Objective To investigate the predictive value of Mayo adhesion probability(MAP)score for intraoperative bleeding during microchannel percutaneous nephrolithotomy(PCNL), so as to provide reference for optimizing surgical decisions.Methods A retrospective analysis was conducted on the clinical data of 86 patients who underwent microchannel PCNL at our hospital during Jan.2018 and Jul. 2025.Patients were divided into two groups based on preoperative CT-derived MAP scores:MAP score＜3 group(n=45)and MAP score≥3 group(n=41).Baseline characteristics, surgical parameters and outcome measures were compared between the two groups.Univariate and multivariate logistic regression analyses were performed to identify risk factors for intraoperative bleeding(defined as a postoperative hemoglobin decrease of ≥20 g/L). Results The incidence of intraoperative bleeding was significantly higher in the MAP score≥3 group than in the MAP score＜3 group(43.9% vs.20.0%, P=0.017).Multivariate analysis identified MAP score ≥3(OR=3.045, 95%CI:1.125-9.547, P=0.019), use of anticoagulant medication(OR=3.016, 95%CI:1.251-9.257, P=0.020), establishment of multiple tracts(OR=5.445, 95%CI:1.798-17.578, P=0.003), and operation time ≥90 minutes(OR=5.697, 95%CI:1.890-13.632, P=0.001)as risk factors for intraoperative bleeding.The area under the curve for the MAP score in predicting intraoperative bleeding was 0.704.Conclusion The MAP score is an independent risk factor for intraoperative bleeding during microchannel PCNL.Preoperative assessment can help identify high-risk patients and provide a basis for optimizing surgical decision-making.

BACKGROUND:The development of artificial intelligence in the medical field is rapidly advancing,with increasing research on its applications in the field of bone trauma.Through bibliometric analysis,this paper analyzed the research hotspots of artificial intelligence in the field of bone trauma in recent years,and predicted the future research trend. OBJECTIVE:To summarize the development history,research status,hot spots,and future development trends of artificial intelligence technology in the field of bone trauma to provide new insights for future research. METHODS:This study selected relevant literature from the Web of Science core database,covering the period from the inception to August 2023,and retrieved 420 articles related to the application of artificial intelligence,machine learning,and deep learning in the field of bone trauma.After manual screening,202 articles related to this article were exported,and Citespace software was used for visual analysis of cooperation of countries,institutions,cited journals,citation analysis,keyword co-occurrence,and other aspects. RESULTS AND CONCLUSION:(1)The overall number of publications from the 202 selected articles showed an upward trend,indicating significant research potential for future studies.The country with the highest centrality and the highest publication volume was the United States.The University of California(USA)was the most prolific research institution.(2)The top five most commonly used keywords in bone trauma research using artificial intelligence were deep learning,artificial intelligence,bone density,machine learning,and diagnosis.The keyword with the highest centrality was bone density,and the keyword with the highest frequency was deep learning.(3)The top 10 most cited reference papers provided comprehensive insights into the feasibility of applying artificial intelligence techniques to the diagnosis of bone trauma from various perspectives.Among them,eight papers focused on bone and joint injuries and deep convolutional neural networks.One paper discussed the use of deep learning in detecting osteoporosis in CT scans to prevent fragility fractures,while another paper explored the correlation between the application of artificial intelligence in identifying changes in skin texture and the recognition of bone characteristics.(4)In the future,the research hotspots of artificial intelligence will mainly focus on the specific study of fractures caused by bone and joint trauma and osteoporosis.The research trend mainly focuses on improving the performance of artificial intelligence algorithms,using new artificial intelligence technologies to accurately classify and quickly and efficiently diagnose bone injuries,especially for the diagnosis of complex and hidden fractures.By establishing finite element analysis models,more standardized evaluations of bone injuries can be achieved.

