Heart failure （HF） is the end-stage of various cardiovascular diseases， with high morbidity and mortality. The existing “new quadruple” standard treatment can hardly reverse the core pathological process of myocardial remodeling， and long-term medication may pose risks of drug resistance and adverse reactions. Therefore， new therapeutic targets and strategies are urgently needed. Metabolic reprogramming is the upstream core mechanism regulating phenotypic polarization and functional activation of macrophages， which drives the occurrence and development of HF through the core axis of metabolic reprogramming-immune imbalance-ventricular remodeling and has become a cutting-edge potential target for the prevention and treatment of HF. Traditional Chinese medicine （TCM） has a long history in the prevention and treatment of HF. A large number of studies in recent years have confirmed that different therapeutic methods of TCM can correct the polarization imbalance， restore the homeostasis of myocardial immune microenvironment， inhibit myocardial injury， and delay the pathological process of HF by targeting and regulating the metabolic reprogramming of glucose， lipids， mitochondria， and amino acids in macrophages. This paper systematically expounds the core pathological mechanism of metabolic reprogramming of macrophages in HF， sorts out the research progress of TCM in preventing and treating HF by intervening this target， analyzes the regulatory rules， summarizes the limitations of existing research， and puts forward future directions. This review aims to provide a systematic theoretical reference and new research ideas for TCM clinical diagnosis and treatment and new drug development of HF.

Background The association between occupational physical activity (OPA) and cardiometabolic risk factors remains controversial, potentially due to differences in the associations between OPA and various cardiometabolic indicators, as well as the lack of a clearly defined optimal OPA range for multiple-indicator synergistic benefits. Objective To investigate the relationship between OPA and cardiometabolic risk factors in individuals at high risk of cardiovascular disease (CVD) in Hubei Province, and to explore an optimal OPA range for multi-indicator improvements. Methods Data were derived from the Hubei Province dataset of the China Health Evaluation And Risk Reduction Through Nationwide Teamwork from 2015 to 2023, including 19028 high-risk CVD individuals. OPA (metabolic equivalent·h·d⁻¹, MET·h·d⁻¹) was assessed using the China Kadoorie Biobank physical activity questionnaire, anthropometric measurements (height, weight, waist circumference) and cardiometabolic indicators (blood pressure, fasting blood glucose, lipid profiles) were measured. Multivariate logistic regression was used to analyze the association between logOPA quartiles (Q1-Q4) and abnormal cardiometabolic indicators, while restricted cubic spline (RCS) models were employed to explore their dose-response relationships. Subgroup and interaction analyses were also conducted by gender. Results The median OPA of all participants was 12.86 MET·h·d⁻¹ (male: 14.40 MET·h·d⁻¹, female: 11.14 MET·h·d⁻¹). After adjusting for confounders, compared with the Q1 group, logOPA in the Q4 group was associated with 20% (OR=0.80, 95%CI: 0.72, 0.89), 14% (OR=0.86, 95%CI: 0.78, 0.96), and 13% (OR=0.87, 95%CI: 0.79, 0.95) reduction in the risk of abdominal obesity, low high-density lipoprotein cholesterol (HDL-C), and metabolic syndrome (MS), respectively, and 33% (OR=1.33, 95%CI: 1.18, 1.49), 33% (OR=1.33, 95%CI: 1.18, 1.50), and 38% (OR=1.38, 95%CI: 1.21, 1.57) increase in the risk of high total cholesterol (TC), high low-density lipoprotein cholesterol (LDL-C), and high non-HDL-C, respectively. Similar trends were observed in males and females, with significant positive associations of logOPA with high TC and high non-HDL-C in males (P_interaction<0.05). The risk of low HDL-C decreased rapidly when logOPA was more than 2.213 (OPA>9.14 MET·h·d⁻¹), showing an inverted L-shaped trend. The risk of high TC, high LDL-C, and high non-HDL-C increased beyond logOPA thresholds of 3.244, 2.476, and 3.377 (OPA >25.64, 11.89, and 29.28 MET·h·d⁻¹), respectively, showing a J-shaped trend. However, logOPA exhibited a U-shaped nonlinear dose-response relationship with blood pressure and fasting blood glucose abnormalities (P_non-linear<0.05) , with minimal risks at logOPA 2.969 and 2.372 (OPA of 19.47 and 10.72 MET·h·d⁻¹). Conclusion OPA exhibits heterogeneous dose-response patterns across cardiometabolic indicators. Integrating the inverted L-, J-, and U-shaped association patterns, we suggest an optimal OPA range of 9.14−25.64 MET·h·d⁻¹ for multiple cardiometabolic indicators in total individuals at high-risk of CVD, with ranges of 9.61−31.34 MET·h·d⁻¹ for males and 8.97−22.87 MET·h·d⁻¹ for females. These findings provide critical evidence for developing OPA interventions strategies targeting high-risk population for CVD.

