This PDF file contains the front matter associated with SPIE Proceedings Volume 12622, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

The work describes deep learning-enabled holographic tomography for neuroblastoma cell processing, analysis, and diagnosis through three-dimensional (3-D) cell Refractive Index (RI) model. Deep learning-assisted approach is applied to execute effective segmentation of 3-D RI cell morphology for the different cellular states under normal, autophagy, and apoptosis. The biophysical parameters of 3-D RI cell morphology are analyzed and selected for learning-based classification to identify cell death pathways. The results show that the proposed approach achieve of 98% in identifying cell morphology through optimized biophysical parameters.

In recent years, label-free microscopy has gained momentum over the well-established fluorescence microscopy, as it allows overcoming many important drawbacks related to the staining process. Among the label-free imaging techniques, Quantitative Phase Imaging (QPI) has emerged since biophysical properties of cells and tissues are measured. The latest development of QPI is Tomographic Phase Microscopy (TPM), which allows reconstructing the 3D volumetric distribution of the Refractive Indices (RIs) at the single-cell level by combining multiple phase-contrast maps recorded all around the sample. Very recently, the TPM paradigm has been even demonstrated working in Flow Cytometry (FC) modality, thus opening the route to the label-free, 3D, quantitative and high-throughput recording of living suspended cells. Nevertheless, the several advantages of QPI and TPM over fluorescence microscopy are counterbalanced by the lack of intracellular specificity due to the stain-free imaging modality. In fact, the inner cell contrast usually is not enough to properly recognize the several organelles, thus preventing intracellular studies. In QPI and in static TPM, virtual staining has been proposed as a solution, based on the training of deep learning strategies to numerically emulate the chemical staining process. However, the virtual staining approach cannot be replicated in the TPM-FC technique since a dataset of paired 3D RI and fluorescent tomograms of cells cannot be created. Here we show a computational method for the stain-free segmentation of the nucleus in 3D inside the TPM-FC tomograms of flowing cells based on an ad hoc clustering of the intracellular voxels according to their statistical similarities.

Deciphering live cell dynamics using time-lapse multiparametric assays is expected to provide new insights into cellular machinery, while fostering groundbreaking biomedical applications. In this work, we take on the challenge to measure the optical response of live cells upon electrical excitation. We build on recent advances in coupled EIS and Quantitative Phase Imaging (QPI) to obtain quantitatively time series of cellular parameters with label-free imaging at high spatial and temporal resolution. We aim to quantitatively assess cellular dynamics (cell cycle progression) both under physiologic conditions and exposed to selected stimuli triggering a wide range of effects from gentle to lethal ones. Using tailored optoelectronic materials, we exploit the coupling of AC electric fields to the substrate for boosting the analytic capabilities of EIS and quantitative phase imaging. This novel multimodal investigation provides new capabilities for gauging subcellular structure and dynamics changes in response to electrical excitation. Among others, we used Magnified Image Spatial Spectrum (MISS) microscopy, a high-speed and sensitive QPI method, to study the distribution of both electrical and optical parameters of live cells. We also present an application of combined EIS-light microscopy concept to assess the alterations of bacterial cells dynamics, at bacterium level, when exposed to a model (bactericidal) antibiotic. This new type of time-lapse microscopy encompassing the dynamics of both structural and electrical cellular fingerprints can provide a rapid phenotypic approach likely to replace some currently used antimicrobial susceptibility/resistance testing assays based on lengthy microbiological methods.

A quasi-common-path lateral-shearing holo-tomographic optical setup coupled to microfluidic channel is designed and build-up. We demonstrate that 3D refractive index profile of flowing cells can be efficiently retrieved. This setup is robust to external vibrations and is scaled down in dimension, in the perspective of employing such systems outside of optical labs. We apply a reconstruction algorithm based on high-order total-variation to cope with the reduced quality of the measurements acquired. Validation of such reconstruction approach is performed. The assessment of the robustness of the proposed solution is allowed by evaluating some biophysical parameters of biological relevance over the reconstructed tomograms.

We report new methods of two-photon polymerization of microlenses with high numerical aperture, large diameter and good optical quality. We characterize the aberrations of these lenses that, coupled to raster scanning optical microscopes, allow two-photon excitation imaging of cells. In-vivo non-linear imaging will be also discussed, opening the possibility to use these micro-lenses in implants for the continuous inspection of biological dynamics in vivo.

In an overview, Digital Holographic Microscopy (DHM) for usage in a biomedical laboratory environment and the application of DHM-based Quantitative Phase Imaging (QPI) for quantification of inflammation and toxicity related effects in tissue sections, cell cultures and blood cells are presented. First, the capabilities to determine inflammation as well as nanomaterial induced pathological alterations in dissected ex vivo colon and lung tissues are illustrated. Then, results from cell culture-based time-lapse growth monitoring assays and perioperative observation of living primary human leucocytes demonstrate DHM as a cytometric tool for in vitro toxicity testing and temporal disease course characterization.

Tissue physiology and especially pathology need a cutting-edge microscopic technique capable of imaging tissue morphology and functioning over a wide view with high-resolution details. Fourier Ptychography (FP), a Quantitative Phase Image (QPI) method, overcomes this trade-off relying on the synthetic Numerical Aperture (NA) principle. FP uses low NA microscope objectives for having huge FoV and multiple illumination angles to synthetize a big NA. Moreover, FP furnishes phase contrast images in a stain-free modality after applying phase retrieval algorithms. The retrieved phase maps allow the possibility of extracting quantitative information about the sample, e.g., refractive index variation, physical thickness and consequently the 3D profile. Here, we apply FP to the analysis of kidney tissues. Both stain-free and stained slides with different dyes and thicknesses are considered. FP phase images are obtained and compared to light-microscopy images of the same slides to discuss the capability of QPI in describing the morphology of kidney samples. Usually, Haematoxylin and Eosin (H&E) stain is considered a gold standard to make pathological inference on sick tissues because it marks cell nuclei. We propose a new way of observing renal inner structures such as glomeruli and tubules, which are clearly visible without staining. This work could lead physicians to use stain-free phase-contrast images, paving the way to extract FP diagnostic and prognostic biomarkers to enrich pathomic. We reach ~ 0.5 μm of resolution over an area of 3.3 mm2 for each sample up to 10 μm of tissue thickness.

