Objective To systematically evaluate the effectiveness and acceptability of antidepressant drugs in the treatment of postpartum depression(PPD).Methods The PubMed,Cochrane Library,Embase,Web of Science,China National Knowledge Infrastructure(CNKI),Wanfang Database,VIP Journals of Chinese Scienc were searched,and Chinese Biomedical Literature Service System(SinoMed)database until November 2023.Screen randomized controlled trials(RCTs)of antidepressant drugs for the treatment of PPD.The treatment group was given antidepressant drugs,and the control group was given placebo or another antidepressant drug.Meta-analysis of effectiveness and acceptability is performed using Stata 17.0 software.Results A total of 27 RCTs with a total of 2 202 patients were included.The results of meta-analysis showed:The top three efficacy relative to placebo were mirtazapine[odds ratio(OR)=2.25,95％confidence interval(CI)=(1.20-3.30),P＜0.05],nortriptyline[OR=1.50,95％CI=(0.55-2.44),P＞0.05],venlafaxine[OR=1.35,95％CI=(0.13-2.56),P＞0.05].Acceptability is compared with placebo in the top three Chinese herbal medicine[OR=0.47,95％CI=(-0.72-1.66),P＞0.05],nortriptyline[OR=-0.08,95％CI=(-1.16-1.33),P＞0.05],venlafaxine[OR=-0.12,95％CI=(-1.47-1.24),P＞0.05].Conclusion Nortriptyline,venlafaxine,trazodone,and duloxetine are effective in treating PPD without obvious adverse drug reactions.

Transformer models have emerged as pivotal tools within the realm of drug discovery,distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes.Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data,these models showcase remarkable efficacy across various tasks,including new drug design and drug target identification.The adaptability of pre-trained trans-former-based models renders them indispensable assets for driving data-centric advancements in drug discovery,chemistry,and biology,furnishing a robust framework that expedites innovation and dis-covery within these domains.Beyond their technical prowess,the success of transformer-based models in drug discovery,chemistry,and biology extends to their interdisciplinary potential,seamlessly combining biological,physical,chemical,and pharmacological insights to bridge gaps across diverse disciplines.This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields.In our review,we elucidate the myriad applications of transformers in drug discovery,as well as chemistry and biology,spanning from protein design and protein engineering,to molecular dynamics(MD),drug target iden-tification,transformer-enabled drug virtual screening(VS),drug lead optimization,drug addiction,small data set challenges,chemical and biological image analysis,chemical language understanding,and single cell data.Finally,we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

OBJECTIVE: This study aimed to evaluate the association between susceptibility genes and non-alcoholic fatty liver disease (NAFLD) in children with obesity. METHODS: We conducted a two-step case-control study. Ninety-three participants were subjected to whole-exome sequencing (exploratory set). Differential genes identified in the small sample were validated in 1,022 participants using multiplex polymerase chain reaction and high-throughput sequencing (validation set). RESULTS: In the exploratory set, 14 genes from the NAFLD-associated pathways were identified. In the validation set, after adjusting for sex, age, and body mass index, ECI2 rs2326408 (dominant model: OR = 1.33, 95% CI: 1.02-1.72; additive model: OR = 1.22, 95% CI: 1.01-1.47), C6orf201 rs659305 (dominant model: OR = 1.30, 95% CI: 1.01-1.69; additive model: OR = 1.21, 95% CI: 1.00-1.45), CALML5 rs10904516 (pre-ad dominant model: OR = 1.36, 95% CI: 1.01-1.83; adjusted dominant model: OR = 1.40, 95% CI: 1.03-1.91; and pre-ad additive model: OR = 1.26, 95% CI: 1.04-1.66) polymorphisms were significantly associated with NAFLD in children with obesity ( P < 0.05). Interaction analysis revealed that the gene-gene interaction model of CALML5 rs10904516, COX11 rs17209882, and SCD5 rs3733228 was optional ( P < 0.05), demonstrating a negative interaction between the three genes. CONCLUSION In the Chinese population, the CALML5 rs10904516, C6orf201 rs659305, and ECI2 rs2326408 variants could be genetic markers for NAFLD susceptibility.
Humans ; Non-alcoholic Fatty Liver Disease/genetics* ; Child ; Male ; Female ; Genetic Predisposition to Disease ; Case-Control Studies ; Exome Sequencing ; Adolescent ; Polymorphism, Single Nucleotide ; Obesity/complications* ; Pediatric Obesity/complications* ; China

