Integration of metabolomics and transcriptomics revealed the biosynthetic mechanism of anti-parasitic compounds in Salinivibrio proteolyticus strain YCSC6

The fermentation broth of Salinivibrio proteolyticus strain YCSC6 shows potent anti-parasitic activity against Uronema marinum,with activity varying in each fermentation stage.To investigate the biosynthetic mechanism of anti-parasitic compounds in strain YCSC6,a comprehensive analysis of metabolomics and transcriptomics over four diff erent time points(12,24,48,and 72 h)was performed.Metabolomics detected 17943 metabolites with 1129 known metabolites.A trend analysis of the known metabolites showed that 575 metabolites,including 69 polyketides,were continuously enhanced,being the potential source of anti-parasitic agents.In addition,941 genes mapped to the same pathways of these metabolites,were screened through the association analysis of metabolites and genes.KEGG pathway enrichment of these genes showed 270 genes mapped to the biosynthesis of secondary metabolites and 192 genes mapped to the biosynthesis of antibiotics.This demonstrates the potent secondary metabolic capacity of strain YCSC6.Finally,a gene-metabolite correlation network was created based on the 575 continuously enhanced metabolites and 43 continuously up-regulated genes.This revealed 13 genes at the key position that mapped to a putative metabolic pathway associated with the biosynthesis of polyketides and caprylic acid,which contributes to the potent anti-parasitic activity of strain YCSC6.This comprehensive analysis of metabolomics and transcriptomics provides insights into the biosynthetic mechanisms of anti-parasitic compounds in strain YCSC6 and guides the exploitation of more anti-parasitic agents for aquaculture.

The Significance of CXCR4 Expression for the Prediction of Lymph Node Metastasis in Breast Cancer Patients

OBJECTIVE The chemokine receptor(CXCR4)CXC chemokine receptor 4)plays an important role in cancer metastasis.We therefore studied differential expression of the CXCR4,as well as that of the biomarker HER2,so as to evaluate whether these biomarkers can be used to predict axillary lymph node metastasis in breast cancer patients. METHODS Immunohistochemistry was used to evaluate the CXCR4 and HER2 expressions and to examine the paraffin sections of the breast cancers at various stages.Positive lymph node expression was found in 80 of the cases,and in 7 there was negative expression. RESULTS Compared to the cases with negative lymph nodes, there was a high expression of CXCR4(26.3% vs.14.3%,P=0.013), and an over-expression of HER2(28.8% vs.14.3%,P=0.011). Moreover,there was a direct correlation between the CXCR4 and HER2 expressions and the tumor staging(P=0.000)and lymph node metastasis(P=0.032).When the two biomarkers,i.e.CXCR4 and HER2,were concurrently labeled,a high expression of one of the biomarkers could be seen in the cases with positive lymph nodes(51.3% vs.28.6%,P<0.003). CONCLUSION The chemokine receptor,CXCR4,is a new-type biomarker in predicting axillary lymph-node metastasis in breast cancers.Compared with the other markers,such as HER2 etc., assessment of CXCR4 can improve the prediction of the presence and extent of lymph node involvement.

Frontiers in Molecular Immunology

Immunology is a discipline to investigate the structure and function of the immune molecules or immune pathway and the causes of immunity to disease, which cover the study of all aspects of the immune system. The earliest concept of acquired immunology was originated from the inoculation of smallpox occurs inWan Quan’s (1499- 1582) Douzhenxinfa,[1] and was further developed by Edward Jenner with the discovery of smallpox vaccine in 1796.[2] Immunology made a great advance towards the end of the 19th century, with the isolation of infectious bacteria by Robert Koch[3] and the demonstration of antibody activity against diphtheria and tetanus toxins by Emil von Behring and Kitasato Shibasaburo.

Differentiation of qualified tea beverages from spoiled ones by the LC-MS-based analysis of their polycarboxylic acids

Polycarboxylic acids(PACs)are important metabolic products in almost all living bodies,yet current analytical methods for detection of PACs in tea beverages are still unsatisfactory due to the complex matrix and physicochemical properties of PACs.In this work,a rapid method was developed for the simultaneous determination of 7 PACs,including tartaric acid,α-ketoglutaric acid,malic acid,malonic acid,cis-aconitic acid,succinic acid,and fumaric acid,in beverages,based on selective removal of the matrix in combination with liquid chromatography–mass spectrometry(LC-MS)analysis.By stirring with activated carbon and the Na2CO3 solution,the matrix in beverages was selectively removed,and PACs were almost retained in the supernatant of diluted Na2CO3 solution.Under optimized parameters,the limit of quantitation for the PACs was in the range of 1–50 ng/mL,and the content of the PACs in 8 beverages was determined with the recovery range of 72.2%–122.5%.The contents of malic acid,malonic acid,and succinic acid in tea beverages were found to be greater than those in non-tea beverages.Moreover,the concentration of these PACs in beverages was found to be multiplied many times in their deterioration period,especially for fumaric acid andα-ketoglutaric acid.These results indicated that PACs can be selected as a criterion to differentiate qualified tea beverages from spoiled beverages.

Adaptive deep residual network for single image super-resolution

In recent years,deep learning has achieved great success in the field of image processing.In the single image super-resolution(SISR)task,the convolutional neural network(CNN)extracts the features of the image through deeper layers,and has achieved impressive results.In this paper,we propose a single image super-resolution model based on Adaptive Deep Residual named as ADR-SR,which uses the Input Output Same Size(IOSS)structure,and releases the dependence of upsampling layers compared with the existing SR methods.Specifically,the key element of our model is the Adaptive Residual Block(ARB),which replaces the commonly used constant factor with an adaptive residual factor.The experiments prove the effectiveness of our ADR-SR model,which can not only reconstruct images with better visual effects,but also get better objective performances.