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.

OBJECTIVE To systematically investigate the changes of volatile components in Euphorbia wallichii after milk and wine processing， and preliminarily elucidate the material basis for reducing toxicity. METHODS Using headspace gas chromatography-mass spectrometry technology， the volatile components in raw E. wallichii， milk-processed E. wallichii， and wine- processed E. wallichii were isolated and identified， and the relative percentage content of each component was calculated by the peak area normalization method. Combining chemometric methods such as principal component analysis and orthogonal partial least- squares discriminant analysis， changes in volatile components in samples after milk and wine processing were compared. Differential components were screened. RESULTS A total of 66 volatile components were identified from the three samples， with the types of compounds primarily comprising alkanes， olefins， heterocycles and esters， among others. A total of 39， 24 and 36 volatile components were identified from raw E. wallichii， milk-processed E. wallichii， and wine-processed E. wallichii， respectively， with 10 components common to all three preparations. Compared with raw E. wallichii， the relative percentage of other components in milk-processed E. wallichii decreased， except for alkanes and esters. The relative percentage of alkanes， olefins， aldehydes and esters in wine-processed E. wallichii increased， but the contents of heterocyclic compounds， ketones， ethers and alcohols decreased. The results of chemometric analysis showed that the volatile components of raw and processed products were significantly different. A total of 5 kinds of differential components in milk-processed products and 3 kinds of differential components in wine-processed products were screened out. Among them， the relative percentage of potential toxic components such as linalool， octanal and 3-pentanone decreased significantly after processing（P＜0.05）. CONCLUSIONS Milk and wine processing may exert a toxicity-reducing effect by reducing the contents of toxic components such as linalool， octanal and 3-pentanonein E. wallichii.

The differences in chemical quality characteristics between Xinjiang Rehmannia glutinosa and R. glutinosa were analyzed to provide a theoretical basis for the introduction and quality control of R. glutinosa. In this study, the high performance liquid chromatography(HPLC) fingerprints of 6 batches of Xinjiang R. glutinosa and 10 batches of R. glutinosa samples were established. The content of iridoid glycosides, phenylethanoid glycosides, monosaccharides, oligosaccharides, and polysaccharides in Xinjiang R. glutinosa and R. glutinosa was determined by high performance liquid chromatography-diode array detection(HPLC-DAD), high performance liquid chromatography-evaporative light scattering detection(HPLC-ELSD), and ultraviolet-visible spectroscopy(UV-Vis). The determination results were analyzed with by chemical pattern recognition and entropy weight TOPSIS method. The results showed that there were 19 common peaks in the HPLC fingerprints of the 16 batches of R. glutinosa, and catalpol, aucubin, rehmannioside D, rehmannioside A, hydroxytyrosol, leonuride, salidroside, cistanoside A, and verbascoside were identified. Hierarchical cluster analysis(HCA) and principal component analysis(PCA) showed that Qinyang R. glutinosa, Mengzhou R. glutinosa, and Xinjiang R. glutinosa were grouped into three different categories, and eight common components causing the chemical quality difference between Xinjiang R. glutinosa and R. glutinosa in Mengzhou and Qinyang of Henan province were screened out by orthogonal partial least squares discriminant analysis(OPLS-DA). The results of content determination showed that there were glucose, sucrose, raffinose, stachyose, polysaccharides, and nine glycosides in Xinjiang R. glutinosa and R. glutinosa samples, and the content of catalpol, rehmannioside A, leonuride, cistanoside A, verbascoside, sucrose, and glucose was significantly different between Xinjiang R. glutinosa and R. glutinosa. The analysis with entropy weight TOPSIS method showed that the comprehensive quality of R. glutinosa in Mengzhou and Qinyang of Henan province was better than that of Xinjiang R. glutinosa. In conclusion, the types of main chemical components of R. glutinosa and Xinjiang R. glutinosa were the same, but their content was different. The chemical quality of R. glutinosa was better than Xinjiang R. glutinosa, and other components in R. glutinosa from two producing areas and their effects need further study.
Rehmannia/classification* ; Drugs, Chinese Herbal/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Quality Control

