Objective To analyze the risk factors of type 2 diabetes mellitus (T2DM) with metabolic-associated fatty liver disease (MAFLD) and explore their relationship with BMI management. Methods A retrospective analysis was conducted of 310 patients with type 2 diabetes who underwent physical examinations at the 363 hospital between March 2023 and March 2025. Among these patients, those with MAFLD were counted. The risk factors of T2DM with MAFLD were analyzed by logistic regression analysis. The relationship between T2DM with MAFLD and BMI management was explored by Spearman correlation coefficient analysis. Results Compared with the non-MAFLD group, the levels of alanine aminotransferase (ALT), fasting insulin (I₀), fasting blood glucose (G₀), BMI, triglyceride (TG), aspartate aminotransferase (AST), and serum uric acid (SUA) were higher while the level of high-density lipoprotein cholesterol (HDL-C) was lower in the MAFLD group (P<0.05). Logistic regression analysis showed that BMI, SUA, I₀, ALT, G₀, and BMI control scale score were risk factors of T2DM with MAFLD (P<0.05). The score of BMI control scale of patients in the MAFLD group was higher than that in the non-MAFLD group (P<0.05). Correlation analysis indicated that T2DM with MAFLD was negatively correlated with BMI management (P<0.05). Conclusion BMI, SUA, I₀, ALT, and G₀ are all risk factors of T2DM with MAFLD. BMI management is negatively correlated with T2DM with MAFLD. Patients with T2DM should control BMI and blood glucose to reduce the occurrence of MAFLD.

OBJECTIVE To investigate the effects of baicalin （BC） on insulin resistance in rats with gestational diabetes mellitus （GDM） and its underlying mechanism based on the adenosine monophosphate-activated protein kinase （AMPK）/suppressor of variegation 3-9 homolog 1 （SUV39H1）/histone H3 lysine 9 trimethylation （H3K9me3） axis. METHODS A GDM rat model was established by a combination of a high-fat diet and streptozotocin injection. The successfully modeled rats were divided into the GDM group， BC low-dose group， BC high-dose group， and high-dose of BC+AMPK inhibitor （Compound C） group， with 10 rats in each group. Another 10 pregnant rats fed a normal diet served as the control group. Rats in each group were given corresponding drugs/normal saline intragastrically and/or intraperitoneally， once daily for 2 consecutive weeks. After the last administration， the levels of fasting blood glucose （FBG）， pancreatic function indexes [fasting insulin （FINS）， homeostasis model assessment of insulin resistance （HOMA-IR）， insulin sensitivity index （ISI）]， blood lipid indexes （total cholesterol， triglyceride， low-density lipoprotein cholesterol）， liver function indexes （alanine transferase， aspartate transferase， alkaline phosphatase）， inflammatory indicators （C-reactive protein， interleukin-1β， interleukin-6）， metabolic regulatory protein [complement-C1q/tumor necrosis factor-related protein 3 （CTRP3）]， insulin sensitivity related factors [glucose transporter 4 （GLUT4）， adiponectin]， and oxidative stress indicators [superoxide dismutase （SOD）， catalase （CAT）， malondialdehyde （MDA）] were measured. Pathological changes in liver tissue were observed， and the expressions of proteins related to the AMPK/SUV39H1/H3K9me3 axis in liver tissue were detected. RESULTS Compared with the GDM group， rats in the BC low- and high-dose groups showed varying degrees of improvement in pathological changes such as disordered cell arrangement， vacuolar degeneration， lipid deposition， and inflammatory cell infiltration in liver tissue. Their FBG and FINS levels， HOMA-IR， the levels of blood lipid indexes， liver function indexes， inflammatory indicators and MDA， and the expressions of SUV39H1 and H3K9me3 were significantly decreased or down-regulated， while metabolic regulatory protein， insulin sensitivity-related factors and AMPK protein phosphorylation levels were significantly increased （ P ＜0.05）. The improvement was more significant in the BC high-dose group （ P ＜0.05）. Compound C could significantly reverse the ameliorative effects of high-dose BC on the above quantitative indicators （ P ＜0.05）. CONCLUSIONS BC can significantly reduce oxidative stress and inflammatory responses， increase serum levels of CTRP3， GLUT4 and adiponectin， thereby improving insulin resistance in GDM rats. These effects may be related to the activation of AMPK and inhibition of SUV39H1-mediated H3K9me3 modification.