Objective To investigate the protective effects of Qiji Special Dietary Food on exercise-induced myocardial injury in mice.Methods An exercise-induced myocardial injury model was established using a treadmill running protocol,and at the same time,the modeled mice were administered Qiji Special Dietary Food via oral gavage,followed by a 4-week treadmill exhaustion test.Serum levels of cardiac troponin T(cTnT),creatine kinase(CK),and lactate dehydrogenase(LDH)were measured.Myocardial tissues were analyzed for superoxide dismutase(SOD)activity and malondialdehyde(MDA)content.Histopathological alterations and ultrastructural changes in myocardial tissue were evaluated using light microscopy and transmission electron microscopy(TEM).Results After 4 weeks of exhaustive training,compared to the control group,the model group exhibited significantly elevated serum cTnT,CK,and myocardial MDA levels(P<0.01),along with reduced myocardial SOD activity(P<0.01).Compared to the model group,high-,medium-,and low-dose treatment significantly attenuated the exhaustive exercise-induced increases in serum cTnT level and myocardial MDA content(P<0.01),restoring these indicators to the levels comparable to those of the normal control group(P<0.05).Additionally,all treatment groups had markedly increased myocardial SOD activity,with no significant difference from the normal group.Histopathological and ultrastructural analyses revealed markedly alleviated myocardial damage in the treatment groups,with the medium-dose group exhibiting the most pronounced protective effects.Conclusion Qiji Special Dietary Food demonstrates significant protective effects against exercise-induced myocardial injury in mice,which maybe associated with its antioxidant activity and mitigation of oxidative stress.

Transformer models have emerged as pivotal tools within the realm of drug discovery, distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes. Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data, these models showcase remarkable efficacy across various tasks, including new drug design and drug target identification. The adaptability of pre-trained transformer-based models renders them indispensable assets for driving data-centric advancements in drug discovery, chemistry, and biology, furnishing a robust framework that expedites innovation and discovery within these domains. Beyond their technical prowess, the success of transformer-based models in drug discovery, chemistry, and biology extends to their interdisciplinary potential, seamlessly combining biological, physical, chemical, and pharmacological insights to bridge gaps across diverse disciplines. This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields. In our review, we elucidate the myriad applications of transformers in drug discovery, as well as chemistry and biology, spanning from protein design and protein engineering, to molecular dynamics (MD), drug target identification, transformer-enabled drug virtual screening (VS), drug lead optimization, drug addiction, small data set challenges, chemical and biological image analysis, chemical language understanding, and single cell data. Finally, we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

Objective To propose a lead attention network-based ST-T change recognition algorithm to detect ECG ST-T changes accurately.Methods Firstly,heartbeat signals were extracted through R-wave localization,and a 12-lead heartbeat matrix was generated by correlation-based screening and merging to realize data augmentation.Secondly,a lead attention module was constructed by combining depthwise convolution(DWConv)with the channel attention squeeze-and-excitation block(SE-block)structure to perceive the differences in ST-T status among electrocardiogram leads.Thirdly,the mapping output by two independent attention modules was fused and splicing with the original signal residual was carried out,so that attention information extraction and original information transfer were enhanced effectively.Finally,SE-ResNet was used as the backbone network to extract signal features to complete the classification and identification of ST-T changes.To validate the recognition performance of the proposed algorithm for ST-T changes in ECG,the 12-lead ECG data of 97 472 patients containing different ECG rhythms were collected for ablation and comparison experiments at the First Affiliated Hospital of Army Medical University.Results The proposed algorithm achieved an AUC of 0.965 with a sensitivity of 90.51%,specificity of 90.23%,positive predictive value of 89.24%and overall accuracy of 90.36%on an independent test set.Comparative analysis demonstrated superior performance to four benchmark architectures,including VGG16,ResNet18,MobileNetV3-Small and ShuffleNet,in terms of both classification accuracy and computational efficiency.Conclusion The algorithm designed can accurately detect ST-T changes and can be used for wearable ECG automatic analysis to assist in the early warning of cardiovascular diseases in both acute and chronic patients and highland residents.[Chinese Medical Equipment Journal,2025,46(7):1-11]

