The promulgation of the Technical Specifications for Clinical Use of Blood (2025 Edition) signifies that China's clinical blood transfusion management has transitioned from mere technical operations to a new stage centered on patient blood management (PBM). Through an in-depth comparison of the new and old specifications, this paper analyzes the core transformations regarding conceptual reconstruction, legal alignment, technological upgrades, and closed-loop management. The new specifications establish PBM principles, reinforce legal safeguards for informed consent and emergency treatment, and construct a comprehensive, refined quality control system by specifying compatibility testing standards and introducing a post-transfusion evaluation system. Medical institutions should seize this opportunity to update management protocols and information systems, deepen multidisciplinary collaboration, and drive the profound transformation of clinical blood use from focusing solely on safety assurance to placing equal emphasis on science and value.

The American Heart Association (AHA) and the American College of Cardiology (ACC), in collaboration with multiple professional organizations, jointly released the "Guideline for the Prevention, Detection, Evaluation and Management of High Blood Pressure in Adults" in August 2025. Based on the latest evidence-based medical findings from February 2015 to January 2025, the guideline proposes an individualized treatment strategy grounded in total cardiovascular disease risk stratification, incorporates the novel PREVENT risk assessment model, lowers the medication initiation threshold and control targets for high-risk populations, and provides specific management recommendations for special populations. This article provides an interpretation of these updates and conducts a comparative analysis with the current status of hypertension prevention and treatment in China as well as Chinese guidelines, aiming to offer reference for hypertension control practices in China.

The American Heart Association (AHA) officially released the "2025 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association" on January 27, 2025. This report systematically compiles the latest statistics on major cardiovascular diseases worldwide, while simultaneously integrating relevant outcome indicators, including quality of care, procedures, and economic costs, and updating the global prevalence patterns and evolving trends of diverse risk factors impacting cardiovascular health, providing essential guidance for the prevention, diagnosis, and treatment of cardiovascular diseases. Synthesizing insights from this pivotal report and other relevant studies, this article highlights key findings concerning the global prevalence and mortality of heart diseases, associated risk factors, and emerging diagnostic and therapeutic technologies.

Hyperuricemia （HUA） is a common metabolic disorder characterized by persistently elevated serum uric acid levels, leading to uric acid-related renal injury through complex mechanisms involving inflammation, oxidative stress, and fibrosis. Key traditional Chinese medicine （TCM） formulas （e.g., Simiao Powder, Tongfengning） and individual herbal compounds （alkaloids, flavonoids, polysaccharides） with urate-lowering and renal protective properties were systematically summarized, including their mechanisms of regulating uric acid transporters （organic anion transporter 3, urate anion transporter 1, glucose transporter type 9）, inhibiting inflammatory responses （via NF-κB signaling）, reducing oxidative stress （via mitochondrial pathways and antioxidant enzyme enhancement）, and attenuating renal fibrosis （via PI3K/AKT signaling）. The challenges of current studies mainly focus on unclear mechanisms of action and insufficient clinical research. Future research may further explore TCM resources, clarify dual-action mechanisms of urate reduction and renal protection, and identify new therapeutic strategies for hyperuricemia-related renal injury.

OBJECTIVE To form an expert consensus addressing clinical issues regarding the use of parenteral direct thrombin inhibitors （DTIs） in special populations. METHODS Led by the Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital（the Affiliated Hospital of UESTC）， a multidisciplinary working group was formed comprising experts from multiple fields， including clinical pharmacy， cardiac surgery， obstetrics， pediatrics and evidence-based medicine. Through literature review and the Delphi method， clinical questions regarding the efficacy and safety of parenteral DTIs used in special populations were identified. A structured design was adopted using the “Population-Intervention-Comparison-Outcome” （PICO） framework；systematic searches were conducted in CJFD， PubMed， Embase and other databases. Relevant evidence from randomized controlled trials，cohort studies and systematic reviews were included and synthesized. Evidence quality was assessed using the Grading of Recommendations Assessment，Development and Evaluation （GRADE） approach， and recommendations were formulated through three rounds of Delphi surveys and expert consensus meetings. RESULTS &CONCLUSIONS Seven clinical questions were ultimately selected （with a consensus rate exceeding 90%）， resulting in the formulation of seven recommendations on the use of parenteral DTIs in special populations， including children， pregnant women， patients with hepatic or renal impairment， patients with mesenteric venous thrombosis， and individuals with thrombophilia. These recommendations clarify the preferred agents， dosing ranges， monitoring parameters， and safety management strategies for parenteral DTIs in these special populations. This expert consensus， which is formulated based on the best available evidence， provides evidence-based guidance for standardized and individualized use of parenteral DTIs in special populations.

