene markers found by each clustering method combined with WGCNA had a good prognostic effect. Therefore, it can be concluded that hierarchical clustering can be replaced by K-means clustering.

In recent years there has been a surge in female Breast Cancer patients leading to an increase in the administration of Electronic Health Records (EHR) data during the treatment process. So far, mammogram examinations are the main means of breast cancer detection. The data obtained from such medical reports remains an important source for constructing AI diagnostic models for breast cancer. With a purpose of contributing and assisting doctors in clinical decision-making through provision of high-quality and efficient tumor diagnosis using AI, this paper explores and trains the breast tumor X-ray examination report, and constructs the breast tumor classification neural network (BTDNN) model to understand the auxiliary diagnosis of breast tumor. The proposed model (BTDNN) builds and uses a semantic network to define and structure the standard for breast cancer X-ray report medical entities and entity annotations which act as the standardized input of the model. Based on the semantic network, we also built a breast cancer diagnosis model based on Phrase level self-attention mechanism that uses Phrase level context technology to train the model for analysing medical reports in the same concept as a health care professional with original, local and global method context, in order to improve the prediction accuracy. As result, we compared our proposed model to several other models and concluded that combining the semantic and contextual technology could improve the final prediction accuracy of a medical diagnosis.

To study the interactive design of products for aging based on sensory enhancement, taking equipment of leg health care as the practice object. Starting from the physiological characteristics and behavioral logic of elderly users. Through methods of household interviews and behavior observation, this paper optimizes the visual, auditory and tactile perception of the leg health care device from the perspective of color, material and interaction design and completes the overall sensory enhancement interaction design of the aging leg health care device.

Accurate gastrointestinal (GI) lesions classification from endoscopic images is crucial in patient diagnosis. The scarcity of annotated training data limits the full clinical impact of supervised deep learning (DL) in clinical settings, which is usually limited due to the scarcity of annotated training data. To alleviate this effect of small data size, we propose a GI lesions classification method based on supervised contrastive representative learning, which creates representations of the lesion from many unannotated endoscopic images. We used 12,147 endoscopic images drawn from private and public sources. Data augmentation techniques are implemented with the encoder network and projector. Supervised contrastive loss is utilized as a loss hypermeter, and the final classification task is performed in the last phase. Our method achieves better lesion classification accuracy (96.4%) than another related state of the methods (self-supervised=94.6%, and cross entropy=93.8%). Future work will improve the robustness of the proposed method's automatic classification accuracy to detect lesion severity levels and implement the proposed approach in multi-modal medical imaging.

Driven by the increase in applications of Machine Learning in the medical industry and in biomedical engineering, we sought to aid in the creation of predictive models within the sports medicine field. In this paper, we look at a set of binary data of extrinsic factors that contribute to anterior cruciate ligament (ACL) injuries. We use multiple algorithms to select the most relevant feature that can be used to aid in making a predictive model. A dataset of binary data was compiled from 12639 sports matches. As a result, the extent of each condition was not able to be measured. Nonetheless, the data is used and is run through the Minimum Redundancy Maximum Relevance (mRMR), Chi-Square, and Random Forest processes. We also weigh the features by using a shallow artificial neural network with an input and output layer. Based on the results, the feature that was selected the most and was highest weighted was the condition of having low rainfall before the sports match.

Cardiovascular disease (CVD) has become the major cause of death worldwide. Today, countries are taking heart disease more and more seriously and are actively seeking solutions. However, it is extremely difficult to achieve a complete cure for heart disease with the current state of global healthcare. This paper analyzes the factors affecting heart disease and builds corresponding models through k-nearest neighbor classification, logistic regression models, decision trees, and random forest classification. Then the author compares their metrics to determine the performance of the models. The experimental results show that the characteristics under study all have some degree of influence on heart disease. Moreover, each analysis method and model have strengths and weaknesses, with random forests performing most satisfactorily. In fact, there is much potential for the improvement in cardiac prediction, including algorithm optimization and physician observation. By combining all methods, the efficiency and accuracy of forecasting can be further improved.

