The PDF file contains the front matter associated with SPIE Proceedings Volume 11900, including the Title Page, Copyright information, and Table of Contents.

Compared to traditional optical technology, Mueller matrix imaging can obtain sample’s complete polarization properties, thus can better characterize the microstructure and anisotropy information of the sample. For thick biological tissues or insitu living organs, backscattering Mueller matrix imaging is particularly attractive. In previous studies, we have established the collinear reflection Mueller matrix microscope based on dual rotating retarders (DRR-CRMMM), whose long acquisition time makes it difficult to characterize the polarization properties of the dynamically changing sample. In this paper, we propose and implement a fast collinear reflection Mueller matrix microscope based on dual DoFP polarimeters (DoFPs-CRMMM) and the corresponding calibration scheme to achieve accurate measurements. The system, which takes a Mueller matrix image within a few seconds, is tested for polarization monitoring of biological tissues during tissue optical clearing, and various polarization feature parameters are derived from the Mueller matrix images to reveal the characteristic microstructure variation of the tissues during the dynamic process of tissue optical clearing.

Artifacts, nonuniform resolution and a slow reconstruction speed have limited the full capabilities of emerging light-field microscopy for in toto extraction of dynamic spatiotemporal patterns in samples. We overcome this limitation through combining a view-channel-depth (VCD) neural network with light-field microscopy, yielding artifact-free three-dimensional image sequences with uniform spatial resolution and high-video-rate reconstruction throughput. We imaged neuronal activities across moving Caenorhabditis elegans and blood flow in a beating zebrafish heart at single-cell resolution with volumetric imaging rates up to 200 Hz.

Utilizing reflective photons could circumvent the penetration limit of FMT, enabling reconstruction of fluorescence distribution near the surface regard less of the object size and extending its applications to surgical navigation and so on. Therefore, a time-domain reflective fluorescence molecular tomography (TD-rFMT) is proposed. The system excites and detects the emission light from the same angle within a field of view of 5 cm. Because the detected intensities of targets depend strongly on the depth, the reconstruction of targets in deep regions would be evidently affected. Therefore, a fluorescence yield reconstruction method with depth regularization and a weighted separation reconstruction strategy for lifetime are developed to enhance the performance for deep targets. Through simulations and phantom experiments, TD-rFMT is proved capable of reconstructing fluorescence distribution within a 2.5-cm depth with accurate reconstructed yield, lifetime, and target position(s).

Light has been nearly perfect in many aspects to probe and treat biological tissues. Its applications, however, are limited to superficial layers beneath sample surface or compromised resolution at depths due to the inherent strong scattering nature of light in tissue. Since 2007, optical wavefront shaping has demonstrated its powers against such strong scattering to achieve focused or controllable optical delivery within or through scattering media. In this talk, we present our recent endeavors in this field towards robust and optimum optical focusing and stimulation. Future roadmaps are also discussed.

Laser speckle imaging has been an indispensable tool for in vivo imaging of blood flow in biological tissues. Here we report a novel design of laser speckle imaging system, which combines confocal illumination and detection with various speckle analysis methods. An illumination line is formed using a cylindrical lens and a 1-D scanning mirror is used to rapidly scan the line across the sample surface. The backscattered light is detected with a line camera at the confocal position. The acquired line speckle patterns can be analyzed with different methods, including temporal autocorrelation and spatial evaluation of speckle contrast, to retrieve the maps of correlation time and flow velocity. The line-scan configuration enables fast image acquisition, while confocal detection helps reject out-of-focus light and define a small focal volume. In vivo image experiments with chick embryos have demonstrated the excellent imaging performance, including depth selectivity, high spatial resolution for visualizing blood flow in the microvasculature, and high temporal resolution for dynamic flow quantification.

The majority of current microfluidic flow cytometers were fabricated by a tractable material, PDMS (Polydimethylsiloxane), which exhibited unsatisfactory optical performances. In this work, we firstly presented an all-glass microfluidic flow cytometer (agFCM) which remarkably improved the optical performance and corresponding blood cell detection accuracy.Picosecond laser was introduced to pattern microfluidic channels, on-chip optical waveguides and on-chip micro-lens on a glass substrate (made with fused silica). The glass debris and burrs caused by laser machining were removed from microfluidic channels by ultrasonic cleaning and CO₂ laser reflux respectively. The fabricated glass micro-channel with on-chip lens was sealed by bonding another glass layer to form the agFCM chip. The experimental results demonstrated that, compared with PDMS based devices, agFCM chip improved the optical performances as follows: 1) Scattering haze of material surface was reduced from 50% to 1.4%, effective light transmittance has increased5%.2) the focused excitation spot in detecting area was reduced from 3.60 to 2.64μm. 3) The coupled optical loss of the chip waveguide is reduced to less than 1dB.To sum up, introducing glass as chip material improved the signal to noise ratio by 0.66dB.The performances of agFCM were verified by microsphere experiments. As expected, the improved optical parameters of agFCM resulted in related improvement on detecting accuracy.

Polarimetry is sensitive to the microstructures and has its advantages in characterizing the tissue microstructures. Our previous work on dynamic polarization changes with tissue clearing has investigated the tissue variations by using glycerol,saturated sucrose and formamide.In this study, we use a fast Mueller matrix microscope to quantitatively compare the different mechanisms of two clearing agents: glycerol and formamide. We obtain the temporal Mueller matrix images with an interval of 15 seconds and extract the temporal features of polarization parameters. Except the depolarization and linear retardance, we also analyze Mueller matrix transformation (MMT) parameters and rotation invariants derived from Mueller matrices. The former is used to characterize the microscale anisotropy of scattering media, and the latter is suitable for assessing the breaking of symmetries of scattering matrix. These Mueller matrix parameters convey the micro characteristic of biological tissues, and then help to explore and explain the microstructural changes of tissue properties by optical clearing.

We proposed a new approach to evaluate tissue rheological properties by assessing the stochastic motion of optical vortices in the pseudo-phase representation of laser speckles. By studying the vortex MSD and VAF, we observed the anomalous diffusion of optical vortices and evaluated the viscoelastic modulus of different gel phantoms and tissue samples with diverse mechanical and optical properties. We established the direct relationship which connects the microscopic motion of the optical vortices to the macroscopic viscoelastic response of the multiple scattering viscoelastic media. We can imagine amounts of biomedical applications including blood coagulability monitoring, atherosclerotic plaque characterization, and tumor localization.

White blood cells are a significant part of immune system, which can prevent human body from infection and invasion of foreign invaders. The count and recognition of white blood cells plays an important role in modern clinical practice. There is an urgent need to modify the conventional methods (such as cytometry), which are time-consuming and labor-intensive for white blood cell counting. This paper describes a microfluidic cytometer for white blood cells integrated a three-dimensional hydrodynamic focusing system and on-chip optical components, which can realize single-cell fluid flow and single-cell detection. Through the experiment, the device achieves the hydrodynamic focusing of cell flow and the detection of side scatter and fluorescence. For classifying and counting of white blood cells, we further perform an experiment using blood samples and get fairly good results.

The whole dynamic process of blood coagulation can be characterized by tracking the MSD of optical vortices with our previous coagulation measurement system. To develop a portable prototype of the coagulation detection system, we use an embedded system for whole blood laser speckle image acquisition, and apply deep learning methods for the temporal and spatial interpolation of the acquired images and the fast localization of optical vortex. The prototype implementation with a compact optical design and experimental validation provide a feasible idea and method for the miniaturization of blood coagulation devices.

Microwave hyperthermic tumor ablation has played an important role in the treatment of bone tumors because of its obvious curative effect, less side effects and fewer complications. However, the real-time thermal injury evaluation model of bone and related soft tissue during microwave ablation is still in exploration. In this paper, it proposes to study thermal injury evaluation optical parameters of bone tissue during microwave ablation. In the microwave ablation experiment, it studied the changes of tissue near-infrared spectrum and optical parameters (reduced scattering coefficient, slope factor, area factor) during specific microwave ablation conditions. It was found that some factors (slope(524-532) and slope(565-570)) changed significantly, correlated with microwave ablation time, which could be used as evaluation parameters of bone thermal injury. The chosen slope factors can well describe the features of bone during microwave ablation, and have the potential to be used in microwave ablation computer-aided design. The results lay a foundation for establishment of a real-time evaluation system of bone tissue during microwave ablation.

Vascular-targeted photodynamic therapy (V-PDT) offers great promise as a treatment modality for vascular-related diseases. The injury of targeted blood vessels correlates to the singlet oxygen generation, which is affected by dosimetric parameters, including photosensitizer concentration, hemoglobin oxygenation concentration, and blood flow velocity. In this study, we developed an optical imaging system that combining hyperspectral imaging (HSI), dual-wavelength reflection imaging (DWRI) (λ₁ = 500 nm and λ₂ = 660 nm) and laser speckle imaging (LSI). The capability for monitoring dosimetric parameters has been demonstrated for in vivo imaging of hemoporfin-mediated V-PDT in a dorsal skinfold window chamber model. The HSI allows for simultaneously monitoring the changes of photosensitizer concentration and vasoconstriction of blood vessels, while the DWRI and LSI were used to measure hemoglobin oxygenation concentration and blood flow velocity, respectively. This study suggests that our home-built optical imaging system holds the potential for assessing the V-PDT efficiency in vivo and optimizing the treatment protocol.