Holo-Tomographic Flow Cytometry is a new technology for single-cell analysis that combine Phase-Contrast Tomography and Flow Cytometry opening to a new approach in biomedical field by high-throughput, tri-dimensional imaging of unstained cell populations. Tomographic Phase Microscopy is a label-free phase contrast imaging method able to supply quantitative and volumetric refractive index distribution at single cell level in adherent or fixed populations. Here, we demonstrate that phase-contrast tomography can be achieved also for cells into a microfluidic environment obtaining accurate 3D tomographic imaging of thousands of flowing and rotating cells thanks to a robust and reliable computational strategy. Recording setups are based on Digital Holography in microscopy configurations integrated with microfluidic apparatus to record interference fringes (hologram) of rotating cells. Computational pipeline includes 3D cell tracking into the microfluidic channel, quantitative 2D phase-contrast maps retrieval for each acquired hologram, robust angle recovery code, tomographic processing to measure the inner refractive index distribution. Holo-Tomographic Flow Cytometry surpasses the limits of conventional Imaging flow cytometers because make available the recording of hundreds of informative images for each flowing cells avoiding the employment of fluorescent tags. Holo-Tomographic Flow Cytometry allows to retrieve the unique all-optical 3D fingerprint for each cell flowing into the field-of-view opening to a wide range of applications such as: (i) identification of inner subcellular compartments; (ii) recognition of nanoparticle uptake and (iii) phenotyping of different subclasses in heterogeneous populations. Future perspectives are presented in the fields of liquid biopsy, drug resistance and genetic disfunctions.

Polarimetry comprises a set of optical techniques of great interest in biophotonics due to its capability to obtain relevant information from biological samples by means of noninvasive and nondestructive methods. For instance, they are useful in pathology detection or different biological structures classification, among others. By studying the polarimetric response of biological samples we can obtain the information of how different structures produce different changes in the polarimetric characteristics of light. These changes depend on the polarimetric properties of the samples: depolarization, dichroism or retardance. From the experimental measurement of the Mueller matrix (M) of a sample, these polarimetric observables related to the mentioned tissue properties can be obtained. In this work, we propose the study of a particular set of observables derived from the Arrow decomposition of M. These parameters are used to inspect different biological tissues properties with the purpose of obtaining images with enhanced contrast of different biological structures in a tissue. In particular, we applied these observables to the study of a sample of animal origin: an ex-vivo cow brain; in order to differentiate between white and gray matter. Obtained results provide the interest of Arrow-derived polarimetric observables which may be of interest in multiple biomedical scenarios such as early pathology detection and diagnosis or enhanced visualization of different structures for clinical applications.

Recently, advanced flow cytometry analysis technology based on digital holography has been extensively studied, which can meet various challenges in clinical diagnosis. Especially in liquid biopsy, it has incomparable advantages. Urothelial Holographic Flow Cytometry (HFC) microscopy can provide rich intracellular information by changing the cell’s intrinsic properties with label-free and high throughput. Carcinoma (UC) is the second most common malignancy in men. Urine cytology detection is the most convenient early cancer screening method for UC patients. Here, we developed HFC to identify the cancer cells in urine. Holographic microfluidic imaging was performed to obtain the phase images of different cells in simulation urine, including red blood cells, white blood cells, epithelial cells, and a small number of cancer cells. This study demonstrates that HFC can achieve high accuracy, high throughput, and label-free cancer cell identification in the urine.

The recent development of tomographic phase imaging flow cytometry has unlocked the possibility to achieve data throughput comparable to the state-of-the-art imaging flow cytometry systems, but with the great advantages to be fully label-free and 3D. On the other hand, the huge amount of data to manage becomes one of the main computational problems to face with. Here we show that by using the 3D version of Zernike polynomials it is possible to efficiently encode single-cell phase-contrast tomograms, demonstrating high data compression capability with negligible information loss. A full simulative analysis is reported also quantifying the trade-off between compression factor and representation accuracy.

Fourier Ptychography (FP) is a quantitative phase imaging technique that overcomes the trade-off between lateral resolution and field of view. Typically, low Numerical Aperture (NA) microscope objectives are used, and super-resolution is obtained by illuminating specimens at different angles, thus generating a larger synthetic NA. These features are pivotal in both cells and tissue slide analysis. FP provides phase contrast images by applying phase retrieval algorithms and the quantitative information can be used to describe and characterize stain-free cells and tissues. To make FP microscopy viable for clinical practice, the issues arising from misalignments of the optical system or the presence of scattering structures to be imaged should be considered though. These non-ideal recording conditions result in phase artefacts in the recovered high-resolution FP reconstruction. To tackle this problem, we propose a blind multi-look FP (ML-FP) algorithm that directly minimizes the artefacts while ensuring correct phase retrieval and can be used by unskilled operators in clinical practice. Here, we show how ML-FP allows the analysis of cells seeded onto micropatterned substrates (for mechanobiology applications) and tissues (for physiology and diagnostic applications). In order to improve robustness in the presence of misalignments, we use the ML-FP outcome as a ground truth and train a GAN architecture to emulate the phase retrieval process. The GAN receives as input the complex amplitude at the first iteration of the FP phase retrieval algorithm and returns in real-time the high-resolution FP complex amplitude.

