OBJECTIVE: This study aimed to investigate the impact of glycemic control and diabetes duration on subsequent myocardial infarction (MI) in patients with both coronary heart disease (CHD) and type 2 diabetes (T2D). METHODS: We conducted a retrospective cohort study of 33,238 patients with both CHD and T2D in Shenzhen, China. Patients were categorized into 6 groups based on baseline fasting plasma glucose (FPG) levels and diabetes duration (from the date of diabetes diagnosis to the baseline date) to examine their combined effects on subsequent MI. Cox proportional hazards regression models were used, with further stratification by age, sex, and comorbidities to assess potential interactions. RESULTS: Over a median follow-up of 2.4 years, 2,110 patients experienced MI. Compared to those with optimal glycemic control (FPG < 6.1 mmol/L) and shorter diabetes duration (< 10 years), the fully-adjusted hazard ratio ( HR) (95% Confidence Interval [95% CI]) for those with a diabetes duration of ≥ 10 years and FPG > 8.0 mmol/L was 1.93 (95% CI: 1.59, 2.36). The combined effects of FPG and diabetes duration on MI were largely similar across different age, sex, and comorbidity groups, although the excess risk of MI associated with long-term diabetes appeared to be more pronounced among those with atrial fibrillation. CONCLUSION Our study indicates that glycemic control and diabetes duration significant influence the subsequent occurrence of MI in patients with both CHD and T2D. Tailored management strategies emphasizing strict glycemic control may be particularly beneficial for patients with longer diabetes duration and atrial fibrillation.
Humans ; Diabetes Mellitus, Type 2/blood* ; Male ; Female ; Middle Aged ; Aged ; Coronary Disease/complications* ; Myocardial Infarction/etiology* ; Retrospective Studies ; China/epidemiology* ; Glycemic Control ; Blood Glucose ; Adult ; Risk Factors ; Time Factors

OBJECTIVE: Observational studies have found associations between inflammatory bowel disease (IBD) and the risk of dementia, including Alzheimer's dementia (AD) and vascular dementia (VD); however, these findings are inconsistent. It remains unclear whether these associations are causal. METHODS: We conducted a meta-analysis by systematically searching for observational studies on the association between IBD and dementia. Mendelian randomization (MR) analysis based on summary genome-wide association studies (GWASs) was performed. Genetic correlation and Bayesian co-localization analyses were used to provide robust genetic evidence. RESULTS: Ten observational studies involving 80,565,688 participants were included in this meta-analysis. IBD was significantly associated with dementia (risk ratio [ RR] =1.36, 95% CI = 1.04-1.78; I ² = 84.8%) and VD ( RR = 2.60, 95% CI = 1.18-5.70; only one study), but not with AD ( RR = 2.00, 95% CI = 0.96-4.13; I ² = 99.8%). MR analyses did not supported significant causal associations of IBD with dementia (dementia: odds ratio [ OR] = 1.01, 95% CI = 0.98-1.03; AD: OR = 0.98, 95% CI = 0.95-1.01; VD: OR = 1.02, 95% CI = 0.97-1.07). In addition, genetic correlation and co-localization analyses did not reveal any genetic associations between IBD and dementia. CONCLUSION Our study did not provide genetic evidence for a causal association between IBD and dementia risk. The increased risk of dementia observed in observational studies may be attributed to unobserved confounding factors or detection bias.
Humans ; Mendelian Randomization Analysis ; Inflammatory Bowel Diseases/complications* ; Dementia/etiology* ; Observational Studies as Topic ; Genome-Wide Association Study

