Aim To reveal the mechanism of CIP4 homologs protein 1(RICH1)are involved in the regu-lation of myocardial fibrosis.Methods Mouse cardiac fibroblasts(MCFs)cells were treated with transforming growth factor-β(TGF-β1)to induce the formation of a myocardial fibrosis cell model;the level of the target protein was detected by Western blotting;and the RICH1 gene was detected by transfection of the cells with plasmid.The RICH1 gene was overexpressed(RICH 1 OE)using plasmid transfection;the RICH1 gene was silenced using siRNA fragment(siRICH1);and the expression levels of myocardial fibrosis marker genes,such as Col1 a1,Col3 a1,and Acta2,were de-tected using RT-qPCR.Results RICH1 was signifi-cantly down-regulated in TGF-β1-treated MCFs;the expression levels of myocardial fibrosis marker genes,such as Col1 a1,Col3a1,and Acta2,were down-regu-lated in the RICH1 OE+TGF-β1 group;and in the siRICH1+TGF-β1 group,myocardial fibrosis marker genes,such as Col1 a1,Col3a1 and Acta2 were up-regulated at the expression level;phosphorylated SMAD2(p-SMAD2)and phosphorylated SMAD3(p-SMAD3)levels were down-regulated in the siRICH1 OE+TGF-β1 group.p-SMAD2 and P-SMAD3 levels were upregulated in the siRICH1+TGF-β1 group.Conclusion RICH1 inhibits TGF-β1-induced myo-cardial fibrosis;RICH1 inhibits TGF-β1-induced myo-cardial fibrosis by negatively regulating the SMAD2/3 signaling pathway.

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.

Aim To reveal the mechanism of CIP4 homologs protein 1(RICH1)are involved in the regu-lation of myocardial fibrosis.Methods Mouse cardiac fibroblasts(MCFs)cells were treated with transforming growth factor-β(TGF-β1)to induce the formation of a myocardial fibrosis cell model;the level of the target protein was detected by Western blotting;and the RICH1 gene was detected by transfection of the cells with plasmid.The RICH1 gene was overexpressed(RICH 1 OE)using plasmid transfection;the RICH1 gene was silenced using siRNA fragment(siRICH1);and the expression levels of myocardial fibrosis marker genes,such as Col1 a1,Col3 a1,and Acta2,were de-tected using RT-qPCR.Results RICH1 was signifi-cantly down-regulated in TGF-β1-treated MCFs;the expression levels of myocardial fibrosis marker genes,such as Col1 a1,Col3a1,and Acta2,were down-regu-lated in the RICH1 OE+TGF-β1 group;and in the siRICH1+TGF-β1 group,myocardial fibrosis marker genes,such as Col1 a1,Col3a1 and Acta2 were up-regulated at the expression level;phosphorylated SMAD2(p-SMAD2)and phosphorylated SMAD3(p-SMAD3)levels were down-regulated in the siRICH1 OE+TGF-β1 group.p-SMAD2 and P-SMAD3 levels were upregulated in the siRICH1+TGF-β1 group.Conclusion RICH1 inhibits TGF-β1-induced myo-cardial fibrosis;RICH1 inhibits TGF-β1-induced myo-cardial fibrosis by negatively regulating the SMAD2/3 signaling pathway.

