Transient receptor potential channels as predictive marker and potential indicator of chemoresistance in colon cancer

Transient receptor potential(TRP)channels are strongly associated with colon cancer development and progression.This study leveraged a multivariate Cox regression model on publicly available datasets to construct a TRP channels-associated gene signature,with further validation of signature in real world samples from our hospital treated patient samples.Kaplan-Meier(K-M)survival analysis and receiver operating characteristic(ROC)curves were employed to evaluate this gene signature’s predictive accuracy and robustness in both training and testing cohorts,respectively.Additionally,the study utilized the CIBERSORT algorithm and single-sample gene set enrichment analysis to explore the signature’s immune infiltration landscape and underlying functional implications.The support vector machine algorithm was applied to evaluate the signature’s potential in predicting chemotherapy outcomes.The findings unveiled a novel three TRP channels-related gene signature(MCOLN1,TRPM5,and TRPV4)in colon adenocarcinoma(COAD).The ROC and K-M survival curves in the training dataset(AUC=0.761;p=1.58e-05)and testing dataset(AUC=0.699;p=0.004)showed the signature’s robust predictive capability for the overall survival of COAD patients.Analysis of the immune infiltration landscape associated with the signature revealed higher immune infiltration,especially an increased presence of M2 macrophages,in high-risk group patients compared to their low-risk counterparts.High-risk score patients also exhibited potential responsiveness to immune checkpoint inhibitor therapy,evident through increased CD86 and PD-1 expression profiles.Moreover,the TRPM5 gene within the signature was highly expressed in the chemoresistance group(p=0.00095)and associated with poor prognosis(p=0.036)in COAD patients,highlighting its role as a hub gene of chemoresistance.Ultimately,this signature emerged as an independent prognosis factor for COAD patients(p=6.48e-06)and expression of model gene are validated by public data and real-world patients.Overall,this bioinformatics study provides valuable insights into the prognostic implications and potential chemotherapy resistance mechanisms associated with TRPs-related genes in colon cancer.

Epitaxially Grown Ru Clusters-Nickel Nitride Heterostructure Advances Water Electrolysis Kinetics in Alkaline and Seawater Media

The epitaxial heterostructure can be rationally designed based on the in situ growth of two compatible phases with lattice similarity,in which the modulated electronic states and tuned adsorption behaviors are conducive to the enhancement of electrocatalytic activity.Herein,theoretical simulations first disclose the charge transfer trend and reinforced inherent electron conduction around the epitaxial heterointerface between Ru clusters and Ni_(3)N substrate(cRu-Ni_(3)N),thus leading to the optimized adsorption behaviors and reduced activation energy barriers.Subsequently,the defectrich nanosheets with the epitaxially grown cRu-Ni_(3)N heterointerface are successfully constructed.Impressively,by virtue of the superiority of intrinsic activity and reaction kinetics,such unique epitaxial heterostructure exhibits remarkable bifunctional catalytic activity toward electrocatalytic OER(226 mV@20 mA cm^(−2))and HER(32 mV@10 mA cm^(−2))in alkaline media.Furthermore,it also shows great application prospect in alkaline freshwater and seawater splitting,as well as solar-to-hydrogen integrated system.This work could provide beneficial enlightenment for the establishment of advanced electrocatalysts with epitaxial heterointerfaces.

Establishment of a developmental atlas and transgenetic tools in the ascidian Styela clava

The ascidian Styela clava is an ecologically important species that is distributed along coastal regions worldwide.It has a long history as a model animal for evolutionary and developmental biology research owing to its phylogenetic position between vertebrates and invertebrates,and its classical mosaic expression patterns.However,the standard developmental atlas and protocols and tools for molecular manipulation of this organism are inadequate.In this study,we established a standard developmental table and provided a web-based digital image resource for S.clava embryogenesis at each developmental stage from fertilized eggs to hatching larvae by utilizing confocal laser microscopy and 3D reconstruction images.It takes around 10 h for fertilized eggs to develop into swimming larvae and 20–30 min to complete the tail regression processes at the metamorphic stage.We observed that the notochord cells in S.clava embryos did not produce an extracellular lumen like Ciona robusta,but showed polarized elongation behaviors,providing us an ideal comparative model to study tissue morphogenesis.In addition,we established a chemical-washing procedure to remove the chorion easily from the fertilized eggs.Based on the dechorionation technique,we further realized transgenic manipulation by electroporation and successfully applied tissue-specific fluorescent labeling in S.clava embryos.Our work provides a standard imaging atlas and powerful genetic tools for investigating embryogenesis and evolution using S.clava as a model organism.

