This study aims to explore the synergistic effects of the main components in salvianolic acids for Injection(SAFI) on key pathological events in cerebral ischemia, elucidating the pharmacological characteristics of SAFI in neuroprotection. Two major pathological gene modules related to endothelial injury and neuroinflammation in cerebral ischemia were mined from single-cell data. According to the topological distance calculated in network medicine, potential synergistic component combinations of SAFI were screened out. The results showed that the combination of caffeic acid and salvianolic acid B scored the highest in addressing both endothelial injury and neuroinflammation, demonstrating potential synergistic effects. The cell experiments confirmed that the combination of these two components at a ratio of 1∶1 significantly protected brain microvascular endothelial cells(bEnd.3) from oxygen-glucose deprivation/reoxygenation(OGD/R)-induced reperfusion injury and effectively suppressed lipopolysaccharide(LPS)-induced neuroinflammatory responses in microglial cells(BV-2). This study provides a new method for uncovering synergistic effects among active components in traditional Chinese medicine(TCM) and offers novel insights into the multi-component, multi-target acting mechanisms of TCM.
Brain Ischemia/metabolism* ; Neuroprotective Agents/pharmacology* ; Animals ; Drugs, Chinese Herbal/administration & dosage* ; Benzofurans/pharmacology* ; Mice ; Drug Synergism ; Caffeic Acids/pharmacology* ; Polyphenols/pharmacology* ; Humans ; Alkenes/pharmacology* ; Endothelial Cells/drug effects* ; Depsides

Compounds isolated from Epimedium include the total flavonoids of Epimedium , icariin, and its metabolites (icaritin, icariside I, and icariside II), which have similar molecular structures. Modern pharmacological research and clinical practice have proved that Epimedium and its active components have a wide range of pharmacological effects, especially in improving sexual function, hormone regulation, anti-osteoporosis, immune function regulation, anti-oxidation, and anti-tumor activity. To date, we still need a comprehensive source of knowledge about the pharmacological effects of Epimedium and its bioactive compounds on the male reproductive system. However, their actions in other tissues have been reviewed in recent years. This review critically focuses on the Epimedium , its bioactive compounds, and the biochemical and molecular mechanisms that modulate vital pathways associated with the male reproductive system. Such intrinsic knowledge will significantly further studies on the Epimedium and its bioactive compounds that protect the male reproductive system and provide some guidances for clinical treatment of related male reproductive disorders.
Male ; Epimedium/chemistry* ; Humans ; Genitalia, Male/drug effects* ; Flavonoids/therapeutic use* ; Animals

As an indispensable trace element in the human body,copper plays an important role in various physiological and biochemical reactions.The dyshomeostasis of copper leads to the disorder of copper metabolism and the occurrence of related diseases.Cuproptosis,a newly proposed regulatory cell death mode,is different from the known apoptosis,pyroptosis,necroptosis,and ferroptosis.Recent studies have found that the dyshomeostasis of copper has been observed in a variety of cancers.Therefore,targeting copper for disease treatment may become a new strategy and a new idea.This article systematically summarizes the fundamental properties of copper,copper dyshomeostasis-related diseases (Menkes syndrome,Wilson's disease,and cancer) and their treatment,and reviews the research progress in cuproptosis.
Humans ; Copper/metabolism* ; Homeostasis ; Neoplasms/metabolism* ; Hepatolenticular Degeneration/metabolism* ; Menkes Kinky Hair Syndrome/metabolism*

This paper outlines the common aspects of constructing integrated urban medical groups,focusing on governance,organizational restructuring,operational modes,and mechanism synergy.It then delves into the challenges in China's group construction,highlighting issues with power-responsibility alignment,capacity evolution,incentive alignment,and performance evaluation.Finally,the paper suggests strategies to enhance China's compact urban medical groups,focusing on governance reform,capacity building,benefit integration,and performance evaluation.

Objective To establish a dynamic prediction model of fatal massive hemorrhage in trauma based on the vital signs time series data and machine learning algorithms.Methods Retrospectively analyze the vital signs time series data of 7522 patients with trauma in the Medical Information Mart for Intensive Care-Ⅳ(MIMIC-Ⅳ)database from 2008 to 2019.According to the occurrence of posttraumatic fatal massive hemorrhage,the patients were divided into two groups:fatal massive hemorrhage group(n=283)and non-fatal massive hemorrhage group(n=7239).Six machine learning algorithms,including logistic regression(LR),support vector machine(SVM),random forests(RF),adaptive boosting(AdaBoost),gated recurrent unit(GRU),and GRU-D were used to develop a dynamic prediction models of fatal massive hemorrhage in trauma.The probability of fatal massive hemorrhage in the following 1,2,and 3 h was dynamically predicted.The performance of the models was evaluated by accuracy,sensitivity,specificity,positive predictive value,negative predictive value,Youden index,and area under receiver operating characteristic curve(AUC).The models were externally validated based on the trauma database of the Chinese PLA General Hospital.Results In the MIMIC-Ⅳ database,the set of dynamic prediction models based on the GRU-D algorithm was the best.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.946±0.029,0.940±0.032,and 0.943±0.034,respectively,and there was no significant difference(P=0.905).In the trauma dataset,GRU-D model achieved the best external validation effect.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.779±0.013,0.780±0.008,and 0.778±0.009,respectively,and there was no significant difference(P=0.181).This set of models was deployed in a public web calculator and hospital emergency department information system,which is convenient for the public and medical staff to use and validate the model.Conclusion A set of dynamic prediction models has been successfully developed and validated,which is greatly significant for the early diagnosis and dynamic prediction of fatal massive hemorrhage in trauma.

