Chronic heart failure （CHF） is a group of complex clinical syndromes caused by abnormal changes in the structure and/or function of the heart due to various reasons， resulting in disorders of ventricular contraction and/or diastole. CHF is a condition where primary diseases such as coronary heart disease， hypertension and pulmonary heart disease recur frequently and persist for a long time， presenting blood stasis in meridians and collaterals， stagnation of water and dampness， and accumulation of Qi in collaterals. Its pathogenesis is complex and may involve myocardial energy metabolism disorders， oxidative stress responses， myocardial cell apoptosis， autophagy， inflammatory responses， etc. According to the theory of restraining hyperactivity to acquire harmony， we believe that under normal circumstances， the adenosine monophosphate-activated protein kinase （AMPK） signaling pathway functions normally， maintaining human physiological activities and energy metabolism. Under pathological conditions， the AMPK signaling pathway is abnormal， causing energy metabolism disorders， inflammatory responses， and myocardial fibrosis. Traditional Chinese medicine （TCM） can regulate the AMPK signaling pathway through multiple mechanisms， targets， and effects， effectively curbing the occurrence and development of CHF. It has gradually become a research hotspot in the prevention and treatment of this disease. Guided by the theory of TCM， our research group， through literature review， summarized the relationship between the AMPK pathway and CHF and reviewed the research progress in the prevention and control of CHF with TCM active ingredients， TCM compound prescriptions， and Chinese patent medicines via regulating the AMPK pathway. The review aims to clarify the mechanism and targets of TCM in the treatment of CHF by regulating the AMPK pathway and guide the clinical treatment and drug development for CHF.

ObjectiveTo investigate the therapeutic effect of Astragali Radix-mediated changes in gut microbiota on treating type 2 diabetes （T2DM）. MethodsA 12-week randomized， placebo-controlled clinical trial enrolled eighty patients with newly diagnosed type 2 diabetes and poor glycemic control in the Qi deficiency type. All patients received insulin therapy. The observation group （40 cases） was administered with Astragali Radix Granules， while the control group （40 cases） received a placebo. Both treamtents were taken orally twice daily. Changes in gut microbiota were assessed by 16s rDNA sequencing. Serum glucagon-like peptide-1 （GLP-1） levels were measured using enzyme-linked immunosorbent assay （ELISA）. Glucose metabolism indicators including fasting blood glucose （FPG）， 2-hour postprandial blood glucose （2 h PG），glycated albumin（GA）， and glycated hemoglobin （HbA1c） were evaluated. Pancreatic function was evaluated using fasting C-peptide （FCP）， 2-hour postprandial C-peptide （2 h CP）， and C-peptide area under the curve （AUC_cp）. Traditional Chinese medicine （TCM） syndrome scores， clinical efficacy， and safety indicators were also observed. ResultsIn terms of glucose metabolism indicators， compared with the baseline， both groups exhibited significantly lower FPG， 2 h PG， GA and HbA1C （P<0.01），while FCP， 2 h CP and AUC_cp were significantly higher （P<0.01）. Compared with the control group after the treatment， the observation group showed significantly lower FPG， 2 h PG， GA and HbA1C（P<0.05， P<0.01），and significantly higher FCP， 2 h CP and AUC_cp （P<0.05， P<0.01）， indicating that Astragali Radix can improve glucose metabolism. In terms of the diversity of gut microbiota， no significant differences were detected in the Chao1， Shannon and Simpson indexes of the two groups compared with their respective baselines. However， compared with the post-treatment control group， the observation group demonstrated significant increases in the Chao1， Shannon and Simpson indexes （P<0.05， P<0.01）. The β-diversity analysis showed significant separation in gut microbiota composition before and after treatment in both groups， indicating that Astragali Radix can significantly alter the structure and improve the diversity of gut microbiota. At the phylum level， compared with the baseline， both groups showed a significant increase in the relative abundance of Bacteroidota（P<0.01）. The relative abundance of the potentially harmful phylum Proteobacteria was significantly lower in the observation Group after treatment （P<0.01）. Compared with the post-treatment control group， the observation group had a significantly higher relative abundance of Bacteroidota（P<0.01）. No significant difference was found in Firmicutes/Bacteroidota （F/B） ratio between the two groups after treatment， and other phyla showed no significant differences. At the genus level， compared with the baseline， the observation group exhibited a significant increase in Bacteroides （P<0.01） and a significant decrease in Escherichia-Shigella （P<0.01）， whereas no significant