Yanchi Tan sheep,a specialty of Ningxia,China,is famous for its excellent meat quality,but the detailed mechanisms of its muscle development and meat quality formation are still unclear.In or-der to preliminarily investigate the unique molecular mechanisms in the muscle development of the sheep,the present study was carried out to collect the longest dorsal muscle(LDM)samples from 6-month-old and 12-month-old female Tan sheep,and we screened the genes and long non-coding RNA(lncRNAs)that may play important roles in regulating the muscle development and meat quality formation through transcriptome sequencing(RNA-seq).The results showed that a total of 504 mRNAs and 1,483 lncRNAs were detected between the two groups of LDMs,with significant differences(P＜0.05).And we also pre-dicted 103 potential lncRNA-mRNA cis-regulatory relationship pairs with significant differences(P＜0.05).Skeletal muscle development-related genes such as MSTN,CDKN1A,FHL1 and skeletal muscle metabolism-related genes such as LPL and SCD were subsequently screened based on the functional anal-ysis of differentially expressed mRNA.Based on the functional analysis of differentially expressed lncRNA target genes,13 lncRNAs potentially related to muscle development(LNC.17926.1,LNC.981.1,LNC.16284.1,etc.)and 8 lncRNAs potentially related to skeletal muscle metabolism(LNC.15496.1,LNC.18149.1,etc.)were identified.5 lncRNAs and 4 mRNAs expressed in both groups were randomly selected for qPCR validation experiments,and their results were consistent with RNA-seq,which corrob-orated with the reliability of the sequencing results.This study lays a solid foundation for future investiga-tions of muscle development,meat quality formation mechanism and molecular breeding in Tan sheep,and provides a scientific basis for improving the meat production performance of other domestic sheep breeds.

Objective:To investigate the effects of TP53 genetic status(wild-type/mutated/null)on the drug resistance of decitabine(DAC)in myelodysplastic syndromes(MDS)and identify key resistance-associated genes.Methods:Two myeloid cell lines with distinct TP53 status(M-07e:wild-type;SKM-1:mutated;)were treated with gradient DAC concentrations(0-10 μmol/L)for 0-72 h.Cell viability was detected by CCK-8 assay.RNA-Seq transcriptomics,and methylation profiling were integrated to analyze differentially expressed genes.Results:Decitabine(DAC)treatment induced time-and dose-dependent inhibition of cell viability in CCK-8 assays,with SKM-1 cells exhibiting the highest resistance(IC50=5 μmol/L vs M-07e=0.5 μmol/L,P＜0.01).Transcriptomic analysis revealed 662 upregulated and 452 downregulated genes in DAC-treated M-07e cells,while SKM-1 cells showed 515 upregulated and 73 downregulated genes.By proteomic profiling,117 upregulated and 136 downregulated proteins were identified in M-07e cells,while 91 upregulated and 46 downregulated proteins were identified in SKM-1 cells following DAC exposure.Through integrated analysis of upregulated genes and proteins expression profiles,181 candidate genes were screened out,while methylation studies identified 884 hypomethylated genes with high-sensitivity loci and CpG density.Notably,31 genes overlapped between these datasets,and functional annotation indicated these drug-resistance-associated genes are primarily involved in positive regulation of cell differentiation,negative regulation of binding processes,and negative regulation of cellular component organization.Conclusion:TP53 mutations drive DAC resistance via epigenetic reprogramming.Targeting these genes may improve outcomes in TP53-mutated MDS.

Berberine is a kind of isoquinoline alkaloid extracted from the roots and rhizomes of many medicinal plants,such as Coptis chinensis of Ranunculus family,Phellodendron chinensis of rutaceae family,and Berberine Sanacanthus family.In recent years,with the deepening of research,berberine has shown re-markable prevention and treatment effect in a variety of neuro-psychiatric disease models.This paper summarizes the research progress of berberine in neuropsychiatric diseases and provides theoretical support for further clinical prevention and treatment of neuropsychiatric diseases.

