Background: This study was performed to characterize the incidence, costs, and risk factors associated with renal and cardiovascular adverse outcomes following primary percutaneous coronary intervention (pPCI) in patients with ST-elevation myocardial infarction (STEMI). Methods: Patients with STEMI who underwent pPCI using iso-osmolar contrast were enrolled at 39 centers. The incidence of acute kidney injury (AKI) and major adverse renal and cardiovascular events (MARCE) was analyzed, as well as inpatient costs. Logistic regression analysis was performed to identify risk factors. Results: Among 2,293 patients, the incidence of AKI and MARCE within 72 hours post-pPCI was 4.14% (n = 95) and 4.40% (n = 101), respectively. AKI and/or MARCE were associated with systolic blood pressure (AKI: odds ratio [OR], 1.009; 95% confidence interval [CI], 1.000–1.018), hypertension (AKI: OR, 1.815; 95% CI, 1.133–2.906; MARCE: OR, 1.760;95% CI, 1.118–2.769), anterior wall infarction (AKI: OR, 1.895; 95% CI, 1.196–3.004; MARCE:OR, 1.939; 95% CI, 1.240–3.032), Killip class (AKI: OR, 1.465; 95% CI, 1.117–1.922; MARCE:OR, 1.467; 95% CI, 1.131–1.903), and serum creatinine (SCr; MARCE: OR, 1.006; 95% CI, 1.000–1.012). Hospitalization costs for patients with STEMI who developed AKI or MARCE were significantly higher than for those without AKI (9,595 ± 5,795 vs. 8,279 ± 3,872 USD, P = 0.003) or without MARCE (9,890 ± 5,616 vs. 8,255 ± 3,859 USD, P < 0.001). Conclusions In patients with STEMI undergoing pPCI with iso-osmolar contrast, the incidence of AKI and MARCE was associated with higher hospitalization costs. Systolic blood pressure, hypertension, anterior wall infarction, Killip class, and SCr were identified as risk factors for these outcomes.

Objective:To compare knowledge graphs (KGs) constructed from standardized clinical pathways and actual examination records within 24 hours of emergency care for acute gastrointestinal hemorrhage (AGH), acute myocardial infarction (AMI), and intracerebral hemorrhage (ICH), and to visually analyze discrepancies between guideline recommendations and real-world practice, thereby exploring a novel methodology for clinical pathway optimization.Methods:KGs were developed using clinical pathway standards and actual examination data collected within the first 24 hours of emergency treatment for AGH, AMI, and ICH. Entity attributes were weighted to visually represent the frequency and extent of examination usage through variable node sizes in the KG. The constructed KGs were used to compare and analyze the differences in type and frequency of examinations performed relative to pathway standards.Results:The proportion of examination items with >50% adherence to clinical pathway standards within 24 hours was 76.92% for AGH, 44.44% for AMI, and 78.57% for ICH. Items from the clinical pathways that were not performed in over 50% of patients accounted for 15.38%, 27.78%, and 21.43% of cases, respectively. Non-pathway examinations increased by 9, 7, and 4 items for each condition, of which 17 items (85%) were performed at least once in more than half of the patients. Visualization via KGs revealed a reduction in redundant examinations by 38.64% between AGH and AMI, 35.00% between AGH and ICH, and 37.50% between AMI and ICH. Overall, a 54.84% reduction in redundant examinations was achieved across all three critical conditions.Conclusions:The visual KG approach effectively integrates both guideline-recommended and experience-driven examinations, serving as a correlational analysis tool to assess deviations between actual clinical practice and standardized pathways. It provides a quantitative foundation for optimizing clinical pathways, with potential for greater efficiency gains as more critical conditions are incorporated into the graph.

Despite therapy with potent antiviral agents, chronic hepatitis B (CHB) patients remain at high risk of hepatocellular carcinoma (HCC). While metabolites have been rediscovered as active drivers of biological processes including carcinogenesis, the specific metabolites modulating HCC risk in CHB patients are largely unknown. Here, we demonstrate that baseline plasma from CHB patients who later developed HCC during follow-up exhibits growth-promoting properties in a case-control design nested within a large-scale, prospective cohort. Metabolomics analysis reveals a reduction in long-chain acylcarnitines (LCACs) in the baseline plasma of patients with HCC development. LCACs preferentially inhibit the proliferation of HCC cells in vitro at a physiological concentration and prevent the occurrence of HCC in vivo without hepatorenal toxicity. Uptake and metabolism of circulating LCACs increase the intracellular level of acetyl coenzyme A, which upregulates histone H3 Lys14 acetylation at the promoter region of KLF6 gene and thereby activates KLF6/p21 pathway. Indeed, blocking LCAC metabolism attenuates the difference in KLF6/p21 expression induced by baseline plasma of HCC/non-HCC patients. The deficiency of circulating LCACs represents a driver of HCC in CHB patients with viral control. These insights provide a promising direction for developing therapeutic strategies to reduce HCC risk further in the antiviral era.