BACKGROUND: Approximately 40% of individuals with diabetes worldwide are at risk of developing diabetic kidney disease (DKD), which is not only the leading cause of kidney failure, but also significantly increases the risk of cardiovascular disease, causing significant societal health and financial burdens. This study aimed to describe the burden of DKD and explore its cross-country epidemiological status, predict development trends, and assess its risk factors and sociodemographic transitions. METHODS: Based on the Global Burden of Diseases (GBD) Study 2021, data on DKD due to type 1 diabetes (DKD-T1DM) and type 2 diabetes (DKD-T2DM) were analyzed by sex, age, year, and location. Numbers and age-standardized rates were used to compare the disease burden between DKD-T1DM and DKD-T2DM among locations. Decomposition analysis was used to assess the potential drivers. Locally weighted scatter plot smoothing and Frontier analysis were used to estimate sociodemographic transitions of DKD disability-adjusted life years (DALYs). RESULTS: The DALYs due to DKD increased markedly from 1990 to 2021, with a 74.0% (from 2,227,518 to 3,875,628) and 173.6% (from 4,122,919 to 11,278,935) increase for DKD-T1DM and DKD-T2DM, respectively. In 2030, the estimated DALYs for DKD-T1DM surpassed 4.4 million, with that of DKD-T2DM exceeding 14.6 million. Notably, middle-sociodemographic index (SDI) quintile was responsible for the most significant DALYs. Decomposition analysis revealed that population growth and aging were major drivers for the increased DKD DALYs in most regions. Interestingly, the most pronounced effect of positive DALYs change from 1990 to 2021 was presented in high-SDI quintile, while in low-SDI quintile, DALYs for DKD-T1DM and DKD-T2DM presented a decreasing trend over the past years. Frontiers analysis revealed that there was a negative association between SDI quintiles and age-standardized DALY rates (ASDRs) in DKD-T1DM and DKD-T2DM. Countries with middle-SDI shouldered disproportionately high DKD burden. Kidney dysfunction (nearly 100.0% for DKD-T1DM and DKD-T2DM), high fasting plasma glucose (70.8% for DKD-T1DM and 87.4% for DKD-T2DM), and non-optimal temperatures (low and high, 5.0% for DKD-T1DM and 5.1% for DKD-T2DM) were common risk factors for age-standardized DALYs in T1DM-DKD and T2DM-DKD. There were other specific risk factors for DKD-T2DM such as high body mass index (38.2%), high systolic blood pressure (10.2%), dietary risks (17.8%), low physical activity (6.2%), lead exposure (1.2%), and other environmental risks. CONCLUSIONS DKD markedly increased and varied significantly across regions, contributing to a substantial disease burden, especially in middle-SDI countries. The rise in DKD is primarily driven by population growth, aging, and key risk factors such as high fasting plasma glucose and kidney dysfunction, with projections suggesting continued escalation of the burden by 2030.
Humans ; Global Burden of Disease ; Risk Factors ; Male ; Female ; Disability-Adjusted Life Years ; Diabetic Nephropathies/epidemiology* ; Middle Aged ; Diabetes Mellitus, Type 2/epidemiology* ; Adult ; Diabetes Mellitus, Type 1/complications* ; Aged ; Adolescent ; Young Adult ; Quality-Adjusted Life Years

