This PDF file contains the front matter associated with SPIE Proceedings Volume 12067, including the Title Page, Copyright information, and Table of Contents

The blood is an important tissue in the human and animal body. It has significant role in the fields of bio-medical diagnosis, animal quarantine, criminal investigation, food safety, etc. However, there are some illegal cases reported about the real blood abused by fake blood recently, which seriously impact the human health and society stability. The rapid and accuracy detection of blood is very important and urgent. To achieve this aim, the photoacoustic spectroscopy was used to detect the real blood and fake one. A set of photoacoustic detection system was established based on OPO pulsed laser and focused ultrasonic detector. In experiments, 150 groups of real and fake blood samples was test, where 120 groups were used as the training samples, 30 groups were used as the test samples. The time-resolved photoacoustic signal and peak-to-peak values of all samples were captured in the wavelengths from 700-1064nm. To classify and distinguish the real and fake blood, the support vector machine (SVM) algorithm was used to train the training blood samples and test the correct rate of classification and distinction of the real and fake blood. The results show that the correct rate is 83.3% by using the SVM algorithm. To further improve the correct rate, the principal components analysis (PCA) algorithm was used to extract the characteristic information from the photoacoustic peak-to-peak values of blood samples in full wavelengths. The correct rates of real and fake blood based on PCA-SVM algorithm under the different principal components were obtained and compared. The results show that the correct rate can be improved to 90% for the PCA-SVM algorithm with 21 principal components.

Microarray chip is a highly sensitive and high-throughput genetic detection technology based on the principle of complementary pairing of nucleic acid sequence bases and using polymerase chain reaction (PCR), and its chip structure and material have a great impact on the detection. Therefore, a new type of PCR chip is designed. The large multi-physical field simulation software Comsol is used to simulate the coupling of thermodynamics and structural mechanics of the designed chip. Finite element simulation is used to experimentally optimize the chip material selection in practice, find the composite material (cyclic olefin copolymer (COC)) that has the least effect on signal processing and does not require polar treatment of the chip substrate, and design the optimal chip structure. Three kinds of standard chips (internal reference, negative and positive) were prepared by using FAM fluorescent probe. Positive luminescent spots were randomly labeled for detection. This detection is used to evaluate the value of practical application of this chip. The results show that the maximum deformation displacement of the chip is 0.6 mm at 4–100℃, which is instantaneously irradiated by a 1 KW radiation light source, and the transmittance of the model calculated by the penetrated radiation power is 83.7%. In practical application, several materials are irradiated with excitation light to detect their excitation effect, and COC has the smallest excitation effect and the lowest background signal value. A chip containing 203 microarray spots was prepared according to the above conclusions, and the detection results were 100% consistent.

Incubation temperature plays an important influential role in the detection process of specific proteins. In this paper, a specific protein detection device was designed and built by taking Lambert-Beer’s law as the basic detection principle. By using the photoelectric effect of the photoelectric sensor, the relative absorbance of the transmissibility sample was detected by the turbidimetric method, and then the substance content in the detected sample was quantitatively analyzed. Meanwhile, the increment PID algorithm was used to control the temperature in the incubation area, and then the finite element analysis method and COMSOL finite element simulation software were employed to analyze the temperature distribution and temperature variation trend in the incubation area of the reaction device. Besides, the microalbumin kit of Beijing Dandan Biotechnology was used to detect the influence of incubation temperature on the calibration curve of microalbumin (mALB) and its changing trend under different temperatures. The experimental results indicated that the increasing PID control algorithm could control the average temperature rise rate of the incubation area at 0.52 ℃/s and the temperature stability at ±0.1 ℃. When the incubation temperature was between 34℃ and 40℃, the change of temperature had no significant effect on the slope of the calibration curve. Within this temperature range, the linearity of the calibration curve gradually increased with the increase of the temperature. This study provided a basic experimental study on the effect of incubation temperature on the detection results of specific proteins.