As one of the core pathogenesis during treatment with traditional Chinese medicine，liver heat runs through different stages of liver disease. The interpretation of its meaning in different medicine categories（traditional Chinese medicine，Tibetan medicine，Mongolian medicine，Uygur medicine，Dai medicine，Yao medicine，etc.） is not unified， and the phenomena of the same name with different meanings，confusion， and misappropriation emerge. This seriously restricts the inheritance，innovation， and clinical application of traditional Chinese medicine and ethnomedicine. By tracing and analyzing liver heat， it is found that liver heat in traditional Chinese medicine is caused by disordered rest and diet， as well as internal injury due to emotional disorder， which leads to liver dysfunction， Qi stagnation， and heat turning to fire in the liver meridian. The liver heat in Tibetan medicine is caused by the accumulated heat of the liver nature and the evil heat in the liver， which stimulates the toxin of Chiba fever. The liver heat in Mongolian medicine derives from the abnormal diet and rest， making excessive Sheila accumulate in the liver and causing disease. The above etiologies are all related to diet， rest，exogenous evil，emotion，and so on， and the pathogenesis is related to the imbalance of Qi and the metabolic disorder of organs. The clinical symptoms are pain in the liver region，yellow eyes， bitter mouth， fever，digestion，and loss of appetite. The principle of treatment and compatibility of prescription are heat-based， with auxiliary detoxification. Other ethnomedicine， such as Uygur medicine， Dai medicine， Yao Medicine，Miao medicine， and She medicine do not have a clear discussion on liver heat，and their etiology， pathogenesis， treatment，and prescription are not systematic，mostly based on a single drug or proven prescriptions.Through the systematic tracing，mining，induction，analysis， and arrangement of the liver heat based on existing literature information database in China，this paper regarded syndrome as the outline and disease as the goal，clarified the similarities and differences of the pathogenesis of liver heat in traditional Chinese medicine，and determined the relationship between liver heat and liver disease and the status quo of syndrome and treatment.This review provides evidence and reference for clinical prevention and treatment，as well as drug development for liver disease.

OBJECTIVE: To evaluate the effect of palliative care on drug use, medical service utilization and medical expenditure of patients with advanced cancer. METHODS: A cohort of patients including pal-liative care and standard care was constructed using the medical records of the patients in Peking University Cancer Hospital from 2018 to 2020, and coarsened exact matching was used to match the two groups of patients. The average monthly opioid consumption, hospitalization rate, intensive care unit (ICU) rate and operation rate, and the average monthly total cost were selected to evaluate drug use, medical service utilization and medical expenditure. Chi-square test and Wilcoxon signed rank test were used to compare the differences between the two groups before and after exposure and the change in the palliative care group. The net impact of palliative care on the patients was calculated using the difference-in-differences analysis. RESULTS: In this study, 180 patients in the palliative care group and 3 101 patients in the stan-dard care group were finally included in the matching, and the matching effect of the two groups was good (L₁ < 0.1). Before and after exposure, the average monthly opioid consumption in the palliative care group was significantly higher than that in the standard care group (Before exposure: 0.3 DDD/person-month vs. 0.1 DDD/person-month, P < 0.01; After exposure: 0.7 DDD/person-month vs. 0.1 DDD/person-month, P < 0.01; DDD refers to defined daily dose), palliative care significantly increased the average monthly opioid consumption in the patients (0.3 DDD/person-month, P < 0.01). The hospitalization rate (48.9% vs. 74.3%, P < 0.01) and operation rate (3.9% vs. 8.8%, P < 0.01) of the patients in palliative care group were significantly lower than those in standard care group, and the ICU rate became similar between the two groups (1.1% vs. 1.6%, P=0.634). Palliative care significantly reduced the patients ' hospitalization rate (-25.6%, P < 0.01), ICU rate (-4.9%, P < 0.01) and operation rate (-14.5%, P < 0.01). Before and after exposure, the average monthly total costs of pal-liative care group were slightly higher than those of standard care group (Before exposure: 20 092.3 yuan vs. 19 132.8 yuan, P=0.725; After exposure: 9 719.8 yuan vs. 8 818.8 yuan, P=0.165). Palliative care increased the average monthly total cost by 2 208.8 yuan, but it was not statistically significant (P=0.316). CONCLUSION Palliative care can increase the opioid consumption in advanced cancer patients, reduce the rates of hospitalization, ICU and surgery, but has no significant effect on medical expenditure.
Humans ; Palliative Care/economics* ; Neoplasms/drug therapy* ; Analgesics, Opioid/economics* ; Male ; Female ; Middle Aged ; Aged ; Hospitalization/economics* ; Intensive Care Units/statistics & numerical data* ; Health Expenditures/statistics & numerical data* ; Adult ; Drug Utilization/statistics & numerical data* ; Patient Acceptance of Health Care/statistics & numerical data*