Objective To systematically analyze the literature characteristics of Journal of Organ Transplantation since its inception. Methods Using the China National Knowledge Infrastructure (CNKI) academic journal full-text database as the data source, all articles published in the Journal of Organ Transplantation from January 2010 to August 2025 were retrieved. After excluding non-academic papers, a total of 1 568 research papers were included. R language 4.3.0, Bibliometrix package 3.2.1, and Citespace software were used to analyze the number of publications, publishing institutions, authors, keywords and other aspects. Results The number of publications in Journal of Organ Transplantation increased from an average of 82 articles per year in the early years after its inception to 113 articles per year in recent years, a growth of 37.8%. The geographical distribution of publishing institutions covers 32 provinces, cities and autonomous regions nationwide, mainly concentrated in the South China, East China and North China regions, and has now basically covered the central and western regions in recent years. The author collaboration network includes 45 authors distributed across 7 major collaboration clusters, forming a stable multi-level national research system centered on key university-affiliated hospitals. The high-frequency keywords are dominated by "liver transplantation" (425 times) and "kidney transplantation" (396 times). The theme evolution shows a clear three-stage characteristic: initially focusing on clinical technology application, deepening to immune mechanism exploration in the middle stage, and recently (since 2022) focusing on cutting-edge research areas such as xenotransplantation. Conclusions Journal of Organ Transplantation has witnessed the rapid development of China's organ transplantation cause, fully reflecting the research status and trends in China's organ transplantation field, and has provided an important platform for the future development and international cooperation in China's organ transplantation field.

ObjectiveBiochemistry and Molecular Biology, a discipline that elucidates life phenomena at the molecular level, serves as a core foundational course in medical education. It provides the theoretical basis for studying other basic and clinical medical subjects, as well as for understanding pathogenesis, disease diagnosis, and treatment. However, its complex content and highly abstract concepts have posed a dual challenge to traditional teaching models: “inefficient instruction” and “inadequate learning outcomes”. Within limited classroom hours, how to engage students and stimulate their intrinsic motivation, and how to help them recognize, understand, and develop a passion for biochemistry from the perspective of the discipline’s essence, have long been key focuses of curriculum research. MethodsUsing the lipid metabolism chapter as an example, this study employs “Rain Classroom”, a generative artificial intelligence (AI)-assisted platform, to support education in four dimensions: teaching, learning, evaluation, and research. In teaching, it assists instructors through virtual experiments, lesson preparation support, knowledge mapping, and assignment design. For learning, it serves as an intelligent study assistant for students, providing automated assignment review, enabling educational resource sharing, and facilitating personalized learning pathways. In evaluation, the platform automates assignment grading, analyzes student performance data, and offers diagnostic feedback and teaching recommendations. In research, it aids educators in collecting and analyzing teaching data, as well as searching for and summarizing relevant literature. ResultsThe results indicate that an educational model integrating teacher-led instruction, student-centered learning, and generative AI assistance significantly enhances teaching quality, students’ self-directed learning abilities, and knowledge mastery. Furthermore, with the support of generative AI, curriculum-based ideological education—focusing on cutting-edge disciplinary advances and topical medical issues—helps cultivate students’ medical spirit of “honoring life and healing the wounded”, thereby fostering the establishment of appropriate professional values. Finally, while generative AI presents both opportunities and challenges for higher education, this study also analyzes potential risks in its teaching applications, emphasizing the need for both instructors and students to avoid over-reliance and to ensure that technological tools consistently serve the fundamental goals of education. ConclusionThis study demonstrates that integrating generative AI, specifically via the “Rain Classroom” platform, can effectively enhance biochemistry education. By supporting teaching, learning, evaluation, and research, this approach improves both educational effectiveness and student outcomes. It also facilitates the incorporation of cutting-edge knowledge and professional ethics, nurturing a patient-centered mindset. Additionally, the study addresses potential implementation risks to ensure that such technological tools remain aligned with the core purpose of education.