Alzheimer’s disease (AD) is a common neurodegenerative disease characterized by cognitive and memory function impairment. Studies have shown that the amyloid-beta (Aβ) plays an important role in the disease progression. The monomeric Aβ has been associated with biological functions, such as memory, learning, and neuroprotection, while the soluble Aβoligomers are the primary toxic agents and the resultant amyloid fibrils are relatively benign. Thus, the conformation detection of Aβ is quite necessary for AD research. IR spectroscopy is an excellent technique used for protein conformational analysis, for the C=O stretching vibration of the peptide is sensitive to the range of 1600-1700cm^{- 1}. In this research, we proposed a method that detects the conformation of soluble Aβ by using Fourier transform infrared (FTIR) spectroscopy with a transmission approach. Although the attenuated total reflectance (ATR) accessory made from zinc selenide or germanium is the most popular approach for recording liquid spectra of the peptides, the volume requires almost 5 mL of soluble Aβ to cover the crystal to achieve a higher signal. Herein we designed a 25×4 mm calcium fluoride (CaF₂) substrate with the center has a groove with 5μm deep and 10 mm diameter, it just needed 2uL of soluble amyloid β-peptide to fill the groove and also achieved a high transmission signal. Moreover, based on this method, we found that the process of oligomer-to-fibrils transition occurred much faster within the first 24 hours, and the secondary structure changed slowly in the following time of 48-96 h. These results demonstrated that FTIR is an exquisite way to characterize the aggregation process of peptides, it not only economizes the reagents but also enables give an almost continuous structural view of such process.

Laser self-mixing interferometry (SMI) is often used for displacement, vibration, and velocity measurement. At present, the measurement accuracy has reached tens of nanometers, but it has not been used for single cell detection. In this research, a microfluidic chip-based equipment using SMI technology for label-free single cell detection was demonstrated. The detection experiments were performed to verify chicken erythrocytes and human breast cancer cells T47D. In order to better analyze these data, the Hilbert transform was used to convert the time domain signal into phase information. It is found that there are more fringes in the signal of larger breast cancer cells. The power spectrum of the signal shows that the velocity of the cell is positively correlated with the Doppler shift. The new method for single cell detection proposed in this paper provides a new idea for real-time cell detection.

High resolution and high precision polymer nanostructures has unique chemical and physical properties, playing an important role in nano-optics, nano-photonics, and high sensitivity biological detection. This paper demonstrated a novel fabrication method of biological detection chip based on polymer nanostructures via nanoimprint lithography. High precision nanostructures such as nanopillar arrays were prepared on chip film via nanoimprint lithography. The polymer nanostructures were used to enhance adhesion to cancer cells, which is low-cost and suitable for mass production. The replication polymer was biocompatibility materials that has no effect on cells. The experiment results show that the nanopillar arrays chip can adhere lung cancer cells in the size of 10-15 μm to achieve the purpose of filtering and detecting cells. Results of the experiments show that this new biological detection chip has potential applications of cancer detection, targeted therapy, food safety testing, and environmental monitoring.

Cervical cancer is one of the major gynecological malignancies that seriously endanger women's health. Patients with early symptoms are not obvious and prone to metastasis and recurrence, leading to poor prognosis of patients with cervical cancer. At present, cytological screening and HPV detection are the main diagnostic methods of cervical cancer in China, but both of them are greatly influenced by doctors' subjective factors, with low specificity and high rate of missed diagnosis. Therefore, a rapid and effective diagnostic method is needed to be explored. In this paper, the serum samples of patients with cervical cancer were taken as the research object, and the experimental serum samples were analyzed by infrared spectroscopy, which provided a clinical basis for the identification and classification of patients with cervical cancer by infrared spectroscopy. In this study, infrared spectral signals of serum of patients with cervical cancer were collected, and spectral signals were analyzed and preprocessed. Partial least squares regression (PLS) was used to select spectral signal features. Then, an Xgboost ensemble learning model is established using GBtree, GBlinear and Dart as the base classifier, and the performance of the model is evaluated by using the ten-dot cross-validation. Finally, the established models are compared.

Hepatic steatosis, the accumulation of lipids within hepatocytes, is defined as intrahepatic fat of at least 5% of liver weight and is an important histological feature. Steatosis may manifest in a variety of liver diseases, and its clinical significance depends on the degree of hepatic steatosis. Excess intrahepatic fat content is a risk factor for disease progression. Increased hepatic steatosis could trigger metabolic dysfunction leading to insulin resistance, dyslipidemia, cardiovascular disease, and progression to non-alcoholic steatohepatitis (NASH), cirrhosis, and hepatocellular carcinoma (HCC). In many chronic liver diseases, hepatic steatosis is associated with increased hepatic fibrosis. Clinical methods of quantifying hepatic steatosis remain semi-quantitative, with potential limitations in precision. Moreover, the evaluation of hepatic steatosis and fibrosis cannot be performed simultaneously. In this work, multiphoton microscopy (MPM) combined two-photon excited fluorescence with second harmonic generation imaging was used to identify the hepatic steatosis and fibrosis in chronic liver disease. The result showed that MPM has the potential to be a pathological diagnostic tool for hepatic steatosis and fibrosis.