Objective: Previous research has explored a variety of mental disorders associated with Internet Gaming Disoder (IGD) and Social Media Addiction (SMA). To date, few studies focused on the network characteristics and investigated mood and sleep symptoms across SMA and IGD of adolescence at a group-specific level. This study aims to identify different characteristics of IGD and SMA and further determine the group-specific psychopathology process among adolescents. Methods: We conducted a cross-sectional study to recruit a cohort of 7,246 adolescents who were scored passing the cutoff point of Internet Gaming Disorder Scale-Short Form and Bergen Social Media Addiction Scale, as grouped in IGD and SMA, or otherwise into the control group. Patient Health Questionnaire-9, Generalized Anxiety Disorder 7-item, and Pittsburgh Sleep Quality Index were assessed for the current study, and all assessed items were investigated using network analysis. Results: Based on the analytical procedure, the participants were divided into three groups, the IGD group (n=789), SMA group (n=713) and control group (n=5,744). The edge weight bootstrapping analysis shows that different groups of networks reach certain accuracy, and the network structures of the three groups are statistically different (pcontrol-IGD=0.004, pcontrol-SMA<0.001, pIGD-SMA<0.001). The core symptom of SMA is “feeling down, depressed, or hopeless”, while IGD is “feeling tired or having little energy”. Conclusion Although IGD and SMA are both subtypes of internet addiction, the psychopathology processes of IGD and SMA are different. When dealing with IGD and SMA, different symptoms should be addressed.

Objective: To construct a prognostic model for unsuccessful removal of nasogastric tube (NGT) was the aim of our study. Methods: This study examined patients with swallowing disorders receiving NGT feeding due to stroke or traumatic brain injury in a regional hospital. Clinical data was collected, such as age, sex, body mass index (BMI), level of activities of daily living (ADLs) dependence. Additionally, gather information regarding the enhancement in Functional Oral Intake Scale (FOIS) levels and the increase in food types according to the International Dysphagia Diet Standardization Initiative (IDDSI) after one month of swallowing training. A stepwise logistic regression analysis model was employed to predict NGT removal failure using these parameters. Results: Out of 203 patients, 53 patients (26.1%) had experienced a failed removal of NGT after six months of follow-up. The strongest predictors for failed removal were age over 60 years, underweight BMI, total dependence in ADLs, and ischemic stroke. The admission prediction model categorized patients into high, moderate, and low-risk groups for removal failure. The failure rate of NGT removal was high not only in the high-risk group but also in the moderate-risk groups when there was no improvement in FOIS levels and IDDSI food types. Conclusion Our predictive model categorizes patients with brain insults into risk groups for swallowing disorders, enabling advanced interventions such as percutaneous endoscopic gastrostomy for high-risk patients struggling with NGT removal, while follow-up assessments using FOIS and IDDSI aid in guiding rehabilitation decisions for those at moderate risk.

Background/Aims: The performance of machine learning (ML) in predicting the outcomes of patients with hepatocellular carcinoma (HCC) remains uncertain. We aimed to develop risk scores using conventional methods and ML to categorize early-stage HCC patients into distinct prognostic groups. Methods: The study retrospectively enrolled 1,411 consecutive treatment-naïve patients with the Barcelona Clinic Liver Cancer (BCLC) stage 0 to A HCC from 2012 to 2021. The patients were randomly divided into a training cohort (n=988) and validation cohort (n=423). Two risk scores (CATS-IF and CATS-INF) were developed to predict overall survival (OS) in the training cohort using the conventional methods (Cox proportional hazards model) and ML-based methods (LASSO Cox regression), respectively. They were then validated and compared in the validation cohort. Results: In the training cohort, factors for the CATS-IF score were selected by the conventional method, including age, curative treatment, single large HCC, serum creatinine and alpha-fetoprotein levels, fibrosis-4 score, lymphocyte-tomonocyte ratio, and albumin-bilirubin grade. The CATS-INF score, determined by ML-based methods, included the above factors and two additional ones (aspartate aminotransferase and prognostic nutritional index). In the validation cohort, both CATS-IF score and CATS-INF score outperformed other modern prognostic scores in predicting OS, with the CATSINF score having the lowest Akaike information criterion value. A calibration plot exhibited good correlation between predicted and observed outcomes for both scores. Conclusions Both the conventional Cox-based CATS-IF score and ML-based CATS-INF score effectively stratified patients with early-stage HCC into distinct prognostic groups, with the CATS-INF score showing slightly superior performance.

