BACKGROUND: The clinical impact of post-percutaneous coronary intervention (PCI) quantitative flow ratio (QFR) in patients treated with PCI for chronic total occlusion (CTO) was still undetermined. METHODS: All CTO vessels treated with successful anatomical PCI in patients from PANDA III trial were retrospectively measured for post-PCI QFR. The primary outcome was 2-year vessel-oriented composite endpoints (VOCEs, composite of target vessel-related cardiac death, target vessel-related myocardial infarction, and ischemia-driven target vessel revascularization). Receiver operator characteristic curve analysis was conducted to identify optimal cutoff value of post-PCI QFR for predicting the 2-year VOCEs, and all vessels were stratified by this optimal cutoff value. Cox proportional hazards models were employed to calculate the hazard ratio (HR) with 95% CI. RESULTS: Among 428 CTO vessels treated with PCI, 353 vessels (82.5%) were analyzable for post-PCI QFR. 31 VOCEs (8.7%) occurred at 2 years. Mean value of post-PCI QFR was 0.92 ± 0.13. Receiver operator characteristic curve analysis shown the optimal cutoff value of post-PCI QFR for predicting 2-year VOCEs was 0.91. The incidence of 2-year VOCEs in the vessel with post-PCI QFR < 0.91 (n = 91) was significantly higher compared with the vessels with post-PCI QFR ≥ 0.91 (n = 262) (22.0% vs. 4.2%, HR = 4.98, 95% CI: 2.32-10.70). CONCLUSIONS Higher post-PCI QFR values were associated with improved prognosis in the PCI practice for coronary CTO. Achieving functionally optimal PCI results (post-PCI QFR value ≥ 0.91) tends to get better prognosis for patients with CTO lesions.

Traditional Chinese medicine (TCM) represents a paradigmatic approach to personalized medicine, developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years, and now encompasses large-scale electronic medical records (EMR) and experimental molecular data. Artificial intelligence (AI) has demonstrated its utility in medicine through the development of various expert systems (e.g., MYCIN) since the 1970s. With the emergence of deep learning and large language models (LLMs), AI's potential in medicine shows considerable promise. Consequently, the integration of AI and TCM from both clinical and scientific perspectives presents a fundamental and promising research direction. This survey provides an insightful overview of TCM AI research, summarizing related research tasks from three perspectives: systems-level biological mechanism elucidation, real-world clinical evidence inference, and personalized clinical decision support. The review highlights representative AI methodologies alongside their applications in both TCM scientific inquiry and clinical practice. To critically assess the current state of the field, this work identifies major challenges and opportunities that constrain the development of robust research capabilities-particularly in the mechanistic understanding of TCM syndromes and herbal formulations, novel drug discovery, and the delivery of high-quality, patient-centered clinical care. The findings underscore that future advancements in AI-driven TCM research will rely on the development of high-quality, large-scale data repositories; the construction of comprehensive and domain-specific knowledge graphs (KGs); deeper insights into the biological mechanisms underpinning clinical efficacy; rigorous causal inference frameworks; and intelligent, personalized decision support systems.
Medicine, Chinese Traditional/methods* ; Artificial Intelligence ; Humans ; Precision Medicine ; Decision Support Systems, Clinical

Natural products (NPs) are an important source of new drugs for the treatment of stroke. Identifying cellular targets for bioactive molecules is a major challenge and critical issue in the development of new drugs for stroke. Small-molecule probes play a unique role in target discovery. However, drawbacks to these probes include non-specificity, unstable activity, and difficulty in synthesis. Small-molecule probes based on NPs at least partially compensate for these shortcomings. NPs feature rich chemical and structural diversity, biocompatibility, and unique biological activities. These features could be exploited to provide new ideas and tools for target discovery. Small-molecule probes based on NPs provide a precise and direct search for interacting protein targets of NPs-active small molecules. This review explores the properties of small-molecule probes based on NPs and their applications in mechanistic studies of stroke and other diseases. We hope that this review will bring new perspectives to the mechanistic study of NPs-active small molecules and accelerate the translation of these ingredients into drug candidates for the treatment of stroke.