difference was seen in the control group . Compared with the control group after treatment， the observation group after treatment had a significantly higher relative abundance of Bacteroides （P<0.01）. No significant differences were seen in other genera. Linear discriminant analysis （LDA） identified potential characteristics taxa： in the observation group， Bacteroidota at the phylum level and Bacteroides and Dubosiella at the genus level， in the control group， Proteobacteria at the phylum level as well as Barnesiella and Staphylococcus at the genus level. Correlation analysis based on a heatmap revealed that GLP-1 levels were positively correlated with Firmicutes， F/B ratio and Fusobacterium， and negatively correlated with Bacteroidota， Proteobacteria， Bacteroides and Escherichia-Shigella. In terms of clinical efficacy， compared with the control group， the total effective rate of the observation group was significantly higher （P<0.05）. Compared with the baseline， the scores for shortness of breath， fatigue， weakness， spontaneous sweating and reluctance to speak significantly decreased in both groups （P<0.01）. Compared with the control group after treatment， the score for weakness was significantly lower in the observation group （P<0.01），indicating that Astragali Radix could improve clinical symptoms and alleviate weakness symptoms. In terms of safety， compared with the baseline， alanine aminotransferase （ALT） levels significantly decreased in both groups （P<0.05，P<0.01），indicating that Astragali Radix did not induce any significant abnormalities in liver and kidney functions. ConclusionAstragali Radix demonstrates the potential to significantly improve the gut microbiota environment in patients of newly diagnosed type 2 diabetes with Qi deficiency. The therapeutic effect may contribute to glycemic control， possibly mediated by an elevation in GLP-1 level. These findings may support its further clinical investigations and potential applications.

OBJECTIVE To introduce the development of an intelligent prescription review decision-support system for anti-tumor drugs and assess its clinical application outcomes. METHODS Relevant data sources， including national and local pharmaceutical administration policies， clinical practice guidelines/consensus， hospital information systems data， and genetic testing results， were integrated. Adhering to the principles of structure， standardization and dynamic updating， a knowledge base covering chemotherapeutic， targeted and immunotherapeutic agents was constructed using a dual-dimensional modeling approach that combined “drug attributes” and “clinical contexts”. This knowledge base was then embedded into the hospital’s electronic medical order system to establish the prescription review decision-support system. The application and performance of the system were evaluated at Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine. RESULTS A knowledge base containing 18 318 prescription review rules for anti-tumor drugs was constructed， and a closed-loop prescription review system was successfully established， encompassing pre-prescription real-time intervention， in-process interactive review， and post-prescription evaluation and analysis. From 2021 to 2024， the system generated a total of 57 879 alerts for prescriptions of five typical categories of anti-tumor drugs. For platinum-containing prescriptions， 22 577 alerts were generated， with Cisplatin for injection （lyophilized） being the most frequently alerted drug （13 445 alerts）， and “ototoxicity risk due to combined use” alerts remained high （7 682 alerts）. For methotrexate-containing prescriptions， 3 721 alerts were recorded， primarily related to “precaution-related issues” （76.4%， 2 843/3 721）. For doxorubicin-containing prescriptions， 17 301 alerts were triggered， primarily related to “dosage and administration” （14 315 alerts）. For human epidermal growth factor receptor 2-targeted agents-containing prescriptions， 1 007 alerts were issued， mostly related to “reimbursement restrictions” （956 alerts）. For programmed death-1/programmed death-ligand 1 inhibitors-containing prescriptions， the alerts increased year by year， totaling 13 273 alerts， primarily related to “inappropriate indication” （9 118 alerts）. Over the 4 years， the physician response rates to system alerts were 21.4%， 27.1%， 33.5% and 51.6%， respectively. CONCLUSIONS An intelligent decision-support system for anti-tumor drug prescription review， encompassing a closed-loop process of “real-time pre-event intervention， interactive in-event prescription review， post-event evaluation and analysis”， has been successfully constructed and implemented throughout the entire workflow. There is a discernible trend in this hospital， where the focus on monitoring anti-tumor drugs is shifting towards immunotherapy drugs. Additionally， the acceptance rate of physicians regarding prescription review opinions has been steadily increasing year by year.