Objective To develop dynamic prediction models based on multiple postnatal time points to support early diagnosis and individualized intervention for bronchopulmonary dysplasia(BPD)in preterm infants with gestational age<32 weeks.Methods Clinical data of 472 preterm infants with gestational age<32 weeks admitted to the Second Xiangya Hospital of Central South University between January 2016 and November 2020 were retrospectively analyzed.Multivariable logistic regression was applied to develop five independent prediction models at postnatal days 1,7,14,21,and 28.The performance of the models was assessed using the area under the receiver operating characteristic curve(AUC)and the Hosmer-Lemeshow test.Results Baseline characteristics such as gestational age and birth weight differed significantly between the BPD group(n=147)and the non-BPD group(n=325)(P<0.05).Predictors of BPD evolved across time points:on day 1,key predictors included gestational age,birth weight,Score for Neonatal Acute Physiology II(SNAP-II),invasive mechanical ventilation,and fraction of inspired oxygen>30%;by day 7,additional variables emerged,including fasting duration>2 days,mean feeding advancement rate<8.5 mL/(kg·d),neonatal respiratory distress syndrome,apnea of prematurity,and positive sputum culture;from day 14 onward,nutrition-and treatment-related indicators were incorporated additionally.The models demonstrated good discrimination at postnatal days 1,7,14,21,and 28,with AUCs of 0.917,0.927,0.939,0.944,and 0.968,respectively,and good calibration(Hosmer-Lemeshow P>0.05).Internal validation showed AUCs ranging from 0.899 to 0.958,indicating robust performance.Conclusions Dynamic postnatal prediction models incorporating indicators spanning perinatal factors,respiratory support,nutritional management,and therapeutic interventions demonstrate high predictive performance and facilitate dynamic risk assessment for BPD in preterm infants with gestational age<32 weeks.

The lab module of exploratory experiment is newly designed in the practical course of bio-chemistry.Here we describe one of the experimental projects,and it originates from new scientific re-search results on the dynamic structure of ATP synthase.This exploratory experiment is organized in the form of real scientific research,which would fully mobilize the initiative and creativity of students in learning theoretical knowledge and experimental technology.Students work in groups and start with refer-ence reading.Through cooperation,they must develop certain experimental plan,handle samples with photocrosslinking technique and utilize the high-throughput electrophoresis method to analyze the dynamic structural change of ε subunit in ATP synthase under different physiological conditions.High quality re-sults from high-throughput electrophoresis can only be obtained through optimized operation and treat-ment,from which students would experience the process of technological innovation.The teaching process of this lab module embodies the student-centered teaching concept and is widely approved and supported by students.The project of ATP synthase closely combines the content of lab course with cut-ting-edge technology.Students can deeply experience the importance of experimental technology innova-tion in solving scientific problems.The practical ability of students would be comprehensively improved through this lab module.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective:To explore the equity and driving path of primary healthcare human resource allocation across 31 provinces in China,providing references for optimizing such allocations.Methods:Using data from the 2022 primary healthcare human resources in 31 provinces in China,the Health Resource Density Index(HRDI)was used to measure the equity of primary healthcare human resource allocation.The fuzzy-set Qualitative Comparative Analysis(fsQCA)was applied to construct configurational pathways influencing on allocation patterns.Results:In 2022,the HRDI for primary healthcare human resources in China was 2.349 0 in the East,1.198 6 in the Central region,and 0.775 2 in the West.Configurational analysis revealed three paths that promote high equity:the internal-external balance-driven model(H1),the government-led model(H2),and the economic-demand combined model(H3),with overall consistency and coverage of 0.955 and 0.794,respectively.Seven paths lead to low equity:internal-external constraint models(L1,L2),economic constraint models(L3),and demand constraint models(L4,L5,L6,L7),with overall consistency and coverage of 0.967 and 0.795,respectively.Conclusions:Significant regional disparities exist in the equity of primary healthcare human resource allocation in China.Population density is a critical factor influencing allocation equity.The collaboration of various factors contributes to enhancing the equity of primary healthcare human resources distribution.Therefore,future efforts to enhance equity should focus on promoting inter-regional mobility and resource sharing,while precisely addressing regional shortcomings to achieve high equity in primary healthcare human resource allocation.

Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2％)and gram-negative organisms(60.8％).The top three organisms were S.aureus(13.6％,1 453/10 688),A.baumannii(10.0％,1 067/10 688),and coagulase-negative Staphylococcus(9.9％,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1％,19.4％,8.8％,30.9％,67.4％,and 28.8％,respectively.Overall,more than 50％of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25％of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80％of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3％in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.