The interest in covalent drugs has resurged in recent decades, spurring the development of numerous specialized computational docking tools to facilitate covalent ligand design and screening. Herein, we present CarsiDock-Cov, a new paradigm distinguishing itself as the first deep learning (DL)-guided approach for covalent docking. CarsiDock-Cov retains the core components of its non-covalent predecessor, leveraging a DL model pretrained on millions of docking complexes to predict protein-ligand distance matrices, along with a dedicated-designed geometric optimization procedure to convert these distances into refined binding poses. Additionally, it incorporates several key enhancements specifically tailored to optimize the protocol for covalent docking applications. Our approach has been extensively validated on multiple public datasets regarding the docking and screening of covalent ligands, and the results indicate that our approach not only achieves comparably improved applicability compared to its non-covalent predecessor, but also exhibits competitive performance against various state-of-the-art covalent docking tools. Collectively, our approach represents a significant advance in covalent docking methodology, offering an automated and efficient solution that shows considerable promise for accelerating covalent drug discovery and design.

Glutamine provides carbon and nitrogen to support the proliferation of cancer cells. However, the precise reason why cancer cells are particularly dependent on glutamine remains unclear. In this study, we report that glutamine modulates the tumor suppressor F-box and WD repeat domain-containing 7 (FBW7) to promote cancer cell proliferation and survival. Specifically, lysine 604 (K604) in the sixth of the 7 substrate-recruiting WD repeats of FBW7 undergoes glutaminylation (Gln-K604) by glutaminyl tRNA synthetase. Gln-K604 inhibits SCFFBW7-mediated degradation of c-Myc and Mcl-1, enhances glutamine utilization, and stimulates nucleotide and DNA biosynthesis through the activation of c-Myc. Additionally, Gln-K604 promotes resistance to apoptosis by activating Mcl-1. In contrast, SIRT1 deglutaminylates Gln-K604, thereby reversing its effects. Cancer cells lacking Gln-K604 exhibit overexpression of c-Myc and Mcl-1 and display resistance to chemotherapy-induced apoptosis. Silencing both c-MYC and MCL-1 in these cells sensitizes them to chemotherapy. These findings indicate that the glutamine-mediated signal via Gln-K604 is a key driver of cancer progression and suggest potential strategies for targeted cancer therapies based on varying Gln-K604 status.
Glutamine/metabolism* ; Myeloid Cell Leukemia Sequence 1 Protein/genetics* ; Humans ; Proto-Oncogene Proteins c-myc/genetics* ; Cell Proliferation ; Signal Transduction ; Neoplasms/pathology* ; F-Box-WD Repeat-Containing Protein 7/genetics* ; Cell Survival ; Cell Line, Tumor ; Apoptosis

The rapid screening of bioactive constituents within traditional Chinese medicine (TCM) presents a significant challenge to researchers. Prevailing strategies for the screening of active components in TCM often overlook trace components owing to their concealment by more abundant constituents. To address this limitation, a fishing strategy based on offline two-dimensional liquid chromatography (2D-LC) combined with surface plasmon resonance (SPR) was utilized to screen bioactive trace components targeting peroxiredoxin 3 (PRDX3), using Uncaria alkaloids (UAs) as a case study. Initially, an orthogonal preparative offline 2D-LC system combining a positively charged C₁₈ column and a conventional C₁₈ column under disparate mobile phase conditions was constructed. To fully reveal the trace alkaloids, 13 2D fractions of UAs were prepared, and their components were characterized using mass spectrometry (MS). Subsequently, employing PRDX3 as the targeting protein, a SPR-based screening approach was established and rigorously validated with geissoschizine methyl ether (GSM) serving as a positive control for binding. Employing this refined strategy, 29 candidate binding alkaloids were fished from the 13 2D fractions. Notably, combining offline 2D-LC with SPR increased the yield of candidate binding components from 10 to 29 when compared to SPR-based screening alone. Subsequent binding affinity assays confirmed that PRDX3 was a direct binding target for the 12 fished alkaloids, with isovallesiachotamine (IV), corynoxeine N-oxide (CO-N), and cadambine (CAD) demonstrating the highest affinity for PRDX3. Their interactions were further validated through molecular docking analysis. Subsequent intracellular H₂O₂ measurement assays and transfection experiments confirmed that these three trace alkaloids enhanced PRDX3-mediated H₂O₂ clearance. In conclusion, this study introduced an innovative strategy for the identification of active trace components in TCM. This approach holds promise for accelerating research on medicinal components within this field.