Objective To construct machine learning models based on preoperative inflammatory and radiological features for the prediction of glioma grading and isocitrate dehydrogenase (IDH) mutation status, and to analyze application values of these models and identify the optimal predictive models. Methods A retrospective analysis was conducted on the data of pathologically confirmed glioma patients admitted to Tongji Hospital Affiliated to Tongji University from March 2019 to March 2023. LASSO regression was used to screen feature variables, and predictive models were constructed based on logistic regression (LR), random forest (RF), support vector machine (SVM), gradient boosting decision tree (XGBoost) and K-nearest neighbor (KNN) algorithms. The model performance was comprehensively evaluated using metrics including discrimination ability, area under the precision-recall curve (AUC), accuracy, F1 score and Brier score. The DeLong test was adopted to compare the AUC values among different models; Friedman rank-sum test was used to determine the overall performance differences of the models, with the Nemenyi test applied for multiple comparison correction. Results In the task of glioma grading prediction, the LR model achieved the highest comprehensive score (0.726), and no significant difference was observed between the LR model and the other four models; age was positively correlated with glioma grading (P=0.003). In the task of IDH mutation status prediction, the XGBoost model obtained the highest comprehensive score (0.832), which was superior to the LR (0.762, P=0.035) and KNN models (0.754, P=0.025), while no statistical differences were found between the XGBoost model and the RF or SVM models. Conclusions The LR model for glioma grading prediction and XGBoost model for IDH mutation prediction constructed based on a task-oriented strategy achieve a favorable interpretability while ensuring optimized performance, thereby providing reliable decision support for the individualized diagnosis and treatment of glioma.

ObjectiveTo investigate the patterns of chronic disease comorbidity among permanent elderly residents in Xuhui District of Shanghai, and to analyze the impact of different comorbidity patterns on the elderly’s ability to perform activities of daily living. MethodsBased on data from the 2015 and 2021 Surveys on Health Status and Health Service Utilization among Permanent Residents in Xuhui District of Shanghai, the study included permanent residents who fully participated in both surveys, were aged 60 years or older at the 2015 survey, self-reported having a chronic disease, and reported no significant changes in their chronic disease status between the two surveys. A prospective cohort study design was adopted, using the 2015 data as the baseline and the 2021 survey data as follow-up data. Physical examinations and questionnaire surveys were conducted by the Shanghai Xuhui District Center for Disease Control and Prevention in the subdistricts and towns within the jurisdiction from April to July in both 2015 and 2021. Latent class analysis (LCA) was used to classify comorbidity patterns across 11 types of chronic diseases. The smaller the values of the Akaike information criterion (AIC), the Bayesian information criterion (BIC), and the sample-corrected Bayesian information criterion (aBIC), the better the model fits. The Barthel index (BI) and the Lawton and Brody Instrumental Activities of Daily Living Scale (LB-IADL) were used to assess the participants’ activities of daily living (ADL) and instrumental activities of daily living (IADL). Multiple linear regression and multivariate logistic regression models were used to analyze the association between different comorbidity patterns and ADL and IADL. ResultsA total of 1 608 study participants were enrolled. Among them, 671 (41.73%) self-reported having no chronic diseases. The prevalence of 11 types of chronic diseases was as follows: hypertension in 743 participants (46.21%), heart disease in 148 participants (9.20%), cerebrovascular disease in 37 participants (2.30%), diabetes or abnormal blood glucose in 310 participants (19.28%), other endocrine system diseases (non-diabetic) in 39 participants (2.43%), malignant tumors in 37 participants (2.30%), chronic lung disease in 16 participants (1.00%), gout in 8 participants (0.50%), musculoskeletal disorders in 34 participants (2.11%), gastric or digestive system diseases in 27 participants (1.68%), and dyslipidemia in 15 participants (0.93%). LCA was used to classify comorbidity patterns of chronic diseases among older adults into 1 to 9 latent category combinations. Model 5 (i.e., 5 latent categories) had the lowest BIC (7 112.69) and aBIC (6 909.38), with a relatively low AIC (6 768.20), indicating the best model fit; thus, five latent categories represented the optimal combination in this study. The five latent categories (and their respective proportions of study participants) were the healthy control group (41.73%), the hypertension group (31.28%), the diabetes-hypertension group (19.28%), the severe illness group (5.29%), and the other metabolic diseases group (2.43%). According to multiple linear regression analyses, compared with the healthy control group, the diabetes-hypertension group had significantly lower BI-20 scores (b=-0.952, 95%CI: -1.317‒ -0.587, P<0.001) and lower IADL scores (b=-0.744, 95%CI: -0.999‒ -0.489, P<0.001); the severe illness group (b=-0.644, 95%CI: -1.072‒ -0.217, P=0.003) and the hypertension group (b=-0.344, 95%CI: -0.562‒ -0.125, P=0.002) had lower IADL scores. According to multivariate logistic regression analyses, compared with the healthy control group, older adults in the diabetes-hypertension group had a higher risk of disability (OR=2.835, 95%CI: 1.392‒5.774), impaired ADL function (OR=2.470, 95%CI: 1.637‒3.726), and impaired IADL function (OR=1.739, 95%CI: 1.264‒2.392); older adults in the severe illness group had a higher risk of impaired ADL function (OR=2.206, 95%CI: 1.171‒4.155). ConclusionAmong the elderly participating in the Survey on Health Status and Health Service Utilization of Permanent Residents in Xuhui District of Shanghai, diabetes-hypertension is one of the key chronic disease comorbidity combinations and has adverse effects on both ADL and IADL. Community health management should prioritize the elderly with diabetes-hypertension comorbidity, and strengthen early screening and comprehensive interventions to slow the decline in ADL and IADL.

Purpose: It was aimed to clarify the casual connection between prostate cancer (PCa) and arthritis by utilizing two-sample Mendelian randomization (MR) analysis and data from National Health and Nutrition Examination Survey (NHANES) database. Materials and Methods: This study utilized NHANES data. Through association analysis and risk stratification analysis, the association between arthritis and PCa were examined. MR analysis was performed to elucidate the causal relationship between arthritis and PCa. Sensitivity analysis and Steiger directionality test confirmed the reliability of the MR analysis results. Results: A total of 23,608 (PCa:controls=413:23,195) participants after a sample exclusion and variable definition process were screened in NHANES database. Adjustments across three diverse models consistently revealed a notable influence of arthritis on PCa progression. Arthritis was identified as a risk factor for PCa (odds ratio [OR] 1.88, 95% confidence interval [CI] 1.36–2.62, p<0.001). Subsequent analysis indicated that in the arthritis-adjusted model with multiple covariates, the area under the curve of the receiver operating characteristic curve was 0.94. The inverse variance weighting method of MR analysis showed a causal relationship between rheumatoid arthritis (RA) and PCa (OR 1.090, 95% CI 1.053–1.128, p<0.001) as well as osteoar-thritis and PCa (OR 1.002, 95% CI 1.001–1.004, p=0.002). This suggested that RA and osteoarthritis were risk factors for PCa. The heterogeneity (p>0.05), horizontal pleiotropy (p>0.05), leave-one-out and Steiger test confirmed reliability of MR results. Conclusions NHANES database and MR analyses identified arthritis as a risk factor for PCa, offering fresh avenues for preventive and therapeutic approaches.