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

Objective:To exploring the value of MR neuroimaging for quantitative assessment of the facial nerve and peripheral lymph nodes in patients with acute peripheral facial paralysis. Methods:Based on a prospective experimental design, 32 patients with idiopathic peripheral facial palsy were enrolled in the experiment. Based on MR neuroimaging technology, MR high-resolution thin-layer images of bilateral facial nerves were acquired. The diameters of different segments of the bilateral facial nerve were measured, including the labyrinthine segment, the geniculate ganglion, the horizontal segment, the vertical segment, the stem-mammary foramen segment, the trunk of the parotid segment, the temporal trunk, and the cervical trunk, as well as the quantitative indicators of peri-auricular and parotid lymph nodes（number, length and diameter of the largest lymph nodes）. Differences in quantitative indices of nerve diameter and peripheral lymph nodes between the paraplegic and healthy sides were compared using the paired t-test and Wilcoxon signed rank test. Results:The diameter of geniculate ganglion, mastoid foramen stem, parotid main trunk, temporal facial trunk, and cervical facial trunk were notably increased on the facial paralysis side compared to the contralateral side（P<0.05）. However, no significant differences were observed in the diameter of labyrinthine segment, horizontal segment, or vertical segment compared to the contralateral side. There were significantly more periauricular lymph nodes on the facial paralysis side than the contralateral side（P=0.001）. Conclusion:MR neuroimaging enables the quantitative assessment of structural changes in the facial nerve of patients with acute peripheral facial paralysis, demonstrating nerve enlargement in the geniculate ganglion, stylomastoid foramen segment, main trunk of the parotid segment, temporal facial trunk, and cervical facial trunk. Additionally, an increased number of periauricular lymph nodes is observed on the affected side. These findings may aid clinicians in assessing the efficacy of treatments and predict the prognosis of these patients.
Humans ; Facial Nerve/diagnostic imaging* ; Magnetic Resonance Imaging/methods* ; Prospective Studies ; Female ; Male ; Neuroimaging/methods* ; Lymph Nodes/diagnostic imaging* ; Facial Paralysis/diagnostic imaging* ; Adult ; Middle Aged

Protein arginine methyltransferase 5 (PRMT5) acts as an oncogene in liver cancer, yet its roles and in-depth molecular mechanisms within the liver cancer immune microenvironment remain mostly undefined. Here, we demonstrated that disruption of tumor-intrinsic PRMT5 enhances CD8⁺ T-cell-mediated antitumor immunity both in vivo and in vitro. Further experiments verified that this effect is achieved through downregulation of the inhibitory immune checkpoint molecule, fibrinogen-like protein 1 (FGL1). Mechanistically, PRMT5 catalyzed symmetric dimethylation of transcription factor 12 (TCF12) at arginine 554 (R554), prompting the binding of TCF12 to FGL1 promoter region, which transcriptionally activated FGL1 in tumor cells. Methylation deficiency at TCF12-R554 residue downregulated FGL1 expression, which promoted CD8⁺ T-cell-mediated antitumor immunity. Notably, combining the PRMT5 methyltransferase inhibitor GSK591 with PD-L1 blockade efficiently inhibited liver cancer growth and improved overall survival in mice. Collectively, our findings reveal the immunosuppressive role and mechanism of PRMT5 in liver cancer and highlight that targeting PRMT5 could boost checkpoint immunotherapy efficacy.

