Geographical Traceability of Clinacanthus nutans with Near-Infrared Pectroscopy and Chemometrics

In this study, a seed origin discrimination model for Clinacanthus nutans was developed. First, 81 C. nutans samples from three seed origin locations were collected, and their Near-Infrared (NIR) spectra were obtained. Next, Principal Component Analysis (PCA) was performed on the NIR spectra of the 81 C. nutans samples. Then, MSC (multiplicative scatter correction), SNV (standard normal variate), first derivative, and second derivative pre-treatments of the C. nutans spectra were performed and combined with the Support Vector Machine (SVM) algorithm for modelling and analysis. Among these methods, first-order derivative pre-treatment achieved the best SVM model effectiveness, with a training set accuracy of 93.44% (57/61) and a test set accuracy of 85.00% (17/20). In order to further improve the discrimination accuracy of the model, three optimization algorithms Grid Search (GS), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) were employed to identify the best c and g parameters for the SVM model. The results demonstrated that the PSO optimization algorithm yielded the best parameters of c = 0.8343, g = 57.8741, with corresponding model training set the accuracy of 96.36% (60/61) and test set the accuracy of 95.00% (20/21). Therefore, developing a seed origin classification model for C. nutans based on NIR spectroscopy combined with chemometrics is feasible and has the advantages of being simple, rapid, and green.

miR-124 suppresses multiple steps of breast cancer metastasis by targeting a cohort of pro-metastatic genes in vitro

Metastasis is a multistep process involving modification of morphology to suit migration, reduction of tumor cell adhesion to the extracellular matrix, increase of cell mobility, tumor cell resistance to anoikis, and other steps. MicroRNAs are well-suited to regulate tumor metastasis due to their capacity to repress numerous target genes in a coordinated manner, thereby enabling their intervention at multiple steps of the invasion-metastasis cascade. In this study, we identified a microRNA exemplifying these attributes, miR-124, whose expression was reduced in aggressive MDA-MB-231 and SK-3rd breast cancer cells. Down-regulation of miR-124 expression in highly aggressive breast cancer cells contributed in part to DNA hypermethylation around the promoters of the three genes encoding miR-124. Ectopic expression of miR-124 in MDA-MB-231 cells suppressed metastasis-related traits including formation of spindle-like morphology, migratory capacity, adhesion to fibronectin, and anoikis. These findings indicate that miR-124 suppresses multiple steps of metastasis by diverse mechanisms in breast cancer cells and suggest a potential application of miR-124 in breast cancer treatment.

Research Progress on the Effects of Dietary Fiber Regulating Gut Microbiota on Sows Reproductive Performance

Dietary fiber(DF)is an essential nutrient in sow diet.It can increase sow satiety and prevent constipation.It can also regulate sow gut microbiota,and the interaction between the two can regulate sows reproductive performance and metabolic function and the growth performance of offspring piglets.It can be seen that the benefits of DF in sow production are inseparable from the interaction of gut microbiota.This paper reviewed the effects of DF on the diversity of sows gut microbiota,and the effects of DF-gut microbiota interaction on sows gut microbiota,metabolism,ovulation and lactation,as well as on offspring production performance,aiming to provide a new strategy for the application and research in sow diet.

股票承销市场中的个人社会关系研究——基于承销双方、承销团成员多重关系视角

本文基于69家券商2 359位高管及1 504家上市公司10 388位高管简历,从校友关系视角考察个人社会关系对IPO承销商选择及承销效果的影响。研究发现:异质主体(承销双方)校友关系能提高券商进入承销团或担任主承销商的概率。同质主体(承销商内部)校友关系会抑制合作。且承销双方高管存在校友关系时,发行人上市后财务业绩与市场表现更优,而券商高管校友关系不对其产生影响。本文有助于从个人社会关系异质性视角剖析"关系承销"的经济后果。