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.

This paper aimed to explore the effects of Duzhong Decoction(DZD)-containing serum on the proliferation and osteoblast differentiation of MC3T3-E1 cells through L-type voltage-gated calcium channels(L-VGCCs). L-VGCCs inhibitors, nifedipine and verapamil, were used to block L-VGCCs in osteoblasts. MC3T3-E1 cells were divided into a control group, a low-dose DZD-containing serum(L-DZD) group, a medium-dose DZD-containing serum(M-DZD) group, a high-dose DZD-containing serum(H-DZD) group, a nifedipine group, a H-DZD + nifedipine group, verapamil group, and a H-DZD + verapamil group. The CCK-8 method was used for cell proliferation analysis, alkaline phosphatase(ALP) assay kits for intracellular ALP activity measurement, Western blot for protein expression level in cells, real-time fluorescence quantitative PCR technology for intracellular mRNA expression level determination, fluorescence spectrophotometer for free Ca~(2+) concentration determination in osteoblasts, and alizarin red staining(ARS) for mineralized nodule formation in osteoblasts. The experimental results show that compared to the control group, DZD groups can promote MC3T3-E1 cell proliferation, ALP activity, and mineralized nodule formation, increase intracellular Ca~(2+) concentrations, and upregulate the protein expression of bone morphogenetic protein 2(BMP2), collagen Ⅰ(COL1), α2 subunit protein of L-VGCCs(L-VGCCα2), and the mRNA expression of Runt-related transcription factor 2(RUNX2), and BMP2. After blocking L-VGCCs with nifedipine and verapamil, the intervention effects of DZD-containing serum were inhibited to varying degrees. Both nifedipine and verapamil could inhibit ALP activity, reduce mineralized nodule areas, and downregulate the expression of bone formation-related proteins. Moreover, the effects of DZD-containing serum on increasing MC3T3-E1 cell proliferation, osteoblast differentiation, and Ca~(2+) concentrations, upregulating the mRNA expression of osteoprotegerin(OPG) and protein expression of phosphorylated protein kinase B(p-Akt) and phosphorylated forkhead box protein O1(p-FOXO1), and upregulating phosphatase and tensin homolog(PTEN) expression were reversed by nifedipine. The results indicate that DZD-containing serum can increase the Ca~(2+) concentration in MC3T3-E1 cells to promote bone formation, which may be mediated by L-VGCCs and the PTEN/Akt/FoxO1 signaling pathway, providing a new perspective on the mechanism of DZD in treating osteoporosis.
Animals ; Osteoblasts/metabolism* ; Cell Proliferation/drug effects* ; Cell Differentiation/drug effects* ; Mice ; Drugs, Chinese Herbal/pharmacology* ; Calcium Channels, L-Type/genetics* ; Alkaline Phosphatase/genetics* ; Serum/chemistry* ; Cell Line ; Osteogenesis/drug effects* ; Bone Morphogenetic Protein 2/genetics*

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

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*

Hepatic stellate cells (HSCs) are the primary fibrogenic cells in the liver, and their activation plays a crucial role in the development and progression of hepatic fibrosis. Here, we report that retinoid X receptor-alpha (RXRα), a unique member of the nuclear receptor superfamily, is a key modulator of HSC activation and liver fibrosis. RXRα exerts its effects by modulating calcium/calmodulin-dependent protein kinase kinase β (CaMKKβ)-mediated activation of AMP-activated protein kinase-alpha (AMPKα). In addition, we demonstrate that K-80003, which binds RXRα by a unique mechanism, effectively suppresses HSC activation, proliferation, and migration, thereby inhibiting liver fibrosis in the CCl₄ and amylin liver NASH (AMLN) diet animal models. The effect is mediated by AMPKα activation, promoting mitophagy in HSCs. Mechanistically, K-80003 activates AMPKα by inducing RXRα to form condensates with CaMKKβ and AMPKα via a two-phase process. The formation of RXRα condensates is driven by its N-terminal intrinsic disorder region and requires phosphorylation by CaMKKβ. Our results reveal a crucial role of RXRα in liver fibrosis regulation through modulating mitochondrial activities in HSCs. Furthermore, they suggest that K-80003 and related RXRα modulators hold promise as therapeutic agents for fibrosis-related diseases.

