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Zhang Y.,CAS Hefei Institutes of Physical Science | Liu Y.,CAS Hefei Institutes of Physical Science | Liu Y.,Wanjiang Center for Development of Emerging Industrial Technology | Hou H.,CAS Hefei Institutes of Physical Science | And 5 more authors.
Zhongguo Jiguang/Chinese Journal of Lasers | Year: 2016

In order to reduce the influence of absorption and scattering on tissue fluorescence spectra, the tissue fluorescence and diffuse reflection are simulated under different optical parameters with the Monte Carlo (MC) method, and a fluorescence recovery algorithm based on the tissue diffuse reflection spectrum is proposed. The empirical parameters in the proposed algorithm are coded as a particle in the solution domain, the classification performance is defined as fitness, and then a particle swarm optimization (PSO) algorithm is established to optimize empirical parameters. Skin fluorescence and diffuse reflection spectra of 327 subjects are collected with a tissue detection system for noninvasive screening of diabetes. The fluorescence spectra are recovered by the empirical approach, and the fluorescence intensity before and after recovery is selected as the input variable for the receiver operating characteristic (ROC) curve analysis, which is applied to evaluating the classification performance in diabetes screening. The sensitivity and specificity are 32% and 76% respectively, and the area under the ROC curve is 0.54 when the spectra before recovery are used, while the sensitivity and specificity are 72% and 86% respectively, and the area under the ROC curve is 0.86 when the spectra after recovery are used. The results indicate that using the tissue fluorescence spectrum recovery algorithm based on PSO can improve the application of tissue fluorescence spectroscopy effectively. © 2016, Chinese Lasers Press. All right reserved. Source


Li F.,CAS Anhui Institute of Optics and Fine Mechanics | Zhang Y.,CAS Anhui Institute of Optics and Fine Mechanics | Wang Y.,CAS Anhui Institute of Optics and Fine Mechanics | Wang Y.,Wanjiang Center for Development of Emerging Industrial Technology | And 5 more authors.
Guangxue Xuebao/Acta Optica Sinica | Year: 2013

Determination of optical parameters of turbid media is quite useful in the photodynamic therapy and optical noninvasive diagnostics. A kind of real coded genetic algorithm incorporated with inverse Monte Carlo method and graphics processing unit based acceleration technology is proposed, which can determine optical parameters from the spatially resolved diffuse reflectance of turbid media by Monte Carlo simulation. Fitness function of accumulated square differences, random tournament selection operator, uniform random crossover operator with extended radius, uniform mutation operator, champion mutation operator are designed to guaranty the algorithm to converge with good population diversity. In the range 0≤μa≤100 cm-1 and 0≤μs≤1000 cm-1, the average relative errors are 0.25% and 0.58%, and the root mean-square errors (RMSEs) are 0.32 cm-1 and 1.68 cm-1 for the absorption coefficient and for the scattering coefficient, respectively, which means that this algorithm is feasible and accurate enough for determination of optical parameters of turbid media. Source


Li F.,CAS Anhui Institute of Optics and Fine Mechanics | Wang Y.-K.,CAS Anhui Institute of Optics and Fine Mechanics | Wang Y.-K.,Wanjiang Center for Development of Emerging Industrial Technology | Zhu L.,CAS Anhui Institute of Optics and Fine Mechanics | And 7 more authors.
Guang Pu Xue Yu Guang Pu Fen Xi/Spectroscopy and Spectral Analysis | Year: 2014

Advanced glycation end products (AGEs) are highly associated with hyperglycemia in human skin tissue, and they also have the autofluorescence characteristic. A self-developed optical noninvasive detection device was used to measure the autofluorescence in human skin tissue, and then a neural network pattern recognition model was used to assess the risk of diabetes mellitus of the subject under survey. After the fluorescence spectra were acquired and processed with principal component analysis, four of the leading principal components were chosen to represent a whole spectrum. The established neural network pattern recognition model has 4 input nodes, 6 hidden nodes and 1 output node. A dataset consisting of 487 cases collected in Anhui Provincial Hospital was used to train the model. Seventy percent cases were used as the training set, 15% as the validation set and 15% as the test set. The model can output subject's risk of diabetes mellitus, or a dichotomous judgment. Receiver operating characteristic curve can be drawn with the area under curve of 0.81, with standard error of 0.02.When using 0.5 as the threshold between diabetes mellitus and non-diabetes mellitus, the sensitivity and specificity of this model is 72.4% and 77.6% respectively, and the overall accuracy is 74.9%. The method using human skin autofluorescence spectrum combined with neural network pattern recognition model is proposed for the first time, and the results show that this method has a better screening effect compared with currently used fasting plasma glucose and HbA1c. Source


Zhao S.-M.,CAS Anhui Institute of Optics and Fine Mechanics | Zhu L.,CAS Anhui Institute of Optics and Fine Mechanics | Zhu L.,Wanjiang Center for Development of Emerging Industrial Technology | Zhu C.-C.,CAS Anhui Institute of Optics and Fine Mechanics | And 10 more authors.
Fenxi Huaxue/ Chinese Journal of Analytical Chemistry | Year: 2014

A real-time polymerase chain reaction (PCR) micro total analysis system (μ-TAS) was constructed by integrating nucleic acid extraction and PCR amplification with real-time fluorescent detection on a same microfluidic chip, allowing fully automated and on-chip analysis. This approach has the advantages such as low sample consumption, fast analysis and simple operation. Micromachining technology was used to fabricate the anodic molds of integrated nucleic acid extraction microfluidic chip. A polydimethylsiloxane (PDMS) substrate with 3D channels was manufactured by a combination of molds and an injection molding method. The glass substrate and the chip were bonded together using a plasma treatment. The μ-TAS included a microfluidic control device by which micro fluidic velocity (0-10 mL min-1) could be adjusted, a TEC platform with a precision of temperature control of 0.1 °C, and a CCD detection module. The DNA of human blood was extracted using a silica gel membrane method on the microfluidic chip. The DNA extraction and detection were preset in the μ-TAS. Human blood lysate (20 μL) was loaded into the extraction chamber and then washed at a speed of 2 mL min-1. DNA and PCR reagents were mixed and then driven into the PCR chamber at a speed of 1 mL min-1. The reference gene GAPDH in extracted genome DNA was amplified by PCR and verified by melting curve analysis. The results of nucleic acid extraction method on the chip were compared with those obtained using a standard manual centrifuge extraction method. The on-chip PCR amplifications gave obvious amplification curves, with CT values of 25.3 and 26.9 respectively. The melting temperature of all the amplification products was 89.9 °C. The results validated that the chip-based method and corresponding device could realize the extraction, amplification and detection of nucleic acid automatically. Copyright © 2014, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences. Source

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