Objective:To investigate the additional prognostic value of coronary CT angiography (CCTA)-based flow reserve fraction (CT-FFR) over semi-quantitative CCTA risk scores in predicting the occurrence of major adverse cardiovascular events (MACE) in type 2 diabetic patients.Methods:A total of 231 patients with type 2 diabetes mellitus who underwent CCTA at Lanzhou University from May 2020 to April 2021 were retrospectively enrolled. Clinical baseline data were collected, and patients were divided into a MACE-positive group (20 cases) and a MACE-negative group (211 cases) based on follow-up results. The CCTA images of all patients were analyzed by semi-quantitative CCTA risk score, which included coronary artery disease reporting and data system classification, segment involvement score, segmental stenosis score, Leaman score, and Leiden score. CT-FFR measurements of CCTA data of all patients were performed using Coronary Analysis software. t-test, U-test, and χ2 test were used to compare baseline parameters between MACE-positive and MACE-negative groups. The Cox proportional hazards regression model was used to analyze the relationship between semi-quantitative CCTA risk score and CT-FFR with the occurrence of MACE, and the area under the curve (AUC) of the receiver operating characteristic (ROC) was used to calculate the efficacy of the prediction model established by the semi-quantitative CCTA risk score combined with CT-FFR. Results:There was no statistically significant difference in baseline data between patients in the MACE-positive and MACE-negative groups ( P>0.05), and there were significant differences in semi-quantitative CCTA risk scores and CT-FFR ( P<0.05). Multivariate Cox proportional risk regression analysis of CT-FFR≤0.80 ( HR=3.860, 95% CI 1.477-10.087, P=0.006) and Leaman score≥5 ( HR=5.210, 95% CI 1.136-23.908, P=0.029) were the best and independent predictors for the occurrence of MACE events. The combined CT-FFR and Leaman score prediction model (AUC=0.791, 95% CI 0.733-0.842, P<0.001) was a better predictor of MACE than CT-FFR alone (AUC=0.718, 95% CI 0.656-0.775, P<0.001) and Leaman score alone (AUC=0.711, 95% CI 0.648-0.768, P<0.001) both had better predictive efficacy ( Z=2.62, 1.98, P=0.009, 0.047). Conclusion:CT-FFR independently predict the occurrence of MACE in patients with type 2 diabetes mellitus and significantly improve the predictive capacity of semi-quantitative CCTA risk score for MACE.

Colorectal cancer is one of the most common malignant tumors of the digestive system in clinical practice.The early detection of colorectal cancer based on artificial intelligence and its further assistance in clinical diagnosis and treatment hold significant clinical importance for achieving long-term benefits for patients.The development and validation of artificial intelligence software rely on high-quality,large-volume,and annotated colorectal cancer imaging datasets.This paper aims to provide a reference for constructing a high-quality colorectal cancer CT database,taking the construction of the database as an example.It discusses the complete process of database establishment,including database description,lesion annotation and storage,database quality evaluation and maintenance.The purpose is to ensure the high quality and exploitability of the source materials in the database,promote the sustainable and healthy development of the medical imaging artificial intelligence industry ecosystem,and accelerate the research,development,and application of industries related to artificial intelligence in colorectal cancer CT imaging.