Machine learning in combination with microscopy is a well-established paradigm for the identification of cells target (e.g. sick cells) or for the statistical study of cells’ populations. In general, the accuracy in classifying single cells depends on the selected imaging modality, i.e., the more informative it is, the more performant the classifier is. Here we show that the combination of machine learning and holographic microscopy is an effective tool to achieve the above goal, thus allowing higher classification performances if compared to other standard microscopies. Moreover, by exploiting a priori information about the samples to identify, the classification performance can be further increased. We demonstrate this paradigm for the differential diagnosis of hereditary anemias, in which RBCs, imaged by holographic microscopy, are used to predict firstly if an anemia occurs, then which type of anemia among five phenotypes.

Intrinsic biophysical cell properties hold an enormous potential for cell class and state classification in microfluidics, allowing to avoid the need of cost intensive fluorescence labelling. Several methods can accomplish cell identification, while convolutional neural networks show an outstanding performance compared to other state-of-the-art classification methods, regarding accuracy and speed. In fact, neural networks show high performance for known image class prediction but struggles when unknown (out of distribution) image classes need to be identified. In such a scenario no prior knowledge of the unknown cell class can be used for the model training, which inevitably results in image misclassification. In fact, to distinguish unknown cell classes, a neural network must first construct an in-distribution of known images to afterwards detect out of distribution as unknowns, which is also called open-set classification assumption. Ones, a new cell class is identified, the neural network can be retrained with the obtained knowledge to dynamically update its cell class database. This process can be simply repeated for each new detected cell class. We applied this open-set idea to scattering pattern snapshots of different classes of living cells obtained in microfluidics. Our outcome shows a proof-of-concept for open-set based convolutional neural network for cell image classification, which can be applied to a wide range of single cell classification approaches to reduce uncertainty in machine learning based technologies.

Multiphoton microscopy is a powerful technique for in-vivo bioimaging. Many high-speed volumetric methods have been integrated with multiphoton microscopy to achieve dynamic signal imaging. In this study, we have developed a Dual-Resonant Scanning Multiphoton (DRSM) microscope that a frame rate of around 8,000 Hz and a volumetric imaging rate of over 30 Hz can be obtained for a big image volume of 343×343×120 μm³ with a large image size of 256×256×80 voxels. The practical feasibility of the DRSM microscope is demonstrated by observing the mushroom bodies of a drosophila brain and performing 3D dynamic observations of moving 10-μm fluorescent beads. However, the volumetric images have a severe negative Signal-to-Noise Ratio (SNR) as a result of a large number of missing voxels for a large scanning volume and the presence of Lissajous patterning residuals. Due to this drawback and a large number of missing voxels in DRSM, a 3D-generator U-Net model is used to inpaint and denoise the images. The results show that the model achieves dynamic volumetric imaging to be performed with significant SNR improvement. The performance of the 3D U-Net model for bioimaging applications is enhanced by training the model with high-SNR in-vitro drosophila brain images captured using a conventional point scanning multiphoton microscope. Through the assistance of transfer learning, the model can be extended to the restoration of in-vivo drosophila brain images with a high image quality and a rapid training time.

The structural and microscopic examination of cartilage and tendon tissue is of central interest for the characterization of torn ligament healing or pathological tissue changes. Conventional microscopy or optical coherence tomography methods can only partially resolve tissue types and their structural orientation. Two or multiphoton microscopy and second harmonic generation provide information about the material composition or alignment of nanoscaled structural proteins. In most systems, femtosecond lasers are used, which leads to high system costs and requires special system components. The aim of this work is to investigate a narrowband nanosecond laser with a pulse energy several orders of magnitude higher, reducing the required number of laser pulses to be averaged per pixel. Second harmonic generation and two photon excited fluorescence can be used to non-invasively examine deeper tissue structures. High lateral resolution was achieved by scanning the sample. Simultaneous real-time visualization of collagenous and cellular structures was attained. Defined aligned collagenous fibers of a sheep tendon were investigated. The anisotropy of the collagenous structures could be demonstrated. It was possible to realize a two-dimensional imaging method with a maximum point density of 5080 PPI and a numerical aperture of 0.15. The method allows the simultaneous separate observation of collagen fibers through the use of second harmonic generation and cellular tissue using a narrow-band nanosecond laser for two photon excited fluorescence.

We describe progress towards developing a low-cost, simple, and compact imaging system for Digital Bead Assays (DBA) for use in Point-of-Care (POC) diagnostic systems. DBA — such as digital ELISA using single molecule arrays (Simoa) — have emerged as a key advance for the sensitive detection of proteins down to attomolar concentrations, i.e., single-digit numbers of proteins in a droplet of blood or another clinical sample. These assays have enabled unique clinical research and diagnostic measurements, e.g., the measurement in blood of protein biomarkers of neurological conditions, enabling “blood tests for the brain” that can detect Alzheimer’s disease 16 years before dementia symptoms arise. For DBA to have its maximum impact on society, it must be available in low-cost, compact equipment that can be used by anyone around the world. For this goal to become a reality, low-cost and simple imaging systems are needed. In this paper, we will describe a concept for a low-cost, simple, and compact DBA imager. We will describe evaluation of low-cost optics — such as cell-phone optics — and cameras, and how image analysis methods can be used to generate useful data from the lower resolution images provided by these systems.

Human health and disease prevention are among the priorities to safeguard astronauts and, in the next future, space tourists. There is a great demand of new reliable biotechnologies that would be eventually implemented on spacecrafts to observe the space-induced effect on humans. One of the main risks is related to the radiation exposure, that is significantly higher than on Earth. For this reason, space agencies are pushing to develop strategies to quantify, oversee and limiting such risks. Here we present an approach based on the combination of microfluidics and stain-free imaging also aided by artificial intelligence to monitor the effect on ionizing radiation on blood cells. The system is based on the Holographic Image Flow Cytometry system where Quantitative Phase Contrast images are retrieved for cell flowing and rotating into a microfluidics circuits. Proof of concept is demonstrated where morphological parameters are identified able to distinguish cell population irradiated at different radiation doses and at different time from the radiation exposure. Blood cell will be analyzed. The presented approach has main advantages respect to standard and already existent technologies for single cell analysis. The first one is the no-need of fluorescence staining thus opening to faster and easier operation steps. The second one is related to cell rotation into the field of view, allowing to acquire images at different rotation angle and thus collecting a broader dataset useful for the application of artificial intelligence network. Furthermore, the system can be miniaturized to a scale portable out of the laboratory environment.