With the rapid development and progress of modern information technology computer networking technology, many colleges and universities have paid attention to the necessity of opening and using computer network courses. The main form of teaching, computer network classroom teaching actually refers to the process in which teachers use computer networks to allow learners to complete basic knowledge exercises. It has become a new way for learners to master basic knowledge, and it has also greatly improved. The disadvantages of traditional teaching methods. For this kind of innovative education, in order to achieve the improvement of teaching efficiency and quality level, it is necessary to effectively base on the background of the development of science and technology, and continuously apply various advanced science and technology to realize the innovative development of Chinese medicine online education. The research focus is based on the concept and characteristics of artificial intelligence to deeply explore its application in traditional Chinese medicine online education.

Paclitaxel (PTX), a definited drug with anti-tumor effect, has been employed in treating various kinds of cancer. However, clinical effects have been hampered by its poor solubility and serious side effects. In this work, we developed an albumin-polymer liposome system for delivering PTX. Maleimide (MI) was employed to facilitate PTX binding with albumin, and liposome was comprised with lecithin and cholesterol. The albumin-bound PTX liposome system exhibited a high encapsulation efficiency, excellent drug load and good particle size. Combination of albumin and liposome, this system has the property to target in tumor issues and PTX could be released in tumor microenvironment by breaking the hydrazone bond to exhibit antitumor activity.

Objective: Using network pharmacology and molecular docking method to predict the main active components and targets of Jiufen Powder in the treatment of rheumatoid arthritis, and to analyze the mechanism of its multi-component, multitarget and multi-pathway. Methods The active components of four traditional Chinese medicines (semen strychni, ephedra, frankincense, myrrh) were collected and screened in the TCMSP, PubChem and Swiss Target Prediction database, and predict their targets; Screening of disease targets associated with rheumatoid arthritis treatment through OMIM and GeneCards databases; Intersecting with Jiufen Powder active component targets to screen out common targets as research targets, A potential protein interaction network was constructed by inputting their common targets into String online analysis platform; Use Cytoscape 3.7.2 software to construct a drug-active component-target visualization network, and use the Metascape platform to perform GO and KEGG enrichment analysis on its core targets to predict its mechanism of action; molecular docking of key targets through molecular docking technology verification. Result The key targets were verified by molesults A total of 40 active components were obtained by screening OB≥30%, DL≥0.18, and corresponding 186 potential action targets; Using "Rheumatoid arthritis" as the key word search for 4465 disease-related targets, and mapped them to potential drug targets,get 124 common targets, among which 9 targets may be useful for the core target of Jiufen Powder treatment of rheumatoid arthritis; A total of 231 nodes and 962 edges were read in the "drug-active component-target" network diagram; There are 22 different signaling pathways in the GO and KEGG enrichment analysis, including the PI3K-Akt signaling pathway , Proteoglycans in cancer, MAPK signaling pathway, chemokine signaling pathway, IL-17 signaling pathway, etc; Molecular docking shows that the compounds in Jiufen Powder have high binding energy with key proteins that cause rheumatoid arthritis. Conclusion Through multi-target and multi-pathway, the potential mechanism of Jiufen Powder in treating rheumatoid arthritis was preliminarily explored, which provided scientific basis for the clinical application and in-depth study of Jiufen Powder.

The key problem of event extraction in the medical field is that the cost of medical data labeling is too high, and the labeled samples are scarce, making medical event extraction difficult. In response to this problem, this paper proposes to perform a partial synonymous replacement of training samples to expand the data, and the data and the original data together constitute new electronic medical record data (i.e. EDA data enhancement); In addition, the unlabeled data is predicted by the medical event extraction model to generate labeled data, and then the accurate labeled data is filtered out and added to the original data to form new electronic medical record data, thereby realizing data enhancement (i.e. UDF data enhancement) , to a certain extent, to solve the problem of the scarcity of medical data samples. Based on augmented data, a medical event extraction model (i.e. TEC_MEE model) based on Transformer Encoder and CRF are constructed to extract attributes of specified events from unstructured Chinese electronic medical record text. The experimental results show that, compared with the baseline model, the TEC_MEE model proposed in this paper obtains better medical event extraction results after data enhancement.