Prostate cancer is one of the most common malignant tumors in elderly men worldwide with the sixth cause of cancer death in men. It has a high mortality rate, and early diagnosis contributes to a favorable prognosis. Noninvasive detection methods with high sensitivity and specificity are therefore always being sought for prostate cancer diagnosis. In this paper, a method for serum analysis combining membrane protein purification with silver nanoparticle-based surface-enhanced Raman spectroscopy (SERS) for non-invasive prostate cancer detection was present. In this work, total serum proteins were isolated from human serum by cellulose acetate (CA) membrane, and then the purified serum proteins were mixed with silver nanoparticles to perform SERS analysis. This method was evaluated by analyzing serum samples from patients with prostate cancer (n = 10) and healthy volunteers (n = 10). To further investigate the diagnostic ability of proteins isolated from human serum, multivariate statistical analysis was employer to analyze SERS data. Principal component analysis combined with linear discriminant analysis (PCA-LDA) was used to identify the serum protein SERS spectra from prostate cancer patients and healthy volunteers, and the diagnosis sensitivity and specificity of prostate cancer were 90% and 80%, respectively, as compared with the healthy volunteer. Moreover, receiver operating characteristic (ROC) curves further confirmed the effectiveness of PCA-LDA diagnostic algorithm. Notably, this algorithm predicted prostate cancer with an area under the curve (AUC) of 0.940. The results demonstrated that serum protein SERS technology combined with PCA-LDA diagnostic algorithm has great potential for the noninvasive screening of prostate cancer.

Quantitative phase imaging (QPI) has quickly emerged as a powerful tool for label-free living cell morphology and metabolism monitoring. However, for current QPI techniques, interference signals from different layers overlay with each other and impede nanoscale optical sectioning. This phenomenon leads to unsatisfactory performances for optically thick or complex scattering biological samples. To address this challenge, we have developed an alternative quantitative phase microscopy with computational hyperspectral interferometry. Nanoscale optical sectioning could be achieved with Fourier domain spectral decomposition. Morphological fluctuations and refractive index distribution could be reconstructed simultaneously with 89.2 nm axial resolution and 1.91 nm optical path difference sensitivity. With this method, we established a label-free cell imaging system for long-term cellular dry mass measurement and in-situ dynamic single cell monitoring. Different intrinsic cell growth characteristics of dry mass between HeLa cells and Human Cervical Epithelial Cells (HCerEpiC) were studied. The dry mass of HeLa cells consistently increased before M phase, whereas that of HCerEpiC increased and then decreased. The maximum growth rate of HeLa cells was 11.7% higher than that of HCerEpiC. We also use the proposed method and system to explore the relationship between cellular dry mass distributions and drug effects for cancer cells. The results show that cells with higher nuclear dry mass and nuclear density standard deviations were more likely to survive the chemotherapy. The presented work shows potential values for cell growth dynamics research, cell health characterization, medication guidance and adjuvant drug development.

Background: Liver cancer is a leading cause of cancer mortality in China. Early diagnosis and treatment play a significant role in reducing liver cancer mortality. Aims: In this preliminary study, the feasibility of using surface enhanced Raman spectroscopy (SERS) of serum to identify primary liver cancer was explored. Materials and methods: Serum samples were obtained from liver cancer patients (n = 25) and healthy controls (n = 30). Nano-silver (Ag) colloids (45 ± 6 nm) were used as the SERS substrate and mixed with serum samples (10 μL). Raman spectra were obtained from a confocal Raman micro-spectrometer (Renishaw) and spectral characteristics analyzed. Results: Analyses of spectral characteristics showed noticeable differences in peak heights between the mean spectra of the control and patients, mainly reflected in following peak positions: increased at 496, 593, 637, 726, 813, 888, and 1137 cm^-1, and decreased at 1580 cm^-1, respectively. Which might be attributable to glycogen, phosphatidylinositol, aminoacid methionine, C-S (protein), C-C stretching, methylene rocking, palmitic acid and C-C stretching, respectively. Conclusion: These preliminary analyses suggest that SERS might be useful for the identification of serum markers of liver cancer.

Cell classification is a fundamental task in biological research and medical practices. In this study, we proposed a singlecell classification pipeline through machine learning and hyperspectral stimulated Raman scattering imaging. The pipeline proposed is validated by using hyperspectral SRS images of two types of pancreatic cancer cells before and after the treatment of drugs that affects cellular cholesterol level. The result demonstrates that the proposed machine learning pipeline is capable of classifying cells with different metabolite dynamics, which provides possibilities for wide applications in cell analysis.

Excimer Laser Coronary Atherectomy (ELCA) uses 308nm laser to eliminate coronary atherosclerosis. It has a good therapeutic effect in diseases such as poor stent expansion, moderate calcification, and acute myocardial infarction. The laser catheter enters the patient's body during the operation and transmits the laser to the lesion, which plays an important role in the success of the operation. In this paper, the finite element simulation analysis of the mechanical properties of the laser catheter is carried out, and innovative optimization design is carried out on this basis. The paper first analyzes the laser catheter composite material, establishes its torsion, compression, and bending finite element model, and analyzes the influence of the microstructure on the mechanical properties of the laser catheter. Set different parameters for the helix angle, number and diameter of the optical fibers in the laser catheter, and simulate the stress conditions under three kinds of loads. The results show that the three variables have a great influence on the stress and deformation of the laser catheter composite material. Then a finite element model of the coronary artery of the heart is established, the laser catheter's movement in the coronary artery is simulated by LS-DYNA, and the effect of the laser catheter's diameter, wall thickness and elastic modulus on the stress of the laser catheter is analyzed. It is found that the laser catheter is subject to greater stress at the bending part of the aortic arch, and the diameter, wall thickness and elastic modulus of the laser catheter have a significant influence on the stress and advancing distance of the laser catheter. Finally, on the basis of simulation analysis and comprehensive consideration of various influencing factors, the parameters of the laser catheter are designed. In order to meet the stress requirements of different positions of the laser catheter, a catheter design with variable fiber helix angle is proposed.

Hemporfin is asecond generation photosensitizerand has been used in combination with laser and LED to treat vascular and cancerousdiseases in China. In this study, four different light sources were evaluated for Hemoporfin PDT. Photobleaching experiments were carried out by exposing Hemoporfin solution to green diode laser, red diode laser, green LED, and red LED, respectively, under the same power density (30 mW/cm²) for different lengths of time. Hemoporfin fluorescence was measured before and after light exposure. Photobleaching kinetics showed the order of greenlaser > green LED > red laser> red LED. This study suggests that all tested light sources could be used for Hemoporfin PDTbut the power density and exposure time of different light sources need to be adjusted in order to achieve the same levels of photodynamic effect.

Positron emission tomography (PET) is an indispensable medical imaging technique which can reveal the physiology activities by injecting special PET tracers. In recent years, deep learning has been widely used in PET reconstruction tasks. In this work, a multiscale direct reconstruction framework based on cGANs has been presented. First, the generator is built as two scales which will combine both global and detail information in training phase. Second, to match the generator, we tried multiscale discriminators. Each discriminator shares the same structure, but operates on different scales. Both coarse field and fine field were scored by the discriminators, so this score considered not only the global structure but also fine details. In order to verify the feasibility of the proposed framework, both simulation datasets and real SD rat dataset were utilized in our experiments. We also compared our method with U-Net and Deep- PET network, the results showed that we got more accurate and real radioactivity images on all datasets.

The importance of accurate attenuation correction (AC) in positron emission tomography (PET) has been widely recognized. However AC based PET/CT or PET/MR suffers from several problems such as artifacts and noises. In this paper, we propose a novel method based on physics-driven Iteration Shrinkage-Thresholding Algorithm (PISTA) to achieve quantitative PET image reconstruction from raw sinogram data without AC. The PISTA utilizes system matrix which is used as geometry of projection between quantitative PET activity images and sinograms without AC, to generate the next updated quantitative PET activity images as the input of learnable part. An evaluation study on simulated phantom data is described, where experimental results have shown great promise for such strategy.

Type 2 diabetes mellitus is one of the most common metabolic diseases in the world. However, frequent blood glucose testing causes continual harm to diabetics, which cannot meet the needs of early diagnosis and long-term tracking of diabetes. Thus non-invasive adjuvant diagnosis methods are urgently needed, enabling early screening of the population for diabetes, the evaluation of diabetes risk, and assessment of therapeutic effects. The human eye plays an important role in painless and non-invasive approaches, because it is considered an internal organ but can be easily be externally observed. We developed an AI model to predict the probability of diabetes from scleral images taken by a specially developed instrument, which could conveniently and quickly collect complete scleral images in four directions and perform artificial intelligence (AI) analysis in 3 min without any reagent consumption or the need for a laboratory. The novel optical instrument could adaptively eliminate reflections and collected shadow-free scleral images. 177 subjects were recruited to participate in this experiment, including 127 benign subjects and 50 malignant subjects. The blood sample and sclera images from each subject was obtained. The scleral image classification model achieved a mean AUC over 0.85, which indicates great potential for early screening of practical diabetes during periodic physical checkups or daily family health monitoring. With this AI scleral features imaging and analysis method, diabetic patients’ health conditions can be rapidly, noninvasively, and accurately analyzed, which offers a platform for noninvasive forecasting, early diagnosis, and long-term monitoring for diabetes and its complications.