Objective: To investigate the chemical compositions of Maxing Shigan Decoction (麻杏石甘汤, MXSGD) and elucidate its anti-influenza A virus (IAV) mechanism from prediction to validation. Methods: Ultra high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was employed to analyze the chemical compositions of MXSGD. Network pharmacology theories were used to screen and identify shared targets of both the potential targets of active ingredients of MXSGD and IAV. A protein-protein interaction (PPI) network was then constructed, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. The binding stability between core bioactive compounds and key targets was validated by molecular docking and dynamic simulations. A total of 24 BALB/c mice were infected with IAV to build IAV mouse models. After successful modelling, the mouse models were randomly divided into model, MXSGD high-dose (2.8 g/kg), MXSGD low-dose (1.4 g/kg), and oseltamivir (20.14 mg/kg) groups, with an additional normal mice as control group (n = 6 per group). The treatments were administered by gavage daily between 8:00 a.m. and 10:00 a.m. for five consecutive days. Upon completion of the administration, the body weight ratio, lung index, protein content in the bronchoalveolar lavage fluid (BALF), and the levels of inflammatory factors including interleukin (IL)-6 and tumor necrosis factor (TNF)-α in mice were measured to preliminarily analyze the therapeutic efficacy of MXSGD against IAV infection. Furthermore, the expression levels of mechanistic target of rapamycin (mTOR), hypoxia inducible factor (HIF)-1α, and vascular endothelial growth factor (VEGF) proteins in the HIF-1 signaling pathway, which was enriched by network pharmacology, were detected by Western blot. Results: A total of 212 chemical components in MXSGD were identified by the UPLC-MS/MS method. These chemical components can be classified into 9 primary categories and 31 secondary categories. After intersecting the chemical component targets with IAV-related targets, a total of 567 potential MXSGD components targeting IAV were identified. The construction of PPI network and the results of both GO and KEGG enrichment analyses revealed that the anti-IAV effects of MXSGD were associated with multiple pathways, including apoptosis, TNF, HIF-1, and IL-17 signaling pathways. The results of molecular docking demonstrated that the binding energies between the core compound 1-methoxyphaseollin and key targets including HIF-1α, mTOR, and VEGF were all lower than – 5.0 kcal/mol. Furthermore, molecular dynamics simulations confirmed the structural stability of the resulting complexes. Animal experiments showed that compared with the normal controls, IAV-infected mice showed significantly reduced body weight ratio, markedly increased lung index, protein content in BALF, and the levels of inflammatory factors such as IL-6 and TNF-α (P < 0.01), thereby causing damage to the lung tissue; consequently, the expression levels of mTOR, HIF-1α, and VEGF proteins in the lung tissues of these mice were significantly elevated (P < 0.01). However, after MXSGD treatment, the mouse models presented a significant increase in body weight ratio, as well as marked decreases in lung index, protein content in BALF, and the levels of inflammatory factors including IL-6 and TNF-α (P < 0.01). Furthermore, the therapy alleviated IAV-induced injuries and significantly downregulated the expression levels of mTOR, HIF-1α, and VEGF proteins in lung tissues (P < 0.01 or P < 0.05). Conclusion MXSGD exerts anti-IAV effects through multi-component, multi-target, and multi-pathway synergism. Among them, 1-methoxyphaseollin is identified as a potential key component, which alleviates virus-induced lung injury and inflammatory response via the regulation of HIF-1 signaling pathway, providing experimental evidence for the clinical application of MXSGD.

Objective To analyze the research status and hotspots in the field of astragalus polysaccharides;To provide references for further research.Methods Research literature about astragalus polysaccharides was retrieved from CNKI,Wanfang Data,VIP,PubMed,and Web of Science databases from 1st,Jan.2013 to 1st,July 2023.NoteExpress 3.7 software was used to manage the literature and ultimately establish a database.Excel 2019,CiteSpace 6.2.2R and VOSviewer 1.6.18 were used to visually analyze the publication volume,authors,institutions,and keywords of the included literature.Results A total of 2 462 articles were included,with 1 284 Chinese articles and 1 178 English articles.The main research institutions were Gansu University of Chinese Medicine,Shandong University of Traditional Chinese Medicine,and Beijing University of Chinese Medicine.The core authors of Chinese literature were Liu Yongqi,Wang Hongxin,Lu Meili,etc.The core authors of English literature included Zhang Wei,Li Ke,Yang Xiaojun,etc.High-frequency keywords of Chinese literature included Astragali Radix,rats,polysaccharides,cell apoptosis,and oxidative stress,etc.High frequency keywords in English literature included expression,in vitro,oxidative stress,apoptosis,etc.Conclusion The research on astragalus polysaccharides focuses on their pharmacological effects and mechanisms.Intestinal flora,immune regulation,autophagy and apoptosis are the hot action mechanisms in this field.The focus of disease research involves tumor and diabetes,and antiviral,anti infection and other pharmacological effects are the research trend.