Extracellular Vesicles (EV) are biogenic nanoparticles released by almost any cell and carry a variety of proteins, lipids, and nucleic acids. By transferring these biomolecules, EVs play important roles in intercellular communication, as such they are gaining increasing importance as potential biomarkers and therapeutic agents. This exciting area of research face big challenges due to EV small size, low refractive index, inherent heterogeneity, and high sensitivity demand in detecting low abundant disease-specific sub-populations. Such need can be met by innovative affinity-probes and digital detection, namely capable to reach the single-molecule sensitivity. Our recent work has identified a class of Membrane-Sensing Peptides (MSP) derived from Bradykinin protein as a novel class of molecular ligands for integrated small EV isolation and analysis. The membrane recognition and binding mechanisms are based on complementary electrostatic interactions between peptide and phospholipids on the outer membrane leaflet, that subsequently can lead to the insertion of hydrophobic residues into the membrane defects. Notably, small EVs present distinctive lipid membrane features in the extracellular environment that could be considered as a universal marker, alternative or complementary to traditional characteristic surface-associated proteins. MSPs are therefore pan-specific, interspecies and interkingdom thus representing a multifarious class of ligands with additional advantages in terms of stability and synthetic versatility.

On-chip microscopy is a major improvement toward portable, completely automated, and high-throughput imaging of biological samples. Fabrication of such devices requires the integration of many different components that are not easy to manufacture with standard methods. Femtosecond laser micromachining of transparent materials is a powerful and versatile technology. High resolution, three-dimensional capabilities and rapid-prototyping possibilities make this technology extremely appealing for the combination of optical and fluidic components. Light-sheet microscopy in optofluidic chips will be presented, as well as the use of structured light to achieve super-resolution.

The most used imaging method for biological samples is based on the use of markers or fluorescent colorants to label the cells micro-structures of interest. However, labeling the cell may cause alteration of its internal constituents, its natural behavior and its life cycle in the case of living cells. Digital Holography (DH) in microscopy is a powerful imaging technique which permits to obtain a posteriori multiple refocusing and quantitative phase contrast images. The main advantage of the DH is the ability to provide the cell morphological features in label-free mode. DH has been proved successfully in different biomedical applications, such as characterization and identification of cancer cells, diagnosis of blood diseases and marker-free detection of lipid droplets. We implemented a Mach-Zehnder interferometer in off-axis configuration which allows recording the resultant digital holograms. Therefore, we performed the 2D numerical reconstruction to achieve the quantitative phase maps through several computational steps, namely Fourier spectrum filtering, numerical refocusing, aberrations suppression and phase unwrapping. Here, we show a detailed study of two different classes of biological samples: HeLa cells and mouse embryonic fibroblasts. Specially, through the proposed method, we investigate the morphological variations induced by lysosomal aggregations to distinguish the difference between lysosomal storage diseases and wild type populations of both cell lines. This work demonstrates the validity and effectiveness of the presented method, revealing its potential to discriminate between healthy and unhealthy cells at subcellular level.

The understanding and analyzing of solid particle behavior in a liquid is a challenge in numerous fields and engineering industry as the petroleum or the cosmetic one. It is indeed essential to know the behavior of soft matter process to avoid problems and ensure the product quality. This study presents the viscometer development working on a resonant optical signal principle by measuring the Free Spectral Range (FSR) parameter of a resonant optical mode during nanoparticles (NPs) sedimentation in a liquid which consists of a water/glycerol mixture. The photonic structure is composed of racetracks micro-resonators made of a UV210 polymer fabricated by deep-UV photolithography developed on an oxidated silicon layer to get a Si/SiO₂ bi-layer. The chip is then integrated in an optical bench to track the evolution of the FSR during the complete sedimentation process. The resonant signal analysis established by an adapted signal processing of silica nanoparticles sedimentation in different water/glycerol concentrations allows us to determine stages and velocity rate of the sedimentation process to finally access to their viscosity. At the same time, measures are performed on a commercial mechanical rheometer so as to compare the dynamic evolution of their viscosity and their associated FSR. The plot of those data versus the glycerol concentration in water obviously shows a possible mathematical transformation between viscosity and FSR slope. There is therefore a good agreement between mechanical and resonant optical measures if we consider the dynamic evolution of both curves; so, this work proves the feasibility of an optical viscometer based on resonant signal.

In this work we present a phase-retrieval-based approach to quantifying the diffusion of drugs through biomembranes or biofilms. So far, the phenomenon was studied based on fringe orientation resulting from a refractive index gradient in the vicinity of the interface. The result is usually obtained with a Mach-Zehnder interferometer with an imaging system. This approach limits the spatial resolution of the method and does not allow observation of local changes in the diffusion. For this reason, we propose to use a single-shot phase retrieval method by utilizing a polarization-sensitive CMOS sensor to obtain four phase-shifted interferograms in a polarization-modified version of the interferometer. Finally, we demonstrate the operation of the system by quantitative analysis of ampicillin diffusion through Pseudomonas aeruginosa biofilm formed on the polyethylene terepthtalate membrane.