There are many situations in medicine and biology when it is desirable to introduce a macromolecule into mammalian cells. Gold nanoparticles mediated photoporation is a promising technique that is an efficient, relatively high-throughput and virus-free method. Up to now different pulse laser and kinds of gold nanoparticles with different size, different shape were employed to achieve photoporation for macromolecule delivery such as dextran, protein and plasmid. Here, gold nanosphere and nanorod activated by nanosecond laser were used to improve permeability of membrane, fluorescence labeled dextran and antibody were delivered into cells. The influence of laser parameters and the micro-environment around cells were analyzed, the results showed that concentration of gold nanoparticles is important for photoporation, the cells is easy to die with higher concentration above 104 gold nanoparticles per cell that corresponding to a narrow irradiation fluence. Results also demonstrated that for cells incubated in PBS, successful permeabilization was observed at lower irradiation fluence than cells incubated in RPMI medium. During irradiation the micro-phenomena was observed by homemade plat, we found that the vapor bubble generation around gold nanoparticles is the main mechanism of the photoporation, and the properties of these nanobubbles are highly dependent on the size of the nanoparticles and the properties of the laser pulse according to extended two-temperature model. In addition, a diffusion model that based on measuring resealing time invasively, was established to assess the loading efficiency, results showed that this approach is an ideal and accurate estimation of the loading efficiency of cells by photoporation for accounting hole-resealing dynamics.

Acquisition of the genes encoding variable regions of paired heavy and light chains (VH:VL) is crucial, but it is a labor and cost-intensive process in traditional methods. This study presents a novel method in which all processing steps for acquiring natively paired VH:VL genes from single cells are finished in a single microfluidic chip. The microfluidic chip performs single-cell trap/in situ fluorescent examination of antibody specificity/cell lysis/gene amplification all at single-cell level. By a proof-of-concept validation of efficiently acquiring paired VH:VL genes of anti-RBD (which is a key protein of SARS-CoV-2 virus) mAbs from single hybridomas, the microfluidic chip has been proved capable of remarkably improving cell loss/human labor/time cost, and more importantly, determinacy of native VH:VL genes pairing which is one of the most decisive factors of effectiveness for antibody discovery.

Photoacoustic imaging (PAI, also called optoacoustic imaging) combines light excitation and ultrasound detection for deep-tissue imaging with light absorption contrast. PAI can map the distribution of endogenous chromophores such as oxy-hemoglobin, deoxy-hemoglobin, lipids, water, and melanin. PAI performs especially well for structural and functional imaging of blood vessels. Its centimeter-deep imaging depth and ultrasound-defined resolution make it well suited for clinical application, where systems employing a linear array ultrasound probe are most commonly used due to simplicity, flexibility, and easy integration with standard ultrasonic imaging. The existing linear array based imaging systems typically employ optical fiber bundles for light delivery, such a scheme enjoys mechanical flexibility, optical stability, and simple light coupling. However, major drawbacks associated with fiber illumination include suboptimal transmission efficiency and a lack of control of the illumination pattern. Articulated arms provide an alternative light delivery option which potentially offer high transmission efficiency, stable and flexible operation, and low cost. Despite its wide applications in cosmetology, articulated arms for light delivery were understudied in the PAI community. In this paper, we reported the fabrication and experimental evaluation of an articulated arm specifically designed for linear-array-based PAI. Without losing the flexibility provided by the linear probe. Moreover, the articulated arm can be equipped with spatial positioning devices to perform three-dimensional reconstructions.

Endoscopic optical coherence tomography (OCT) has been demonstrated for volumetric imaging of subsurface features with high resolution. However, it is difficult to enable endoscopic OCT angiography (OCTA) due to the low inter-frame stability of endoscopic OCT. Recently, stable distal rotational scanning of micromotor catheter enabled imaging of structural features in the en face plane as well as endoscope OCTA. However, most endoscopic OCT in the lab and almost all commercial ones use proximal scanning catheters for diagnosing endoscopic tissues which should be designed much smaller than micromotor catheters. Here, we presented a proximal scanning endoscopic OCT technology that enabled OCTA. A spatiotemporal singular value decomposition (SVD) process was used to remove the eigen components that represented static tissue signals to generate that of the final moving particles. Primary results revealed that the endoscopic imaging system enabled OCTA in the two-and three-dimensional in vitro flow phantom. As the catheter’s outer diameter is less than 1 mm, the system is of potential for providing a more accurate assessment for pancreatic and bile duct cancers and even cardiovascular disease in clinical applications.

Based on the pulse theory of the traditional Chinese medicine, the pulse diagnostic instrument can diagnose diseases. The most important step in pulse diagnosis is to extract the characteristic points from the measured pulse wave. The flat pulse waveform is gained from the pulse wave measured by the photoelectric sensor. The collected signal is filtered and denoised through wavelet transform to make the waveform smoother and reduce the impact of noise on subsequent feature extraction. Feature extraction of signal is mainly analyzed and processed in time domain, frequency domain and time frequency domain. In the time domain, some feature points of the original waveform are extracted. In the frequency domain, Fourier transform of the original signal is used to extract the spectral characteristics of the signal. In the time-frequency domain, the feature of signals are extracted by using of the Hilbert yellow transform. The original signal is decomposed through EMD (Empirical Mode Decomposition) to obtain several IMF (Intrinsic Mode Function), and then the Hilbert transform is carried out on several IMF to obtain the Hilbert spectrum. All the spectra are summarized to obtain the original spectrum. Through the combination of the wavelet transform and Hilbert yellow transform to process the original waveform, the characteristics of the pulse wave can be more clearly and accurately in the time domain, frequency domain and time-frequency domain, which is conducive to the subsequent judgment of the disease corresponding to the waveform.

Renal calculi (kidney stones) that occur in human urethra is considered as one of the most painful urological disorders. Recurrence rates are close to 50%, it affects 5-15% of the population worldwide and the costs to individuals and society are high. Accurate analysis of such calculi plays a vital role in the evaluation of urolithiasis patients and in taking appropriate preventive measures to inhibit the formation or growth of kidney stones. In this paper, surface-enhanced Raman spectroscopy (SERS) was used to detect and analyze the plasma from patients with kidney stones and normal volunteer. In this preliminary experiment, principal component analysis (PCA) was used as a spectral dimensionality reduction method, and linear discriminant analysis (LDA) was used to classify the SERS spectra of plasma samples from patients with kidney stones (n=10) and healthy volunteers (n=10). The high quality SERS spectra were obtained in the range of 400-1800cm-1. The discriminant sensitivity and specificity were 80% and 100%, respectively. The difference spectrum analysis combined with the assignment of SERS bands indicated that there were subtle but significant changes between the normal and the kidney stone plasma, indicating that the contents of nucleic acids, proteins, lipids and other bio-molecules in different cell lines had special changes. The (ROC) curve of receiver performance further confirms the effectiveness of the diagnosis algorithm based on PCA-LDA. This exploratory work shows that the combination of SERS technology and PCA-LDA algorithm has great potential in the development of a label-free, non-invasive and accurate detection and screening of kidney stone.

In this work, Surface-enhanced Raman spectroscopy (SERS) involving blood plasma was investigated; the objective was to determine whether this approach could distinguish prostate cancer with benign prostatic hyperplasia. The experimental samples were prepared by blood plasma mixed with the silver colloid over an aluminum plate substrate. A total of 14 SERS spectra for prostate cancer (PCa) and 14 spectra for benign prostatic hyperplasia (BPH) were successfully gathered from patients who came from Fujian Provincial Hospital. Difference spectrum analysis combined with the assignment of Raman bands indicated that there were subtle but distinct changes between prostate cancer (PCa) and benign prostatic hyperplasia (BPH), which could be related to the level of prostate specific antigen (PSA); because it has been reported that the level of PSA is increased in men who have prostate cancer compared with those with benign prostatic hyperplasia (BPH). To further make clear the difference of Prostate cancer (PCa) and benign prostatic hyperplasia (BPH), the spectral data was combined with multivariate analysis processes. Principal component analysis (PCA), as a spectral dimensionality reduction approach, and in conjunction with linear discriminant analysis (LDA) were employed to identify the samples, to build diagnostic algorithms. The leave-one-out cross-validation method was used to validate the diagnostic algorithms; the result showed that a sensitivity of 95.8% and a specificity of 100.0% which indicated can significantly differentiate PCa and BPH groups. In addition, we further verify the validity of the diagnosis algorithm based on PCA-LDA diagnosis algorithm by using receiver operating characteristic (ROC) curves. The results of experiment study suggest that SERS combined with PCA-LDA algorithms has great potential for clinical screening of benign prostate hyperplasia and prostate cancer.

At present, bladder cancer has become a common malignant tumor around the world, and the number of deaths from bladder cancer is also increasing year by year. Therefore, it is necessary to develop a powerful technology for further analysis. In this paper, we used a new method of surface enhanced Raman spectroscopy (SERS) to detect the plasma of 10 normal volunteers and 10 patients with bladder cancer, and successfully recorded their spectra. At the same time, the plasma of normal persons and patients was analyzed by difference spectrum analysis, principal component analysis(PCA), linear discriminant analysis(LDA) algorithm, and receiver operating characteristic (ROC) curves. The difference spectrum analysis shows that there are slight but significant differences in the spectra between normal plasma and bladder cancer plasma, which may indicate that some changes have taken place in the contents of protein, nucleic acid and lipid in patients with bladder cancer. PCA was used to investigate the correlation of multiple variables, so as to reduce the dimension, and combined with the LDA algorithm to distinguish normal samples and patient samples, the sensitivity and specificity are 80% and 100%, respectively. Finally, the area under the receiver operating characteristic（ROC） curve is 0.97, which further proves the validity of the diagnostic algorithm based on the PCA-LDA diagnostic algorithm. The exploratory work showed that the combination of SERS technology and PCA-LDA algorithm could distinguish the plasma of normal people and bladder cancer patients. And further showed that SERS could be used as a simple and effective method for the detection of clinical cancer.