Gastrointestinal (GI) cancers are a leading cause of cancer morbidity and mortality worldwide. Despite advances in treatment, cancer relapse remains a significant challenge, necessitating novel therapeutic strategies. In this study, we engineered nanobody-based chimeric antigen receptor (CAR) natural killer (NK) cells targeting cadherin 17 (CDH17) for the treatment of GI tumors. In addition, to enhance the efficacy of CAR-NK cells, we also incorporated CV1, a CD47-SIRPα axis inhibitor, to evaluate the anti-tumor effect of this combination. We found that CDH17-CAR-NK cells effectively eliminated GI cancers cells in a CDH17-dependent manner. CDH17-CAR-NK cells also exhibit potent in vivo anti-tumor effects in cancer cell-derived xenograft and patient-derived xenograft mouse models. Additionally, the anti-tumor activity of CDH17-CAR-NK cells is synergistically enhanced by CD47-signal regulatory protein α (SIRPα) axis inhibitor CV1, likely through augmented macrophages activation and an increase in M1-phenotype macrophages in the tumor microenvironment. Collectively, our findings suggest that CDH17-targeting CAR-NK cells are a promising strategy for GI cancers. The combination of CDH17-CAR-NK cells with CV1 emerges as a potential combinatorial approach to overcome the limitations of CAR-NK therapy. Further investigations are warranted to speed up the clinical translation of these findings.

T-cell acute lymphoblastic leukemia (T-ALL) is a highly aggressive hematologic malignancy with a poor prognosis, despite advancements in treatment. Many patients struggle with relapse or refractory disease. Investigating the role of the super-enhancer (SE) regulated gene ubiquitin-specific protease 20 (USP20) in T-ALL could enhance targeted therapies and improve clinical outcomes. Analysis of histone H3 lysine 27 acetylation (H3K27ac) chromatin immunoprecipitation sequencing (ChIP-seq) data from six T-ALL cell lines and seven pediatric samples identified USP20 as an SE-regulated driver gene. Utilizing the Cancer Cell Line Encyclopedia (CCLE) and BloodSpot databases, it was found that USP20 is specifically highly expressed in T-ALL. Knocking down USP20 with short hairpin RNA (shRNA) increased apoptosis and inhibited proliferation in T-ALL cells. In vivo studies showed that USP20 knockdown reduced tumor growth and improved survival. The USP20 inhibitor GSK2643943A demonstrated similar anti-tumor effects. Mass spectrometry, RNA-Seq, and immunoprecipitation revealed that USP20 interacted with hypoxia-inducible factor 1 subunit alpha (HIF1A) and stabilized it by deubiquitination. Cleavage under targets and tagmentation (CUT&Tag) results indicated that USP20 co-localized with HIF1A, jointly modulating target genes in T-ALL. This study identifies USP20 as a therapeutic target in T-ALL and suggests GSK2643943A as a potential treatment strategy.

Objective To explore the disinfection effect of periodic hypochlorous acid infusion on water supply pipelines.Methods Water specimens from 6 water outlets of central sterile supply department were collected at baseline for microbial culture.After introducing a slightly acidic hypochlorous acid water generator,water speci-mens were collected every 10 days.Continuous disinfection with hypochlorous acid was carried out on the 1st-3rd day,and discontinued on the 4th-10th day.Water specimens of 6 water outlets were collected on the 1st,4th,7th,and 10th day of each cycle,in total 3 cycles.Microbial culture and metagenomic next-generation sequencing(mNGS)analysis were conducted simultaneously on all water specimens from the outlets of the endoscope cleaning tank.Results Before disinfection of the pipeline,a total of 18 bottles of water specimens were collected.Bacterial count of water specimens from 10 bottles(55.56％)was between 102 and 104 CFU/mL,mainly Sphingomonas ad-hesins and Bacillus cereus.After disinfection,only 2 out of 72 water specimens(2.78％)exceeded the bacterial lim-it.The mNGS results showed that three most dominant bacterial genera in the pre-disinfection water specimens were Sphingomonas,Methylobacterium,and Ralstonia,with stringent mapped reads number(SMRN)ranging from 10 000 to 100 000;while the most dominant bacterial genera in post-disinfection water specimens were Lacto-baci-llus,Ralstonia,Acinetobacter,and Bradyrhizobium.PCoA analysis showed that there was a statistically sig-nificant difference in β-diversity of water specimens before and after disinfection(P＜0.05).Conclusion Periodic hypochlorous acid infusion disinfection can effectively remove bacterial biofilms in water pipelines,but there is a risk of bacterial biofilm recovery during disinfection suspension.In the future,monitoring and management of medical water should be strengthened.