Cervical cancer is one of the most common female malignant tumors in the world. In recent years, the incidence of cervical cancer has tended to be younger, which has attracted great attention from all countries in the world. Early and accurate diagnosis of cervical cancer is of great significance to patients. At present, the common diagnostic methods of cervical cancer in China include cytological screening and HPV detection, but these methods are generally greatly affected by doctors' subjective factors and cannot fully meet the domestic clinical needs, so a rapid and accurate diagnosis of cervical cancer is of great value for exploration and research. In this paper, serum infrared spectroscopy technology combined with machine learning was used to diagnose and classify cervical cancer patients. Firstly, the spectral data were preprocessed by smoothing and normalization, and principal component analysis (PCA) was used to reduce dimension. The obtained data were imported into Support Vector Machines with Particle Swarm Optimization (PSO-SVM), Random Forest (RF) and K-Nearest Neighbor (KNN) models for classification, and ten-fold cross-validation was used to verify the performance of the model. Finally, the established models are compared.

Recently, near-infrared (NIR) excitation has been suggested for PDT improvement and therapy of cancer.In this study, 5-aminolevulinic acid (ALA), a kind of photosensitizer, were coordinated to CuInS₂/ZnS QDs to form the CuInS₂/ZnS-ALA conjugates. An efficient transfer of energy from the donor (QDs) to the acceptor (ALA) was demonstrated through forster resonance energy transfer (FRET). The treatment effects of the conjugates in vivo was confirmed under 1300nm femtosecond laser. The results demonstrate that the CuInS2/ZnS-ALA conjugates are promising for PDT and can be used in imaging and biomedical field.

Tumor microenvironment (TME) is composed of tumor cells, stromal cells and the extracellular matrix (ECM), that it plays an important role in the occurrence and development of tumors, such as promoting local drug resistance, immune escape, and distal metastasis. Based on second harmonic generation (SHG) and two-photon excited fluorescence (TPEF), multiphoton microscopy (MPM) has the ability to label-freely visualize extracellular matrix and cells in the TME. In addition, combined SHG and TPEF imaging can be used to generate similar pathological images, providing additional information for pathologists and even surgeons. Cancer cells, adipocytes, microvessel, collagen fibers, and tumor-infiltrating lymphocytes (TILs) which were the important components in the TME were imaged using MPM in this study. The results showed that MPM can clearly present the tissue structure and cell morphology in the microenvironment. With the development and widely used of MPM, in the future, MPM imaging may be able to perform clinical imaging of the tumor microenvironment without the need for invasive operations. MPM may become a novel imaging tool for imaging various prognostic factors in breast cancer.

Accurate measurement of ocular axis length (AL) is important for myopia control and vision recovery after cataract lens implantation. A low-coherence dual-beam external differential interference ocular AL measurement system (i.e. the new AL system) was built based on a modified Twyman-Green interferometer with a 790 nm infrared laser as the light source. Combined with digital signal processing techniques, the weak light interferometric signals acquired by DAQ card are processed synchronously. The FIR digital filter and signal envelope extraction method are designed to improve the signal-to-noise ratio, so as to obtain a high signal-to-noise ratio AL interference signal. To verify the effectiveness of the system, the correlation and consistency of AL between the new AL system and IOLMaster are analyzed. The results showed that the new AL system can provide valid AL measurements, indicating that the new AL system developed by our team can be used for routine clinical AL measurements.

The technical requirements and development trends of optical filters applied in bioscience area were introduced in this paper. The related optical filters were mainly used in biomedical equipment which were based on biomedical optical testing methods, such as absorption photometric analysis, fluorescence analysis, and Raman analysis etc. To manufacture the optical filters, Plasma Assisted Reactive Magnetron Sputtering (PARMS) technology was used, super-multilayer precision thickness control methods and super-multilayer micro defect control technology were developed. The high performance optical thin film filters, with high transmission (T_pk>95%), steep edge (OD6 cut-off steepness less than 1%) and deep blocking with neighborhood cut-off depth blocking better than OD7 were manufactured.