PURPOSE: Early mortality in major trauma has decreased, but MODS remains a leading cause of poor outcomes, driven by trauma-induced cytokine storms that exacerbate injuries and organ damage. METHODS: This prospective cohort study included 79 major trauma patients (ISS >15) treated in the National Center for Trauma Medicine, Peking University People's Hospital, from September 1, 2021, to July 31, 2023. Patients (1) with ISS >15 (according to AIS 2015), (2) aged 15-80 years, (3) admitted within 6 h of injury, (4) having no prior treatment before admission, were included. Exclusion criteria were (1) GCS score <9 or AIS score ≥3 for TBI, (2) confirmed infection, infectious disease, or high infection risk, (3) pregnancy, (4) severe primary diseases affecting survival, (5) recent use of immunosuppressive or cytotoxic drugs within the past 6 months, (6) psychiatric patients, (7) participation in other clinical trials within the past 30 days, (8) patients with incomplete data or missing blood samples. Admission serum inflammatory cytokines and pathophysiological data were analyzed to develop machine learning models predicting MODS within 7 days. LR, DR, RF, SVM, NB, and XGBoost were evaluated based on the area under the AUROC. The SHAP method was used to interpret results. RESULTS: This study enrolled 79 patients with major trauma, and the median (Q₁, Q₃) age was 51 (35, 59) years (52 males, 65.8%). The inflammatory cytokine data were collected for all participants. Among these patients, 35 (44.3%) developed MODS, and 44 (55.7%) did not. Additionally, 2 patients (2.5%) from the MODS group succumbed. The logistic regression model showed strong performance in predicting MODS. Ten key cytokines, IL-18, Eotaxin, MCP-4, IP-10, CXCL12, MIP-3α, MCP-1, IL-1RA, Cystatin C, and MRP8/14 were identified as critical to the trauma-induced cytokine storm and MODS development. Early elevation of these cytokines achieved high predictive accuracy, with an AUROC of 0.887 (95% CI 0.813-0.976). CONCLUSION Trauma-induced cytokine storms are strongly associated with MODS. Early identification of inflammatory cytokine changes enables better prediction and timely interventions to improve outcomes.
Humans ; Prospective Studies ; Middle Aged ; Male ; Female ; Adult ; Aged ; Cytokine Release Syndrome/etiology* ; Adolescent ; Young Adult ; Aged, 80 and over ; Wounds and Injuries/complications* ; Cytokines/blood* ; Multiple Organ Failure/diagnosis* ; Machine Learning

Objective To study the changes in serum levels of microRNA(miR)-590-3p and lymphocyte chemotactic factor(XCL1)in patients with acute leukemia complicated by infection,and to analyze the diag-nostic value of serum miR-590-3p and XCL1 levels for acute leukemia complicated by infection.Methods A total of 96 patients with acute leukemia admitted to the hospital from January 2022 to April 2024 were select-ed as the leukemia group.They were separated into an infected group(n=54)and a non infected group(n=42)based on whether infection occurred.Another 90 healthy volunteers who underwent physical examinations during the same period were included as the control group.Enzyme-linked immunosorbent assay was applied to detect serum levels of XCL1.Quantitative real-time PCR was applied to detect serum levels of miR-590-3p.General clinical data was collected and analyzed.Multivariate Logistic regression was applied to analyze the in-fluencing factors for infection in patients with acute leukemia.Receiver operating characteristic(ROC)curve was plotted to analyze the diagnostic value of miR-590-3p and XCL1 for acute leukemia complicated by infec-tion.Pearson method was applied to analyze the correlation between miR-590-3p,XCL1 with C-reactive pro-tein(CRP)and procalcitonin(PCT).Results Compared with the control group,the serum level of XCL1 in the leukemia group was greatly increased(P＜0.05),relative expression level of miR-590-3p was significantly reduced(P＜0.05).Compared with the non infected group,the serum levels of XCL1,CRP,and PCT in the infected group were significantly increased(P＜0.05),relative expression level of miR-590-3p was significant-ly reduced(P＜0.05).Serum CRP,PCT,and XCL1 were all risk factors for infection in patients with acute leukemia(P＜0.05),and miR-590-3p was a protect factor for infection in patients with acute leukemia(P＜0.05).The area under the curve(AUC)of serum miR-590-3p,XCL1,CRP,PCT and miR-590-3p+XCL1 in diagnosing the infection in acute leukemia patients were 0.825,0.851,0.795,0.778 and 0.927,respectively.The AUC of miR-590-3p+XCL1 diagnosis was better than that of XCL1(Z=2.791,P=0.005),CRP(Z=2.491,P=0.013),PCT(Z=2.729,P=0.006),miR-590-3p(Z=2.274,P=0.023)diagnosed alone.XCL1 was positively correlated with CRP and PCT(P＜0.001),and miR-590-3p was negatively positively correlated with XCL1,CRP and PCT(P＜0.001).Conclusion In patients with acute leukemia complicated by infection,serum level of XCL1 increases,relative expression level of miR-590-3p decreases and the combination of the two has certain diagnostic value for patients with acute leukemia complicated by infection.

