Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

Ischemic stroke(IS) is a complex pathological process involving multiple cellular and molecular mechanisms and it is characterized by high mortality, high disability, and high recurrence. In recent years, the incidence of IS in China has been increasing year by year, and it has a trend of occurring in increasingly young individuals. Herb pairs are the smallest unit of traditional Chinese medicine(TCM) compatibility and an important part of TCM compounding, and the research on them is of great significance in guiding the clinical medication. Pharmacological studies have confirmed that certain herb pairs can exert anti-ischemic effects through various pathways such as reducing inflammation, alleviating oxidative stress, protecting the nervous system, and promoting neovascularization. By reviewing the relevant articles in the past decade, this paper probes into the combination rules, modern experimental studies, and combination ratios of the commonly used herb pairs from the etiology and pathogenesis of IS and summarizes 18 commonly used and deeply studied herb pairs, with a view to providing reference for the application, research, and development of clinical medicines.
Humans ; Drugs, Chinese Herbal/chemistry* ; Animals ; Ischemic Stroke/metabolism* ; Medicine, Chinese Traditional

OBJECTIVE: To evaluate the dynamic changes of glucocorticoid (GC) dose and the feasibility of GC discontinuation in rheumatoid arthritis (RA) patients under the background of Chinese medicine (CM). METHODS: This multicenter retrospective cohort study included 1,196 RA patients enrolled in the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from September 1, 2019 to December 4, 2023, who initiated GC therapy. Participants were divided into the Western medicine (WM) and integrative medicine (IM, combination of CM and WM) groups based on medication regimen. Follow-up was performed at least every 3 months to assess dynamic changes in GC dose. Changes in GC dose were analyzed by generalized estimator equation, the probability of GC discontinuation was assessed using Kaplan-Meier curve, and predictors of GC discontinuation were analyzed by Cox regression. Patients with <12 months of follow-up were excluded for the sensitivity analysis. RESULTS: Among 1,196 patients (85.4% female; median age 56.4 years), 880 (73.6%) received IM. Over a median 12-month follow-up, 34.3% (410 cases) discontinued GC, with significantly higher rates in the IM group (40.8% vs. 16.1% in WM; P<0.05). GC dose declined progressively, with IM patients demonstrating faster reductions (median 3.75 mg vs. 5.00 mg in WM at 12 months; P<0.05). Multivariate Cox analysis identified age <60 years [P<0.001, hazard ratios (HR)=2.142, 95% confidence interval (CI): 1.523-3.012], IM therapy (P=0.001, HR=2.175, 95% CI: 1.369-3.456), baseline GC dose ⩽7.5 mg (P=0.003, HR=1.637, 95% CI: 1.177-2.275), and absence of non-steroidal anti-inflammatory drugs use (P=0.001, HR=2.546, 95% CI: 1.432-4.527) as significant predictors of GC discontinuation. Sensitivity analysis (545 cases) confirmed these findings. CONCLUSIONS RA patients receiving CM face difficulties in following guideline-recommended GC discontinuation protocols. IM can promote GC discontinuation and is a promising strategy to reduce GC dependency in RA management. (Trial registration: ClinicalTrials.gov, No. NCT05219214).
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Arthritis, Rheumatoid/drug therapy* ; Glucocorticoids/therapeutic use* ; Medicine, Chinese Traditional ; Retrospective Studies

Cancer is a serious global health problem and a major cause of human death. Conventional cancer treatments often run the risk of impairing vital organ functions. Anticancer peptides (ACPs) are considered to be one of the most promising therapeutic agents against common human cancers due to their small sizes, high specificity, and low toxicity. Since ACP recognition is highly limited to the laboratory, expensive, and time-consuming, we proposed pLM4ACP, a model for predicting ACPs based on machine learning and protein language models. In this model, the protein language model ProtT5 was used to extract the features of ACPs, and the extracted features were input into the support vector machine (SVM) classification algorithm for optimization and performance evaluation. The model showcased significantly higher accuracy than other methods, with the overall accuracy of 0.763, F1-score of 0.767, Matthews correlation coefficient of 0.527, and area under the curve of 0.827 on the independent test set. This study constructs an efficient anticancer peptide prediction model based on protein language models, further advancing the application of artificial intelligence in the biomedical field and promoting the development of precision medicine and computational biology.
Machine Learning ; Antineoplastic Agents/chemistry* ; Humans ; Peptides/chemistry* ; Support Vector Machine ; Algorithms ; Computational Biology/methods* ; Neoplasms/drug therapy*