Establishing identity is a scientific identification activity that tests the characteristic reflections left by the objects in order to determine whether the objects appearing successively in a case are identical. To mine the key information of forensic medical images and accurately establishing identity, a multi-task learning network that can simultaneously perform clavicle segmentation, gender determination, and identity recognition for adult chest radiographs was built. Key issues such as multi-scale feature mining and integration in the case of multi-tasking, multi-loss function optimization combination, and sub-task interaction analysis were further investigated. For multi-scale feature mining and integration, a multi-resolution parallel sub-network structure similar to a high-resolution network was adopted. Different sub-tasks were connected to different sub-networks for output as needed, effectively improving the accuracy of single tasks. Auto-adaptive online settings of the loss functions balanced the learning convergence progress of different sub-networks and effectively improved the generalizability of the multi-task learning framework. At the same time, the interaction between different subtasks was analyzed, upon which the triplet loss function of integrating auxiliary information was proposed, which further improved the accuracy of identity determination. The results showed that compared to single-task learning, multitask learning achieved better results in the IOU(Intersection over Union) of clavicle segmentation and accuracy of gender and identity determination. Auto-adaptive settings of the loss functions achieved similar performance compared to iterative manual settings on weights of each sub-task. By adopting the triplet loss function of integrating auxiliary information, the accuracy of identity determination was further improved. This study performed well in the three tasks of clavicle segmentation, gender determination, and identity recognition, and had strong applicability in the research and development of multi-task learning.

Sleep apnea syndrome is a sleep breathing disease. At present, polysomnography has some problems. The patients feel uncomfortable, and manual judgment of sleep breathing events is labor-intensive. This paper provides a portable on-line monitoring and prevention system for sleep apnea syndrome, which can independently distinguish sleep apnea and sleep hypopnea events according to multi-sensor monitoring data, and adopt a variety of correction and adjustment methods to intervene sleep apnea events. The experimental results show that the method proposed in this paper can accurately determine the current sleep breathing state in time, and has clinical application value.

In this day and age, with the improvement of medical level, we continue to try more difficult operations to save more patients. However, the consequent problem is that postoperative recovery requires a large number of medical staff, which seriously consumes the energy of the doctors and nurses. This paper aims to propose a feasible scheme of an intelligent cloud platform medical monitoring system (IMMS). Through the deployment of the system, we can realize the real-time monitoring of patient signs as well as intelligent diagnosis of illness, and the system can send the acquired information to the doctor in time. Through this system, the hospital can not only ensure doctors’ rest, but also facilitate timely treatment.

Objective This study evaluates the feasibility of combining parameters derived from three-dimensional quantitative coronary angiography (3D-QCA) with fractional flow reserve (CT-FFR) calculated by computed tomography based on an artificial intelligence deep learning algorithm and to further assess the relevance of coronary artery stenosis lesions and myocardial functional lesions.

Methods This study retrospectively included 595 patients suspected of coronary heart disease who received coronary computed tomography angiography (CTA) or invasive coronary angiography (no coronary artery therapy has been performed in the past, coronary CTA examination was completed after admission followed by coronary angiography, and the interval was no more than 14 days) during hospitalization from December 2017 to December 2020. From these patients, a total of 1004 diseased blood vessels have been studied. Subsequent 3D-QCA was completed, followed by CT-FFR calculations, and the correlation analysis of the relevant parameters was carried out. According to the CT-FFR value, the patients were divided into non-functional lesion group with CT-FFR < 0.80 (n = 633) and functional lesion group with CT-FFR≤0.80 (n = 371). The diseased vessels included 443 anterior descending (LAD), 283 left circumflex (LCX), and 278 right coronary (RCA) vessels. ROC curves were drawn to analyze the sensitivity and specificity of 3D-QCA parameters for predicting non-functional lesions.

