In recent years, advances in laser-based technologies have fueled a continuing optical revolution in neuroscience. Laser technology has the advantages of non-invasiveness, high spatial resolution, and high specificity, and has been widely used in neuroscience research. It has been found that many brain diseases are related to the changes of ion channels and neuron discharge characteristics. The study of the effect of weak laser light on the characteristics of ion channels of central nervous cell membranes can guide the treatment of certain brain diseases by direct action of laser probes on brain tissue. In our research, The hippocampal neurons of SD rats were irradiated with 850 nm and 980 nm near-infrared lasers, the currents of potassium and sodium channels before and after laser stimulation were recorded synchronously with a patch-clamp amplifier. It was found that the 980 nm, 20 mW laser has a stronger regulatory effect on potassium channel currents at the same irradiation dose, the neuron inhibitory effect is obvious when the laser is irradiated for 15 minutes. The 850 nm, 20 mW laser has more obvious regulation and recovery effect on sodium channel currents, the neuron inhibitory effect is obvious when the laser is irradiated for 10 minutes. In addition, we theoretically developed a thermal transfer model of the near-infrared laser on the microenvironmental temperature field in the neuronal solution, mainly analyzing photothermal effects of irradiated cells at different wavelengths (850 nm and 980 nm) and different powers (5 mW, 10 mW, 20 mW, 75 mW). The model calculation indicates that the 980 nm, 75 mW laser photothermal effect under the same conditions has greater temperature rise, which increases the neuronal surface temperature by 6-10°C under the heat transfer model studied here, and find the light source parameters needed for neurogenesis and excitement.
Laser self-mixing interferometry (SMI) is often used for displacement, vibration, and velocity measurement. At present, the measurement accuracy has reached tens of nanometers, but it has not been used for single cell detection. In this research, a microfluidic chip-based equipment using SMI technology for label-free single cell detection was demonstrated. The detection experiments were performed to verify chicken erythrocytes and human breast cancer cells T47D. In order to better analyze these data, the Hilbert transform was used to convert the time domain signal into phase information. It is found that there are more fringes in the signal of larger breast cancer cells. The power spectrum of the signal shows that the velocity of the cell is positively correlated with the Doppler shift. The new method for single cell detection proposed in this paper provides a new idea for real-time cell detection.
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