Hepatohilar cholangiocarcinoma is a common malignant tumor of the biliary system,and radical surgery is one of the important treatment methods.Due to the narrow space at the hi-lum and the high rate of anatomical variation,radical surgery is challenging.By using medical imag-ing technology and 3D reconstruction,surgeons can accurately determine the stage and classifica-tion of hilar cholangiocarcinoma preoperatively.They can assess the tumor's resectability by Ac-cording to the bile duct separation limit points(U point,P point)and anticipate the impact of portal vein,bile duct,and arterial variations on the surgical plan,thereby improving the rate of radical re-section and reducing complication rates.

OBJECTIVE: To explore the prevalence and clinical manifestations of ring chromosomes among children featuring abnormal development. METHODS: From January 2015 to August 2021, 7574 children referred for abnormal development were selected, and their peripheral blood samples were subjected to G-banded chromosomal karyotyping analysis. RESULTS: Twelve cases of ring chromosomes were detected, which have yielded a prevalence of 0.16% and included 1 r(6), 2 r(9), 1 r(13), 1 r(14), 2 r(15), 1 r(21) and 3 r(X). The children had various clinical manifestations including growth and mental retardation, limb malformation, and congenital heart disease. For two children with r(9) and two with r(15) with similar breakpoints, one child with r(9) and one with r(15) only had growth retardation, whilst another with r(9) and another with r(15) also had peculiar facies and complex congenital heart disease. The r(X) has featured some manifestations of Turner syndrome. CONCLUSION Ring chromosomes are among the common causes for severe growth and mental retardation in children with diverse clinical phenotypes. Clinicians should pay attention to those with developmental anomalies and use chromosomal analysis to elucidate their genetic etiology.
Humans ; Ring Chromosomes ; Intellectual Disability/genetics* ; Turner Syndrome/genetics* ; Phenotype ; Heart Defects, Congenital/genetics*

Rats ; Animals ; Urinary Bladder Neck Obstruction/pathology* ; Survivin/genetics* ; Urinary Bladder/pathology* ; Fibrosis

Objective: To explore the mechanism of exosome-derived LncRNA ESCCAL-1 regulating the miR-874 /ITGBL1 axis in the progression of colorectal cancer ( CRC) ． Methods : The differentially expressed genes in CRC were analyzed using the Gene Expression Omnibus( GEO) database．Expressions of LncRNA ESCCAL-1，miR-874 and ITGBL1 in CRC tissues and cell lines (SW480，SW620，HCT116 and HT29) and adjacent normal tissues and NCM460 cell lines were detected by qRT-PCR ; 3-( 4，5-dimethylthiazol-2-yl ) -2，5diphenyltetrazoliumbromide (MTT) ，clone formation and flow cytometry was used to detect cell proliferation，colony formation and apoptosis ; dual luciferase reporter assays were used to verify the interaction between miR-874 and ESCCAL-1，ITGBL1 ; fluorescence in situ hybridization was used to determine the subcellular localization of LncRNAESCCAL-1 ．Exosomes were isolated from serum using the Exosome extraction kit. Results : The expressions of ESCCAL-1 and ITGBL1 in CRC tissues and cell lines were higher than those in adjacent normal tissues and NCM460 cell lines，while the opposite was true for miR-874 (P＜0. 05) ．Knockdown of ESCCAL-1 can inhibit CRC cell proliferation and colony formation and promote apoptosis．There are specific binding sites formiR-874 and ESCCAL-1，and miR-874 inhibitor could partially reverse the effect of knockdown ESCCAL-1 in CRC (P＜0. 05) ．ESCCAL-1 upregulates ITGBL1 by adsorbing miR-874．The serum levels of ESCCAL-1 and exo-ESCCAL-1 in CRC patients were higher than those in the control group．Serum exo-ESCCAL-1 may be a valuable diagnostic indicator for CRC treatment (P＜0. 05) . Conclusion ESCCAL-1 promotes CRC progression by regulating the miR-874/ ITGBL1 axis，and ESCCAL-1 may be an effective molecular target for CRC therapy.