Functional dyspepsia (FD), characterized by persistent or recurrent dyspeptic symptoms without identifiable organic, systemic or metabolic causes, is an increasingly recognized global health issue. The objective of this guideline is to equip clinicians and nursing professionals with evidence-based strategies for the management and treatment of adult patients with FD using traditional Chinese medicine (TCM). The Guideline Development Group consulted existing TCM consensus documents on FD and convened a panel of 35 clinicians to generate initial clinical queries. To address these queries, a systematic literature search was conducted across PubMed, EMBASE, the Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP Database, China Biology Medicine (SinoMed) Database, Wanfang Database, Traditional Medicine Research Data Expanded (TMRDE), and the Traditional Chinese Medical Literature Analysis and Retrieval System (TCMLARS). The evidence from the literature was critically appraised using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. The strength of the recommendations was ascertained through a consensus-building process involving TCM and allopathic medicine experts, methodologists, pharmacologists, nursing specialists, and health economists, leveraging their collective expertise and empirical knowledge. The guideline comprises a total of 43 evidence-informed recommendations that span a range of clinical aspects, including the pathogenesis according to TCM, diagnostic approaches, therapeutic interventions, efficacy assessments, and prognostic considerations. Please cite this article as: Zhang SS, Zhao LQ, Hou XH, Bian ZX, Zheng JH, Tian HH, Yang GH, Hong WS, He YY, Liu L, Shen H, Li YP, Xie S, Shu J, Zeng BF, Li JX, Liu Z, Xiao ZH, Xiao JD, Zheng PY, Huang SG, Chen SL, Fei GJ. International clinical practice guideline on the use of traditional Chinese medicine for functional dyspepsia (2025). J Integr Med. 2025; 23(5):502-518.
Dyspepsia/drug therapy* ; Humans ; Medicine, Chinese Traditional/methods* ; Practice Guidelines as Topic ; Drugs, Chinese Herbal/therapeutic use*

OBJECTIVE: To assess the independent and combined effects of air pollutants, meteorological factors, and greenspace exposure on new tuberculosis (TB) cases. METHODS: TB case data from Shanghai (2013-2018) were obtained from the Shanghai Center for Disease Control and Prevention. Environmental data on air pollutants, meteorological variables, and greenspace exposure were obtained from the National Tibetan Plateau Data Center. We employed a distributed-lag nonlinear model to assess the effects of these environmental factors on TB cases. RESULTS: Increased TB risk was linked to PM _2.5, PM ₁₀, and rainfall, whereas NO ₂, SO ₂, and air pressure were associated with a reduced risk. Specifically, the strongest cumulative effects occurred at various lags: PM _2.5 ( RR = 1.166, 95% CI: 1.026-1.325) at 0-19 weeks; PM ₁₀ ( RR = 1.167, 95% CI: 1.028-1.324) at 0-18 weeks; NO ₂ ( RR = 0.968, 95% CI: 0.938-0.999) at 0-1 weeks; SO ₂ ( RR = 0.945, 95% CI: 0.894-0.999) at 0-2 weeks; air pressure ( RR = 0.604, 95% CI: 0.447-0.816) at 0-8 weeks; and rainfall ( RR = 1.404, 95% CI: 1.076-1.833) at 0-22 weeks. Green space exposure did not significantly impact TB cases. Additionally, low temperatures amplified the effect of PM _2.5 on TB. CONCLUSION Exposure to PM _2.5, PM ₁₀, and rainfall increased the risk of TB, highlighting the need to address air pollutants for the prevention of TB in Shanghai.
China/epidemiology* ; Humans ; Air Pollutants/analysis* ; Tuberculosis/epidemiology* ; Incidence ; Meteorological Concepts ; Particulate Matter/adverse effects* ; Environmental Exposure ; Male ; Female ; Adult ; Air Pollution ; Middle Aged

This comprehensive review synthesizes the latest advancements in understanding inflammatory disorders affecting cerebral small vessels, a distinct yet understudied category within cerebral small vessel diseases (SVD). Unlike classical SVD, these inflammatory conditions exhibit unique clinical presentations, imaging patterns, and pathophysiological mechanisms, posing significant diagnostic and therapeutic challenges. Highlighting their heterogeneity, this review spans primary angiitis of the central nervous system, cerebral amyloid angiopathy-related inflammation, systemic vasculitis, secondary vasculitis, and vasculitis in autoinflammatory diseases. Key discussions focus on emerging insights into immune-mediated processes, neuroimaging characteristics, and histopathological distinctions. Furthermore, this review underscores the importance of standardized diagnostic frameworks, individualized immunomodulation approaches, and novel targeted therapies to address unmet clinical demands.
Humans ; Cerebral Small Vessel Diseases/pathology* ; Inflammation/pathology* ; Cerebral Amyloid Angiopathy/pathology* ; Vasculitis, Central Nervous System/pathology* ; Vasculitis/pathology*

Recently,the theoretical system and practical path for the deep integration of digitalization and traditional industrialization have gradually matured.Medical innovation and digital technology are progressing,and the deep integration of intensive care medicine and intelligence is surpassing the traditional informatization and ushering in new development opportunities.Technologies such as 5G,big data,artificial intelligence,and digital twins can help to understand more complex critical care issues,improve the diagnoses and prediction of diseases and symptoms,develop more accurate treatment strategies,and even transform the service model of critical care medicine.This paper summarizes the application and challenge of digital technology in the practical scenarios of critical care medicine,so as to further consolidate infrastructure,enrich application scenarios,accelerate implementation,improve effectiveness,and strengthen the safety and compliance with the regulations.