The accurate distinction of the true and fake blood is very important work in the fields of biomedical treatment, criminal investigation, animal inspection, food safety, etc. In this work, the near infrared spectroscopy was used to obtain the spectral of blood samples. Four kinds of animal blood (horse, cow, rabbit, and sheep) and two kinds of fake blood (props blood, and red ink) were test. 120 groups and 30 groups of blood were used as the training sample and test samples. In the experiments, the optical diffuse reflection spectra of blood samples were obtained at the wave-number from 4000cm^-1 to 10000cm^-1. From the experimental results, it can be seen that the optical spectra profiles are very similar between the animal blood and between the fake blood, although the spectra profiles between the true blood and the fake blood are different. At the same time, the spectra overlap are also existed in the true and fake blood, which results in the difficulty of distinguishing the different types of blood. To rapidly and accurately distinguish the true and fake blood, the wavelet neural networks (WNN) algorithm was used to train the training blood samples. Under two optimal learning rate factors, the correct rate of distinguishing true and fake blood is about 23.3%. To improve the correct rate, the genetic algorithm (GA) was used to optimize the weights, thresholds, scaling and translation factors of WNN. Under the optimal parameters of WNN-GA algorithm, the correct rate reaches 56.7%. To further improve the correct rate, the principal components analysis (PCA) algorithm was combined into WNN-GA, i.e., PCA-WNN-GA algorithm was used. The correct rate can reach 96.7% under the optimal principal components. Therefore, near infrared spectroscopy combined with WNN-GA algorithm has the potential value in the identification of blood origin.

Background: Acute tubular necrosis (ATN) after renal ischemia-reperfusion would cause the loss of functional units in the kidney, that are usually used to characterize the activity of the kidney. Apparently, ATN will lead to uneven distribution of uriniferous tubules. The renal activity could be evaluated by analyzing the uniformity of renal tubular distribution. Methods: Optical coherence tomography (OCT) has been proved to have the ability of imaging the microstructure of kidney in vivo and in real time. Based on the renal ischemia-reperfusion model of Wistar rats described in previous studies, kidneys of three Wistar rats were ischemia for 75 minutes and reperfused for one and a half hour. The normal kidney before ischemia and every 5 minutes after blood reperfusion were imaged using a SDOCT system in 3D mode in vivo. Inhomogeneous distribution of tubules could be clearly observed in the en face OCT images of kidney after blood reperfusion. Box dimension based on fractal theory can be used to evaluate the uniformity of object distribution. This paper applied box dimension to assess the uniformity of renal tubular distribution in OCT images of kidney. The fractal dimension of en face OCT images at the same depth below the renal capsule were calculated using Fractal box count toolbox in ImageJ. Results: The results showed that the box dimensions of OCT kidney images changed a lot at different times of ischemia-reperfusion process. The value was largest for normal kidney, and reached a minimum when ischemia, then gradually increased to a stable value after reperfusion. Therefore, the fractal box dimension value could be applied to assess the status of kidney. Conclusion: The renal tubular uniformity featured by fractal box dimension of OCT images could be used to evaluate the renal ischemia - reperfusion injury.

With the outbreak of COVID-19，masks，as the most important personal protective equipment, its necessity and importance becomes evident. Particle protective performance, as the key index of masks, the accuracy of its test result is very important. In this study, based on the high-precision photometer, the calibration method of particle protective performance testers for mask is studied. The protective performance is evaluated by the percentage of particle concentration reduction of before and after the mask. Photometric method is a relatively mature technology of particle concentration measurement, with advantages of portability and quick response. In our study, two photometers are used in the calibration. In order to ensure the accuracy, it is necessary to calibrate the two photometers first. Aerosol with concentrations about 1, 10, 20 and 30 mg/m³ is generated in the test chamber, respectively. The filter weight method is used to measure the concentration in the test chamber as the standard values. Within the weighing time, the concentration test results measured by the two photometers are recorded and calibrated with the concentration results measured by the weight method. For the two calibrated photometers, one is used to measure the particle concentration in the test chamber, the other is used to measure the particle concentration in the mask which is attached to the head mold. In this way, the particle protective performance value measured by the instrument can be calibrated. In our experiment, the extended uncertainty of the calibration results are lower than 3%.

Optical coherence elastography (OCE) is a new biomedical optical elastic imaging technology. It inherits the advantage of optical coherence tomography (OCT) with high resolution, and it has sub-nanometer displacement measurement sensitivity. OCE uses OCT to detect the deformation of biological tissue along the depth direction under loading, so as to obtain the elastic information of tissue. Among the OCE forms with various loading strategies, compression OCE has attracted great interests for its ease of implementation. However, the quantitative measurement of the loading remains a challenge. Therefore, in this study, we developed a handheld OCE system based on compression OCE with a specially designed stress sensor for loading measurement. The OCE system is built based on swept-source OCT, and a handheld sampling probe was developed with a specially-designed pressure sensor for load measurement. The OCE probe with the stress sensor is evaluated on both artificial phantom and human skin. The results show that the OCE system has a good potential for elasticity measurement on biological tissues in vivo.

Corneal nerve fibers (CNF) usually exhibit changes associated with ocular and systemic diseases. Thus, in clinic, CNF is imaged by corneal confocal microscopy (CCM) for ocular disease diagnosis. To obtain an objective and accurate diagnosis, CNF needs to be segmented from CCM image and further its centerline is extracted to pave the wave for producing quantitative diagnostic markers. It is reasonable to state that the performance of CNF segmentation and centerline extraction places a big impact on the disease diagnosis. Therefore, in this study, we aim to improve the CNF segmentation and centerline extraction. CNF segmentation algorithm is developed based on UNet++, which is modified by adding skip connection to be more applicable to multi-scale information. Following CNF segmentation, a new CNF centerline extraction algorithm is developed based on neighborhood statistics. Compared with the traditional thinning algorithm and the skeleton extraction algorithm, our method yields a more consistent and smoother central line extraction by reducing the effect of imperfect segmentation and noise which is hard to avoid in deep learning segmentation. The proposed segmentation method is evaluated on an open dataset by comparing with the conventional UNet, UNet++ and UNet3+. The proposed centerline extraction method is evaluated on the same image dataset by comparing with the traditional thinning algorithm and the skeleton extraction algorithm. The results show that our method can outperform the conventional UNet++ in terms of Acc (accuracy), TPR (True Positive Rate), TNR (True Negative Rate), Dice and FDR (False Discovery Rate). The centerline extraction method can extract the centerline with less errors.

Photosensitizer is a key element of photodynamic therapy (PDT). Currently, only limited numbers of photosensitizers are available for antitumor PDT in China. YLG-1 (Ang-Da-Fen-Qi) is a newly developed second-generation chlorin-type photosensitizer. In this preliminary study, the killing effect of combination of YLG-1 and 652 nm diode laser on human nasopharyngeal carcinoma cells and human ovarian cancer cells were investigated. In vitrostudy suggests that YLG-1 mediated PDT activity has strong cancer cell killing effect and therefore potentials for antitumor PDT applications.

Diabetes can not only disrupt the blood brain barrier and the homeostasis of brain microenvironment, but also affect the function of immune cells. Since diabetes is a chronic disease, it is of great value to investigate the changes of various physiological indicators with the development of diabetes, while there are few relevant studies. In this work, the changes of blood brain barrier and microglial function in mice with the development of diabetes was in vivo monitored, using recently arisen skull optical clearing window with a variety of optical imaging techniques. The results showed that with the development of diabetes mellitus, the permeability of the blood brain barrier in the cortex of mice increased gradually, which further induced the morphological and functional changes of microglia. This study is expected to provide a reference for the study of diabetic complications, as well as interventional treatment and efficacy evaluation of diabetes mellitus.

The spinal cord injury (SCI) is a common disease of the central nervous system. Early diagnosis and assessment of patients with SCI in favor of timely treatment, can help patients recover from illness as soon as possible. In this study, we use multiphoton microscopy (MPM) to obtain the high-resolution images of fresh, unfixed, unstained rat spinal cord specimens (normal spinal cord tissue and the tissue of SCI). Our results show that MPM has great potential to identify the characteristics of SCI including the changes in the proliferation and hypertrophy of astrocytes and bleeding area. With the development of MPM, this technique can act as an efficient tool for early diagnosis and assessment of SCI.

In recent years, cancer has become a common health problem faced by all mankind. Liver cancer and prostate cancer are the most common malignant tumors in the world. Early diagnosis is of great significance for the effective treatment of cancer patients and prolonging their life. Therefore, there is an urgent need to develop a powerful method to detect multiple types of cancer. In this work, we developed a surface enhanced Raman spectroscopy combined with principal component analysis (PCA) and linear discriminant analysis (LDA) multivariate statistical method to detect and screen patients with prostate cancer and liver cancer. In order to further verify the validity of PCA-LDA, the receiver operating characteristic（ROC）curve is used to evaluate the effectiveness of the algorithm. The comparison of the average spectra showed that there was a significant difference between the serum samples of patients with liver cancer and patients with prostate cancer. This may be related to the changes of molecular structure and composition of human serum caused by diseases. PCA-LDA algorithm was used to classify SERS in serum of patients with liver cancer and serum of patients with prostate cancer. The sensitivity and specificity were 100% and 90%, respectively. the receiver operating characteristic（ROC）curve shows that the area under the curve is 1. The results show that the combination of SERS and PCA-LDA algorithm has high accuracy in the discrimination and classification of liver cancer and prostate cancer, and the detection is fast and sensitive, which is a potential detection and screening method.