The core pathogenesis of attention deficit hyperactivity disorder （ADHD） lies in deficiency， stasis and stagnation. Deficiency arises from kidney essence depletion and spleen dysfunction in transportation and transformation， leading to inadequate nourishment of the marrow sea. Stasis caused by qi deficiency leads to obstruction in channels and collaterals， resulting in obstructed marrow transport. Stagnation is associated with the excess of the five minds transforming into fire， which scorches the brain orifices and leads to loss of control over marrow utilisation. Based on this， a "supplementation-unblocking-regulation" therapeutic approach is proposed. For deficiency， the focus is on supplementing kidney and fortifying spleen， and replenishing the marrow sea. For stasis， the priority is to unblock and open the orifices， and clear the marrow channels. For stagnation， the core is to clear fire and contain the mind， regulate and restore vital activity. In clinical practice， it is necessary to identify the primary and secondary pathogenic mechanisms and apply dynamic， combined treatment， integrating Chinese herbal medicine， acupuncture， and guiding exercises throughout the process， aiming to provide a reference for the diagnosis and treatment of ADHD with traditional Chinese medical.

BackgroundMonitoring the blood concentrations of antipsychotic drugs and their metabolites can guide the adjustment of clinical treatment plans， improving therapeutic efficacy while reducing adverse effects. However， there is currently a lack of a method that can accurately and efficiently quantitatively detect multiple antipsychotic drugs and their metabolites. ObjectiveTo establish a ultra-high performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS） method for the simultaneous identification and quantitation of 12 antipsychotic drugs and their main metabolites in human serum. MethodsUsing UPLC-MS/MS technology， protein precipitation method was employed for sample pretreatment. An Agela Technologies Durashell C₈ chromatographic column （50 mm×3.0 mm， 5 μm） was selected for chromatographic separation with gradient elution. The flow rate was 0.4 mL/min， and the total analysis time was 5 minutes. The column temperature was 40℃. The mass spectrometry detection was carried out in the multiple reaction monitoring （MRM） mode， and the isotope internal standard method was used for quantification. ResultsThe relative standard deviation （RSD） of the internal standard normalization matrix effect factor for 12 antipsychotic drugs and their main metabolites at low and high quality concentrations was all less than 15%. The extraction recovery rate was 85% to 115%. They showed good linear relationships within their respective standard curve ranges （r>0.995）. At low， medium， and high quality concentrations， the accuracy was 85.24% to 114.71%， and the RSD of intra-batch and inter-batch precision was all ≤14.15%， with good stability. ConclusionAll the analytical performance indicators of this method meet the verification requirements， providing an analytical means for the quantitative detection of antipsychotic drugs and their main metabolites in human serum. ［Funded by The Third Batch of Science and Technology Projects in Chaozhou City in 2023 （number， 202303GY02）］

Background Amid global climate change, extreme environmental events are occurring more frequently, and it is imperative to investigate the impacts of combined exposure to fine particluate matter (PM_2.5) and cold spells (CS) on population mortality. Objective To analyze the association between sequential extreme PM_2.5-cold spell (EP-CS) events and non-accidental mortality among residents in Zigong City from 2016 to 2021. Methods Using time-series study design, meteorological data in Zigong were collected from the Zigong Meteorological Bureau for the period from January 1, 2016 to December 31, 2021, while daily non-accidental mortality data were obtained from the mortality surveillance system of the Zigong Center for Disease Control and Prevention. We adopted the percentile method to define extreme PM_2.5 events and cold spells. We analyzed the risk effect of EP-CS events on non-accidental mortality among residents in this city and explored the potential amplification of damage resulting from different patterns of consecutive extreme events by using distributed lag nonlinear model (DLNM). We also conducted stratified analyses based on age, gender, education level, and marital status. Results The EP-CS events demonstrated a significant impact on non-accidental mortality among the local residents, exhibiting a certain lagged effect. The effects on the overall residents lasted from lag0 (RR=1.030, 95%CI: 1.013, 1.048) to lag14 (RR=1.035, 95%CI: 1.019, 1.052). Notably, the effects were more pronounced among females, individuals aged 65 years and above, and those who were never married, divorced, or widowed. Different patterns of EP-CS events all associated with adverse effects, the health impact of EP-CS events was significantly greater than that of individual PM_2.5 pollution or CS events. The analysis of lag effects across different event patterns revealed that the overall effect of EP-CS events with shorter intervals (0–7 d) had a stronger effect compared to EP-CS with longer intervals (8–14 d), and the RR values of lag14 were 1.034 (95%CI: 1.015, 1.054) and 1.017 (95%CI: 1.007, 1.027), suggesting that the damaging effect of compound events occurring in the short term was more significant. Conclusion All sequential extreme EP-CS events have an impact on non-accidental mortality among residents in this city, with compound events demonstrating a stronger effect. Females, individuals aged ≥65 years, and those who were never married, divorced, or widowed are more sensitive to EP-CS events.