In this conference, we will discuss the advancements in Terahertz (THz) spectroscopy and imaging regarding biophotonics applications. In recent years, THz technology helped various fields, from fundamental physics to industrial process control. THz spectrometers offer a wide spectrum range and high dynamic range, enabling the analysis of semi-transparent materials and living tissues. THz imaging has shown potential in applications such as cancer detection, diabetes foot syndrome, burn wound analysis, and plant hydration assessment. Spectroscopy in the THz range is particularly promising for studying biological systems, including proteins and their compounds. However, challenges such as the strong absorption of water, temperature stability, and small sample sizes need to be overcome. Techniques like scanning microscopy, integrated photonics, and metallic broadband approaches have been explored to enhance THz analysis. Despite the challenges, THz technology has found industrial applications and efforts are being made to improve data processing and error evaluation. Additionally, a proposed method aims to enhance the resolution of THz systems, making them suitable for gas spectroscopy and the sensing of volatile organic compounds relevant to biology.

Three-dimensional (3D) bioprinting approaches that enable large-scale constructs and high-resolution simultaneously are very attractive to tissue engineering applications and health industries. However, both characteristics hardly meet at reasonable printing times in current 3D bioprinting technologies, affecting the introduction of 3D scaffolds in medical applications. To overcome this limitation, we recently introduced a Vat Photopolymerization (VP)-based bioprinting method named Light Sheet Stereolithography (LS-SLA) and demonstrated the fabrication of centimeter-scale scaffolds with micrometer-scale features (⪆; 13 μm) by using off-the-shelf optical compounds. The high performance in LS-SLA results from using a rectangular uniform beam instead of a rotational symmetric laser beam, which generates light sheets with large length-to-width aspect ratios on the vat film. Beam shaping optics are components used to perform the beam transformation, and guarantee the accuracy, uniformity, and size of the 3D constructs. This work proposes freeform optics to perform the laser beam shaping in the LS-SLA device and describes the progress of our investigations from design to proof-of-concept-demonstrating. The results show that rectangular beams are readily produced by freeform optics resulting in compact and energy efficient systems, and that further considerations on the real laser output are necessary to deliver high beam uniformities. Tackling the design challenges of this work leads to energy efficient and high accuracy LS-SLA systems.

We present the multimodal characterization of thin polymeric membrane by digital holography-based methods. Herein, two microscope techniques had been chosen to reveal the morphology of membranes, which are conventional off-axis Digital Holography (DH) and Space-Time Digital Holography (STDH). The complementary features of the different methods allow for a bottom-up analysis of the related membranes. Meanwhile, the dynamic forming process of polymeric membrane at the air-water interface is revealed in real-time by CDH. By comparing the imaging results of different methods, the application range of different imaging methods is analyzed in detail.

“Anyone who uses a microscope has likely noticed the limitation of the trade-off between the field of view and the resolution”. To acquire highly resolved images at large fields of view, existing techniques typically record sequential images at different positions and then digitally stitch composite images. There are alternatives to this mechanical scanning procedure, such as structured illumination microscopy or Fourier ptychography that record sequential images at varying illuminations prevent mechanical scanning for high-resolution image composites. However, all of these approaches require sequential images and thus compromise speed, temporal resolution and experimental throughput. Here we present the Multi-Camera Array Microscope (MCAM), which is a microscope system that utilizes an array of many synchronized cameras, each with an individual imaging lens, for simultaneous image capture. The MCAM enables enhanced imaging capabilities and novel applications in various scientific and medical fields, by combining the images acquired from each individual camera-lens pair.

Lab-on-a-Chip microfluidic devices represent an innovative and cost-effective solution in the current trend of miniaturization and simplification of imaging flow cytometry. Cell tracking is a fundamental technique for investigating a variety of biophysical processes, from intracellular dynamics to the characterization of cell motility and migration. The conventional target positioning based on holography is typically addressed by decoupling the calculation of the optical axis position and the transverse coordinates. The 2D positions of each cell are located based on the phase contrast. The axial position of the cell area is calculated by refocused external criterion in complex amplitude wavefront. Computing resources and time consumption may increase because all the frames need to be performed calculations in the spatial frequency domain. We proposed a space-time digital hologram encoding method to speed up 3D holographic particle tracking. The 2D positions of each cell are directly located by morphological calculation based on the hologram. The complex amplitude wavefronts are directly reconstructed by space-time phase shifting to calculate the axial position by refocused external criterion. Only spatial calculation is considered in the proposed method. The proposed approach can be used in microfluidics to analyze objects flowing in microfluidics channels.

In Digital Holography (DH) modality for lab-on-chip applications, the cells passing through the Field of View (FOV) of a microscope can be detected and analyzed even if they are flowing at different depths in a microfluidic channel. If the cells rotate while flowing along the channel, they can be probed by light beams from many different directions while they cross the holographic FOV, thus, it is possible to retrieve the 3D refractive index map of each flowing cell, i.e., a 3D phase-contrast tomogram. Since in biological samples many cells flow close to each other along the FOV, so giving the possibility of increasing the throughput of the system, it is important to establish how close the cells can be to avoid mutual disturbing effects on their rotation due to hydrodynamic interactions. Here, we investigate by means of direct numerical simulations the effects of the hydrodynamic interactions among several cells on their rotational behavior and mechanical deformation during the flow along a microfluidic channel, which are two essential aspects connected to the possibility of recovering the tomograms.

Optofluidic microscopy has been an open challenge during past decade; it is also a well-established paradigm where precise control of microfluidic streams is smartly exploited. Digital Holography (DH) has been proved as one of the optimal tools for flow-cytometry, cell sorting and classification, cell counting and study of cell mechanics. In this framework, Space-Time Digital Holography (STDH) is a convenient complement to conventional holographic cell imaging. Thanks to a spatiotemporal reassembling strategy, one single space-time hologram can efficiently store information of a series of time-lapse holograms using a small subset of detecting elements, e.g. a linear sensor array. In this case, the modulated pattern of interference fringes is projected onto a new hybrid space-time domain and reassembled by time series. Here we propose a phase-retrieval process in STDH for optofluidics, which allows the quantitative phase information reconstruction for flowing cells in different focus planes simultaneously with extended field of view. For a space-time hologram storing information from flowing cells, a unique flow velocity meeting the matching condition of STDH would enable accurate space-time phase shifting. In the case of mismatches between cells speed and recording frame rate, an ad-hoc reconstruction algorithm is developed that compensates for the mismatch and retrieves the correct phase-contrast map of the sample by smartly adapting the method to the microfluidic speed. Based on the proposed strategy, we show the 4D mapping of flowing cells in space-time domain; in other words, the ASTDH is able to encode efficiently a 4D information in a 2D map, self-adapting to unexpected variations of the flow profiles.