MSWNet:A visual deep machine learning method adopting transfer learning based upon ResNet 50 for municipal solid waste sorting

An intelligent and efficient methodology is needed owning to the continuous increase of global municipal solid waste(MSW).This is because the common methods of manual and semi-mechanical screenings not only consume large amount of manpower and material resources but also accelerate virus community transmission.As the categories of MSW are diverse considering their compositions,chemical reactions,and processing procedures,etc.,resulting in low efficiencies in MSW sorting using the traditional methods.Deep machine learning can help MSW sorting becoming into a smarter and more efficient mode.This study for the first time applied MSWNet in MSW sorting,a ResNet-50 with transfer learning.The method of cyclical learning rate was taken to avoid blind finding,and tests were repeated until accidentally encountering a good value.Measures of visualization were also considered to make the MSWNet model more transparent and accountable.Results showed transfer learning enhanced the efficiency of training time(from 741 s to 598.5 s),and improved the accuracy of recognition performance(from 88.50%to 93.50%);MSWNet showed a better performance in MSW classsification in terms of sensitivity(93.50%),precision(93.40%),F1-score(93.40%),accuracy(93.50%)and AUC(92.00%).The findings of this study can be taken as a reference for building the model MSW classification by deep learning,quantifying a suitable learning rate,and changing the data from high dimensions to two dimensions.

Engineering Coordination Environment of Cobalt Center in Molecular Catalysts for Improved Photocatalytic CO_(2) Reduction

The creation of effective and inexpensive catalysts is essential for photocatalytic CO_(2) reduction.Homogeneous molecular catalysts,possessing definite crystal structures,are desirable to study the relationship between catalytic performance and coordination microenvironment around catalytic center.In this report,we elaborately developed three Co(II)-based molecular catalysts with different coordination microenvironments for CO_(2) reduction,named[CoN_(3)O]ClO_(4),[CoN_(4)]ClO_(4),and[CoN_(3)S]ClO_(4),respectively.The optimal[CoN_(3)O]ClO_(4) photocatalyst has a maximum TON of 5652 in photocatalytic reduced CO_(2) reduction,which is 1.28 and 1.65 times greater than that of[CoN_(4)]ClO_(4) and[CoN_(3)S]ClO_(4),respectively.The high electronegativity of oxygen in L1(N,N-bis(2-pyridylmethyl)-N-(2-hydroxybenzyl)amine)provides the Co(II)catalytic centers with low reduction potentials and a more stable*COOH intermediate,which facilitates the CO_(2)-to-CO conversion and accounts for the high photocatalytic activity of[CoN_(3)O]ClO_(4).This work provides researchers new insights in development of catalysts for photocatalytic CO_(2) reduction.

Metal-organic layers as reusable solid fluorination reagents and heterogeneous catalysts for aromatic fluorination

Reusable solid fluorination reagents and heterogeneous catalysts are ideally suited for late-stage fluorination with fast and clean conversion and simplified work-up.Here we report Pd-functionalized two-dimensional metal-organic layers(MOLs)as solid reagents and heterogeneous catalysts to efficiently fluorinate a broad scope of aromatic compounds.Site isolation in the MOLs provides a unique opportunity to stabilize highly active F-containing species for the chemical conversion.A terpyridine(TPY)-based ligand on the MOL,together with a 2-chloro-1,10-phenanthroline(phenCl)as a co-ligand,chelates Pd^(Ⅱ)toform a reactive center.After treatment with Selectfluor/H_(2)0,an(N-fluoroxy)-(2-chloro)-phenanthrolinium[N-(FO)-phenCl^(+)]moiety is produced from the co-ligand on the Pd center.This active species serves as a stochiometric solid fluorination reagent,which shows different regioselectivities and reactivities as compared to homogeneous catalysts that involves Pd^(Ⅲ/Ⅳ)-F intermediates in catalytic cycles.The MOLs can also be used as heterogeneous catalysts for fluorination using Selectfluor.This work highlights opportunities in using MOLs to stabilize unique active sites for late-stage fluorination.

An Old Story Retold: Loss of G1 Control Defines A Distinct Genomic Subtype of Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma （ESCC） has a high mortality rate. To determine the molecular basis of ESCC development, this study sought to identify characteristic genome-wide alterations in ESCC, including exonic mutations and structural alterations. The clinical implications of these genetic alterations were also analyzed. Exome sequencing and verification were performed for nine pairs of ESCC and the matched blood samples, followed by validation with additional sam- ples using Sanger sequencing. Whole-genomc SNP arrays were employed to detect copy number alteration （CNA） and loss of heterozygosity （LOH） in 55 cases, including the nine ESCC samples subjected to exome sequencing. A total of 108 non-synonymous somatic mutations （NSSMs） in 102 genes were verified in nine patients. The chromatin modification process was found to be enriched in our gene ontology （GO） analysis. Tumor genomes with TP53 mutations were signifi- cantly more unstable than those without TP53 mutations. In terms of the landscape of genomic alterations, deletion of 9p21.3 covering CDKN2A/2B （30.9%）, amplification of 1 1q13.3 covering CCND1 （30.9%）, and TP53 point mutation （50.9%） occurred in two-thirds of the cases. These results suggest that the deregulation of the G1 phase during the cell cycle is a key event in ESCC. Furthermore, six minimal common regions were found to be significantly altered in ESCC samples and three of them, 9p21.3, 7p 11.2, and 3p 12.1, were associated with lymph node metastasis. With the high correlation of TP53 mutation and genomic instability in ESCC, the amplification of CCND1, the deletion of CDKN2A/2B, and the somatic mutation of TP53 appear to play pivotal roles via G1 deregulation and therefore helps to classify this cancer into different genomic subtypes. These findings provide clinical significance that could be useful in future molecular diagnoses and therapeutic targeting.