Objective To systematically evaluate the effectiveness and acceptability of antidepressant drugs in the treatment of postpartum depression(PPD).Methods The PubMed,Cochrane Library,Embase,Web of Science,China National Knowledge Infrastructure(CNKI),Wanfang Database,VIP Journals of Chinese Scienc were searched,and Chinese Biomedical Literature Service System(SinoMed)database until November 2023.Screen randomized controlled trials(RCTs)of antidepressant drugs for the treatment of PPD.The treatment group was given antidepressant drugs,and the control group was given placebo or another antidepressant drug.Meta-analysis of effectiveness and acceptability is performed using Stata 17.0 software.Results A total of 27 RCTs with a total of 2 202 patients were included.The results of meta-analysis showed:The top three efficacy relative to placebo were mirtazapine[odds ratio(OR)=2.25,95％confidence interval(CI)=(1.20-3.30),P＜0.05],nortriptyline[OR=1.50,95％CI=(0.55-2.44),P＞0.05],venlafaxine[OR=1.35,95％CI=(0.13-2.56),P＞0.05].Acceptability is compared with placebo in the top three Chinese herbal medicine[OR=0.47,95％CI=(-0.72-1.66),P＞0.05],nortriptyline[OR=-0.08,95％CI=(-1.16-1.33),P＞0.05],venlafaxine[OR=-0.12,95％CI=(-1.47-1.24),P＞0.05].Conclusion Nortriptyline,venlafaxine,trazodone,and duloxetine are effective in treating PPD without obvious adverse drug reactions.

Objective To propose a lead attention network-based ST-T change recognition algorithm to detect ECG ST-T changes accurately.Methods Firstly,heartbeat signals were extracted through R-wave localization,and a 12-lead heartbeat matrix was generated by correlation-based screening and merging to realize data augmentation.Secondly,a lead attention module was constructed by combining depthwise convolution(DWConv)with the channel attention squeeze-and-excitation block(SE-block)structure to perceive the differences in ST-T status among electrocardiogram leads.Thirdly,the mapping output by two independent attention modules was fused and splicing with the original signal residual was carried out,so that attention information extraction and original information transfer were enhanced effectively.Finally,SE-ResNet was used as the backbone network to extract signal features to complete the classification and identification of ST-T changes.To validate the recognition performance of the proposed algorithm for ST-T changes in ECG,the 12-lead ECG data of 97 472 patients containing different ECG rhythms were collected for ablation and comparison experiments at the First Affiliated Hospital of Army Medical University.Results The proposed algorithm achieved an AUC of 0.965 with a sensitivity of 90.51%,specificity of 90.23%,positive predictive value of 89.24%and overall accuracy of 90.36%on an independent test set.Comparative analysis demonstrated superior performance to four benchmark architectures,including VGG16,ResNet18,MobileNetV3-Small and ShuffleNet,in terms of both classification accuracy and computational efficiency.Conclusion The algorithm designed can accurately detect ST-T changes and can be used for wearable ECG automatic analysis to assist in the early warning of cardiovascular diseases in both acute and chronic patients and highland residents.[Chinese Medical Equipment Journal,2025,46(7):1-11]

Objective:To investigate the effect of single nucleotide polymorphism (SNP) of FCN gene on the susceptibility of pre-eclampsia (PE) in Han nationality pregnant women.Methods:A total of 274 PE pregnant women (PE group) and 154 healthy pregnant women (control group) admitted to Boai Hospital of Zhongshan, Affiliated Hospital to Southern Medical University from October 2020 to October 2022 were collected. The general information, medical history, reproductive history, blood pressure, body mass index and blood biochemical indicators before delivery were compared between the two groups. Twenty-three SNP loci of FCN gene family were genotyped by time-of-flight mass spectrometry, and the serum levels of ficolins (ficolin-1, -2 and -3) were detected by enzyme-linked immunosorbent assay.Results:(1) Compared with the control group, the body mass index, mean arterial pressure, gestational age at delivery, blood urea nitrogen, alanine aminotransferase, aspartate aminotransferase, direct bilirubin, albumin, and C-reactive protein in the PE group were significantly higher than those in the control group (all P<0.05). The levels of N-terminal pro-B type natriuretic peptide (NT-proBNP), placental growth factor (PlGF) and human soluble vascular endothelial growth factor receptor-1 (sFlt-1) were significantly different between the two groups (all P<0.05). (2) Among the 23 SNP loci in FCN gene family, 18 loci were in Hardy-Weinberg genetic equilibrium, including 5 loci in FCN1 gene, 10 loci in FCN2 gene, and 3 loci in FCN3 gene. Five loci that did not conform to Hardy-Weinberg genetic equilibrium were not included in the subsequent analysis. Compared with the control group, the genotype distribution of 3 loci of FCN2 gene (rs7872508, rs11103563, rs73664188) and 1 locus of FCN3 gene (rs3813800) in the PE group were significantly different (all P<0.05). After Bonferroni correction, only the genotype distribution of rs7872508 and rs73664188 in FCN2 gene were statistically different between the PE group and the control group (all P<0.05). Further analysis showed that for the rs7872508 locus of FCN2 gene, compared with GG genotype, genotype GT ( OR=3.025, 95% CI: 1.080-8.471) and TT ( OR=4.777, 95% CI: 1.758-12.979) both significantly increased the risk of PE (both P<0.05). For rs73664188 locus of FCN2 gene, compared with TT genotype, genotype TC ( OR=0.510, 95% CI: 0.334-0.778) significantly reduced the risk of PE ( P<0.05). (3) Compared with the control group, the serum levels of ficolin-1 and ficolin-2 in pregnant women in the PE group were significantly reduced (both P<0.05), while the level of ficolin-3 showed no significant change ( P=0.271). Correlation analysis showed that the serum levels of ficolin-2 in pregnant women in the PE group were significantly positively correlated with PlGF level ( r=0.321, P<0.001), and significantly negatively correlated with sFlt-1 level ( r=-0.187, P=0.002) and NT-proBNP level ( r=-0.392, P<0.001). Further analysis revealed that the serum levels of ficolin-2 in pregnant women of the PE group with GT and TT genotypes at rs7872508 locus of FCN2 gene were significantly reduced (both P<0.05), while the serum level of ficolin-2 in pregnant women of the PE group with TC genotype at the rs73664188 locus were significantly increased ( P<0.05). Conclusion:The SNP of FCN2 gene in FCN gene family might be related to the susceptibility to PE and have an effect on serum ficolin-2 level in PE pregnant women.