Flow cytometry is a technique widely used in biology and medicine for high-throughput acquisition of various parameters from cells in flow. Beside the established detection of scattering and fluorescence signals with single point detectors, several microscopy techniques have been combined with microfluidic systems to achieve imaging flow cytometry. Among these methods, Quantitative Phase Imaging (QPI) based on off-axis Digital Holographic Microscopy (DHM) is a label-free technique for time-resolved quantitative image analysis of almost transparent biological samples, enabling biophysical cellular features such as refractive index, volume and dry mass. When combined with Bright-Field (BF) microscopy, multimodal DHM systems provide complementary high-resolution intensity images with minimized coherence induced noise, allowing an improved identification of the regions of interest in cell cultures that are suitable for QPI analysis, the identification of small absorbing intracellular structures, and collocation of absorbance and phase changes induced by the different organelles within the cells. Recently, we have implemented a simple and robust single-capture BF and DHM imaging technique within a commercial bright-field microscope named Single Capture Bright Field and Spatially Multiplexed Interferometric Microscopy (SC-BF-SMIM). Here, SC-BF-SMIM technique is combined with a common microfluidic layout which allows the analysis of flow living cells. The platform is characterized for evaluation of living cells in flow, and its capability for imaging flow cytometry is demonstrated.

For ovarian cancer patients, paclitaxel remains to be primary chemotherapy drug. Once drug resistance is developed, it will lead to tumor progression and metastasis during chemotherapy. Many studies have shown that the development of drug resistance in cancer cells can cause morphological changes. Digital holographic microscopy is an interferometric imaging technique that can obtain 3D quantitative morphological information of label-free cells. Combining with microfluidics enables high-throughput holographic image acquisition of suspended cells. In this work, four kinds of epithelial ovarian cancer cells with different drug sensitivity, SKOV3 cells, SKOV3_Ta_2μM cells, SKOV3_Ta_8μM cells, and SKOV3_Ta_20μM cells were studied. Several machine learning algorithms were used to perform multi-classification on the extracted morphological features of four types of cells. Then, we employ the SHapley Additive exPlanations (SHAP) method to interpret the classification model. The SHAP value of each feature is calculated and sorted to obtain the important morphological features.

We discuss the use of machine learning in computational imaging for manufacturing process inspection and control. In a recent article we described a physics-enhanced auto-correlation based estimator (Peace) for quantitative speckle. We derived an explicit forward relationship between the Particle Size Distribution (PSD) and the speckle autocorrelation for particle sizes significantly larger than the wavelength (x100 to approximately x1,000). We subsequently trained a machine learning kernel to invert the autocorrelation and obtain the PSD, using the explicit forward model to reduce the number of experimentally acquired examples. In this talk, we present an expanded discussion of Peace and its properties, including spatial and temporal sampling and accuracy, and more general applications.

The presence of microgravity and ionizing radiation during spaceflight missions causes excessive Reactive Oxygen Species (ROS) production that contributes to oxidative cellular stress and multifunctional damage in astronauts. This knowledge has underlined the importance of frequent monitoring of astronaut’s health to have early diagnoses. In this scenario, the biosensor diagnostic devices could offer the necessary analytical performance to study pathological astronaut conditions. Herein, we propose an innovative biosensor for detecting highly diluted biomarkers at picogram level by using the pyro-electrohydrodynamic jet (p-jet) system. The detection limit of the system was confirmed using a model protein as the Bovine Serum Albumin (BSA) by optimizing its deposition on different functionalized glass substrates through different chemical reactions starting with a manual procedure. Based on these results, the epoxy glass activated surface was chosen as the best slide for p-jet experiments. The characterization of the processes was performed through different spectroscopic techniques such as infrared-spectroscopy (IR) or confocal fluorescence. In the context of long-term human missions, our revolutionary approach could be extremely useful to monitor the astronaut health.

Integrated optics has been intensively developed the last decades for the production of components for telecommunications or sensors in metrology. The basic element constitutes the waveguide which transmits the information by guiding the light. The manufacturing processes take place in clean rooms with controlled atmosphere (pressure, temperature, dust) and with generally various deposition and coating machines. The production of these photonics devices remains relatively expensive since it is carried out in a clean room by series of manipulations which requires the intervention of a specialized engineer into a specific environment. More recently, techniques for manufacturing different mechanical parts of mostly research scientific devices have been developed using commercial 3D printers without the need of clean room environment. With such commercial machines, plastic materials are heated and then shaped by controlling their flow through a nozzle. This work concerns the study of the feasibility of realizing and shaping a kind of integrated optics by a simple 3D printer in a normal environment. It aims to understand and develop the fabrication of an integrated planar optics with polymer waveguides using a 3D printer and G-code programming. The coating processes and the G-codes of the 3D printer have been developed in order to produce the thermoplastic polyurethane (TPU) guiding structures onto a silicon/silica wafer. Finally, the characterization of this TPU organic (measurements of surface or energy tension, Raman analysis, ellipsometry measurements) and the optical injection made possible to validate this concept in terms of production and approach. The results concerning the shaping of various rib waveguides and obtaining a propagation of the light in organic thermoplastic polyurethane planar guides with fiber tapers by this simple and low-cost printing processes are positive. This work further proves that the development of integrated optics on thermoplastic polyurethane by 3D printing is possible; this opens the way to the realization of other optical patterns based on the 3D printer principle.

