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 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.

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: 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 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 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.

2-(4-Methylthiazol-5-yl) ethyl nitrate hydrochloride (W1302) is a nitro containing derivative of clomethiazole, which is a novel neuroprotective agent with both carbon monoxide (NO) donor and weak γ-aminobutyric acid type A (GABA_A) receptor allosteric regulatory excitatory effect. The current study used a rat model of transient middle cerebral arteryocclusion (tMCAO) brain injury to evaluate the therapeutic effect of W1302 on ischemic stroke and explore its potential mechanisms of action. This experiment has been reviewed and approved by the Laboratory Animal Management and Use Committee of the Institute of Materia Medica, Chinese Academy of Medical Sciences (ethical review forms No. 620, 632, 5013). The results showed that gavage administration of 1, 3, and 10 mg·kg^-1 of W1302 can significantly reduce the volume of cerebral infarction in rats with ischemia for 2 h and reperfusion for 24 h, and the therapeutic effect was better than that of 200 mg·kg^-1 of DL-3n-butylphthalide. W1302 significantly increased NO levels in blood and brain tissue. It increased cerebral blood flow and brain adenosine triphosphate (ATP) content after reperfusion, as well as, inhibited the expressions of inflammatory factors tumor necrosis factor-α (TNF-α) and interleukin-1β (IL-1β) in brain tissue. The time window of W1302 was between 120-180 min after ischemia. These research results demonstrated that W1302 could increase NO release, dilate blood vessels, and increase cerebral blood flow, improve energy supply to brain tissue and increase ATP levels, and inhibit neuro-inflammation, which playing the protective roles in tMCAO stroke model rats. This provides theoretical support for the clinical application of W1302 in the treatment of ischemic stroke.

Objective To observe the efficacy and safety of Morinda officinalis oligosaccharides in the continuation treatment of mild and moderate depression.Methods An open,single-arm,multi-center design was adopted in our study.Adult patients with mild and moderate depression who had received acute treatment of Morinda officinalis oligosaccharides were enrolled and continue to receive Morinda officinalis oligosaccharides capsules for 24 weeks,the dose remained unchanged during continuation treatment.The remission rate,recurrence rate,recurrence time,and the change from baseline to endpoint of Hamilton Depression Scale(HAMD),Hamilton Anxiety Scale(HAMA),Clinical Global Impression-Severity(CGI-S)and Arizona Sexual Experience Scale(ASEX)were evaluated.The incidence of treatment-related adverse events was reported.Results The scores of HAMD-17 at baseline and after treatment were 6.60±1.87 and 5.85±4.18,scores of HAMA were 6.36±3.02 and 4.93±3.09,scores of CGI-S were 1.49±0.56 and 1.29±0.81,scores of ASEX were 15.92±4.72 and 15.57±5.26,with significant difference(P＜0.05).After continuation treatment,the remission rate was 54.59％(202 cases/370 cases),and the recurrence rate was 6.49％(24 cases/370 cases),the recurrence time was(64.67±42.47)days.The incidence of treatment-related adverse events was 15.35％(64 cases/417 cases).Conclusion Morinda officinalis oligosaccharides capsules can be effectively used for the continuation treatment of mild and moderate depression,and are well tolerated and safe.