OBJECTIVE To construct three-class （insufficient， normal， excessive） and two-class （insufficient， normal） models for predicting plasma concentration of valproic acid （VPA）， and compare the performance of these two models， with the aim of providing a reference for formulating clinical medication strategies. METHODS The clinical data of 480 patients who received VPA treatment and underwent blood concentration test at the Xi’an International Medical Center Hospital were collected from November 2022 to September 2024 （a total of 695 sets of data）. In this study， predictive models were constructed for target variables of three-class and two-class models. Feature ranking and selection were carried out using XGBoost scores. Twelve different machine learning algorithms were used for training and validation， and the performance of the models was evaluated using three indexes: accuracy， F1 score， and the area under the working characteristic curve of the subject （AUC）. RESULTS XGBoost feature importance scores revealed that in the three-class model， the importance ranking of kidney disease and electrolyte disorders was higher. However， in the two-class model， the importance ranking of these features significantly decreased， suggesting a close association with the excessive blood concentration of VPA. In the three-class model， Random Forest method performed best， with F1 score of 0.704 0 and AUC of 0.519 3 on the test set； while in the two-class model， CatBoost method performed optimally， with F1 score of 0.785 7 and AUC of 0.819 5 on the test set. CONCLUSIONS The constructed three-class model has the ability to predict excessive VPA blood concentration， but its prediction and model generalization abilities are poor； the constructed two-class model can only perform classification prediction for insufficient and normal blood concentration cases， but its model performance is stronger.

Objective: To investigate the association of serum alanine aminotransferase (ALT) with left ventricular hypertrophy (LVH) in adolescents, and to provide scientific evidence for the early screening and intervention strategy of cardiac structure damage. Methods: Data were obtained from the third follow up survey (October 2023) of the "Huantai Childhood Cardiovascular Health Cohort Study", including 1 156 healthy adolescents aged 12-17 with complete information. The sample population was stratified into low ( Q 1 group), medium ( Q 2 group), and high ( Q 3 group) ALT levels based on tertiles within the same gender and age groups. Inter group comparisons were conducted using analysis of variance and trend test. A multivariate Logistic regression model was used to analyze the association between ALT levels and LVH, and stratified analyses were performed by gender and age groups. Results: With the increase of ALT quantile level, the detection rate of LVH showed an increasing trend ( Q 1: 3.7%; Q 2: 10.6%; Q 3: 16.7%, Z= 5.89 , P <0.01). After adjusting for potential covariates, compared with the ALT group ( Q 1), the group ( Q 3) increased the risk of developing LVH in adolescents ( OR=2.09, 95%CI =1.21-4.12). Stratified analyses by age and sex showed a significant association only in boys and younger individuals aged 12 to 14 years [ OR (95% CI ) were 2.64(1.04-7.67) and 3.24( 1.35 -9.06), both P <0.05)]. Conclusion Elevated serum ALT levels are associated with an increased risk of LVH in adolescents, and early detection and control of abnormal liver enzyme levels can help reduce early vascular structural damage and prevent adverse cardiovascular events.

Objective: To map the research hotspots, developmental trends, and existing challenges in the integration of artificial intelligence (AI) with multi-omics in traditional Chinese medicine (TCM) through comprehensive bibliometric analysis. Methods: China National Knowledge Infrastructure (CNKI), Wanfang Data, China Science and Technology Journal Database (VIP), Chaoxing Journal Database, PubMed, and Web of Science were searched to collect literature on the theme of AI in TCM multi-omics research from the inception of each database to December 31, 2024. Eligible records were required to simultaneously address AI, TCM, and multi-omics. Quantitative and visual analyses of publication growth, core authorship networks, institutional collaboration patterns, and keyword co-occurrence were performed using Microsoft Excel 2021, NoteExpress v4.0.0, and Cite Space 6.3.R1. AI application modes in TCM multi-omics research were also categorized and summarized. Results: A total of 1 106 articles were enrolled (932 Chinese and 174 English). Publication output has increased continuously since 2010 and accelerated after 2016. Region-specific collaboration clusters were identified, dominated by Beijing University of Chinese Medicine, China Academy of Chinese Medical Sciences, Shanghai University of Traditional Chinese Medicine, and Nanjing University of Chinese Medicine. Keyword co-occurrence analysis revealed that current AI applications predominantly centered on metabolomics and algorithms such as cluster analysis and data mining. Research foci mainly ranked as follows: single herbs, herbal formulae, and disease-syndrome differentiation. Conclusion Machine learning methods are the predominant integrative modality of AI in the realm of TCM multi-omics research at present, utilized for processing omics data and uncovering latent patterns therein. The domain of TCM, in addition to investigating omics information procured through high-throughput technologies, also integrates data on traditional Chinese medicinal substances and clinical phenotypes, progressing towards joint analysis of multi-omics, high-dimensionality of data, and multi-modality of information. Deep learning approaches represent an emerging trend in the field.