Objective To compare the safety and efficacy of curettage and their combination with uterine artery embolization(UAE)in the treatment of cesarean scar pregnancy(CSP)patients with a low score(≤4)in the ultrasound quantification scoring system.Methods Based on our inclusion and exclusion criteria of this randomized controlled study,the women with CSP who had an ultrasonic quantitative score≤4 and were treated in our department from May 2020 to August 2023 were enrolled,and then randomly divided into a curettage group(n=48)and a UAE combination group(n=47)in a ratio of 1∶1.General information,intraoperative conditions,and use of rescue measures within 3 months after operation were collected in the 2 groups of patients.All the patients were followed up until October 2024 to observe the pregnancy outcomes and determine the impact on the menstrual volume after the resumption of normal menstruation.Results The patients from the both groups completed the follow-up.Except for the maximum gestational sac diameter,there were no significant differences in other baseline data between the 2 groups,and the curettage group had notably more patients having a gestational sac diameter≤25 mm than the combination group[37(77.1%)vs 27(57.4%),P<0.05].No statistical differences were observed between the 2 groups in the intraoperative bleeding volume and use of rescue measures within 3 months after surgery.The combination group had obviously more patients with reduced menstrual volume after the resumption of normal menstruation than the dilation and curettage group[30(63.8%)vs 13(27.1%),P<0.001].There were no statistically differences in pregnancy outcomes and the number of days to resume menstruation between the 2 groups.Conclusion For CSP patients with a score of≤4 in the ultrasound quantification scoring system,curettage show no significant difference in therapeutic effectiveness,and even have better efficacy and safety when compared with curettage combined with UAE.

Objective To construct 5 machine-learning models and compare their performance in predicting the associations between pre-pregnancy socio-psycho-behavioral exposures of both spouses and preconception outcomes.Methods Based on Chongqing Preconception Reproductive Health and Birth Outcome Cohort of volunteers recruited from Chongqing Health Center for Women and Children during January 2019 and March 2022,5 447 couples were recruited and surveyed through interviewer-interview for the demographic and social-psychological-behavioral data of both spouses(221 variables).According to the inclusion and exclusion criteria,4 097 couples were finally included,and randomly assigned into a training set(n=2 867 spouses)and a validation set(n=1 230 spouses)at a ratio of 7∶3.Feature analysis and collinear screening were applied to select the potential exposure factors.In consideration of difficulty to carry out semen parameters analysis in primary healthcare institutions,feature Set 1 including sperm parameters and feature Set 2 excluding semen parameters were constructed by including or excluding sperm quality simultaneously in the training set and the validation set.Five algorithms,that is,Logistic Regression,Naive Bayes,Random Forest,Gradient Boosting Machine,and Support Vector Machine,were used to construct preconception outcome prediction models,and the parameters of each model were optimized using random search combined with grid search.The predictive performance of each model was compared using precision,recall,F1 score,area under the receiver operating characteristic curve(AUC),and calibration curve.The optimal model was then selected by comparing the changes in the predictive ability of the questionnaire data for fertility outcomes with or without semen parameters.Results There were 24 variables screened out in feature Set 1,and 16 variables in feature Set 2.In feature Set 1,the gradient boosting machine performed better,with a relatively higher AUC value(0.651)and better F1 score(0.61).The logistic regression model performed stably(AUC value=0.647)and was suitable as the reference model.The random forest(AUC value=0.641),Naive Bayes(AUC value=0.641),and support vector machine(AUC value=0.634)performed second-best.By utilizing the gradient boosting machine,comparable results were found between the predictions from feature sets with or without semen parameters,as in feature Set 1,the AUC value of its validation set was 0.651(95%CI:0.629～0.681),the prediction accuracy was 0.63,the recall rate was 0.65,and the average precision value F1 was 0.61;and in feature Set 2,the AUC value of its validation set was 0.649(95%CI:0.624～0.663),and both the calibration curves were close to the ideal curve.The prediction results indicated that in feature Set 1,the features highly negatively correlated with preconception outcomes were female age,male age,and no pregnancy within 1 year without contraception,while the features highly positively correlated with preconception outcomes were female pregnancy history,total sperm vitality,and use of contraceptive measures before enrollment.Conclusion Among the 5 machine-learning algorithms performed in this cohort data,the gradient boosting machine shows slightly better performance.There are 24 factors being associated with preconception outcomes in both spouses,and the performance of the simplified model excluding semen parameters is not significantly declined.It is feasible to use machine-learning methods to predict human preconception outcomes through social-psychological-behavioral questionnaires.