ObjectiveTo investigate a suspected outbreak of healthcare-associated infection with carbapenem-resistant Klebsiella pneumoniae (CRKP) in a geriatric emergency ward, and to provide references for the prevention and control of multidrug-resistant bacteria in a hospital in Shanghai. MethodsOn-site epidemiological investigation, combined with environmental hygiene monitoring and pulsed field gel electrophoresis (PFGE) molecular typing method, were adopted to investigate a suspected outbreak of CRKP infection in the geriatric emergency ward of a hospital from October to November 2022, aiming at finding out factors caused the outbreak before taking corresponding control measures. ResultsA total of 3 cases of healthcare-associated CRKP infection were identified, of which 2 cases were homologous to a previous case of community-associated CRKP infection. What’s more, the 2 cases lived in the same ward with the latter and with adjacent beds, but the third case was non-homologous to the community-associated infection case. A total of 46 samples were collected from the environmental surfaces and the hands of healthcare workers, of which 7 samples tested positive for CRKP and were identical to the strains from the 2 healthcare-associated infection cases and the 1 community-associated infection case, originating from the bedrails, bedside tables, surface of non-invasive ventilator, bed curtains and panels of monitoring equipment, with a detection rate of 15.22%. But none of the 11 samples from the hands of healthcare workers tested positive for CRKP. The outbreak was effectively controlled after taking specific prevention and control measures such as strengthening personnel management, intensifying environmental cleaning and disinfection and strictly enforcing hand hygiene among healthcare workers. Subsequently, no similar new cases were reported during the 14-day follow-up period. ConclusionIncomplete environmental cleaning and disinfection, as well as inadequate enforcement of hand hygiene among heatheare workers may have contributed to the suspected outbreak of CRKP in the geriatric emergency ward. Early warning and timely investigation of suspected outbreaks of multidrug-resistant bacteria are crucial for preventing and controlling such outbreaks in hospitals.

Objective To explore the feasibility and clinical value of endoscopic resection of duodenal papilla tumors with a maximum diameter greater than 3 cm. Methods A retrospective analysis was conducted on the clinical data of all 12 patients who underwent endoscopic resection of duodenal papilla tumors at the Endoscopy Center of Zhongshan Hospital (Xuhui Hospital), Fudan University and Rongcheng Hospital of Traditional Chinese Medicine from September 2017 to May 2023. The size of the tumors all exceeded 3 cm. Results All 12 patients successfully completed the operation, with a complete resection rate of 91.7% (11/12) and an en-bloc resection rate of 91.7% (11/12). One patient experienced delayed bleeding due to unclosed wound during operation and received endoscopic hemostasis; 11 cases underwent partial wound closure operation with pancreatic and biliary stent placement, without perforation or postoperative stenosis. Among them, 2 cases (18.2%) experienced delayed bleeding and received endoscopic hemostasis treatment. After operation, 1 case (8.3%) experienced nausea, vomiting, upper abdominal discomfort, and elevated blood amylase levels, who was later treated conservatively. During the mean follow-up period of 30.5 (1.0-69.0) months, 1 patient experienced recurrence and underwent surgical resection. Conclusions Endoscopic resection of duodenal papilla tumors can treat large diameter duodenal papilla tumors exceeding 3 cm, but postoperative complications may occur and require special attention. Postoperative placement of pancreatic and biliary stents and wound closure may reduce the incidence of complications.

Objective To explore the mechanism by which zinc-regulated transporters, iron-regulated transporter-likeprotein 4 (ZIP4) regulates glycolysis and its impact on tumor progression in cholangiocarcinoma (CCA), providing a theoretical basis for targeted therapy of CCA. Methods ZIP4 expression in CCA was analyzed using the GEPIA database. Immuno-histochemistry (IHC) was used to detect ZIP4 expression in 20 paired CCA and adjacent non-tumor tissues. Stable ZIP4-overexpressing CCA cell lines (ZIP4-OE) were established. Gene set enrichment analysis was used to screen differentially expressed genes and pathways in ZIP-OE CCA cells. ZIP4, N-myc proto-oncogene protein (MYCN), and histone-lysine N-methyltransferase 2E (KMT2E) were knocked down using small interfering RNAs (siRNAs). The expression of glycolysis-related gene (glucose transporter 1 [Glut1], hexokinase 2 [HK2], and lactate dehydrogenase A [LDHA]) was measured by real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). Glycolytic activity was assessed by measuring the extracellular acidification rate (ECAR). Cell proliferation was evaluated using colony formation assays, and cell migration was assessed using Transwell assays. A xenograft mouse model was constructed to examine CCA tumor growth. Protein levels of ZIP4, KMT2E, H3K4me3 (tri-methylation of lysine 4 on histone H3), and MYCN were detected by Western blotting. Results GEPIA database analysis and IHC results confirmed significantly higher ZIP4 expression levels in CCA tissues compared to adjacent non-tumor tissues (P＜0.05). Compared to the control group, the ZIP4-OE group exhibited a significantly increased ECAR, along with significantly enhanced proliferation and migration abilities (P＜0.01). Conversely, knockdown of ZIP4 suppressed CCA cells proliferation and migration. GEPIA analysis indicated that ZIP4 upregulates the transcription of oncogene MYCN, as well as glycolysis-related genes. Knockdown of MYCN abolished the ZIP4 overexpression-induced upregulation of Glut1, HK2, and LDHA gene transcription, reduced glycolysis, and significantly inhibited CCA cell proliferation and migration (P＜0.05). Mechanistic studies demonstrated that ZIP4 increases H3K4me3 level via KMT2E, leading to MYCN transcription. Knockdown of KMT2E in CCA cells suppressed the ZIP4 overexpression-induced enhancement in H3K4me3 modification, resulting in MYCN downregulation and significantly reduced CCA cells proliferation and migration (P＜0.05). Conclusions ZIP4 upregulates H3K4me3 modification through KMT2E, which recruits transcription factors to activate the transcription of MYCN. This subsequently enhances cellular glycolysis and promotes the proliferation and migration of CCA cells.