Background::The association and its population heterogeneities between low-density lipoprotein cholesterol (LDL-C) and all-cause and cardiovascular mortality remain unknown. We aimed to examine the dose-dependent associations of LDL-C levels with specific types of cardiovascular disease (CVD) mortality and heterogeneities in the associations among different population subgroups.Methods::A total of 2,968,462 participants aged 35-75 years from China Health Evaluation And risk Reduction through nationwide Teamwork (ChinaHEART) (2014-2019) were included. Cox proportional hazard models and Fine-Gray subdistribution hazard models were used to estimate associations between LDL-C categories (<70.0, 70.0-99.9, 100.0-129.9 [reference group], 130.0-159.9, 160.0-189.9, and ≥190.0 mg/dL) and all-cause and cause-specific mortality.Results::During a median follow-up of 3.7 years, 57,391 and 23,241 deaths from all-cause and overall CVD were documented. We observed J-shaped associations between LDL-C and death from all-cause, overall CVD, coronary heart disease (CHD), and ischemic stroke, and an L-shaped association between LDL-C and hemorrhagic stroke (HS) mortality ( P for non-linearity <0.001). Compared with the reference group (100.0-129.9 mg/dL), very low LDL-C levels (<70.0 mg/dL) were significantly associated with increased risk of overall CVD (hazard ratio [HR]: 1.10, 95% confidence interval [CI]: 1.06-1.14) and HS mortality (HR: 1.37, 95% CI: 1.29-1.45). Very high LDL-C levels (≥190.0 mg/dL) were associated with increased risk of overall CVD (HR: 1.51, 95% CI: 1.40-1.62) and CHD mortality (HR: 2.08, 95% CI: 1.92-2.24). The stronger associations of very low LDL-C with risk of CVD mortality were observed in individuals with older age, low or normal body mass index, low or moderate 10-year atherosclerotic CVD risk, and those without diagnosed CVD or taking statins. Stronger associations between very high LDL-C levels and all-cause and CVD mortality were observed in younger people. Conclusions::People with very low LDL-C had a higher risk of all-cause, CVD, and HS mortality; those with very high LDL-C had a higher risk of all-cause, CVD, and CHD mortality. On the basis of our findings, comprehensive health assessment is needed to evaluate cardiovascular risk and implement appropriate lipid-lowering therapy for people with very low LDL-C.

Aim To investigate the protective effect of berberine(BBR)on mice with unilateral ureteral obstr-uction(UUO)and explore its mechanism.Methods C57BL/6 mice were randomly divided into the sham group,UUO group,and BBR treatment groups(50,100 and 200 mg·kg-1),with eight mice in each group.Except the sham group,the other groups were subjected to left ureteral ligation to establish the UUO model.Af-ter modeling,the mice in the sham and UUO groups were fed normal saline,and the mice in the BBR treat-ment groups were fed(50,100,200)mg·kg-1 BBR by gavage for 14 days,respectively.Biochemical analy-zer was employed to detect the levels of serum creati-nine(Scr)and blood urea nitrogen(BUN).HE,Mas-son,TUNEL and immunohistochemical staining were used to observe the pathological changes of renal tis-sue.ELISA was employed to detect the expression of pro-inflammatory cytokines in renal tissue homogenate.Western blot was used to detect the protein levels of NF-κB p65,TGF-β1 and CTGF in mouse kidney.Re-sults Compared with the UUO group,the levels of Scr and BUN in the BBR group were significantly reduced.Renal injury and interstitial fibrosis were alleviated.The expression of pro-inflammatory cytokines decreased in kidney.The expression of NF-κB p65,TGF-β1 and CTGF decreased.All results showed some degree of dose dependence.Conclusion Berberine has a sig-nificant protective effect on unilateral ureteral obstruc-tion mice,and the mechanism may be that BBR has the potential to inhibit NF-κB p65/TGF-β1/CTGF signa-ling pathway,thus reducing renal inflammation and fi-brosis.