The Type III Secretion System (T3SS) serves as a pivotal virulence apparatus for numerous Gram-negative bacterial pathogens, enabling them to infect both animal and plant hosts. Functioning as a molecular syringe, the T3SS directly translocates bacterial effector proteins from the bacterial cytoplasm into the interior of eukaryotic host cells. These effectors are central weapons that precisely manipulate a wide spectrum of host cellular physiological processes, ranging from cytoskeletal dynamics to immune signaling, to establish a favorable niche for bacterial survival and proliferation. Among the diverse arsenal of T3SS effectors, the YopJ family constitutes a critical group of virulence factors. Members of this family are characterized by a conserved catalytic triad structure—a hallmark of the CE clan of cysteine proteases that has been evolutionarily repurposed to confer acetyltransferase activity. A defining and intriguing feature of these enzymes is their stringent dependence on a host-derived eukaryotic cofactor, inositol hexakisphosphate (IP₆), for allosteric activation. This requirement acts as a sophisticated molecular safeguard, ensuring enzymatic activity only within the appropriate host environment, thereby preventing detrimental effects on the bacterium itself. While seminal studies on individual members such as Yersinia’s YopJ and Salmonella’s AvrA have provided deep mechanistic insights, a systematic and integrative understanding of the structure-function relationships across the entire family remains fragmented. Key questions persist regarding how a conserved catalytic core has diverged to recognize distinct host substrates in different kingdoms of life. To address this gap, this article provides a systematic review of the YopJ family, focusing on three interconnected aspects: their structural features, their catalytic mechanism, and their divergent immunosuppressive strategies in animal versus plant hosts. By conducting a comparative analysis of the sequences and resolved three-dimensional structures of three representative members (e.g., HopZ1a, PopP2, AvrA), we elucidate regions of significant variation embedded within the conserved core catalytic architecture. These variable regions, often involving surface loops and substrate-binding interfaces, are crucial determinants of target specificity and functional specialization. The functional divergence of this effector family is most apparent when comparing their modes of action in different hosts. In animal hosts, YopJ-family effectors primarily sabotage innate immune signaling pathways. They achieve this by acetylating key serine and threonine residues within the activation loops of critical kinases in the MAPK and NF‑κB pathways. This post-translational modification blocks the phosphorylation and subsequent activation of these kinases, leading to potent suppression of inflammatory cytokine production. Conversely, in plant hosts, the strategy broadens to dismantle the two-tiered plant immune system. YopJ homologs target a more diverse set of substrates, including immune-associated receptor-like cytoplasmic kinases (RLCKs), microtubule networks via tubulin acetylation (which disrupts cellular trafficking and signaling), and transcription factors central to defense gene regulation. This multi-target approach effectively suppresses both Pattern-Triggered Immunity (PTI) and Effector-Triggered Immunity (ETI). In conclusion, this synthesis aims to deepen the mechanistic understanding of YopJ family-mediated pathogenesis by integrating structural biology with cellular function across host kingdoms. Elucidating the precise molecular basis for substrate selection—how conserved platforms achieve target diversity—is a major frontier. Furthermore, this knowledge provides a vital theoretical foundation for developing novel anti-virulence strategies. Targeting the conserved IP₆-binding pocket or the catalytic acetyltransferase activity itself represents a promising avenue for designing broad-spectrum inhibitors that could disarm this critical family of bacterial effectors, potentially offering new therapeutic approaches against a range of pathogenic bacteria.

Objective To explore the effectiveness of the generative large language model MedGo in nursing decision-making for elderly patients with multimorbidity. Methods A quasi-randomized controlled trial study was conducted involving 6 junior nurses, 6 senior nurses and the MedGo model from January 1, 2025 to March 31, 2025 at the Emergency Internal Medicine Ward of Shanghai East Hospital Affiliated to Tongji University. Clinical data of 120 elderly patients with multimorbidity were analyzed to compare the performance of the three groups in four tasks (nursing diagnosis assessment, nursing intervention formulation, complication identification, and complication prevention) from three evaluation dimensions: decision-making time consumption, decision accuracy, and decision-making quality. Results In terms of decision-making time, the senior nurse group completed all four tasks faster than the junior nurse group (P＜0.01), and the MedGo group completed all four tasks faster than the junior nurse group (P＜0.001) and the senior nurse group (P＜0.001). In terms of decision-making accuracy, senior nurse group scored higher than junior nurse group in all four tasks (P＜0.001), while the MedGo group outperformed the senior nurse group only in complication identification (P＜0.001). In terms of decision-making quality, the MedGo group scored higher than junior nurse group (P＜0.001) and senior nurse group (P＜0.001) in all four tasks. Conclusions The MedGo model demonstrates advantages of high efficiency, accuracy, and quality in nursing decision-making for elderly patients with multimorbidity; senior nurses outperform junior nurses in decision-making, providing diverse references for clinical nursing decision-making.