OBJECTIVE: This review summarized the first 10-year progresses and controversies in the concept of anteromedial cortical support reduction, to provide references for further study and clinical applications. METHODS: Relevant domestic and foreign literature on cortical support reduction was extensively reviewed to summarize the definition of positive, neutral, and negative support, anteromedial cortices at the inferior corner, intraoperative technical tips for fracture reduction, radiographic assessment at different periods, comparison between positive versus neutral and medial versus anterior support, and the clinical efficacy of Chang reduction quality criteria (CRQC) and postoperative stability score. RESULTS: Anteromedial cortical support reduction was only focused on the cortex of anteromedial inferior corner, with no concern the status of lateral wall or lesser trochanter. Anteromedial cortex was seldom involved by fracture comminution, it was thicker, denser, and stronger, and was the key for mechanical buttress of the head-neck fragment to share compression load. Positive, neutral, and negative support were also called "extramedullary, anatomic, and intramedullary reduction", respectively. There was hardly seen parallel cortical apposition, but characterized by some kinds of head-neck rotation, for example 10°-15° flexed rotation for positive cortical contact and support. Due to intraoperative compression and postoperative impaction, the status of cortical support may be changed at different time of radiographic examination. The positive medial cortex support was more reliable with less reduction loss than its neutral counterpart, and the anterior cortex contact was more predictive than the medial cortex for final results. As incorporation the bearing of cortex apposition and using a 4-point score, CRQC demonstrated more efficacy and was gradually accepted and applied in the evaluation of trochanteric fracture reduction quality. Postoperative stability score (8 points) provided a assessment tool for early weight-bearing in safety to prevent mechanical failure. CONCLUSION Anteromedial cortical support reduction is a key point for stability reconstruction in the treatment of trochanteric femur fractures. Evidence has definitely shown that non-negative (positive and neutral) is superior to negative (loss of cortical support). There is a tendency that positive cortex support is superior to neutral, but high quality study with large sample size is needed for a clear conclusion.
Humans ; Femur/diagnostic imaging* ; Fracture Fixation, Internal/methods* ; Hip Fractures/diagnostic imaging* ; Treatment Outcome ; Fracture Fixation, Intramedullary/methods*

OBJECTIVE: To explore the clinical presentation and genetic etiology of a case with Xeroderma pigmentosum in conjunct with basal cell carcinoma and melanoma. METHODS: A male patient with Xeroderma pigmentosum treated at Xinxiang Central Hospital in October 2022 was selected as study subject. Whole exome sequencing (WES) was carried out. Candidate variants were verified by Sanger sequencing of his family members. This study was approved by the Ethics Committee of the hospital (Ethics No.: 2021-167). RESULTS: Magnetic resonance imaging showed that the patient has a solid soft tissue mass in the anterior and lower part of his right eyeball and a small nodule on the left nasal wing. Histopathological biopsy showed that the periocular tumor was basal cell carcinoma in conjunct with malignant melanoma, and the nasal wing tumor was basal cell carcinoma. WES and Sanger sequencing revealed that he has harbored compound heterozygous variants of the XPC gene, namely c.2391delT (p.F797Lfs*11) and IVS1+1G>A, which were inherited from his father and mother, respectively. Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), the variants were rated as likely pathogenic (PVS1+PM2_Supporting+PM3) and pathogenic (PVS1+PM2_Supporting+PM3+PP5), respectively. The c.2391delT variant was unreported previously. Bioinformatic analysis suggests that it could significantly affect the tertiary structure of XPC protein. CONCLUSION The c.2391delT(p.F797Lfs*11) and IVS1+1G>A compound heterozygous variants probably underlay the pathogenesis in this patient. The detection of the novel variant has enriched the mutational spectrum of the XPC gene.
Humans ; Male ; Xeroderma Pigmentosum/genetics* ; Basal Cell Carcinoma/genetics* ; DNA-Binding Proteins/genetics* ; Melanoma/genetics* ; Mutation ; Skin Neoplasms/genetics* ; Middle Aged ; Exome Sequencing ; Pedigree