Objective:To compare the clinical efficacy of fixed and non-fixed coronoid process fractures in the treatment of terrible triad of the elbow.Methods:Databases including CNKI, Wanfang Data Knowledge Service Platform, VIP, China Medical Journal Full-text Database, PubMed, Cochrane Library, Scopus and Web of Science were searched for relevant literatures on the treatment of elbow terrible triad. Postoperative elbow function score, range of motion, postoperative complications and other information were extracted, and meta-analysis was performed using Stata 18.0 statistical software.Results:A total of 139 patients from 5 literatures were included in the meta-analysis. All included literatures were in English, and the Newcastle-Ottawa Scale scores were 7-8 points. The results of meta-analysis showed that there was no statistically significant difference in the postoperative Mayo Elbow Performance Score (MEPS) between the two groups [ SMD=-0.33, 95% CI(-0.67, 0.01), P=0.061]. In Regan-Morrey type I and O'Driscoll type I coronoid process fractures, the MEPS of the coronoid fixation group was lower than that of the non-fixation group, and the difference was statistically significant [ SMD=-0.46, 95% CI(-0.88, -0.03), P=0.032]; the upper extremity functional disability score of the coronoid fixation group was higher than that of the non-fixation group, and the difference was statistically significant [ SMD=0.45, 95% CI(0.02, 0.89), P=0.041]. There were no statistically significant differences in the postoperative elbow flexion-extension range [ SMD=-0.31, 95% CI(-0.68, 0.07), P=0.109] and pronation-supination range [ SMD=-0.14, 95% CI(-0.51, 0.24), P=0.470] between the two groups. Conclusion:In the treatment of elbow terrible triad, the postoperative joint function score of non-fixation of Regan-Morrey type I and O'Driscoll type I coronoid process fractures is better than that of fixation.

Elemene is widely recognized as an effective anti-cancer compound and is routinely administered in Chinese clinical settings for the management of several solid tumors,including non-small cell lung cancer(NSCLC).However,its detailed molecular mechanism has not been adequately demonstrated.In this research,it was demonstrated that elemene effectively curtailed NSCLC growth in the patient-derived xenograft(PDX)model.Mechanistically,employing high-throughput screening techniques and subsequent biochemical validations such as microscale thermophoresis(MST),microRNA-145-5p(miR-145-5p)was pinpointed as a critical target through which elemene exerts its anti-tumor effects.Inter-estingly,elemene serves as a binding stabilizer for miR-145-5p,demonstrating a strong binding affinity(dissociation constant(KD)=0.39±0.17 μg/mL)and preventing its degradation both in vitro and in vivo,while not interfering with the synthesis of the primary microRNA transcripts(pri-miRNAs)and precursor miRNAs(pre-miRNAs).The stabilization of miR-145-5p by elemene resulted in an increased level of this miRNA,subsequently suppressing NSCLC progression through the miR-145-5p/mitogen-activated pro-tein kinase kinase kinase 3(MAP3K3)/nuclear factor kappaB(NF-κB)pathway.Our findings provide a new perspective on revealing the interaction patterns between clinical anti-tumor drugs and miRNAs.