Preventive medicine is growing in importance, with vascular stiffness being a key factor. Blood flow velocity plays a crucial role in assessing vascular health. If velocity exceeds 12 m/s, it indicates an unhealthy vascular condition. Traditional methods of measuring blood flow velocity involve contact-based systems, but there is a rising demand for non-contact alternatives. Two common non-contact methods are Doppler laser interferometry and shearing-speckle interferometry. The latter is simpler, cost-effective, and mitigates the impact of body movement. This study aimed to develop a blood flow velocity measurement device using shearing-speckle interferometry. Experimental results demonstrated successful estimation of blood flow velocity using this method, showing potential for its application in preventive medicine to monitor and diagnose vascular stiffness.

Oral hygiene is one of the key measures recommended by WHO. The aim of this work is to assess the efficiency of different methods and materials for manufacturing dental prostheses regarding the biofilm that is formed both on the dental prosthesis and on its surrounding tissue. Several such prostheses are considered, manufactured using three techniques: (i) conventional, (ii) milling, and (iii) printing. Two assessment methods are utilized for the biofilm characterization: microbiology evaluations and Optical Coherence Tomography (OCT) imaging. The latter involves an in-house Swept Source (SS) OCT system operating at 1300 nm, with a 15 μm axial resolution. In the sampling method, cells are detached from the surface of the gingival mucosa and dental prostheses by scraping (like in the Babes-Papanicolau cytological examination for the evaluation of the cervical mucosa). After sampling they are placed on glass slides for examination, forming what is called smears. The presence of physiological or pathogenic microflora can be identified on these smears, as well as the local effect, which translates into the induction of an immune response. The smears are stained by using both APT-Drăgan and Babeș-Papanicolau methods. The advantage of the cytological examination consists in its efficiency, safety, speed, simplicity, and in the fact that it is a non-invasive medical procedure. Smears obtained from the surface of the gingival mucosa and dental prostheses are examined under an optical microscope. Cellularity and bacterial flora are evaluated, comparing them on different types of prostheses, depending on the cellular and inflammatory elements on the mucosal surface. The cytodiagnostic identified cellular lesions of an inflammatory, allergic, and tumor nature. On the other hand, the study demonstrated that OCT can quantitatively evaluate the width of the biofilm (i.e., of the smear in this ex vivo investigation). The two types of techniques can thus complement each other. Conclusions are drawn regarding the efficiency of each of the considered manufacturing methods and materials.

A Structured Wave Plate (SWP) is an optical element allowing the generation of optical vortices and vector fields with spatially variant polarization. The SWP has recently become a key tool in various optical experiments, including biological imaging. As the SWP has a birefringent structure, the polarization transformation meets the optimal performance only for monochromatic light of design wavelength. Our work focuses on polychromatic illumination, significantly expanding the practical utilization of the polarization microscope. We experimentally investigate the performance of the polarization microscope with the SWP when imaging a phase calibration target under polychromatic illumination.

In today's world, more and more emphasis is placed on non-invasive, label-free diagnostic types in order to avoid the destruction of tissue structures. One example is Flow cytometry, which allows the differentiation of single cells. In order to realize a spectrally and angularly resolved scattered light measurement setup, which allows both the differentiation of cell clusters and provides information about the cell state, a special multispectral light source in the visible/near infrared wavelength range was developed. For this purpose, single-mode fiber-coupled laser diodes of defined wavelengths are coupled into a polarization-maintaining fiber using a developed wavelength-selective coupler and an optical switch. The desired polarization is set by a polarization-maintaining fiber using paddles. A developed electronical circuit with integrated temperature control enables the selection of the wavelengths as well as the control of the laser diodes. In addition to that, the light source achieves the required modulated operation in the nanosecond range to generate short pulses of 600 ns with a peak pulse power of about 3 mW for time-resolved data acquisition. The fiber-based system can be flexibly integrated into a scattered light measurement setup, and principal component analysis was used to differentiate between the tissues of pig heart, pig liver, pig stomach, and sheep tendon based on the scattered light.

Quantitative Phase Imaging (QPI) combined with microfluidics enables high-throughput label-free imaging flow cytometry for acquisition of physical data from heterogeneous particle suspensions. For a reliable analysis of the sample flow, it is crucial that all particles in the sample fluid flow are monitored within the Field of View (FOV) of the QPI image recording device. We thus evaluated the capabilities of hydrodynamic focusing on a microfluidic system with a rectangular cross section-area and its compatibility with off-axis Digital Holographic Microscopy (DHM), an interferometry-based variant of QPI. To characterize the hydrodynamic focusing effect, the lateral distribution of living pancreatic tumor cells in flow that were used as probe particles in the sample flow was analyzed at different positions along the microfluidic channel from acquired series of DHM QPI images. Moreover, the influence of sample flow velocity and variations in the sample and sheath flow ratio on the sample stream with was determined. Our results demonstrate that the utilized micro fluidics unit is capable for hydrodynamic focusing of the sample fluid in DHM-based QPI and that its operation parameters allow a precise variable tuning of a focused particle stream.

Probiotic bacteria are microbial species known to confer benefits to health. In order to act effectively as probiotics, microencapsulated bacteria have to maintain their viability during the gastro-intestinal transit and their motility to reach epithelial cells of the intestine. Here we use Bio-Speckle Dynamic Assays (BSDA) for rapidly testing the microencapsulation performance in experiments simulating gastro-intestinal conditions. Label-free samples are probed by coherent light to infer ensemble motility information. Then, we use Digital Holography (DH) in transmission microscopy mode and 3D tracking as complementary tools to infer strain-specific locomotion profiles at the single cell level.

