Exploration research on the fusion of multimodal spectrum technology to improve performance of rapid diagnosis scheme for thyroid dysfunction

The spectral fusion by Raman spectroscopy and Fourier infrared spectroscopy combined with pattern recognition algorithms is utilized to diagnose thyroid dysfunction serum, and finds the spectral segment with the highest sensitivity to further advance diagnosis speed. Compared with the single infrared spectroscopy or Raman spectroscopy, the proposal can improve the detection accuracy, and can obtain more spectral features, indicating greater differences between thyroid dysfunction and normal serum samples. For discriminating different samples, principal component analysis (PCA) was first used for feature extraction to reduce the dimension of high‐dimension spectral data and spectral fusion. Then, support vector machine (SVM), back propagation neural network, extreme learning machine and learning vector quantization algorithms were employed to establish the discriminant diagnostic models. The accuracy of spectral fusion of the best analytical model PCA‐SVM, single Raman spectral accuracy and single infrared spectral accuracy is 83.48%, 78.26% and 80%, respectively. The accuracy of spectral fusion is higher than the accuracy of single spectrum in five classifiers. And the diagnostic accuracy of spectral fusion in the range of 2000 to 2500 cm^?1 is 81.74%, which greatly improves the sample measure speed and data analysis speed than analysis of full spectra. The results from our study demonstrate that the serum spectral fusion technique combined with multivariate statistical methods have great potential for the screening of thyroid dysfunction.     

Bifidobacteria-mediated immune system imprinting early in life

1. Download : Download high-res image (173KB)
2. Download : Download full-size image

     

Vague-to-crisp dynamics of percept formation modeled as operant (selectionist) process

We model the vague-to-crisp dynamics of forming percepts in the brain by combining two methodologies: dynamic logic (DL) and operant learning process. Forming percepts upon the presentation of visual inputs is likened to model selection based on sampled evidence. Our framework utilizes the DL in selecting the correct “percept” among competing ones, but uses an intrinsic reward mechanism to allow stochastic online update in lieu of performing the optimization step of the DL framework. We discuss the connection of our framework with cognitive processing and the intentional neurodynamic cycle.     

Functional RelBE-Family Toxin-Antitoxin Pairs Affect Biofilm Maturation and Intestine Colonization in Vibrio cholerae

Toxin–antitoxin (TA) systems are small genetic elements that typically encode a stable toxin and its labile antitoxin. These cognate pairs are abundant in prokaryotes and have been shown to regulate various cellular functions. Vibrio cholerae, a human pathogen that is the causative agent of cholera, harbors at least thirteen TA loci. While functional HigBA, ParDE have been shown to stabilize plasmids and Phd/Doc to mediate cell death in V. cholerae, the function of seven RelBE-family TA systems is not understood. In this study we investigated the function of the RelBE TA systems in V. cholerae physiology and found that six of the seven relBE loci encoded functional toxins in E. coli. Deletion analyses of each relBE locus indicate that RelBE systems are involved in biofilm formation and reactive oxygen species (ROS) resistance. Interestingly, all seven relBE loci are induced under the standard virulence induction conditions and two of the relBE mutants displayed a colonization defect, which was not due to an effect on virulence gene expression. Although further studies are needed to characterize the mechanism of action, our study reveals that RelBE systems are important for V. cholerae physiology.     

Fungi short-chain carboxylate transporter: shift from microbe hereditary functional component to metabolic engineering target

Applied Microbiology and Biotechnology - Short-chain carboxylic acids and their derivatives are widely utilized in all aspects of our daily life. Given their specific functional groups, these...     

Perfect Terahertz Absorption with Graphene Surface Plasmons in the Modified Otto Configuration

Perfect terahertz (THz) absorption in the modified Otto configuration with the insertion of monolayer graphene sheet has been numerically demonstrated. This perfect absorption originates from the enhancement of the electrical field owing to the excitation of the transverse magnetic (TM) polarized surface plasmons at the interface of two dielectrics with monolayer graphene. It is found that the absorption peak occurs at the specific incident angles, which can be employed for realizing the angular absorbers. We further demonstrate that the angle of the peak absorption and the corresponding wavelength can be manipulated by changing the Fermi energy of monolayer graphene sheet via electrostatic biasing. Moreover, the behaviors of the perfect absorption are strongly dependent on the dielectric constants and thicknesses of the surrounding dielectrics.