OBJECTIVE: To explore and quantify the association of hot night exposure during the sperm development period (0-90 lag days) with semen quality. METHODS: A total of 6,640 male sperm donors from 6 human sperm banks in China during 2014-2020 were recruited in this multicenter study. Two indices (i.e., hot night excess [HNE] and hot night duration [HND]) were used to estimate the heat intensity and duration during nighttime. Linear mixed models were used to examine the association between hot nights and semen quality parameters. RESULTS: The exposure-response relationship revealed that HNE and HND during 0-90 days before semen collection had a significantly inverse association with sperm motility. Specifically, a 1 °C increase in HNE was associated with decreased sperm progressive motility of 0.0090 (95% confidence interval [ CI]: -0.0147, -0.0033) and decreased total motility of 0.0094 (95% CI: -0.0160, -0.0029). HND was significantly associated with reduced sperm progressive motility and total motility of 0.0021 (95% CI: -0.0040, -0.0003) and 0.0023 (95% CI: -0.0043, -0.0002), respectively. Consistent results were observed at different temperature thresholds on hot nights. CONCLUSION Our findings highlight the need to mitigate nocturnal heat exposure during spermatogenesis to maintain optimal semen quality.
Humans ; Male ; Semen Analysis ; Adult ; Sperm Motility ; Hot Temperature/adverse effects* ; China ; Middle Aged ; Spermatozoa/physiology* ; Young Adult

Insulin-like growth factor 2 (IGF2) is a critical endocrine mediator implicated in male reproductive physiology. To investigate the correlation between IGF2 protein levels and various aspects of male infertility, specifically focusing on sperm quality, inflammation, and DNA damage, a cohort of 320 male participants was recruited from the Women's Hospital, Zhejiang University School of Medicine (Hangzhou, China) between 1 st January 2024 and 1 st March 2024. The relationship between IGF2 protein concentrations and sperm parameters was assessed, and Spearman correlation and linear regression analysis were employed to evaluate the independent associations between IGF2 protein levels and risk factors for infertility. Enzyme-linked immunosorbent assay (ELISA) was used to measure IGF2 protein levels in seminal plasma, alongside markers of inflammation (tumor necrosis factor-alpha [TNF-α] and interleukin-1β [IL-1β]). The relationship between seminal plasma IGF2 protein levels and DNA damage marker phosphorylated histone H2AX (γ-H2AX) was also explored. Our findings reveal that IGF2 protein expression decreased notably in patients with asthenospermia and teratospermia. Correlation analysis revealed nuanced associations between IGF2 protein levels and specific sperm parameters, and low IGF2 protein concentrations correlated with increased inflammation and DNA damage in sperm. The observed correlations between IGF2 protein levels and specific sperm parameters, along with its connection to inflammation and DNA damage, underscore the importance of IGF2 in the broader context of male reproductive health. These findings lay the groundwork for future research and potential therapeutic interventions targeting IGF2-related pathways to enhance male fertility.
Humans ; Male ; Insulin-Like Growth Factor II/metabolism* ; Infertility, Male/genetics* ; DNA Damage ; Adult ; Inflammation/metabolism* ; Spermatozoa/metabolism* ; Semen Analysis ; Semen/metabolism* ; Tumor Necrosis Factor-alpha/metabolism* ; Histones/metabolism* ; Interleukin-1beta/metabolism*

Background Under the background of global warming, research on association between ambient temperature and risk of injury is needed. Objective To examine the effect of temperature on injury in Bao'an district, Shenzhen and identify the sensitive population, thereby providing a scientific basis for formulating prevention and control strategies and measures of injury. Methods The injury reports from the Injury Surveillance System and the meteorological data of Bao'an District between 2018 to 2022 were collected. The meteorological data were sourced from the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) land reanalysis data. Based on time-stratified case-crossover design, conditional logistic regression combined with distributed lag nonlinear model was used to evaluate the exposure-response association between ambient temperature and injury. The stratified analyses were further conducted by gender, age, and causes of injury. Results A total of 156205 injury cases were collected from the injury surveillance sentinel hospitals in Bao'an District of Shenzhen from 2018 to 2022, and the median of daily average temperature during the same period was 20.0 ℃. The exposure-response curve showed that the risk of injury was positively correlated with temperature. The linearized analysis revealed that each 1°C increase in temperature was associated with a 1.05% (95%CI: 0.68%, 1.42%) rise in injury risk (ER). Notably, the effect was greater in females (ER=1.31%, 95%CI: 0.67%, 1.94%) than males (ER=0.92%, 95%CI: 0.47%, 1.37%). Among age groups, adults ＞60 years faced the highest risk (ER=1.91%, 95%CI: −0.36%, 4.24%). The top three temperature-associated injury risks were sharp instrument injuries (ER=2.19%, 95%CI: 1.16%, 3.22%), animal injuries (ER=1.71%, 95%CI: 0.86%, 2.56%), and blunt injuries (ER=071%, 95%CI: −0.08%, 1.51%). The impact of temperature on unintentional injuries (ER=1.11%, 95%CI: 0.72%, 1.49%) was higher than that on intentional injuries (ER=0.43%, 95%CI: −0.85%, 1.72%). Severe injuries (ER=2.20%, 95%CI: −3.09%, 7.77%) were more affected by temperature than mild injuries (ER=1.00%, 95%CI: 0.58%, 1.43%) and moderate injuries (ER=1.15%, 95%CI: 0.42%, 1.89%). Conclusion The increase in ambient temperature associates with injury occurrence, and the impact of temperature exhibits obvious heterogeneity among different populations, indicating that targeted intervention measures should be taken for different populations and types of injuries.