Objective: To evaluate the association between pre-and post-diagnosis body mass index (BMI) and risk of colorectal cancer (CRC) death. Methods: The cohort consisted of 3, 057 CRC patients from Shanghai who were diagnosed from Jan. 1, 2009 to Dec. 31, 2011 and aged from 20 to 74 years. The pre- and post-diagnosis BMI and clinical and lifestyle factors were collected at baseline. Death information was collected using record linkage with the Shanghai Cancer Registry and telephone confirmation during follow-up by the end of 2019. The Cox proportional regression model was used to estimate HR with 95% CI. Results: Analysis by multivariable Cox model showed no association between pre-diagnosis BMI and death risk in both male and female patients. Male patients with a post-diagnosis underweight BMI had an elevated risk of death compared to those in normal weight (HR=1.69, 95% CI: 1.21-2.37), especially in early stage cases. Overweight patients (HR=0.74, 95% CI: 0.61-0.89) and patients with obesity class Ⅰ (HR=0.63, 95% CI: 0.45-0.89)had better survival with decreased risks of death, especially in advanced stage cases. The decreased death risk in patients with obesity class Ⅱ was not significant (HR=0.57, 95% CI: 0.24-1.39). The P(trend) value for decreased risk of death with increased BMI in female patients was statistically significant (P<0.001), and the overweight and obesity class Ⅰ categories had better survival in advanced stage(HR(overweight)=0.62, 95% CI: 0.42-0.93; HR(obesity class Ⅰ)=0.39, 95% CI: 0.16-0.98). Both male and female patients with post-diagnosis BMI loss >2.0 kg/m(2) had an increased death risk when compared with those with stable BMI (change≤1.0 kg/m(2)) between pre- and post-diagnosis. BMI gain after diagnosis did not change death risk. Conclusions: Post-diagnosis BMI in the overweight or obesity class Ⅰ groups might be conducive to prolonging male CRC patients' survival, while underweight might result in poor prognosis. Keeping weight and avoiding excessive weight loss should be suggested for all CRC patients after diagnosis.
Female ; Humans ; Male ; Body Mass Index ; China/epidemiology* ; Colorectal Neoplasms/complications* ; Obesity/complications* ; Overweight/complications* ; Proportional Hazards Models ; Prospective Studies ; Risk Factors ; Thinness/complications* ; Young Adult ; Adult ; Middle Aged ; Aged

Objective: To evaluate the association between pre-and post-diagnosis body mass index (BMI) and risk of colorectal cancer (CRC) death. Methods: The cohort consisted of 3, 057 CRC patients from Shanghai who were diagnosed from Jan. 1, 2009 to Dec. 31, 2011 and aged from 20 to 74 years. The pre- and post-diagnosis BMI and clinical and lifestyle factors were collected at baseline. Death information was collected using record linkage with the Shanghai Cancer Registry and telephone confirmation during follow-up by the end of 2019. The Cox proportional regression model was used to estimate HR with 95% CI. Results: Analysis by multivariable Cox model showed no association between pre-diagnosis BMI and death risk in both male and female patients. Male patients with a post-diagnosis underweight BMI had an elevated risk of death compared to those in normal weight (HR=1.69, 95% CI: 1.21-2.37), especially in early stage cases. Overweight patients (HR=0.74, 95% CI: 0.61-0.89) and patients with obesity class Ⅰ (HR=0.63, 95% CI: 0.45-0.89)had better survival with decreased risks of death, especially in advanced stage cases. The decreased death risk in patients with obesity class Ⅱ was not significant (HR=0.57, 95% CI: 0.24-1.39). The P(trend) value for decreased risk of death with increased BMI in female patients was statistically significant (P<0.001), and the overweight and obesity class Ⅰ categories had better survival in advanced stage(HR(overweight)=0.62, 95% CI: 0.42-0.93; HR(obesity class Ⅰ)=0.39, 95% CI: 0.16-0.98). Both male and female patients with post-diagnosis BMI loss >2.0 kg/m(2) had an increased death risk when compared with those with stable BMI (change≤1.0 kg/m(2)) between pre- and post-diagnosis. BMI gain after diagnosis did not change death risk. Conclusions: Post-diagnosis BMI in the overweight or obesity class Ⅰ groups might be conducive to prolonging male CRC patients' survival, while underweight might result in poor prognosis. Keeping weight and avoiding excessive weight loss should be suggested for all CRC patients after diagnosis.
Female ; Humans ; Male ; Body Mass Index ; China/epidemiology* ; Colorectal Neoplasms/complications* ; Obesity/complications* ; Overweight/complications* ; Proportional Hazards Models ; Prospective Studies ; Risk Factors ; Thinness/complications* ; Young Adult ; Adult ; Middle Aged ; Aged