Aim To study the role of norepinephrine in regulating cancer-associated fibroblasts to promote the proliferation and migration of lung cancer cells.Meth-ods Primary cancer-associated fibroblasts and lung cancer A549 cells were cultured.RT-PCR and West-ern blotting were used to detect the expression of VEGF,IL-6 and IL-8 in cancer-associated fibroblasts after norepinephrine intervention,and the effect of nor-epinephrine on the expression of E-cadherin and vim-entin in co-cultured CAFs and lung cancer A549 cells were evaluated,and scratching experiments were used to verify that norepinephrine promoted the migration of lung cancer A549 cells.Results Norepinephrine in-duced the high expression of VEGF,IL-8 and IL-6 in CAFs cells in a concentration-dependent manner.β-adrenergic inhibitor(propranol)could inhibit the ex-pression of VEGF,IL-8 and IL-6 in CAFs cells.Norep-inephrine could inhibit the expression of E-cadherin in lung cancer A549 cells co-cultured with CAFs,promote the upregulation of vimentin,and enhance the migration ability of A549 cells.Conclusion Norepinephrine promotes the proliferation and migration of lung cancer A549 cells through CAFs.

Objective We aimed to compare the efficacy and prognosis of percutaneous coronary intervention(PCI)in complex and high-risk patients with coronary heart disease(CHD)treated with extracorporeal membrane oxygenation(ECMO)combined with intra-aortic balloon pump(IABP)assistance,and explore the application value of combined use of mechanical circulatory support(MCS)devices in complex PCI.Methods A total of patients who met the inclusion criteria and underwent selective PCI supported by MCS at the Department of Cardiology,the First Affiliated Hospital of the Air Force Medical University from January 2018 to December 2022 were continuously enrolled.According to the mechanical circulatory support method,the patients were divided into ECMO+IABP group and IABP group.Clinical characteristics,angiographic features,in-hospital outcomes,and complications were collected.The intra-hospital outcomes and major adverse cardiovascular events(MACE)at one month and one year after the procedure were observed.The differences and independent risk factors between the two groups in the above indicators were analyzed.Results A total of 218 patients undergoing elective PCI were included,of which 66 patients were in the ECMO+IABP group and 152 patients were in the IABP group.The baseline characteristics of the two groups of patients were generally comparable,but the ECMO+IABP group had more complex lesion characteristics.The proportion of patients with atrial fibrillation(6.1％vs.0.7％,P=0.030),left main disease(43.9％vs.27.0％,P=0.018),triple vessel disease(90.9％vs.75.5％,P=0.009),and RCA chronic total occlusion disease(60.6％vs.35.5％,P＜0.001)was higher in the ECMO+IABP group compared to the IABP group.The proportion of patients with previous PCI history was higher in the IABP group(32.9％vs.16.7％,P=0.014).There was no statistically significant difference in the incidence of in-hospital complications between the two groups(P=0.176),but the incidence of hypotension after PCI was higher in the ECMO+IABP group(19.7％vs.9.2％,P=0.031).The rates of 1-month MACE(4.5％vs.2.6％,P=0.435)and 1-year MACE(7.6％vs.7.9％,P=0.936)were comparable between the two groups.Multivariate analysis showed that in-hospital cardiac arrest(OR 7.17,95％CI 1.27-40.38,P=0.025)and after procedure hypotension(OR 3.60,95％CI 1.10-11.83,P=0.035)were independent risk factors for the occurrence of 1-year MACE.Conclusions Combination use of ECMO+IABP support can provide complex and high-risk coronary heart disease patients with an opportunity to achieve coronary artery revascularization through PCI,and achieve satisfactory long-term prognosis.