Microvascular network distributes all around the body. Blood vessel is the main channel of tumor development and metastasis, and it is also the channel of drug therapy. So, the tumor vessel feature is very important for characterizing the tumor progress. In our study, OCT was applied on capturing the structure of normal and tumor tissue. Speckle variance algorithm was used to deduce vessel information. And then, vessel character, such as measurable diameters of lumen in blood vessels, vessels tortuosity index and vessel density of vascular between normal vessel and tumor vessel were displayed quantitatively. The result could uncover the difference between the normal and tumor vessel and will help to understand tumor angiogenesis.

Prostate cancer (PCa) is a main cause of cancer-related death among men aged 50 years and above in the world. To the date, prostate-specific antigen (PSA) is a representational tumour marker which has been widely used in the early diagnosis of PCa. However, in realistic clinical tests, high serum levels of PSA show a high probability for false-positive results, leading to misdiagnoses. The main clinical manifestations of benign prostatic hyperplasia (BPH) is histological hyperplasia of the interstitial and glandular components of the prostate, caused the elderly male are painful to urinate, renal function decreased and so on. Prostate adenocarcinoma of which is very similar to BPH can be expressed in a variety of clinical forms. The difference between the two diseases is that BPH as a benign disease can be cured with proper treatment, however PCa as a malignant tumor and major contributor to cancer-related deaths which there is is difficult to cure so far, so it is important to diagnose and treat it at an early stage. By and large, there are several ways to distinguish between BPH and PCa, including rectal touch, prostate biopsy, PSA testing. These screening tools may give rise to unnecessary biopsies and hurt physical and mental health of patients. To avoid unnecessary invasive biopsy, a new technology namely Metabolomics was introduced. It can closely reflect the content changes of various substances in that the metabolites are expressed in the downstream of genome, transcriptome and proteome. Metabolites are not only excreted in the blood, but also excreted in sweat, respiration, urine, feces, etc. This provides a possibility and a novel idea for noninvasive diagnosis. Urine, as a kind of metabolite, can be used to realize non-invasive cancer detection and diagnosis of other diseases. This non-invasive method detecting diseases by used urine analysis has great potential in cancer diagnosis, monitoring and screening. In addition, many metabolites that may reflect cancer specificity are concentrated in and excreted through urine, which further verifies the logicality of this method. In this study, urine samples were collected from patients who were histologically diagnosed with benign prostatic hyperplasia (BPH) or prostate cancer (PCa). By using surface-enhanced Raman spectroscopy (SERS) with silver nanoparticles, a total of 60 SERS spectra 400~1800 cm^-1 were collected from 10 PCa subjects and 10 BPH subjects. Difference spectrum analysis combined with the assignment of Raman bands state clearly that there were obvious changes between prostate cancer and benign prostatic hyperplasia, which could be related to the special changes of xanthopterin, inosine, hypoxanthine, xanthine, uric acid, and urea during pathological changes. In order to distinguish PCa and BPH further, Multivariate statistical techniques, including principal component analysis (PCA) and linear discriminant analysis (LDA) diagnostic algorithms, was employed to analyze the spectra with the result of the diagnostic sensitivity and specificity of 90% and 80%, respectively. It was indicated that the method, using SERS of urine sample combined with PCA-LDA, exhibited good classifications of PCa and BPH. In addition, the effectiveness of PCA-LDA diagnostic algorithm was verified by receiver operating characteristic (ROC) curves and area under the curve (AUC) value was 0.980 (AUC value between 0.85 and 0.95 represents that the effect is very good). Overall, the results of test exhibited the great potential of surface-enhanced Raman spectroscopy analysis of urine combined with PCA-LDA for noninvasive screening and distinguishing PCa from BPH.

The recently reported solvent-based optical clearing method FDISCO can preserve various fluorescent signals very well. However, the strict low-temperature storage condition of FDISCO is not conducive to long-time or repetitive imaging usually conducted at room temperature (RT). Therefore, it is important to solve the contradiction between fluorescence preservation and imaging condition. We develop a modified FDISCO clearing method, termed FDISCO+, to change the preservation condition from low temperature (LT) to RT. Two alternative antioxidants were screened out to effectively inhibit the peroxide generation in the clearing agent at RT, enabling robust fluorescence preservation of cleared samples. FDISCO+ achieves comparable fluorescence preservation with the original FDISCO protocol and allows long-time storage at RT, making it easier for researchers to image and preserve the samples. FDISCO+ is expected to be widely used due to its loose operation requirements.

Mast cells (MCs) undergo degranulation activated by various secretagogues and rapidly secrete pre-formed mediators include in secretory granules, involving in numerous progresses of immune response, hypersensitivity and carcinogenesis. Therefore, it is essential for MCs degranulation detection in vivo and in real-time, particularly the measurement of MC degranulation at single cell level. At the aim of single cell degranulation detection, we here developed a secretion-sensitizing FRET probe, designated tryptase-sensitizing probe (Tryprobe). After treated with C48/80 or trypsin, activated MCs will degranulate to release inflammatory mediators. The release of tryptase in the process of degranulation will destroy the non-fluorescent FRET system of Tryprobe, and then the fluorescence production was detected by fluorescence spectrometer or CCD imaging equipment. Curcumin–pretreated P815 cells sensitized with C48/80, the fluorescence intensity of FRET system significantly declined than the drugs stimulation groups. From single cell scale, the cell morphology is nearly unchanged when cells under the rest state without drug activation. However, after drugs stimulation, the cell morphology is becoming distorting at various degrees, some cells morphology even break in intense degranulation. The morphology change of single mast cell can be observed distinctly in bright field and green fluorescent channel. To real-time observe single mast cell degranulation, we also established Intensity-Scatter correlation for the reconstruction of degranulation to build an evaluation standard for single cell degranulation using Tryprobe detection method. Accordingly, we anticipate this Intensity-Scatter correlation method using Tryprobe system as a template to be applied to other secretions detection of single cell in the cell and molecular biological fields.

Raman micro-spectroscopy (RMS) is a powerful technique for the identification, classification, and diagnosis of cancer cells and tissues.¹ The requirement for long acquisition times of 1-30 s have impeded clinical application. The slow acquisition time can be overcome by the use of coherent Raman scattering (CRS), a class of thirdorder nonlinear optical spectroscopies that employ a sequence of light pulses to set-up a vibrational coherence within the ensemble of molecules inside the laser focus. The two most widely employed CRS techniques are coherent anti-Stokes Raman scattering (CARS) and stimulated Raman scattering (SRS) both of which achieve extremely high acquisition speeds up to the video rate, but traditional architectures are limited in terms of “single frequency” detection resulting from the use of picosecond pump and Stokes pulses with an optical bandwidth of a few wavenumbers. An important breakthrough has been recently achieved by the Cicerone group² using a femtosecond Er:fiber laser oscillator followed by two erbium doped fiber amplifier arms; one arm is frequency doubled to generate narrow-band pulses at 770 nm with a flat-top 3.8 ps temporal profile, while the other is spectrally broadened in a highly non-linear fiber to generate a broad supercontinuum spanning the 900–1350 nm wavelength region. This pulse combination enables extraction of the CARS response by both the two-color and the three-color mechanism. While all previous broadband CARS systems failed to provide a low-noise spectrum in the fingerprint region, this approach has enabled Raman spectra in the whole biologically relevant frequency region (500–3500 cm^-1) to be captured with 10 cm^-1 resolution and 3.5 ms acquisition. Here, we provide guidance on the initial setup and optimization of this bCARS micro-spectroscopy system, with specific examples of the common pitfalls encountered during the setup. This is particularly useful for those coming from a background of designing spontaneous Raman spectroscopy systems for biomedical applications.

To establish a simple multiconfiguration theory and engineering scheme to realize the accurate detection of objects under the surface of diffuse scattering medium. Enhanced polarization imaging technology, related algorithms and perfect imaging methods are adopted to ensure the correctness and optimization of the system. The simulation results show that the system can meet the application requirements of relevant criteria.

Raman micro-spectroscopy is an optical technique that can provide information on the biochemical composition of biological cells. Raman cytology, whereby Raman spectra are recorded from the nucleus of human epithelial cells is an active area of research. This typically involves the application of multivariate statistical algorithms to classify cell type, or disease group, based on the Raman spectrum. Although this approach has been shown to improve the diagnostic sensitivity of clinical cervical, bladder, and oral cytology for the identification of cancer cells, there has been no clinical adoption to date. The main reasons for this are the slow recording time and lack of reproducibility. In this paper, we review a recently proposed automated Raman cytology system based on image processing that can record several thousands of cell nuclei/day. The automation process is implemented using an open-source microscopy control system called Micro-Manager, which can readily be adapted by those with existing Raman microscopes and is designed to target the unstained nucleus, identified by imaging a plane below the sample, which is the primary target for Raman cytology based cancer diagnostics. In this paper we investigate the application of automated Raman cytology for the classification of two sub-types of Triple Negative Breast Cancer Cell Lines prepared using the ThinPrep protocol and we discuss how this approach could potentially improve the diagnostic sensitivity of Fine Needle Aspiration Cytology for Breast Cancer Diagnosis.