Yttrium-90 selective internal radiation therapy (⁹⁰Y-SIRT) is a treatment technique that delivers radioactive microspheres precisely to the arterial vascular bed of neoplasms, utilizing beta radiation to administer a high local dose of radiation to the neoplasm tissues. This technology has demonstrated significant efficacy in patients with unresectable pirmary liver cancers and liver metastases. This article systematically reviews the development history and clinical application status of ⁹⁰Y-SIRT in the treatment of liver cancer, and looks forward to future development directions.

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

Objective:To assess the efficacy and safety of azacitidine combined with lenalidomide in MDS patients and explore potential mechanisms of therapeutic response.Methods:Sixteen MDS patients with TP53 mutations received azacitidine plus lenalidomide at ZhongDa Hospital, Southeast University (January 2021–June 2025). Efficacy and safety were assessed, and TP53 mutation status was correlated with treatment response. Whole-transcriptome sequencing and bioinformatics were used to explore molecular biomarkers associated with therapeutic efficacy.Results:Sixteen patients (median age 69.5 years, range 52–82; 8 males, 8 females) were enrolled. According to the Molecular International Prognostic Scoring System (IPSS-M), 1, 2, and 13 patients were classified as median low, high, and very high risk, respectively. Among 16 TP53-mutated patients, 11 had biallelic mutations and 5 had monoallelic mutations. Overall response rate was 56.3% (9/16), composite complete remission rate (CRc) was 31.3% (5/16), and hematology improvement rate was 25% (4/16). Among TP53-mutated patients, the response rate was 56.3% (9/16), with variant allele frequency dropping from 65.6% to 16.5% in responders ( P=0.017). In patients with TP53 mutations and complex karyotype, response rate was 53.8% (7/13), with 57.1% (4/7) showing disappearance of CK post-treatment. The most common grade 3–4 nonhematologic adverse events were infections (9/16, 56.3% ), including pneumonia (4/16, 25.0% ), gastrointestinal infections (3/16, 18.8% ), perianal infections (1/16, 6.3% ) and sepsis (1/16, 6.3% ). High CBX8 expression may be linked to treatment response. Conclusion:Azacitidine plus lenalidomide is an effective and safe therapy for MDS, including patients with TP53 mutations and complex karyotypes. Treatment markedly reduces TP53 variant allele frequency in responders, and high CBX8 expression may predict therapeutic response.

Objective To analyze the serum metabolomic changes of preterm infants with bronchopulmonary dysplasia(BPD)at postmenstrual age(PMA)36 weeks,screen potential biomarkers and associated metabolic pathways,and assess their relationship with short-term respiratory outcomes.Methods A retrospective case-control study was conducted.Infants with gestational age 28-32 weeks admitted to the Children's Hospital Affiliated to Zhengzhou University from January to December 2024 were included.Twenty infants with BPD and 20 gestational age-,birth weight-,and sex-matched non-BPD preterm infants were included.Serum collected at PMA 36 weeks was subjected to untargeted metabolomics analysis,and associations with short-term respiratory outcomes were analyzed.Results Thirteen potential biomarkers distinguishing BPD were identified(area under the curve>0.75,P<0.05).Eight biomarkers—including terephthalic acid,phosphatidylinositol,fumarate,and lysophosphatidic acid—were significantly upregulated(FC≥1.5),while five biomarkers,such as 7α-hydroxy-3-oxo-4-cholestenoate ester and phosphatidylcholine,were significantly downregulated(FC≤1/1.5).Pathway analysis indicated five pathways associated with BPD,including glycerophospholipid metabolism and phenylalanine metabolism.Dysregulation of glycerophospholipid and bile acid metabolism may affect adverse short-term respiratory outcomes in infants with BPD.Conclusions The 13 significantly different metabolites may serve as biomarkers for the diagnosis of BPD.Glycerophospholipid metabolism is associated with the occurrence of BPD and with adverse short-term respiratory outcomes.