Nanoparticles (NPs) internalization process in living cells has large perspectives for drug-delivery applications, but the efficient cellular uptake is still a remarkable challenge. Recently, it has been demonstrated that nanographene oxide (nGO) particles are massively internalized into the cell cytoplasm, opening the way of using graphene family materials for the above goal. Internalized nGO can interact with intracellular elements, thus modifying the life cycle pathways. Therefore, there is a great interest in studying the cellular uptake process and the volumetric distribution of nGO inside the cells. He we report on the use of holographic microscopy for quantitatively evaluating the nGO cellular uptake in both 2D and 3D. In particular, quantitative phase images of adherent cells with internalized nGO are used to measure the cells biovolume variation in time, while tomographic reconstructions of cells in flow cytometry condition are exploited to visualize in 3D the distribution of nGO within the cell's cytoplasm. The study is conducted on NIH-3T3 cells to analyze the effects of nGO in vitro and monitoring the cell culture was for several hours to allow a time-lapse of nGO uptake.

In recent years, the dynamic role of Lipid Droplets (LDs) in many cellular activities has been increasingly brought to light. In fact, it has been discovered that LDs are involved in many pathologies (e.g., diabetes, atherosclerosis, pathogen infections, neurodegenerative diseases and cancer). Moreover, it has been demonstrated that their number and size increase during an inflammation or infectious inside the immune cells, also with the COVID-19. Therefore, detecting LDs within single cells could aid the diagnosis of several pathologies. Currently, the gold-standard technique in this field is Fluorescence Imaging Flow Cytometry (FIFC), in which the single-cell analysis of fluorescence microscopy is implemented in high-throughput modality thanks to the flow-cytometry module. However, to overcome the drawbacks related to the fluorescence staining, Holographic Imaging Flow Cytometry (HIFC) has gaining momentum as label-free alternative to the FIFC tool. Thanks to the interferometric principles at the basis of digital holography, it has been already demonstrated that a suspended cell acts as a biological lens with specific focusing features. Here we show that the presence of intracellular LDs inside the cell is able to change its focalization features, measured through a HIFC system. Therefore, based on this property, we demonstrate that a detection of single cells containing intracellular LDs is possible by means of a direct analysis of the digital holograms recorded in flow cytometry modality. The attained results open the route to the development of a fast, non-destructive, and high-throughput tool for the diagnosis of LDs-related pathologies by exploiting the biolens’ signature in HIFC.

Digital Holography (DH) is a label-free optical microscopy technique which allows reconstructing the Quantitative Phase Maps (QPMs) of transparent biological specimens. In a QPM, the phase-contrast is endogenous and is due to the Refractive Index (RI) and thickness differences. Although phase-contrast allows a quantitative characterization of the whole biological sample, it is often not enough to ensure an adequate intracellular segmentation, also because of the lack of exogenous markers, e.g., fluorescent dyes. Here we investigate a biological strategy for increasing the intracellular contrast inside epidermal onion cells to recognize their nuclei within the QPMs. Plant cells continuously undergo dehydration-hydration loops during their lifetime since dehydration is reversible when plasmolysis is not reached. Therefore, by setting specific environmental temperature and humidity, we can induce dehydration, thus provoking the water evaporation from the vacuole and therefore increasing the nucleus-cytoplasm contrast. Moreover, the reduction of the turgor pressure causes a rearrangement of the cytoskeleton, thus allowing nuclear roto-translations. We exploit an ad-hoc algorithm to estimate the nucleus rolling angles around the image plane. Then, we perform phase-contrast tomography to reconstruct the three-dimensional (3D) RI distribution of the plant cells’ nuclei by operating in complete reversible conditions, i.e., before plasmolysis when no cell damage has occurred. Finally, we segment the nuclear tomograms to isolate the 3D nucleoli, thus providing quantitative measurements about their volumes, dry masses, and RI statistics. In this way, DH can be further exploited for the label-free and non-invasive analysis of several plant cell lines at the nuclear and sub-nuclear level.

With the improvement in industrial production technologies, many products related to thin-film materials have been produced, especially in the field of daily chemistry. Because of its special physical and chemical properties, film material has become the best carrier, and a detailed measurement of its characteristics is highly required. The thickness characterizing of the thin film is a long-term challenge, one of the well-known methods is the interferometry. Recently, digital holographic approaches have been considered as one of the best candidates for thin film thickness mapping; it allows real-time, contactless, label-free, and full-field thickness measurement. Thanks to above features, holography-based thin film fabrication paradigm has been established rapidly. In this framework, we present a strategy for forming free-standing thin liquid film under the monitoring of Digital Holography (DH): a customized iris diaphragm has been used to stretch the liquid droplet inside to a thin liquid film. Under the condition of quantitatively adjusting the opening speed and radius of the iris, the precise manufacturing of the desired thin film can be achieved. In this case, DH is implemented to provide the thickness distribution of the droplet during stretching; the real-time thickness mapping of thin film builds up a close loop controlling for fabrication process. Based on this strategy, we performed a series experiments of thin liquid films fabrication and the opening process of thin film have been studied by spatiotemporal modeling. The results show that customized iris diaphragm is a good strategy for quantitative fabrication of thin liquid films.

Cancer remains a significant global medical challenge, and the selection of effective treatment modalities is crucial for an optimistic prognosis. Photothermal therapy, being non-invasive and targeted, holds immense potential for future therapeutic developments. Due to their high biocompatibility, carbon nano-onions particles are frequently employed as photothermal materials. The investigation of the dynamic three-dimensional distribution of these nanoparticles within cancer cells is imperative for constructing an accurate photothermal conversion model. In this research, we employed digital holographic tomography to monitor the temporal changes in the three-dimensional distribution of onion-like carbon nanoparticles within colorectal cancer cells. We reconstructed the three-dimensional refractive index distribution of carbon nano-onions particles within cancer cells at different time points. Further, we quantified two morphological parameters, surface area and volume, of these nanoparticles within cancer cells and performed preliminary analysis of their temporal evolution. This methodology introduces a novel perspective to study the interaction between Carbon nano-onions particles and cancer cells, enhancing our understanding of the photothermal therapy mechanism.