Biological tissue is a multiple random scattering medium. The study of the propagation of acousto-optic signals in biological tissues is an important and complex issue in acousto-optical tomography(AOT). In this paper, the finite element simulation software COMSOL Multiphysics is used to simulate the propagation of acousto-optic signal modulated by ultrasound in double-layer tissue. The effects of different types of ultrasounds on acousto-optic signals in tissues are studied. The influence of the optical properties of the target tissue and non-target tissue on the acousto-optic signal in the double-layered tissue is also discussed. The simulation results show that the waveform of the acousto-optic signal is very similar to that of the ultrasonic wave. The acousto-optic signal presents a periodic variation as the ultrasonic frequency changes. The peak-to-peak value and average value of the acousto-optic signal are affected by the optical properties of double-layer tissue. However, the modulation depth of the acousto-optic signal only depends on the optical characteristics of the tissue in the ultrasound focal zone (target tissue), and has nothing to do with the optical characteristics of the tissue outside the ultrasound zone (non-target tissue). The modulation depth has a good antiinterference performance, which is conducive to image processing and reconstruction in AOT.

For specific cerebrovascular diseases such as epilepsy and Alzheimer's disease, it is urgent to detect the chronic changes of regional cerebral blood flow (rCBF) for a long time. interferometric diffusing wave spectroscopy (iDWS) based on optical heterodyne detection is expected to improve the detection sensitivity and reduce the interference of scalp blood flow. However, iDWS technology is difficult to achieve two-dimensional blood flow imaging. Therefore, this research proposes a interferometric diffusing speckle contrast imaging (iDSCI) system for monitoring rCBF, which combines an improved diffusion speckle contrast analysis method with iDWS technology. The dynamic phantom experiment demonstrated a good linear relationship between the reconstructed relative blood flow index and the actual flow velocity, and multi-parameter analysis validated the effectiveness of the iDSCI system in monitoring rCBF velocity, improving detection accuracy from 0.82 to 0.97. Therefore, the iDSCI system has the potential to provides a new theoretical basis for the early diagnosis and treatment of cerebrovascular diseases in the future.

Diabetic retinopathy (DR) accounts for accumulated damage to retinal blood vessels which can lead to blindness if it is not detected in its early stage. Optical coherence tomography angiography (OCTA) provides noninvasive and dye-free method to assess 3D retinal and choroid circulations which has been used to evaluate DR ever since it was proposed. In this study, widefield OCTA (WF-OCTA) images were provided by the swept-source optical coherence tomography (SS-OCT) with a 12mm×12mm single scan centered on the fovea and a convolutional neural network (CNN) model was proposed to extract small lesions present in images for the early detection of DR. The proposed model achieved a classification accuracy of 95%, sensitivity of 97.12% and specificity of 87.90% in detecting DR. The accuracy of the model for DR staging is 85.74%, which is higher than that of the Vgg16 by 5.76% and the Inception-V3 by 4.49%. This work demonstrated reproducible and consistent detection results with high sensitivity and specificity.

High-throughput 3D imaging of multiple organs and organisms at cellular resolution is a recurring challenge in statistical experiments. Here we report on a computational light-sheet microscopy achieving high-throughput high-resolution mapping of multiple macro-scale organs. Through combining a dual-side confocally-scanned Bessel light-sheet illumination with a content-aware compressed sensing (CACS) computation, our approach yields 3D images with high, isotropic spatial resolution and rapid acquisition over two-order-of-magnitude faster than conventional 3D microscopy implementations. And we designed a holder suitable for multi-sample imaging to avoid wasting time during switching samples when imaging a batch of biological samples. This multi-sample holding module improves the switching time to 1s per sample, providing notably higher throughput for batch samples imaging. In addition, we can analyze the imaging results in different application requirements, such as accurately region segmentation, nuclei counting, etc., which have played an important role in the research of biomedical issues.

The tradeoff between spatial-temporal resolutions and phototoxicity prevents fast 3D super-resolution imaging from living cells, hindering the reveal of the subcellular interactions. Key challenges lie in the quests to optimal excitation and efficient super-resolution. Here, we present a double-ring modulated SPIM design toward an ultrathin uniform light sheet with low side lobes. The combination of IDDR SPIM with our isotropic divide-stages-to-process (ID) networks allows live-cell imaging at isotropic 100 nm resolution with a volume rate up to 17 Hz for thousands of time points.

Raman spectroscopy is a popular research avenue that can require expensive equipment in order to provide the optimal results. Determining the most appropriate equipment that can deliver the required results is a time consuming process. Having a reliable method of estimating the effect that a new optical element will have on the signal to noise ratio of the spectra collected by the system would be advantageous. This paper provides methodology for using software to virtually substitute a CCD in a given Raman spectrometer and evaluating the effect that the CCD would have on the signal to noise ratio of the resulting spectra. The methodology detailed herein shows that it is possible to emulate the effect of an alternative CCD to within 6% accuracy when the signal to noise ratio of the simulated data is compared to that of an experimental dataset.

Combining photodynamic therapy (PDT) and immunotherapy modalities has shown encouraging therapeutic efficacy against various metastasis cancers. Developing a functional nanoparticle for tumor-targeting and on-demand release of drug is still a major focus for advancing therapeutic approach. Herein, we assembled a β-cyclodextrin (β-CD) modified MMP-2 responsive peptide with a photosensitizer-loaded liposome to construct a tumor immune microenvironment and laser dual-triggered nano system (matrix metalloproteinase 2 (MMP-2) responsive peptide liposome, MR@Lip) for melanoma therapy. The β-CDs encapsulating SB-3CT were released due to the cleavage of the peptide substrate by MMP-2 which is highly expressed in tumor stroma. The localized released SB-3CT was kept in the stroma and inhibited the expression of MMP, down-regulating the soluble NKG2D ligands. The liposome loading photosensitizer Ce6 targeted and killed melanoma cells under laser irradiation, while induced the expression of NKG2D ligands and finally leading to an increase in sensitivity of A375 cells to NK cells. This study might provide novel insight into the development of a new nanomedicine to achieve programmed release of antitumor drugs and better integration of PDT and immune therapy for melanoma.

Marine plankton are micro and diverse, and most of them are still non-cultivable. So single-cell analysis, focused on the study of diversity and heterogeneity of their cells, has become a hot issue in marine microbiology research, which relies on sound single-cell preparation technology for upstream operations. By combining micro-optical tweezers technology with microfluidic droplet wrapping technology, we developed a fluorescence microscopic optical tweezers system for plankton sorting. Our system consists of a micro-optical tweezers module, a fluorescence module, an imaging module and a sorting module. Using this system, we conduct single-cell observation, monitoring, capture manipulation, separation and extraction of microplankton in seawater samples. The specific process is as follows: 1. Prepare samples, including grading filtration and enrichment of seawater sampled in Qingdao offshore. 2. Observe and select the target single-cell with a specific sorting chip on the microscopic optical tweezers single-cell sorting system. And perform visualized microdroplet single-cell sorting through optical tweezers capture manipulation. 3. Take out the target living single-cell after forming microdroplets. Using our experimental system, we are able to provide precise technical support for downstream experiments including single-cell culture, sequencing and monoclonality. In addition, our method has the advantages of flexible operation, intact cells and visualization as "what you see is what you get". Meanwhile, it has a 100% single-cell acquisition rate while maintaining the high viability of the sorted cell.

In order to solve the problems of low recognition accuracy for motor imagery EEG signals, this paper presents a feature extraction and classification algorithm based on decision tree and CSP-SVM. Firstly, we select the fixed frequency of signals ranging from 8 to 30 Hz. Secondly, multiple spatial filters are constructed by using the one versus the rest common spatial pattern (OVR-CSP) and extract the feature vectors. Support vector machine (SVM) is employed to classify the feature vectors so that the best spatial filter is selected. We build the first branch of decision tree with the spatial filter selected and SVM. Then, OVR-CSP and SVM are used to build the branches of the decision tree repeatedly. Finally, 2005 BCI competition IIIa data set is used to validate the effect of the proposed algorithm. The results show that the highest accuracy of the proposed algorithm can reach 94.27% which proves the effectiveness of the algorithm.

In the clinical treatment of tumors using microwave ablation (MWA), although temperature can be used as an important reference index for evaluating the curative effect of MWA, it cannot fully reflect the biological activity status of tumor tissue during MWA. Finding multi-parameter comprehensive evaluation factors to achieve real-time evaluation of therapeutic effects has become the key for precise ablation. The near-infrared spectroscopy and optical parameters (absorption coefficient (μ_α), reduced scattering coefficient (μ'_s), etc.) of biological tissues also change dynamically due to changes in cell morphology and protein tertiary structure during tissue thermal damage. Real-time measurement of the optical parameters of tumor during MWA can be achieved by using minimally invasive function near-infrared spectroscopy. MWA of tumor is essentially a process of protein denaturation and gradual coagulation. During the process of coagulation, the tissue hardness (which could be reflected by Young's modulus, E) also changes in real time. Shear wave elastography can measure Young's modulus in real-time and obtain 2D image. This paper focuses on the real-time evaluation of MWA based on reduced scattering coefficient and Young's modulus. The MWA experiment was conducted on porcine liver in vitro, the two-parameter simultaneous acquisition system was designed to obtain the μ'_s and E of the liver during MWA. After measuring the μ'_s and E of different zones after ablation, combining the parameter changes during the ablation and the analysis of the cell activity of the liver after ablation, an evaluation model was established.

