The quantitative expressions of lymphangiogenic factors and metastasis in human colorectal cancers

Objective： The purpose of this paper was to study the expression levels of newly described lymphatic endothelial markers – LYVE-1, Prox-1, podoplanin and 5’-nucleotidase, and their correlation with metastasis of human colorectal cancers. Methods： Tumor and corresponding tumor-side normal tissue samples were obtained from resected specimens immediately after operation. Expression level of each factor was determined by quantitative real-time PCR （RT-PCR） and Western blot technique. Results： Expression levels of lymphatic endothelial markers LYVE-1, Prox-1, podoplanin and 5’-nucleotidase were significantly different in tumor and tumor-side normal groups. Expression levels of Prox-1 and podoplanin were higher in patients with positive lymph node metastasis than those without metastasis. LYVE-1, but not 5’-nucleotidase expression level was higher in both cancer and normal groups. Conclusion： These results indicate that combined quantitative analysis of lymphangiogenic markers LYVE-1, Prox-1 and podoplanin in colorectal cancer specimens may be useful in predicting metastasis of colorectal cancer to regional lymph nodes. However, the role of 5’-nucleotidase in predicting metastasis of colorectal cancer still remains to be further analyzed.

Carnosine concentration and expression profiles of carnosine related genes in Mytilus after beta-alanine injection

Carnosine and its analogues are histidine-containing dipeptides(HCDs)playing diverse functions in vertebrates.However,the distribution and the metabolism of carnosine in invertebrates are still unknown.In this study,Mytilus coruscus,a shellfish with important economic value in China,was selected for the investigation of HCD content and the expression profiling of carnosine-related genes in various mussel tissues.Quantification of HCD by amino acids analyzer revealed a low concentration of anserine in muscular tissues in Mytilus,indicating the presence of HCD even in an invertebrate.mRNA expression of five carnosine metabolic-related genes was profiled in various tissues,and the results highlighted the relative higher expression level of these genes in muscular tissues.Considering the fact that beta-alanine supplementation can increase the HCD content in vertebrates,a beta-alanine injection was performed and the changes of HCD concentration and the mRNA expression of carnosine related genes were investigated in five mussel tissues.The results revealed the increase of HCD concentration,as well as the up-regulated expression level of related genes,in tested tissues of beta-alanine injected mussels.Transcriptomic analysis for the whole soft tissue of mussel before and after beta-alanine injection were performed,and 3569 differential expression genes(DEGs)were identified in the beta-alanine injected group when compared to their expression levels in the control.These data indicated the complex eff ects of betaalanine on M.coruscus metabolism,and those DEGs enriched in pathways of cancers,muscle contraction,and tyrosine metabolism highlighted the possible functions of beta-alanine in cell proliferation,sports,and melanogenesis,respectively.

Methane hydrate formation in porous media:Overview and perspectives

Natural gas hydrate(NGH)has recently received more attention as a cleaner alternative energy source that not only reduces carbon emissions caused by the use of conventional fossil fuels but also plays a key role in global climate change.Furthermore,hydrate-based technologies,particularly hydrate-based carbon capture and storage,have enormous promise for decreasing global carbon emissions,and porous media play an important role in all hydrate-based technologies.Accordingly,this paper reviews the recent applications of porous media in the field of methane hydrate(MH)formation and analyzes the influence of porous media systems on MH phase equilibria and formation kinetics.This is because the efficiency of hydrate-based technologies is determined mainly by the phase equilibrium and formation kinetics of hydrates.The influence of the nature of the media on MH formation in porous media systems is comprehensively summarized to understand how porous media can efficiently enhance the kinetics of hydrate formation.Promoters are necessary for rapid hydrate formation,and the effect of various promoters on MH formation was also evaluated.Based on the aforementioned overview and understanding,the mechanisms for MH formation in various porous media systems are proposed.Finally,the future perspectives and challenges of hydrate-based technologies in tackling global climate change were discussed.This review provides a fundamental understanding of the application and development of porous media in rapid hydrate formation,a fair evaluation of the performance of various porous media systems,and critical insights into major research foci.

Deep Learning-Based Emotion Detection

In order to make artificial intelligence smarter by detecting user emotions, this project analyzes and determines the current type of human emotions through computer vision, semantic recognition and audio feature classification. In facial expression recognition, for the problems of large number of parameters and poor real-time performance of expression recognition methods based on deep learning, Wang Weimin and Tang Yang Z. et al. proposed a face expression recognition method based on multilayer feature fusion with light-weight convolutional networks, which uses an improved inverted residual network as the basic unit to build a lightweight convolutional network model. Based on this method, this experiment optimizes the traditional CNN MobileNet model and finally constructs a new model framework ms_model_M, which has about 5% of the number of parameters of the traditional CNN MobileNet model. ms_model_M is tested on two commonly used real expression datasets, FER-2013 and AffectNet, the accuracy of ms_model_M is 74.35% and 56.67%, respectively, and the accuracy of the traditional MovbliNet model is 74.11% and 56.48% in the tests of these two datasets. This network structure well balances the recognition accuracy and recognition speed of the model. For semantic emotion detection and audio emotion detection, the existing models and APIs are used in this experiment.