BACKGROUND:Although previous studies have reported associations between lipids and the risk of osteoporotic pathological fractures,the specific causal relationships between lipid level and osteoporotic pathological fractures remain unclear.OBJECTIVE:To elucidate the causal relationship between lipids and osteoporotic pathological fractures using a two-sample bidirectional Mendelian randomization analysis.METHODS:The data for 178 lipid metabolites were obtained from the IEU-GWAS database(developed by the MRC Integrative Epidemiology Unit at the University of Bristol,UK,which provides extensive summary data from genome-wide association studies),while osteoporotic pathological fracture data(from 173 619 European participants)were acquired from the FinnGen database(constructed by the Finnish national gene research program,focusing on investigating relationships between genomics and health/disease in the Finnish population).Osteoporotic pathological fracture data were used as the outcome variable,with lipids serving as exposures,for the bidirectional Mendelian randomization study to evaluate the causal effects of different lipids on osteoporotic pathological fractures.The UK Biobank database was employed as a validation set by switching the outcome variable to verify the findings horizontally.RESULTS AND CONCLUSION:(1)The inverse variance weighted analysis indicated that each unit increase in sterol ester(27∶1/20∶2)levels was associated with a 25.55％increase in the risk of osteoporotic pathological fractures(odds ratio=1.256,95％confidence interval:1.001-1.575,P=0.049),suggesting a significant positive correlation between elevated sterol ester levels and increased fracture risk.Reverse Mendelian randomization analysis revealed a significant negative association between osteoporotic pathological fractures and three types of phosphatidylcholine.Horizontal validation yielded consistent results,confirming sterol ester as a risk factor for osteoporotic pathological fractures.(2)The results indicate that sterol ester is a risk factor for osteoporotic pathological fractures,while phosphatidylcholine serves as a protective factor.These findings strengthen the evidence supporting the effect of lipids on the risk of osteoporotic pathological fractures.Although the GWAS data used in this study were derived from European populations,given the broad commonality of human genetics,the results provide valuable reference significance for improving osteoporosis in Chinese populations through lipid regulation.

BACKGROUND:Although previous studies have reported associations between lipids and the risk of osteoporotic pathological fractures,the specific causal relationships between lipid level and osteoporotic pathological fractures remain unclear.OBJECTIVE:To elucidate the causal relationship between lipids and osteoporotic pathological fractures using a two-sample bidirectional Mendelian randomization analysis.METHODS:The data for 178 lipid metabolites were obtained from the IEU-GWAS database(developed by the MRC Integrative Epidemiology Unit at the University of Bristol,UK,which provides extensive summary data from genome-wide association studies),while osteoporotic pathological fracture data(from 173 619 European participants)were acquired from the FinnGen database(constructed by the Finnish national gene research program,focusing on investigating relationships between genomics and health/disease in the Finnish population).Osteoporotic pathological fracture data were used as the outcome variable,with lipids serving as exposures,for the bidirectional Mendelian randomization study to evaluate the causal effects of different lipids on osteoporotic pathological fractures.The UK Biobank database was employed as a validation set by switching the outcome variable to verify the findings horizontally.RESULTS AND CONCLUSION:(1)The inverse variance weighted analysis indicated that each unit increase in sterol ester(27∶1/20∶2)levels was associated with a 25.55％increase in the risk of osteoporotic pathological fractures(odds ratio=1.256,95％confidence interval:1.001-1.575,P=0.049),suggesting a significant positive correlation between elevated sterol ester levels and increased fracture risk.Reverse Mendelian randomization analysis revealed a significant negative association between osteoporotic pathological fractures and three types of phosphatidylcholine.Horizontal validation yielded consistent results,confirming sterol ester as a risk factor for osteoporotic pathological fractures.(2)The results indicate that sterol ester is a risk factor for osteoporotic pathological fractures,while phosphatidylcholine serves as a protective factor.These findings strengthen the evidence supporting the effect of lipids on the risk of osteoporotic pathological fractures.Although the GWAS data used in this study were derived from European populations,given the broad commonality of human genetics,the results provide valuable reference significance for improving osteoporosis in Chinese populations through lipid regulation.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.