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

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

Purpose::The toughest challenge in pedestrian traffic accident identification lies in ascertaining injury manners. This study aimed to systematically simulate and parameterize 3 types of craniocerebral injury including impact injury, fall injury, and run-over injury, to compare the injury response outcomes of different injury manners.Methods::Based on the total human model for safety (THUMS) and its enhanced human model THUMS-hollow structures, a total of 84 simulations with 3 injury manners, different loading directions, and loading velocities were conducted. Von Mises stress, intracranial pressure, maximum principal strain, cumulative strain damage measure, shear stress, and cranial strain were employed to analyze the injury response of all areas of the brain. To examine the association between injury conditions and injury consequences, correlation analysis, principal component analysis, linear regression, and stepwise linear regression were utilized.Results::There is a significant correlation observed between each criterion of skull and brain injury ( p < 0.01 in all Pearson correlation analysis results). A 2-phase increase of cranio-cerebral stress and strain as impact speed increases. In high-speed impact (> 40 km/h), the Von Mises stress on the skull was with a high possibility exceed the threshold for skull fracture (100 MPa). When falling and making temporal and occipital contact with the ground, the opposite side of the impacted area experiences higher frequency stress concentration than contact at other conditions. Run-over injuries tend to have a more comprehensive craniocerebral injury, with greater overall deformation due to more adequate kinetic energy conduction. The mean value of maximum principal strain of brain and Von Mises stress of cranium at run-over condition are 1.39 and 403.8 MPa, while they were 1.31, 94.11 MPa and 0.64, 120.5 MPa for the impact and fall conditions, respectively. The impact velocity also plays a significant role in craniocerebral injury in impact and fall loading conditions (the p of all F-test < 0.05). A regression equation of the craniocerebral injury manners in pedestrian accidents was established. Conclusion::The study distinguished the craniocerebral injuries caused in different manners, elucidated the biomechanical mechanisms of craniocerebral injury, and provided a biomechanical foundation for the identification of craniocerebral injury in legal contexts.

Objective To systematically search,evaluate and summarize the best evidence for prevention and management of extravasation in peripheral intravenous infusion in NICU neonates,and provide a reference for clinical practice and standard formulation.Methods A comprehensive systematic search of websites and databases was conducted to explore literature on prevention and management of extravasation in NICU neonates,including clinical decisions,guidelines,expert consensuses,evidence summaries and systematic reviews.The search encompassed the entire period from database inception to July 2023.2 researchers independently evaluated the quality of the literature,extracted and integrated the evidence.Results The study included a total of 9 articles,comprising 1 clinical decision,3 guidelines,3 expert consensus documents,and 2 evidence summaries.Ultimately,25 pieces of evidence were synthesized,covering risk factors,catheter indwelling and maintenance,extravasation assessment and treatment,and team building,education and training.Conclusion The evidence provided practical and specific recommendations that can guide healthcare institutions in formulating strategies to prevent and treat extravasation during peripheral intravenous infusion in NICU neonates,while also offering evidence-based guidance for applying the evidence in clinical practice.

Recently, deep learning has achieved impressive results in medical image tasks. However, this method usually requires large-scale annotated data, and medical images are expensive to annotate, so it is a challenge to learn efficiently from the limited annotated data. Currently, the two commonly used methods are transfer learning and self-supervised learning. However, these two methods have been little studied in multimodal medical images, so this study proposes a contrastive learning method for multimodal medical images. The method takes images of different modalities of the same patient as positive samples, which effectively increases the number of positive samples in the training process and helps the model to fully learn the similarities and differences of lesions on images of different modalities, thus improving the model's understanding of medical images and diagnostic accuracy. The commonly used data augmentation methods are not suitable for multimodal images, so this paper proposes a domain adaptive denormalization method to transform the source domain images with the help of statistical information of the target domain. In this study, the method is validated with two different multimodal medical image classification tasks: in the microvascular infiltration recognition task, the method achieves an accuracy of (74.79 ± 0.74)% and an F1 score of (78.37 ± 1.94)%, which are improved as compared with other conventional learning methods; for the brain tumor pathology grading task, the method also achieves significant improvements. The results show that the method achieves good results on multimodal medical images and can provide a reference solution for pre-training multimodal medical images.
Humans ; Algorithms ; Brain/diagnostic imaging* ; Brain Neoplasms/diagnostic imaging* ; Recognition, Psychology