Objective:To analyze clinical, immunopathological, therapeutic, and prognostic features of epidermolysis bullosa acquisita (EBA) .Methods:A retrospective study was conducted on patients with confirmed EBA at the Department of Dermatology, West China Hospital, Sichuan University from January 1, 2015 to July 30, 2022. Their clinical, immunopathological, therapeutic and prognostic features were analyzed. The autoimmune bullous skin disorder intensity score (ABSIS) was used to assess the severity of lesions in patients with EBA, and the visual analogue scale (VAS) to assess itch intensity. Descriptive statistical analysis was primarily carried out, and the correlation between disease severity scores and itch scores was analyzed using Pearson correlation analysis.Results:A total of 13 patients with EBA were included, including 9 males and 4 females, with the age at the clinic visit being 49.0 ± 20.6 years and ABSIS scores being 24.2 ± 10.7 points. One patient was diagnosed with classical EBA, while the remaining 12 patients with inflammatory EBA. Mucosal involvement was observed in 6 cases, whose oral mucosae were all affected. All patients had itching to varying degrees, with VAS scores of 5.6 ± 2.2 points; 9 of the 12 inflammatory EBA patients had VAS scores of ≥ 5 points, whereas 1 classical EBA patient had a VAS score of 2 points; there was no significant correlation between the ABSIS scores and VAS scores ( r = -0.02, P > 0.05). Histopathological examination showed subepidermal cleavages or blister formation and varying degrees of perivascular inflammatory cell infiltration in the superficial dermis of patients with inflammatory EBA. Direct immunofluorescence assay demonstrated linear IgG deposits along the basement membrane zone in all 13 patients, including 12 with concomitant linear C3 deposits in the basement membrane zone, 5 with linear IgA deposits, and 2 with IgM deposits. Indirect immunofluorescence on salt-split skin showed IgG deposition on the dermal side of the salt-split skin in the 13 patients. An elevated eosinophil count in the peripheral blood was observed in 1 out of 11 patients, while increased total IgE levels were noted in 3 out of 9 patients. Among the 13 EBA patients, 11 were treated with systemic glucocorticoids (equivalent to 10 - 100 mg/d of prednisone), and the other 2 were treated with compound glycyrrhizin tablets, sulfasalazine, hydroxychloroquine sulfate, and minocycline hydrochloride alone or in combination. During the follow-up period of 34.0 (27.5, 66.0) months in the 13 patients, 8 achieved complete remission after drug withdrawal, 2 achieved complete remission on therapy, 1 achieved partial remission on minimal therapy, and 2 presented with uncontrolled condition. The time to complete remission off/on therapy was 6.0 (3.8, 17.5) months. Conclusions:The inflammatory phenotype seems to be relatively common in EBA patients, with itching to varying degrees, and oral mucosa was the most commonly involved mucosa in those with mucosal damage. After treatment with systemic glucocorticoids alone or in combination with immunomodulators, most patients could achieve complete remission.