Outcome Statistical analysis confirms that the differences in coronary artery diameter stenosis rate [(28.83±13.25)% and (39.29±15.39)%, P<0.001], cross-sectional area stenosis rate [(47.75±17.64)% and (60.89±17.12)%, P<0.001 ], volume stenosis rate [(22.20±8.85) % and (29.73±8.66) %, P＜0.001] of non-functional lesion group and functional lesion group were significant. While above parameters was found to be negatively correlated with CT-FFR values (the correlation coefficients were r=-0.359, P<0.001, r=-0.361, P<0.001, r=-0.382, P<0.001), coronary artery stenosis diameter [( 1.75 ± 0.50) mm vs ( 0.83 ± 0.39) mm, P＜0.001], stenosis cross-sectional area [(2.59 ± 1.45) mm^2 vs (1.58 ± 1.11) mm^2, P <0.001], plaque volume [(39.95±26.24) mm^3 vs. (45.86±27.73) mm^3, P<0.001] were found to be positively correlated with the CT-FFR value with statistical significance (the correlation coefficients were r = 0.433, P < 0.001, r = 0.413, P < 0.001, r = -0.076, P = 0.016). The stenosis diameter greater than 1.455mm predicted non-functional ischemia with a sensitivity of 71.7% and a specificity of 64.2%. The stenosis cross-sectional area greater than 1.585 mm^2 predicted nonfunctional ischemia with a sensitivity of 73.5% and a specificity of 60.1%

Conclusions There is a specific correlation between the diameter stenosis rate, area stenosis rate, and volume stenosis rate of coronary artery in the relevant parameters of quantitative analysis of three-dimensional coronary angiography and CTFFR value. However, the sensitivity and specificity of predicting whether the lesions are myocardial ischemia-related lesions are not high. Besides, since CT-FFR has certain characteristics in the functional evaluation of related diseased blood vessels, we recommended popularizing and promoting CT-FFR measurement technology for patients with suspected coronary heart disease before coronary angiography.

The early manifestations of lung cancer are pulmonary nodules, and a computer aided diagnosis (CAD) model can help doctors to diagnose pulmonary nodules. However, when some new samples arrives, the existing model incremental update methods have problems such as catastrophic forgetting and high update spatiotemporal cost. To overcome the above problems, this paper proposes an incremental learning method for lung nodule detection based on elastic weight Consolidation (EWC) and feature distillation. First, lung parenchyma is segmented on CT images; secondly, the original model is optimized based on the elastic weight integration algorithm, the Fisher information matrix is simplified to a parameter weight matrix to reduce the amount of calculation, and then a regularization penalty term is introduced into the update process based on the parameter weight matrix The loss function limits the changes of important parameters to obtain the incrementally updated optimization model; finally, the original model is used as the teacher network, and the optimization model is used as the student network to calculate the feature distillation loss to improve the performance of the optimization model, which is realized without forgetting the learned knowledge. Sufficient fit to new samples. The method in this paper is cross-validated on the LUNA16 dataset. The results show that the method in this paper improves the incremental learning ability of the model, achieves good results in sensitivity and accuracy, and achieves low false positives and reduces space-time overhead.

Traditional oral anesthesia injections usually use manual syringes. The injection method is relatively rough, and the injection dose and speed are uncontrollable. It is easy to cause excessive injection or insufficient dose, resulting in pain symptoms for patients. In response to this problem, a high-precision painless oral anesthesia injection instrument was designed to replace manual precise injection. Through the description of the system composition and the finite element analysis of the transmission system, the system structure scheme is determined. Based on the pharmacokinetic compartment model, a two-compartment kinetic model was established, and the variation curve of the target drug concentration with the injection rate was calculated. By maintaining a constant level of drug concentration in the gingival tissue, combined with the detection of pressure changes during the injection process, an anesthesia channel can be created, thereby eliminating the patient's pain and achieving the goal of painless and comfortable treatment.