BACKGROUND: Lung adenocarcinoma is an important pathohistologic subtype of non-small cell lung cancer (NSCLC). Invasive non-mucinous pulmonary adenocarcinomas (INMA) tend to have a poor prognosis due to their significant heterogeneity and diverse histologic components. Establishing a histologic grading system for INMA is crucial for evaluating its malignancy. In 2021, the International Association for the Study of Lung Cancer (IASLC) proposed that a new histological grading system could better stratify the prognosis of INMA patients. The aim of this study was to establish a visualized nomogram model to predict INMA IASLC grading preoperatively by means of dual-energy computed tomography (DECT), fractal dimension (FD), clinical features and conventional CT parameters. METHODS: A total of 112 patients with INMA who underwent preoperative DECT were retrospectively enrolled from March 2021 to January 2025. Patients were categorized into low-intermediate grade and high grade groups based on IASLC grading. The clinical characteristics and conventional CT parameters, including baseline features, biochemical markers, and serum tumor markers, were collected. DECT-derived parameters, including iodine concentration (IC), effective atomic number (eff-Z), and normalized IC (NIC), were collected and determined as NIC ratio (NICr) and fractal dimension (FD). Univariate analysis was employed to compare differences in conventional characteristics and DECT parameters between the two groups. Variables demonstrating statistical significance were subsequently incorporated into a multivariate Logistic regression analysis. A nomogram model integrating clinical data, conventional CT parameters, and DECT parameters was developed to identify independent predictors for IASLC grading of INMA. The discriminatory performance of the model was evaluated using receiver operating characteristic (ROC) curve analysis. RESULTS: Multivariate analysis identified smoking history [odds ratio (OR)=2.848, P=0.041], lobulation sign (OR=2.163, P=0.004), air bronchogram (OR=7.833, P=0.005), eff-Z in arterial phase (OR=4.266, P<0.001), and IC in arterial phase (OR=1.290, P=0.012) as independent and significant predictors for IASLC grading of INMA. The nomogram model constructed based on these indicators demonstrated optimal predictive performance, achieving an area under the curve (AUC) of 0.804 (95%CI: 0.725-0.883), with specificity and sensitivity of 85.3% and 65.7%, respectively. CONCLUSIONS The nomogram model based on clinical features, imaging features and spectral CT parameters have a large potential for application in the preoperative noninvasive assessment of INMA IASLC grading.
Humans ; Nomograms ; Female ; Male ; Middle Aged ; Tomography, X-Ray Computed/methods* ; Lung Neoplasms/pathology* ; Aged ; Retrospective Studies ; Adenocarcinoma of Lung/pathology* ; Neoplasm Grading ; Adult

Metastasis serves as an indicator of malignancy and is a biological characteristic of carcinomas. Epithelial-mesenchymal transition (EMT) plays a key role in the promotion of tumor invasion and metastasis and in the enhancement of tumor cell aggressiveness. Prostaglandin E synthase 3 (p23) is a cochaperone for heat shock protein 90 (HSP90). Our previous study showed that p23 is an HSP90-independent transcription factor in cancer-associated inflammation. The effect and mechanism of action of p23 on lung cancer metastasis are tested in this study. By utilizing cell models in vitro and mouse tail vein metastasis models in vivo, the results provide solid evidence that p23 is critical for promoting lung cancer metastases by regulating downstream CXCL1 expression. Rather than acting independently, p23 forms a complex with RNA-binding motif protein 14 (RBM14) to facilitate EMT progression in lung cancer. Therefore, our study provides evidence for the potential role of the RBM14-p23-CXCL1-EMT axis in the metastasis of lung cancer.

Elemene is widely recognized as an effective anti-cancer compound and is routinely administered in Chinese clinical settings for the management of several solid tumors, including non-small cell lung cancer (NSCLC). However, its detailed molecular mechanism has not been adequately demonstrated. In this research, it was demonstrated that elemene effectively curtailed NSCLC growth in the patient-derived xenograft (PDX) model. Mechanistically, employing high-throughput screening techniques and subsequent biochemical validations such as microscale thermophoresis (MST), microRNA-145-5p (miR-145-5p) was pinpointed as a critical target through which elemene exerts its anti-tumor effects. Interestingly, elemene serves as a binding stabilizer for miR-145-5p, demonstrating a strong binding affinity (dissociation constant (K _D) = 0.39 ± 0.17 μg/mL) and preventing its degradation both in vitro and in vivo, while not interfering with the synthesis of the primary microRNA transcripts (pri-miRNAs) and precursor miRNAs (pre-miRNAs). The stabilization of miR-145-5p by elemene resulted in an increased level of this miRNA, subsequently suppressing NSCLC progression through the miR-145-5p/mitogen-activated protein kinase kinase kinase 3 (MAP3K3)/nuclear factor kappaB (NF-κB) pathway. Our findings provide a new perspective on revealing the interaction patterns between clinical anti-tumor drugs and miRNAs.