This study aimed to assess the role of prostate-specific antigen density (PSAD) and negative multiparametric magnetic resonance imaging (mpMRI) in predicting prostate cancer for biopsy-naïve men based on a large cohort of the Chinese population. From a prostate biopsy database between March 2017 and July 2021, we retrospectively identified 240 biopsy-naïve patients with negative prebiopsy mpMRI (Prostate Imaging Reporting and Data System version 2 [PI-RADS v2] score <3). Logistic regression analysis was performed to select the potential predictors for clinically significant prostate cancer (csPCa). Receiver operating characteristic (ROC) curve analysis and area under the ROC curve (AUC) were performed to assess the diagnostic accuracy. The negative predictive values of mpMRI in excluding any cancer and csPCa were 83.8% (201/240) and 90.8% (218/240), respectively. ROC curve analysis indicated that PSAD was the most promising predictor, with an AUC value of 0.786 (95% confidence interval [CI]: 0.699-0.874), and multiparametric logistic regression analysis confirmed that higher PSAD remained a significant marker for predicting csPCa (odds ratio [OR]: 10.99, 95% CI: 2.75-44.02, P < 0.001). Combining negative mpMRI and PSAD below 0.20 ng ml^-2 obviously increased the predictive value in excluding PCa (91.0%, 101/111) or csPCa (100.0%, 111/111). If a PSAD below 0.20 ng ml^-2 was set as the criterion to omit biopsy, nearly 46.3% of patients (463 per 1000) with negative mpMRI could safely avoid unnecessary biopsy, with approximately 4.2% of patients (42 per 1000) at risk of missed diagnosis of PCa and no patients with csPCa missed. A PI-RADS v2 score <3 and a PSAD <0.20 ng ml^-2 could be potential criteria for the Chinese population to omit prompt biopsy safely.
Male ; Humans ; Prostatic Neoplasms/pathology* ; Prostate-Specific Antigen ; Multiparametric Magnetic Resonance Imaging ; Magnetic Resonance Imaging/methods* ; Retrospective Studies ; Biopsy ; Image-Guided Biopsy/methods*

Objective: To retrospectively analyze the data of Chinese patients with newly diagnosed acute promyelocytic leukemia (APL) to preliminarily discuss the clinical and cytogenetic characteristics. Methods: From February 2004 to June 2020, patients with newly diagnosed APL aged ≥ 15 years who were admitted to the Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Science & Peking Union Medical College were chosen. Clinical and laboratory features were retrospectively analyzed. Results: A total of 790 cases were included, with a male to female ratio of 1.22. The median age of the patients was 41 (15-76) years. Patients aged between 20 and 59 predominated, with 632 patients (80%) of 790 patients classified as low and intermediate risk and 158 patients (20%) of 790 patients classified as high risk. The white blood cell, platelet, and hemoglobin levels at diagnosis were 2.3 (0.1-176.1) ×10(9)/L, 29.5 (2.0-1220.8) ×10(9)/L, and 89 (15-169) g/L, respectively, and 4.8% of patients were complicated with psoriasis. The long-form type of PML-RARα was most commonly seen in APL, accounting for 58%. Both APTT extension (10.3%) and creatinine>14 mg/L (1%) are rarely seen in patients at diagnosis. Cytogenetics was performed in 715 patients with newly diagnosed APL. t (15;17) with additional chromosomal abnormalities were found in 155 patients, accounting for 21.7%; among which, +8 was most frequently seen. A complex karyotype was found in 64 (9.0%) patients. Next-generation sequencing was performed in 178 patients, and 113 mutated genes were discovered; 75 genes had an incidence rate>1%. FLT3 was the most frequently seen, which accounted for 44.9%, and 20.8% of the 178 patients present with FLT3-ITD. Conclusions: Patients aged 20-59 years are the most common group with newly diagnosed APL. No obvious difference was found in the ratio of males to females. In terms of risk stratification, patients divided into low and intermediate risk predominate. t (15;17) with additional chromosomal abnormalities accounted for 21% of 715 patients, in which +8 was most commonly seen. The long-form subtype was most frequently seen in PML-RARα-positive patients, and FLT3 was most commonly seen in the mutation spectrum of APL.
Adult ; Aged ; Chromosome Aberrations ; Cytogenetics ; Female ; Humans ; Leukemia, Promyelocytic, Acute/genetics* ; Male ; Middle Aged ; Mutation ; Oncogene Proteins, Fusion/genetics* ; Retrospective Studies ; Young Adult