Objective:To investigate the effect of low-dose aspirin combined with dydrogesterone in the treatment of patients with polycystic ovary syndrome (PCOS) complicated with infertility and its influence on hormones and helper T cytokines.Methods:300 PCOS patients with infertility in the Second Affiliated Hospital of Air Force Military Medical University were selected from January 2018 to October 2023. A prospective randomized controlled study was performed. The study subjects were divided into control group and observation group by random envelope method, with 150 cases in each group. The control group was treated with dydrogesterone on the basis of routine intervention, while the observation group was combined with low-dose aspirin on the basis of the control group. The efficacy, pregnancy rate, hormones, Th1 and Th2 cytokines and incidence of adverse reactions were compared in between groups. Measurement data with normal distribution was represented by xˉ± s. Comparison between groups was performed by two-sample t-test and paired t-test was used for comparison before and after treatment. Enumeration data was represented by n(%). Comparison between groups was performed by χ2 test. Results:After treatment, the total effective rate of treatment and pregnancy rate in observation group were higher than those in control group [86.00%(129/150) vs. 74.67% (112/150), 63.33% (95/150) vs. 47.33% (71/150)] ( χ2=6.10, P=0.014, χ2=6.73, P=0.010). Serum levels of follicle-stimulating hormone (FSH) and luteinizing hormone (LH) in both groups were lower after treatment than those before treatment, and the levels in observation group were lower than those in control group [(5.27±1.01) U/L vs. (6.40±1.13) U/L, (6.78±0.87) U/L vs. (7.16±0.91) U/L], and serum estradiol level was higher than that before treatment, and the level in observation group was higher compared to control group [(93.35±8.17) ng/L vs. (82.45±9.14) ng/L] ( t=9.13, 3.70, 10.89, all P<0.001). After treatment, serum γ-interferon, interleukin (IL-2), IL-4 and IL-6 levels were all lower in both groups than those before treatment, and the above levels were lower in observation group than those in control group [(56.96±4.64) ng/L vs. (61.36±4.41) ng/L, (38.74±7.43) ng/L vs.(45.63±8.64) ng/L, (41.03±7.06) ng/L vs. (43.36±8.12 ng/L), (23.14±4.33) ng/L vs. (27.14±5.14) ng/L] ( t=8.42, 7.40, 2.65, 7.29, P<0.001, <0.0 010.008, <0.001). There was no statistical significance in the total incidence rate of adverse reactions between observation group and control group [12.67%(22/150) vs. 9.33% (14/150), χ2=0.85, P=0.356]. Conclusions:Low-dose aspirin combined with dydrogesterone has a significant clinical effect in the treatment of PCOS with infertility, and it can improve 3-month pregnancy rate, and effectively regulate hormones levels and Th1 and Th2 cytokines, and it will not increase adverse reactions, with high safety.

Objective:To develop a treatment-related quality of life scale for Chinese patients with multiple myeloma (MM) and to test its reliability and validity.Methods:The initial scale was constructed through a literature search, Delphi expert correspondence, and cognitive testing. This study conducted a preliminary survey of 379 patients with MM and a formal survey of 865 patients from the hematology departments of 155 hospitals nationwide from February 2024 to March 2024. The final scale was obtained after conducting item analysis and reliability and validity tests on the initial scale.Results:The constructed scale contains 36 items covering six domains: physiological, psychological, social, treatment side effects, general health, and others. In the preliminary survey, the Cronbach’s alpha coefficient of each item ranged from 0.597 to 0.939, and the test-retest reliability was 0.747 ( P<0.001). Exploratory factor analysis extracted eight common factors with a cumulative variance contribution of 60.058%. In the formal survey, the Cronbach’s alpha coefficient of each item ranged from 0.484 to 0.930, and the test-retest reliability was 0.835 ( P<0.001). Confirmatory factor analysis revealed a comparative fit index of 0.750, a root-mean-square error of approximation of 0.090, and a root-mean-square residual of 0.067. Conclusion:The treatment-related quality of life scale for Chinese patients with MM designed in this study exhibited good reliability and validity, reflecting the impact of treatment on the quality of life of patients. This scale can provide a reference to clinicians for assessing the disease status of patients.

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.