ObjectiveTo analyze the distribution, drug resistance characteristics, and changing trends of Acinetobacter baumannii (AB) isolated from environmental surfaces and healthcare workers’ hands in a grade Ⅱ level A general hospital in Xuhui District of Shanghai from 2018 to 2023, and to provide reference for infection control in the hospital. MethodsEnvironmental samples were collected quarterly from critical surfaces and healthcare workers’ hands in the intensive care unit (ICU), geriatrics, and respiratory departments from 2018 to 2023. Clinical isolates were obtained from all patients with AB infections in ICU, geriatrics, respiratory department, rehabilitation department, infectious diseases department, emergency department, cardiology department, and orthopedics of the hospital from 2018 to 2023. Retrospective analyses were performed on AB detection rates, strain origins, resistance rates to commonly used antimicrobial agents, and resistance gene features, comparing the antimicrobial resistance between clinically isolated strains and environmentally isolated strains. ResultsFrom 2018 to 2023, a total of 1 416 samples were collected from the hospital and a total of 272 strains of AB were detected, with a positive detection rate of 19.21%. The detection rate gradually decreased year-on-year (χ²_trend=45.290, P<0.001). The majority of samples originated from patient-contacted items (34.56%, 94/272), followed by shared items (26.84%, 73/272) and healthcare worker-contacted items (15.07%, 41/272). From 2018 to 2023, the resistance rate of AB on environmental surfaces and healthcare workers’ hands to commonly tested antibiotics in the hospital ranged from 10% to 40%. The resistance rates to cefotaxime (42.52%) and piperacillin (38.58%) were relative high, while the resistance to polymyxin E (1.57%), polymyxin B (2.36%), and doxycycline (3.94%) maintained low. The annual fluctuations in resistance to cefotaxime, piperacillin, ceftriaxone, tobramycin, doxycycline, minocycline and cotrimoxazole were statistically significant (all P<0.05). There were statistically significant differences in the resistance of clinical and environmental isolates to ampicillin/sulbactam, cefepime, ceftazidime, subamphetamine, meropenem, piperacillin, aztreonam, gentamicin, tobramycin, minocycline, ciprofloxacin, levofloxacin, and cotrimoxazole in the hospital from 2018 to 2023 (all P<0.05). The resistance rate of clinical isolates was generally high, especially to β-lactam and quinolone drugs, which were mostly above 80% [such as cefepime (93.86%), cefotaxime (97.37%), imipenem (98.25%), and ciprofloxacin (99.12%)]. The resistance rate of environmental isolated strains to similar antibiotics was relatively lower, mostly concentrated at 10%‒30%. The whole-genome sequencing of 34 carbapenem-resistant Acinetobacter baumannii (CRAB) strains isolated from the hospital environment in 2023 revealed that the main resistance mechanism was overexpression of efflux pumps (51.97%), followed by changes in target sites (32.46%). Among the 34 CRAB strains, carbapenem resistance genes OXA-23 and OXA-51 were detected in 6 strains (17.65%), while genes such as KPC, IMP, VIM, and SIM were not detected. ConclusionFrom 2018 to 2023, AB in the hospital environment exhibited high resistance rates to certain antimicrobial agents and carried multiple resistance genes, indicating a potential transmission risk. It is necessary to further strengthen bacterial resistance monitoring and hospital infection control, and use antibiotics reasonably.