For middle-aged and elderly patients with conditions such as spinal fractures and degenerative spinal diseases, spinal internal fixation is a core surgical procedure for reconstructing spinal stability, heavily relying on the biomechanical stability provided by pedicle screw systems. Whereas, these patients are often complicated by osteoporosis that can significantly compromise the stability of the bone-pedicle screw interface, leading to a marked increase in pedicle screw loosening and surgical failure rates. The bone cement-augmented pedicle screw technique, which involves injecting bone cement into the vertebral body or screw trajectory to optimize the mechanical properties of the bone-pedicle screw composite, has been proven to significantly enhance fixation strength and effectively prevent screw-related failures, thereby reducing the incidence of internal fixation failure in high-risk populations undergoing spinal fusion. However, the widespread clinical application of this technique has faced challenges such as inaccurate clinical decision-making (indication and contraindication selection), non-standardized operative practices, and insufficient awareness of complication prevention, resulting in considerable variability in clinical outcomes and even severe complications. To address this, Prof. Luo Fei from First Affiliated Hospital of Army Medical University initiated the project and the Chinese Association Orthopaedic Surgeons organized relevant experts to develop the Evidence-based clinical practice guideline for bone cement-augmented pedicle screw technique ( version 2025), based on current evidence. The guidelines put forward 8 recommendations regarding the clinical value, scope of application, and operational standards of the technique, aiming to provide evidence-based medical support and technical standardization for clinical decision-making.

Objective: To explore the influencing factors and network structure of aggressive behaviors among college students based on propensity score matching (PSM), so as to provide precise targeted interventions for the prevention and improvement of aggressive behaviors among college students. Methods: A total of 2 652 college students were selected by convenient sampling method from three colleges in Wuhan, Hubei Province in June 2023. Questionnaire surveys were carried out by using the Buss-Warren Aggression Questionnaire (BWAQ), Ruminative Responses Scale (RRS), Cognitive Emotion Regulation Questionnaire-Chinese Version (CERQ-C), Family APGAR Index (APGAR) ,Brief Fear of Negative Evaluation Scale (BFNES).By bias score matching (PSM) for 1∶1 matching, univariate and multivariate Logistic regression analysis, and network analysis were conducted on the college students. Results: College students with higher levels of ruminant thinking，non adaptive emotional regulation and fear of negative appraisal were more likely to have highly aggressive behaviors（ OR =1.14，1.18，1.06），and those with higher adaptive emotional regulation and family care index were more likely to have highly aggressive behaviors ( OR =0.88，0.82)( P < 0.01 ). Network structure was significantly different between the two groups ( M =0.27, P <0.05). The core affective factors of college students with high levels of aggressive behavior were brooding reflective pondering and symptom rumination( EI =3.50, 3.49, 3.48 )，low aggressive behavior college students core affective factors were adaptive emotion regulation growth and non adaptive emotion regulation( EI =4.37, 4.12, 4.08). Conclusion Factors affecting Chinese college students aggressive behaviors are of different characteristics on different behaviour types, and targeted interventions should be adopted to reduce aggressive behaviors of college students.

Ultrasonography（US）is the first-line imaging modality recommended by domestic and international guidelines for liver tumor screening，owing to its non-invasive nature，real-time dynamic imaging capability，cost-effectiveness，and operational convenience. In recent years，the integration of artificial intelligence（AI）and medical imaging has emerged as a major research focus. By leveraging large-scale data training，AI models can automatically recognize and analyze input imaging data and generate predictive outcomes. Notably，AI-based ultrasound imaging technology has achieved breakthrough advancements in the diagnosis and treatment of liver tumors. These innovations significantly improve diagnostic accuracy，optimize treatment strategies，predict disease progression and prognosis，and monitor therapeutic response. This article provides a comprehensive review of the latest applications and research progress of AI in ultrasound-based diagnosis and treatment of liver tumors.