Objective:To evaluate the feasibility of a six-step suspension technique for endoscopic lateral neck dissection (LND) through the chest-breast approach in patients with papillary thyroid carcinoma (PTC).Methods:This is a retrospective case series study.Clinical data of 81 PTC patients who underwent endoscopic LND via the chest-breast approach using the six-step suspension method at the Department of Thyroid Surgery, Shenzhen People′s Hospital were collected from January 2022 to October 2024. The cohort consisted of 15 male and 66 female patients, with age of (35.2±10.2)years (range:8.5 to 65.0 years). Key variables, including LND duration, total operative time, postoperative hospital stay, details of lymph node metastasis, postoperative complications, and follow-up data were recorded and analyzed.Results:The duration of LND was (131.8±42.2)minutes (range: 65 to 275 minutes), and the total operative time was (195.5±49.6)minutes (range: 110 to 390 minutes). The postoperative hospital stay was (4.8±1.5)days(range:3 to 15 days). The number of dissected lateral cervical lymph nodes was 32.7±10.1 (range: 11 to 54). The maximum tumor diameter was (16.1±10.1)mm(range:2 to 30 mm), while the maximum size of metastatic lymph nodes was (16.7±6.2)mm(range:7 to 30 mm). The positivity rate was 24.7% (841/3 410) in the lateral cervical+central lymph node and 16.1% (427/2 646) in the lateral cervical lymph node. Postoperative lymphatic leakage occurred in 2 patients, both of whom were successfully treated conservatively. No other significant complications were reported. During the postoperative follow-up period, which lasted for (18.3±7.4) months (range: 1.1 to 34.4 months), the mean postoperative serum thyroglobulin (Tg) level ( M(IQR)) was 0.05 (0.50) μg/L (range: 0.01 to 7.90 μg/L), with 86.4% of patients showing a Tg ≤1.00 μg/L. Through imaging evaluations, no evidence of residual disease or recurrence was detected. Conclusion:Endoscopic LND via the chest-breast approach, utilizing the six-step suspension method, maybe a feasible and effective technique with promising clinical outcomes.

Objective West Nile virus(WNV)is one of the most common mosquito-borne zoonotic viruses worldwide,with unique transmission dynamics and varied hosts.Lots of ecological and host factors have been reported to influence the host adaptation and transmission of WNVs,however,general genomic features of WNVs are less focused,except for some exact host-specific genotypes at molecular level.Artificial intelligence that analyzes genome composition characteristics currently shows significant advantages in identifying and predicting viral host adaptability.This research aimed to establish a convolutional neural network(CNN)model to predict the host adaptability of WNVs based on general genomic features.Methods Presently available WNV gene sequences were embedded for their genomic features with an embedding approach of dinucleotide composition representation(DCR).And DCR-based distribution difference of WNV samples among various hosts was performed with unsupervised learning methods.Then a classification model was built with a convolutional neural network(CNN)framework based on genomic DCR to evaluate the adaptation of the WNVs from birds,mammals and mosquitos.Additionally,host-specific amino acids in WNV proteins were inferred via Bayes method.Results DCR features could effectively distinguish host-specific WNVs.The trained CNN model predicted accurately mammalian susceptible WNVs from avian susceptible WNVs,however,much less accurately for mosquito/mammalian WNVs.Such predicted host adaptation was interpreted as host specified significance of biased amino acid distribution on the bayes-inferred sites in WNV proteins,implying a possible high significance of these sites for WNV adaptive phenotypes.Conclusions Genomic compositional features of WNVs are host-specific,and such genomic bias facilitates predicting the adaptation of WNVs to avian or mammalian hosts via deep learning methods.DCR-based decomposition is helpful to recognize the high risk of infecting mammals of WNVs.The present study provides a general knowledge of genomic features contributing to host adaptation to WNVs.

OBJECTIVES: We propose a multi-feature fusion model based on manually extracted features and deep learning features from endoscopic images for grading rebleeding risk of peptic ulcers. METHODS: Based on the endoscopic appearance of peptic ulcers, color features were extracted to distinguish active bleeding (Forrest I) from non-bleeding ulcers (Forrest II and III). The edge and texture features were used to describe the morphology and appearance of the ulcers in different grades. By integrating deep features extracted from a deep learning network with manually extracted visual features, a multi-feature representation of endoscopic images was created to predict the risk of rebleeding of peptic ulcers. RESULTS: In a dataset consisting of 3573 images from 708 patients with Forrest classification, the proposed multi-feature fusion model achieved an accuracy of 74.94% in the 6-level rebleeding risk classification task, outperforming the experienced physicians who had a classification accuracy of 59.9% (P<0.05). The F1 scores of the model for identifying Forrest Ib, IIa, and III ulcers were 90.16%, 75.44%, and 77.13%, respectively, demonstrating particularly good performance of the model for Forrest Ib ulcers. Compared with the first model for peptic ulcer rebleeding classification, the proposed model had improved F1 scores by 5.8%. In the simplified 3-level risk (high-risk, low-risk, and non-endoscopic treatment) classification task, the model achieved F1 scores of 93.74%, 81.30%, and 73.59%, respectively. CONCLUSIONS The proposed multi-feature fusion model integrating deep features from CNNs with manually extracted visual features effectively improves the accuracy of rebleeding risk classification for peptic ulcers, thus providing an efficient diagnostic tool for clinical assessment of rebleeding risks of peptic ulcers.
Humans ; Deep Learning ; Peptic Ulcer ; Risk Assessment ; Peptic Ulcer Hemorrhage ; Recurrence