Diffuse correlation spectroscopy (DCS) derives blood flow index (BFI) by measuring the temporal intensity fluctuations of multiply scattered light. Blood flow index (BFI) and especially its variations were demonstrated to be approximately proportional to absolute blood flow. In this paper, we have proposed a predictive method for calculating blood flow as well as oxygen saturation, based on a deep neural network of long short-term memory (LSTM) architecture. The simulated multiwavelength normalized intensity autocorrelation function data for various blood flows and oxygen saturations were used to train the LSTM architecture. The results validated the feasibility of the proposed method for quantification of blood flow and oxygen saturation simultaneously in DCS. The proposed approach would be an alternative method for oxygen metabolism monitoring.

The choroid is involved in the pathogenesis of several ocular conditions. However, most techniques of fundus imaging have focused on the retinal layer because the choroid is beyond the penetration depth of the detection light. In this study, a multimodal Near-infrared Photoacoustic Microscopy (NIR-PAM) and Optical Coherence Tomography (OCT) system was developed to image choroid. Polyethylene glycol (PEG) modified FI nanoparticles (FINPs) with absorption peak up to 1064 nm were used as a contrast agent to enhance NIR-PAM and OCT for in vivo imaging of choroid. After intravenous injection of PEG-FINPs into Brown Norway (BN) rats (8 weeks), the rat choroid was time-serially monitored with PAM and OCT: 1 min, 3 min, 5 min, 10 min, 15 min, 30 min, and 60 min. Signal increased by 381% in PAM and 109% in OCT at 1 min. The choroidal vessels were clearly visualized in the NIR-PAM compared with that in VIS-PAM imaging using 532 nm light source.

Myopia is a significant cause of visual impairment which may lead to many complications. Though the mechanism of myopia is not clear, the changes of the biological parameters and the optical performance of eyes were suggested as a key mechanism. In order to investigate the mechanism of myopia, in this paper, the time serial evaluation of biological parameters was performed and the optical performance of myopic model mouse eyes were evaluated by using optical coherence tomography (OCT) and ZEMAX software. The biological parameters were compared, and the optical performance of mouse eyes were evaluated in the myopic model mouse eyes, normal control mouse eyes and atropine-treated mouse eyes. The correlation analysis of the statistics indicated that the development of myopia was significantly related to the corneal curvature radius, center corneal thickness, vitreous depth and axial length (P<0.05). The analysis of biological parameters proved that the peripheral RMS wavefront aberration of eyes played more crucial roles in the development of myopia than the center parameters, and the degree of myopia would be proofed by the hyperopic wavefront aberration. The myopic model mouse eyes had larger corneal curvature radius, thicker center corneal thickness, deeper vitreous depth and longer axial length than normal mouse eyes. The experimental results of atropine-treated eyes suggested that atropine could relieve myopia and eye enlargement via a nonaccommodative mechanism. This study provides a new method for evaluations of the optical performance of eyes and the study of myopia.

Abstract Transcranial photobiomodulation (tPBM) has been shown to be a non-invasive method of brain stimulation that can affect the nervous system. The aim of this study was to determine how the flicker frequency of near-infrared light affects the brain. Methods: An 810nm near infrared array was used as the stimulator. 50 healthy subjects volunteered to participate in the study. 40 subjects were randomly divided into four groups. Each group underwent a 30-minute near infrared array radiation with four different frequencies (i.e., 0Hz，5Hz, 10Hz, and 20Hz) respectively on the forehead. The rest 10 subjects formed the control group, in which the stimulator did not work. Electroencephalogram (EEG) signals of all subjects during each test were recorded. In the simultaneous tPBM-EEG study, EEG source imaging (ESI) was applied for EEGs. The relative energy of the alpha band was analyzed to be the parameter for the default mode network (DMN). Result: The region of the most obvious difference between experimental groups and the control group at the source level was the prefrontal lobe. Higher stimulation frequency would cause a larger difference(P<0.05). Compared with the control group, the DMN network activity and connectivity of the experimental groups were enhanced, and the higher the stimulation frequency, the extent of increase was larger. Conclusions: Larger frequency of the near-infrared light would cause more distinct brain activities in the stimulated areas, and it can enhance the functional connectivity of the brain's DMN network more effectively. It indicates that near-infrared light may improve brain cognitive function and ameliorate neurodegenerative diseases.

Psoriasis is a common chronic inflammatory skin disease with high prevalence, chronicity, disfiguration, disability. Real-time detection of psoriatic pathological characteristics by optical technology is of great significance for the diagnosis and treatment of psoriasis. We used multiphoton microscopy (MPM) imaging technology based on intrinsic nonlinear optical signals to image the skin of a mouse psoriasis model induced by imiquimod (IMQ). The changes of cells and collagen in psoriasis skin tissue were obtained and analyzed, comparing with the hematoxylin and eosin (H and E) stained image. We found that the MPM technique could clearly observe the differences between normal and psoriasis skin. This is of great significance to the pathogenesis of psoriasis and also provides adjuvant imaging method for the treatment of psoriasis.

Photoacoustic imaging (PAI) is a biomedical imaging modality that can provide structural, functional, and molecular information. In PAI, laser pulses illuminate the tissue, and transient light absorption leads to instant thermal expansion and succeeding ultrasound emission. Since oxy- and deoxyhemoglobin are the major light-absorbing chromophores in biological tissue, PAI has very high contrast and is intrinsically suitable for the imaging of blood vessels. Meanwhile, superb microvascular imaging (SMI) is an emerging ultrasound imaging technique for angiography. In comparison to traditional color Doppler and power Doppler techniques which rely on the suppression of low-velocity components, SMI works by an intelligent algorithm that renders small vessels with low flow velocity visible. To date, there is no work to compare PAI and SMI in terms of vascular imaging capabilities. In this paper, we provide our recent evaluation results in imaging depths, speeds, sensitivities, and resolutions of these two modalities through phantom experiments and in-vivo studies. We used PAI and SMI to image the human forearm, and our preliminary data show that PAI is superior in imaging speeds, and sensitivities for superficial blood vessels. We acknowledge that more work needs to be done to compare the two techniques in diverse clinical applications more quantitatively, and we hope our work can pave the way for such systematic studies..

Laser induced breakdown spectroscopy (LIBS) is a rapid and simple detection method with almost no sample preparation. In this paper, LIBS was used to detect the electrolyte elements Na and K in human blood. The liquid drop method and evaporation method were used to improve the LIBS detection capability. The polynomial fitting method and wavelet transform method were proposed to optimize the LIBS spectrum. The results showed that, the signal to background ratio (SBR) of Na Ⅰ 588.99nm spectral line increased by 20.57 times after use the methods, and the SBR of K Ⅰ 766.49nm increased 24.65 times. The intensity of Na Ⅰ 588.99nm spectral line obtained by liquid drop method is 1.05 times higher than evaporation method, and 194.08 times higher than direct detection the human blood through test tube. The intensity of K Ⅰ 766.49nm spectral line obtained by liquid drop method is 2.41 times high than evaporation method. According to the results, LIBS is suitable for the detection of electrolyte elements Na and K in human blood. The polynomial fitting method and wavelet transform method can greatly increase the SBR of Na Ⅰ 588.99nm and K Ⅰ 766.49nm in human blood. The liquid drop method can greatly improve the LIBS detection capability of electrolyte elements Na and K in human blood. Compared with the existing blood electrolyte elements detection methods, liquid drop method is more efficient and easier to operate.

Finding an effective monitoring and evaluation factor for therapeutic effect of microwave ablation is becoming a research focus. Previous MWA experiments on in vitro porcine liver found that reduced scattering coefficient ( μ'_s ) is an efficient optical evaluation parameter. Results indicated that μ'_s of normal tissue and coagulation tissue is 3-5 cm^-1 and 17-19 cm^-1, respectively, and μ'_s is highly related to the degree of thermal damage. This paper aims to validate if these results from in vitro porcine liver also applies to real tumor. Two sets of experiments were carried out with human liver tumor specimens. In the first experimental set, the tumor specimen was heated by water bath at constant temperature of 80 ℃ for 5 minutes, and μ'_s was obtained before and after the heating process. In the second set, another tumor specimen was heated by MWA with microwave power of 10 W for 5 min, reduced scattering coefficient and temperature changes were measured during ablation. In the first experiment, μ'_s value was 4.10 cm^-1 before heating and increased to 17.16 cm^{- 1} after complete tissue protein coagulation. In the second experiment, μ'_s grew exponentially first and eventually stabilized. μ'_s values are consistent with previous experiments on in vitro porcine liver. These results also validates that the μ'_s values reflect the degree of thermal damage, and be captured in real-time. To sum up, μ'_s is an effective real-time thermal damage monitoring and evaluation factor that can be applied to real tumors.

Necrosis is a form of cell death which is histologically characterized by homogeneous clusters and sheets of dead cells. Although several studies have indicated that the presence of tumor necrosis in pathological specimens may provide adverse prognostic information in solid tumor, the mechanism of necrosis is still unclear. Based on two-photon excited fluorescence (TPEF) and second-harmonic generation (SHG), multiphoton microscopy (MPM) is commonly used to monitor the morphological changes of biological tissues. In this study, we performed MPM imaging of the breast tissue and found that MPM can be used to rapidly classify the early and late-stage tumor necrosis in invasive breast cancer according to the changes of intracellular proteins. It demonstrated that MPM may provide a new assistant tool for pathologists to quickly and effectively classify the early and late-stage tumor necrosis.