Contemporarily, obesity, as a chronic disease, has seriously affected the quality of daily life and attracted the attention of scholars. This research will investigate 2111 observations on eating habits and behaviour patterns of obesity based on five machine learning approaches (Decision Tree (DT), Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), Random Forest (RF) and Extremely Randomized Trees (ERT) models). By adding 16 factors in the data into five models successively according to their correlation with obesity level from strong to weak, one explores the impact of different factor quantities on the prediction of obesity status. According to the three metrics of accuracy score, Kappa score and Matthews correlation coefficient, the classification effect of the five models tended to be stable and saturated when the quantity of factors reached a certain value. Additionally, the accuracy of the model classification will be greatly improved when the correlation coefficients between the new factor and the added factors are small. Meanwhile, among the five models, XGBoost model has the best classification effect under 14 factors, with an accuracy of 97.16%. The research of this paper further explores the classification effects of different models on obesity status under different factor quantities. Overall, these results shed light on guiding the related research of the internal relationship between different factor quantities and the classification effect of different machine learning approaches.

Alzheimer’s disease (AD) is a chronic neurodegenerative disease that is irreversible and insidious. Contemporarily, there is a very high incidence in the elderly and the causality of the disease remains unclear. The existing medications can only relieve the symptoms but cannot cure them completely. At present, the state-of-art machine learning approaches have been widely used in neurological diseases. This paper proposes machine learning approach to predict whether people will develop AD at an early stage based on the data from OASIS. By comparing the prediction results of four machine learning methods, the BP Neural Network had the best performance, whose accuracy rate reaches 86%. In terms of the state-of-art model to diagnose AD, it could lead to a reduction in the use of medical equipment and interventions at an earlier stage. Overall, these results shed light on broadening the implementation of machine learning techniques in medicine.

Detection of protein complexes and key proteins from protein-protein interaction networks is an important research direction in Bioinformatics and Systems Biology, which has attracted researchers' attention in the past decades. However, mature algorithms for detecting statistically significant protein complexes are still very limited. Two algorithms gain popularity in recent years and they are the ClusterONE and SSF algorithms. The ClusterONE has the advantages of high accuracy and low time complexity, while the SSF is a protein complexes detection method based on the Fisher exact test, which has the advantages of less information and high accuracy. In this paper, we have used ClusterONE and SSF algorithms to complete the screening of protein complexes. Our results demonstrate a key protein prediction algorithm based on protein centrality ordering and activation of the Tanh function. By combining the recognition of protein complexes with the screening of key proteins, the selected key proteins appeared with stronger reliability, thus providing an excellent contribution to protein Bioinformatics.

Contemporarily, lung cancer remains a critical medical issue worldwide, where the survival rate has increased by a dramatic extent from 13% to 22.6%. On this basis, it is necessary to analysis the impacts of factors on the lung cancer in curing the disease. In this paper, the influencing factors that affect the lung cancer are investigated based on the state-of-art machine learning scenarios. Generally, it is feasible to build the prediction model in terms of machine learning approaches to find out the causality of lung cancer. In this case, five models (i.e., Linear regression, random forest classifier, decision tree classifier, boosting classifier, and XGB classifier) are implemented in this research to evaluate the factors based on Python Scikit-learn package and panada package. According to the evaluations, the random forest is the best model among the five models. The precision of the model is 100%, while it might have overfitting. Therefore, it is necessary to increase the sample size and reduce the model complication by applying outer example test. Based on the estimations, the importance of features on lung cancer is evaluated, which offers a guideline for preventing lung cancer and reduce the rate of mortality and incidence of the disease. These results shed light on guiding further exploration to address the issue of curing lung cancer.

Early diagnosis of children with autism spectrum disorder (ASD) is critical. EEG is a signal that reflects the spontaneous and rhythmic electrophysiological activity of neurons in the brain, and contains a large amount of physiological and pathological information. In this paper, two entropy features, permutation entropy and wavelet entropy, as well as two functional connectivity features, coherence and phase synchronization, were extracted from the EEG signals of ASD children and normal children, and then independent samples t-test was used to analyze the differences between groups. The results show that the entropy value of the autism group is lower than that of the normal control group, the EEG complexity is lower, and the wavelet entropy difference is the most significant; Compared with the normal group, the EEG signal connectivity of the autism group was weaker, and the four frequency bands of delta, theta, alpha and beta were significantly different, especially the difference between the frontal lobe and other brain regions was the most obvious. The results of this study can provide a reliable scientific basis for the clinical diagnosis of autism.