Sleep disorder is a common clinical disease that easily induces and aggravates cognitive disorders, especially the decline in learning and memory ability. In recent years, phototherapy has been widely studied as a non-invasive, safe, and less side-effect physical therapy method. Phototherapy may become an effective treatment for sleep disorders. In this study, we investigated the effects of phototherapy on learning and memory in sleep deprivation model mice, and to investigate the effects of phototherapy on inflammatory response, oxidative stress and the brain-derived neurotrophic factor (BDNF)/tropomyosin receptor kinase B(TrkB)signaling pathway in sleep-deprived mice. The mice were randomly divided into 3 groups: control group, sleep deprivation group and phototherapy group (468 nm, 100 lux, 300 lux and 900 lux). The results showed that sleep deprivation led to an increase in swim latency and a lower number of platform crossings, promoted the expression of tumor necrosis factor-alpha(TNF-α), decreased the expression of superoxide dismutase(SOD) activity, and decreased the mRNA expression of BDNF, TrkB, and Akt. After phototherapy, the phototherapy group had a shorter swimming latency, higher number of plateau crossings, decreased the expression of TNF-α, increased expression of SOD. The mRNA expression of BDNF, TrkB, and Akt increased, and the effect of 300 lux light dose was more significant. Therefore, phototherapy can repair the oxidative stress damage caused by sleep deprivation, regulate the inflammatory response, promote the expression of BDNF to compensate for the relatively short period of sleep deprivation, protect their cognitive ability, and alleviate the learning and memory deficits caused by sleep deprivation.

Traditionally, diffuse correlation spectroscopy (DCS) derives blood flow (BF) by measuring of the temporal intensity fluctuations of multiply scattered light from a single source-detector pair. In this paper, a multi-wavelength DCS approach was proposed to quantify tissue blood flow and scattering coefficient based on long short-term memory (LSTM) architecture. Phantom experiments were established to measure normalized intensity autocorrelation function data by multi-wavelength DCS system at different velocities and scattering coefficients. The results support the notion of using proposed LSTM architecture for quantification of blood flow and scattering coefficient in DCS.

Cervical carcinoma is one of the most common gynecological malignancies in the world. Here we have measured the 2D light scattering patterns of two representative types of cervical cancer cell lineage cells (HeLa, H8) at six different defocusing distances. The light scattering patterns vary at different defocusing distances, where the longer the defocusing distance, the larger the pattern area is. The classification performance for cervical cancer cells at different defocusing distances is evaluated based on support vector machine (SVM) classification algorithm. Speckle features are extracted by histogram of oriented gradient (HOG). Under six defocusing distances, the difference between the highest and lowest accuracy is 5.09%. The study of defocusing effects on cell classification with 2D light scattering static cytometry may help for the development of high speed and high performance imaging flow cytometry, and the combination of flow cytometry and machine learning holds great promise for automating the early clinical diagnosis of cervical cancer and other diseases.

Optical Coherence Tomography (OCT) is a medical diagnostic method using low coherence optical interferometry imaging. It has the advantages of non-invasive, and high resolution, and can realize three-dimensional imaging of the internal structure of biological tissues. Traditional medical imaging techniques have some defects, such as low imaging depth of confocal microscope and low resolution of ultrasonic imaging. OCT makes up for these defects and has been widely used in various fields of medicine, which has greatly improved the accuracy of clinical diagnosis. Compared with the temporal OCT technology, the spectral OCT technology has a faster imaging speed and has basically replaced the temporal OCT technology. This paper briefly describes the imaging principle of OCT technology, and analyzes the optical properties of biological tissues, and determines the design index of OCT system. A high-resolution spectral domain optical coherence tomography system was designed according to the indicators. A high-resolution spectral domain optical coherence tomography system was designed according to the indicators. The central wavelength of the light source used was 840nm, the bandwidth was 180nm, the theoretical axial resolution was 1.73μm, the theoretical spectral resolution was 0.09nm, and the imaging depth was 1.96mm in the air.