Objective:To explore the equity and driving path of primary healthcare human resource allocation across 31 provinces in China,providing references for optimizing such allocations.Methods:Using data from the 2022 primary healthcare human resources in 31 provinces in China,the Health Resource Density Index(HRDI)was used to measure the equity of primary healthcare human resource allocation.The fuzzy-set Qualitative Comparative Analysis(fsQCA)was applied to construct configurational pathways influencing on allocation patterns.Results:In 2022,the HRDI for primary healthcare human resources in China was 2.349 0 in the East,1.198 6 in the Central region,and 0.775 2 in the West.Configurational analysis revealed three paths that promote high equity:the internal-external balance-driven model(H1),the government-led model(H2),and the economic-demand combined model(H3),with overall consistency and coverage of 0.955 and 0.794,respectively.Seven paths lead to low equity:internal-external constraint models(L1,L2),economic constraint models(L3),and demand constraint models(L4,L5,L6,L7),with overall consistency and coverage of 0.967 and 0.795,respectively.Conclusions:Significant regional disparities exist in the equity of primary healthcare human resource allocation in China.Population density is a critical factor influencing allocation equity.The collaboration of various factors contributes to enhancing the equity of primary healthcare human resources distribution.Therefore,future efforts to enhance equity should focus on promoting inter-regional mobility and resource sharing,while precisely addressing regional shortcomings to achieve high equity in primary healthcare human resource allocation.

Objective:To explore the CT manifestation characteristics of peripancreatic aneurysms related to pancreatitis (PRPA).Methods:A retrospective analysis was conducted on the clinical data of 15 patients with pancreatitis-related aneurysms collected in Deyang People's Hospital from June 2017 to February 2025. Among them, there were 11 males and 4 females, with an age of (56.5±16.9) years. Record the CT manifestations of the patients, and observe the PRPA tumor-carrying arteries, morphology, quantity, bleeding, calcification, dynamic changes, etc.Results:The CT results showed that there were a total of 26 PRPAs in 15 patients. The aneurysm walls of the PRPAs had no calcification, among which 12 cases were single and 1 case was double. Two cases were multiple. The patients were pancreatitis complicated with muscle fiber dysplasia. Among them, one case had 5 PRPAs and the other had 7 PRPAs. Of the 26 PRPAs, 12 were sac-like, 8 were beaded, 4 were fusiform, and 2 were columnar in shape. The numbers of aneurysm-carrying arteries and PRPA were as follows: 8 in the pancreaticoduodenal artery, 7 in the hepatic artery and its branches, 6 in the splenic artery and its branches, 2 in the left gastric artery, 1 in the gastroduodenal artery, 1 in the middle colonic artery, and 1 in the ileocolonic artery. The CT diagnosis report missed 16 PRPAs, with a missed diagnosis rate of 61.5% (16/26). Among the 11 ruptured PRPAs, 4 were missed, with a missed diagnosis rate of 36.4%. Three missed aneurysms were diagnosed by digital subtraction angiography, and one was retrospectively analyzed by CT. Among the 15 unruptured PRPAs, 12 were missed, with a missed diagnosis rate of 80.0%. All the missed aneurysms were detected by retrospective CT analysis. There were 2 images without re-examination and 24 images with re-examination. Among the PRPAs with re-examination images, 4 disappeared after interventional embolization on the same day, 1 relapsed after interventional embolization on the same day, with a reduction in volume and disappeared after 3 days. Three cases underwent elective interventional embolization, among which two shranked and one enlarged before interventional embolization. Among the 16 cases that did not receive interventional treatment, 7 disappeared on their own, 1 was completely liquefied, 5 shrank but did not disappear, 2 remained stable in size without any change, and 1 increased. Among the re-examined PRPA images, 7 showed signs of enlargement.Conclusion:The main characteristics of PRPA are high rupture rate, prone to missed diagnosis and dynamic changes in size.