Objective:To explore the effects of repeated transcranial magnetic stimulation(rTMS)at different stimulating sessions on upper limb motor function and brain functional connectivity in stroke patients,targeting on stimu-late the contralateral premotor cortex(PMC). Method:Sixty patients with upper limb motor dysfunction after ischemic stroke were randomly assigned to 6-week rTMS group,4-week rTMS group,2-week rTMS group or control group,each with 15 participants.Up-per limb Brunnstrom stage,Fugl-Meyer assessment for upper extremity(FMA-UE)and Wolf motor function test(WMFT)were assessed before and after treatment to evaluate behavioral outcomes.The functional connec-tivity was analyzed by resting state functional magnetic resonance imaging(rs-fMRI)with the contralateral PMC as the seed point. Result:After treatment,the FMA-UE and WMFT scores of the 2-week rTMS group were significantly differ-ent from those of the 4-week and 6-week rTMS groups(P＜0.05),but there was no significant difference be-tween the 4-week rTMS group and the 6-week rTMS group(P＞0.05).Functional connectivity analysis using contralateral PMC as a seed point showed that functional connections were enhanced between contralateral PMC and ipsilateral anterior central gyrus,as well as the contralateral middle temporal gyrus and precuneus af-ter rTMS treatment(P＜0.05). Conclusion:The 4-week rTMS group has the best duration-benefit compared with the 2-week rTMS group and the 6-week rTMS group.The probable mechanism was related to that rTMS treatment could reduce the ef-fect of interhemispheric inhibition on motor cortex,and then enhance the cortico-cortical functional connectivi-ty in the contralateral hemisphere effectively,resulting in the recovery of upper limb motor function.

This work was aimed at predicting and verifying B-cell epitopes of SARS-CoV-2 E protein through bioinformatics methods,and clarifying the dominant B cell epitopes with mouse polyclonal antibody serum prepared through SARS-CoV-2 re-combinant E protein immunization and human positive serum vaccinated with inactivated SARS-CoV-2 vaccine.The structural and B-cell linear epitopes of SARS-CoV-2 E protein were predicted with SOPMA,Expasy,SWISS-MODEL,IEDB database,and Bepid-2.0 software.Candidate epitopes were expressed as GST-tagged recombinant protein fragments in an E.coli sys-tem,and their immunoreactivity with mouse and human poly-clonal positive serum against SARS-CoV-2 E protein was de-tected by western blotting and indirect ELISA,respectively.The epitope prediction results showed that E protein contained linear B cell epitopes Ser6-Val14 and Tyr57-Pro71,and the conformational epitopes of Glu8-Val12,Leu39-Tyr59,and Ser60-Leu65.The GST tagged recombinant E protein fragments of E1 and E3,containing Ser6-Val14 and Tyr57-Pro71 epitopes,respectively,as well as E2 without an epitope sequence as a control,were expressed in an E.coli expression system and successfully purified with an Ni-NTA column.Western blotting and indirect ELISA analysis indicated that all mouse and human SARS-CoV-2 positive sera positively reacted with only E1 and E3 proteins,but negatively reacted with E2 protein,thus indicating that the corresponding epitope prediction with Ser6-Val14 and Tyr57-Pro71 was correct.This study successfully predicted and preliminarily identified two linear B cell epitopes of SARS-CoV-2 E protein,thus providing a reference for the preparation of new coronavirus vaccines and the analysis of immune response characteristics.

Heterotypic cell-in-cell structures(heCICs)mediate unique non-autonomous cell death,which are widely involved in a variety of important pathological processes,such as tumorigenesis,pro-gression and clinical prognosis.Methylenetetrahydrofolata dehydrogenase 2(MTHFD2),one of the key enzymes of one-carbon metabolism,is highly expressed in a variety of tumor cells.In this study,in order to investigate the effect of MTHFD2 on the formation of heCICs,liver cancer cells and immune cells were first labeled separately by live cell dyes,and the heCIC model was established by using fluorescence mi-croscopy for cell imaging and analysis.After transiently knocking down MTHFD2 in cells by RNAi,we found that the ability of PLC/PRF/5 and Hep3B to form heCICs with immune cells was significantly in-creased(all P＜0.01).MTHFD2 recombinant expression plasmid was constructed by the homologous re-combination method,and MTHFD2 overexpression cell lines were further constructed.Then,the effect of MTHFD2 overexpression on the ability to form heCICs was detected by co-culturing the overexpression cell lines with immune cells.The results showed that the rate of heCIC formation was significantly re-duced after overexpression of MTHFD2(all P＜0.001).In conclusion,this study demonstrated that MTHFD2 is a negative regulator of heCIC formation,providing a research basis for targeting MTHFD2 to promote heCIC formation and enhance the in-cell killing of immune cells.