Handmade Cloning (HMC) is a method of somatic cell nuclear transfer (SCNT) that eliminates the need for micromanipulators, making it a novel revolution in embryology. Not only is it cheaper than its predecessor, traditional cloning that uses micromanipulators, but it is also more efficient in terms of birth rate and economic expenditures. Given that the technology is relatively recent, variations in HMC procedure and method have been explored in different species and experiments; these modifications generally have a positive effect on HMC efficiency in such experiments. In recent years, the increasing number of research in HMC generally fall into two categories: first, the factors that contribute to HMC’s improved efficiency. Two, HMC’s possible usage in genealogy and transgene integration. Hence, this review will highlight and summarize the factors that contribute to HMC efficiency, the issues and setbacks that obstruct HMC development, as well as a glimpse into the future of HMC.

Objective: Based on the network pharmacology method, the active ingredient gene target network and protein interaction network of Acorus tatarinowii were constructed, and the functions and signaling pathways involved in the obtained gene targets were analyzed, so as to explore the possible mechanism of action of Acorus tatarinowii in the treatment of ischemic stroke. Methods: TCMSP, UniprotKB, Genecards, TTD, OMIM and Drugbank were used to search the main active components of Acorus tatarinowii and the target of Acorus tatarinowii in the treatment of ischemic stroke. The STRING database and Cytoscape3.8.2 software were used to construct the protein-protein interaction network and analyze it to predict the core protein targets of Acorus tatarinowii in the treatment of ischemic stroke. KEGG and GO analysis of key genes were performed using Metascape database to predict possible signaling pathways and biological processes. Results: Four active compounds and 76 corresponding action targets of Acorus tatarinowii was retrieved from TCMSP database. PPI network has 45 core target proteins. KEGG enrichment analysis predicted possible pathways including fluid shear stress, cGMP-PKG signaling pathway, NF-Kappa B signaling pathway, HIF-1 signaling pathway, VEGF signaling pathway, AMPK signaling pathway, etc. GO enrichment analysis of possible biological processes included circulatory system processes, reactive oxygen metabolism, responses to oxygen levels, endothelial cell migration, and exogenous apoptotic signaling pathways. Molecular docking results showed that kaempferol could stably bind to MAPK8, VCAM1, ICAM1, HMOX1 and PPARG, and 8-isopentenylkaempferol could stably bind to PPARG, MAPK14 and ESR1.Conclusions: This study found that Acorus tatarinowii may play a therapeutic role in the treatment of ischemic stroke from anti-inflammatory, anti-oxidation, promoting new angiogenesis and other aspects, providing a new idea and theoretical basis for the clinical application and clinical drug research and development of Acorus tatarinowii

In this paper, we describe the classification, algorithms, and application status of search and rescue robots. By analyzing various types of robots, the robot design can be simple and easy to use, reliable in structure, and low cost. In difficult disaster situations, they can also recognize and track the victim. Furthermore, rather than laboratory technologies, robotics in the search and rescue category should be based on proven and implementable technologies. Traditional tracked robots are now widely used in our daily lives. The robots are also now commercially available. This is motivating and keeps them up to date. In this article, we present an overview of the current state of this cardinality, the prospects for robot search and rescue, relevant research on different mainstream search and rescue algorithms, and the working principles of these algorithms. Our findings will be used to determine which robotic path planning systems are best suited for distinctive and complex environmental programs. In order to look into the future, we also discuss the current situation, limitations, open questions, and challenges.

This paper proposed a vessel segmentation method based on Gabor features and U-Net. According to the eigenvectors of Hessian matrix of each pixel in the image, the vessel direction of each point was obtained to set the direction of Gabor filter, and the Gabor features of different vessel width at each point were extracted to establish the 6-D vectors of each point. By reducing the dimension of the 6-D vector, the 2-D vector of each point was obtained and fused with the original image G channel. U-Net was used to classify the fused image to segment vessels. The experimental results of this method in DRIVE dataset showed that this method had a good effect on the detection of small vessels and vessels at the intersection.