Objective To observe the value of preoperative magnetization transfer imaging(MTI)for predicting postoperative pancreatic fistula(POPF)after distal pancreatectomy(DP).Methods A total of 65 patients with pancreatic tumor who underwent DP and preoperative MR scanning were retrospectively enrolled and divided into clinically relevant POPF(CR-POPF)group(n=14,with grade B or C fistula),biochemical fistula group(n=31,postoperative drain fluid amylase level exceeding 3 times the upper limit of normal)and non-fistula group(n=20,postoperative drain fluid amylase level not exceeding 3 times the upper limit of normal)based on postoperative records.Clinical data and magnetization transfer ratio(MTR)of pancreatic tissue at the surgical margin were compared among 3 groups.The predictive value of MTR for CR-POPF was evaluated according to the area under the curve(AUC)of receiver operating characteristic(ROC)curve.Results Patients' age,intraoperative blood loss and the proportion of pancreatic ductal adenocarcinoma in both CR-POPF group and biochemical fistula group were lower than those in non-fistula group(all adjusted P＜0.05),while no significant difference was found between the former two groups(all adjusted P＞0.05).MTR of pancreatic tissue at the surgical margin in CR-POPF group was lower than that in both biochemical fistula group and non-fistula group(both P＜0.05),whereas no statistical difference was detected between the latter two groups(P＞0.05).The AUC of MTR for predicting CR-POPF after DP was 0.727.Conclusion Preoperative MTI could be used to predict POPF after DP.

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

Objective To observe the value of preoperative magnetization transfer imaging(MTI)for predicting postoperative pancreatic fistula(POPF)after distal pancreatectomy(DP).Methods A total of 65 patients with pancreatic tumor who underwent DP and preoperative MR scanning were retrospectively enrolled and divided into clinically relevant POPF(CR-POPF)group(n=14,with grade B or C fistula),biochemical fistula group(n=31,postoperative drain fluid amylase level exceeding 3 times the upper limit of normal)and non-fistula group(n=20,postoperative drain fluid amylase level not exceeding 3 times the upper limit of normal)based on postoperative records.Clinical data and magnetization transfer ratio(MTR)of pancreatic tissue at the surgical margin were compared among 3 groups.The predictive value of MTR for CR-POPF was evaluated according to the area under the curve(AUC)of receiver operating characteristic(ROC)curve.Results Patients' age,intraoperative blood loss and the proportion of pancreatic ductal adenocarcinoma in both CR-POPF group and biochemical fistula group were lower than those in non-fistula group(all adjusted P＜0.05),while no significant difference was found between the former two groups(all adjusted P＞0.05).MTR of pancreatic tissue at the surgical margin in CR-POPF group was lower than that in both biochemical fistula group and non-fistula group(both P＜0.05),whereas no statistical difference was detected between the latter two groups(P＞0.05).The AUC of MTR for predicting CR-POPF after DP was 0.727.Conclusion Preoperative MTI could be used to predict POPF after DP.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To investigate the effects of TP53 genetic status(wild-type/mutated/null)on the drug resistance of decitabine(DAC)in myelodysplastic syndromes(MDS)and identify key resistance-associated genes.Methods:Two myeloid cell lines with distinct TP53 status(M-07e:wild-type;SKM-1:mutated;)were treated with gradient DAC concentrations(0-10 μmol/L)for 0-72 h.Cell viability was detected by CCK-8 assay.RNA-Seq transcriptomics,and methylation profiling were integrated to analyze differentially expressed genes.Results:Decitabine(DAC)treatment induced time-and dose-dependent inhibition of cell viability in CCK-8 assays,with SKM-1 cells exhibiting the highest resistance(IC50=5 μmol/L vs M-07e=0.5 μmol/L,P＜0.01).Transcriptomic analysis revealed 662 upregulated and 452 downregulated genes in DAC-treated M-07e cells,while SKM-1 cells showed 515 upregulated and 73 downregulated genes.By proteomic profiling,117 upregulated and 136 downregulated proteins were identified in M-07e cells,while 91 upregulated and 46 downregulated proteins were identified in SKM-1 cells following DAC exposure.Through integrated analysis of upregulated genes and proteins expression profiles,181 candidate genes were screened out,while methylation studies identified 884 hypomethylated genes with high-sensitivity loci and CpG density.Notably,31 genes overlapped between these datasets,and functional annotation indicated these drug-resistance-associated genes are primarily involved in positive regulation of cell differentiation,negative regulation of binding processes,and negative regulation of cellular component organization.Conclusion:TP53 mutations drive DAC resistance via epigenetic reprogramming.Targeting these genes may improve outcomes in TP53-mutated MDS.

Berberine is a kind of isoquinoline alkaloid extracted from the roots and rhizomes of many medicinal plants,such as Coptis chinensis of Ranunculus family,Phellodendron chinensis of rutaceae family,and Berberine Sanacanthus family.In recent years,with the deepening of research,berberine has shown re-markable prevention and treatment effect in a variety of neuro-psychiatric disease models.This paper summarizes the research progress of berberine in neuropsychiatric diseases and provides theoretical support for further clinical prevention and treatment of neuropsychiatric diseases.