Unmixing multispectral photoacoustic (PA) images is difficult because the excitation spectra in deep tissue are contaminated by absorption and scattering of the surrounding tissue in a highly unpredictable manner. In this work, we found a close relationship between the covariance matrix of a multispectral photoacoustic image and its average tissue oxygenation level. Based on the photon diffusion process, a spectral-domain model of multispectral photoacoustic imaging is established. Combined with the above two findings, accurate estimation of blood oxygen saturation (median error 2.7%) and accurate probe identification (detection rate 86%, false alarm rate 0.035%) were realized in realistic simulation test.

The tumor microenvironment is now recognized as an important participant of tumor progression. As the most abundant extracellular matrix component in tumor microenvironment, collagen plays an important role in tumor development. The imaging study of collagen morphological characteristics in tumor microenvironment is of great significance for understanding the state of tumor. Multiphoton microscopy (MPM) based on second harmonic generation (SHG) and two-photon excitation fluorescence (TPEF) can be used to monitor the morphological changes of biological tissues without labeling. In this study, MPM was used to perform label-free imaging of the tumor border, the transition zone near the tumor, and the normal tissue away from the tumor sequentially from the center of the tumor in early invasive breast cancer samples. We found that collagen morphology varies significantly in different regions of breast cancer tumor tissue. The collagen content was further quantified and the results showed that the collagen content was significantly different in these three regions. The study of collagen remodeling around tumors may provide a new basis for optimal negative margin width of breast-conserving surgery and a new perspective for understanding tumor metastasis.

Photoacoustic Blood Pressure Recognition Based on Deep LearningXiaoman Zhang, Huaqin Wu, Biying Yu, Sulian Wu, Weijie Wu,Jianyong Cai*and Hui Li* Key Laboratory of OptoElectronicScience and Technology for Medicine of Ministry of Education,Fujian Provincial Key Laboratory of Photonics Technology,College of Photonic and Electronic Engineering, Fujian Normal University Ministry of Education, Fuzhou 350007, P.R. ChinaABSTRACTContinuous and non-invasive real-time measurement of human blood pressure is of great importance for health care and clinical diagnosis.Photoacoustic imaging allows absorption-based high-resolution spectroscopyin vivo imaging with a depth beyond that of optical microscopy. In this study,a novel photoacoustic imaging systemis usedfor monitoring and imaging of vesselpulsation,whichcan realize simple, non-invasive and continuous measurement and recognition of blood pressure. Combined with deep learning method, a model is established to effectively evaluate the dependence of blood vessel elasticity on theblood pressure.These results can quickly and accurately identify the photoacoustic signals of blood vessels under different pressures.

Port-wine stains (PWS) are one of the most common congenital vascular malformations. PWS lesions result in pink or purplish red patches on skin, which mostly occur on the face or neck, thus greatly reduce the life quality of PWS patients. The key point of treating PWS is selectively block the dilated vessels located in the dermis. Hence, mastering the information of PWS morphological parameters would contribute to PWS treatment. Optical coherence tomography (OCT) is a non-invasive, label-free, rapid, high resolution optic imaging method, which can image skin structure and has been greatly developed in recent 20 years. This review will address what is presently known about OCT on PWS detection at home and abroad.

In this work, a simple and effective sensor using single-mode fiber (SMF) tapered structure is developed to detect different concentrations of acetylcholine solutions, and its function is to test the probe's performance. A layer of synthesized gold nanoparticles (AuNPs) and zinc oxide nanoparticles (ZnO-NPs) is used to immobilize this type of SMF-based tapered structure. The work is based on the well-known phenomenon of localized surface plasmon resonance (LSPR) principle. A tapered region of the probe with a high fraction power of evanescent wave can stimulate LSPR and produce specific absorption peaks sensitive to the refractive index variation. The sensor probes performance was examined, including their stability, repeatability, reusability, and selectivity. Furthermore, the biosensor's ability to improve performance was tested in the experiment.

Optical biosensors based in the fluorescence resonance energy transfer (FRET) phenomenon require of fluorophores. The use of fluorophores requires of a complex optical system that often leads to signal loss. Thus, a new approach based in a Black Hole Quencher (BHQ) that further simplifies the biosensor is sought. This approach potentially increases the sensitivity and accuracy. For the development of this approach, the gliadin conjugate with BHQ-10 must be established first. In the present work, we used the physical phenomenon of FRET to study the gliadin conjugation with BHQ-10 molecule. We performed an experiment with a fluorophore (6-Carboxyfluorescein or 6-FAM) labeled aptamer and non-covalently attached to graphene oxide (GO). The gliadin from gluten was conjugated with BHQ using two different cross-linking reagents present in BHQ: BHQ-10 succinimidyl ester and BHQ-10 carboxylic acid. BHQ-10 with carboxylic acid as the cross-linking reagent demonstrated to be an efficient reaction for gliadin conjugation with BHQ-10. The average quenching efficiency obtained was 62% in comparison to the gliadin as a control experiment. This sets the basis for the breakthrough development of a simplified gluten detection biosensor based on absorbance measurements instead of different wavelength ranges as fluorophores do. The aim is to develop a point-of-care microfluidic system that measures gliadin from gluten in a sensitive, accurate and cost-efficient manner.

The influence of solution polarity and viscosity on fluorescence decay parameters in free and protein-bound NADH was studied. The fluorescence in NADH dissolved in water, methanol, ethanol, propylene glycol, and alcohol dehydrogenase-containing solution was two-photon excited by femtosecond laser pulses at 720 nm and recorded by means of the time-correlated single photon counting (TCSPC) method. Fluorescence decay times and corresponding weighting coefficients were determined by fit from polarization-insensitive fluorescence decay experimental signals. The fluorescence decay times τ₁ and τ₂, and weighting coefficients a₁ and a₂ were found to depend significantly on the solution type. A model describing the dependence of the fluorescence decay parameters on the microenvironment in solutions with different polarity and viscosity has been developed. According to the model, the heterogeneity in the measured fluorescence decay times in NADH and the time values were closely related with the charge distributions in the cis and trans configurations of the nicotinamide ring that result in different electrostatic field and different non-radiative decay rates. The influence of solution polarity and viscosity on the measured fluorescence decay times was investigated. As shown in high viscous solutions the increase of fluorescence decay times in NADH was mostly due to slowing down of the nuclei motions during the vibrational relaxation and intramolecular nuclear rearrangement whereas in low viscous solutions the fluorescence decay times follow the change of solution polarity.

The paper presents the study of anisotropic fluorescence decay of FAD in water-methanol solutions of different concentrations in the range of 0-80%. The fluorescence decay parameters: decay times, corresponding weighting coefficients, fluorescence anisotropy, and rotation diffusion time have been determined from experiment using the TCSPC method as function of methanol concentration and analyzed. The fluorescence kinetics demonstrated doubleexponential decay with two fluorescence decay times of about 2 and 4 ns. The decay times τ₁ and τ₂ were found to be the same under excitation at 450 nm and at 355 nm within experimental error bars and were practically independent of methanol concentration. The fluorescence anisotropy under 450 nm and 355 nm excitation was determined to be about 0.35 and 0.23, respectively indicating that the directions of the excitation transition dipole moments via the first and the second absorption bands differed significantly from each other. Also, the anisotropy was found to be practically independent of methanol concentration. The rotational diffusion time was proportional to the solution viscosity at lower methanol concentrations up to 40%, and reached a plateau at higher concentrations while the solution viscosity dropped down. This behavior was explained due to the increase of FAD solvation in the MeOH-water solution under the condition of FAD unfolding due to the denaturation effect.

This paper describes a detailed study of spectral and time-resolved photoprocesses in human platelets and their complexes with platinum (Pt) nanoparticles (NPs). Fluorescence, quantum yield, and platelet amino acid lifetime changes in the presence and without femtosecond ablated platinum NPs have been studied. Fluorescence spectroscopy analysis of main fluorescent amino acids and their residues (tyrosine (Tyr), tryptophan (Trp), and phenylalanine (Phe)) belonging to the platelet membrane have been performed. The possibility of energy transfer between Pt NPs and the platelet membrane has been revealed. Förster Resonance Energy Transfer (FRET) model was used to perform the quantitative evaluation of energy transfer parameters. The prospects of Pt NPs usage deals with quenching-based sensing for pathology’s based on platelet conformations as cardiovascular diseases have been demonstrated.

The Mycobacterium tuberculosis (MbT) drug resistance remains a serious problem for global public health and usually leads to a lethal outcome. Precise and rapid identification of a specific MbT strain is vital for the appointment of antituberculosis therapy. We continue investigation of deactivated MbT strains of the Beijing family by Raman spectroscopy method and focus on Raman spectra analysis for the identification of potential biomarkers for different MbT strains. . We have studied extrapulmonary Beijing strain with XDR resistance. Samples were investigated by Raman spectrometry with He-Ne (λ=633 nm) laser excitation source in the «fingerprint» region. As a result, new spectral features were determined. They describe spectral discrimination between drug-sensitive and drug-resistant strains identified for extra-pulmonary forms of tuberculosis. We suppose that the obtained results can be useful for new diagnostic tools development for the identification of different MbT strains in clinical and research practice.