Objective To explore the predictive value of fat attenuation index(FAI)and fibrous plaque index(FPI)for the prognosis of patients with acute coronary syndrome(ACS).Methods A retrospective cohort study was conducted on 334 ACS patients undergoing percutaneous coronary intervention(PCI)in the First Affiliated Hospital of Army Military Medical University and Yongchuan Hospital of Chongqing Medical University from March 2021 to July 2023.All patients received coronary computed tomography angiography(CCTA)to measure FAI and FPI.According to the occurrence of major adverse cardiovascular events(MACE)with 1 year of follow-up,they were divided into MACE group(n=108)and non-MACE group(n=226).The baseline data,CCTA data and results of laboratory tests were collected and compared between the 2 groups.Multivariate logistic regression analysis was used to analyze the relationship of FAI and FPI with the prognosis of ACS patients,and ROC curve was drawn to evaluate its predictive efficiency.Results Among the 334 ACS patients,108(32.34%)experienced MACE.When compared with the non-MACE group,the MACE group exhibited significantly larger proportions of diabetes(72.22%vs 31.86%)and left main coronary artery disease(18.52%vs 7.08%),but lower success rate of operation(79.63%vs 93.81%,P<0.05).Radiologic results showed that the proportion of severe stenosis(20.37%vs 10.62%),FAI(-80.12±6.41 HU vs-72.34±7.09 HU)and FPI(0.58±0.41 vs 0.26±0.12)were obviously increased in the MACE group than the non-MACE group(P<0.05).Laboratory tests indicated that there were statistical differences between the 2 groups in high-density lipoprotein-cholesterol(HDL-C,1.20±0.15 vs 1.09±0.16 mmol/L),miR-126(0.91±0.12 vs 0.96±0.15)and SST2(38.45±5.67 vs 34.30±4.89 ng/mL,P<0.05).Multivariate Logistic regression analysis revealed that FAI(OR=1.200,95%CI:1.136～1.268),FPI(OR=63.157,95%CI:14.126～282.374),moderate stenosis(OR=1.332,95%CI:1.024～1.859),severe stenosis(OR=1.480,95%CI:1.074～2.039),miR-126(OR=0.007,95%CI:0.001～0.077),and sST2(OR=1.192,95%CI:1.113～1.277)were independent predictors of MACE(P<0.05).ROC curve analysis displayed that stenosis degree(AUC=0.622,95%CI:0.561～0.683,P=0.001),FAI(AUC=0.790,95%CI:0.741～0.839,P=0.001)and FPI(AUC=0.700,95%CI:0.638～0.761,P=0.001),miR-126(AUC=0.646,95%CI:0.584～0.707,P=0.001),sST2(AUC=0.700,95%CI:0.638～0.761,P=0.001)had certain predictive values for ACS prognosis.Conclusion Coronary FAI and FPI can be used as independent prognostic indicators of ACS patients,and their numerical changes are closely related to plaque stability and inflammatory state.