Objective: To investigate the factors influencing intraoperative blood transfusion in patients with hip fractures and to develop a machine learning (ML) model for predicting this risk. Methods: A total of 424 patients with hip fractures who underwent surgical treatment between November 2022 and March 2025 in our hospital were selected. Key feature variables of intraoperative blood transfusion risk were identified using the Boruta algorithm. Four different ML algorithms—support vector machine (SVM), linear discriminant analysis (LDA), mixed discriminant analysis (MDA), and extreme gradient boosting (XGBoost)—were used to develop predictive models for intraoperative blood transfusion risk. The predictive performance of the four ML models were evaluated using accuracy, precision, receiver operating characteristic (ROC) curves, precision-recall curves (PRC), precision-recall gain curves (PRGC), and F1 scores. Shapley additive interpretation (SHAP) was used to interpret the final model. Results: Among the 424 patients, 77(18.2%) received intraoperative blood transfusion. The Boruta algorithm identified albumin (ALB), activated partial thromboplastin time (APTT), types of anesthesia, types of fracture, and hemoglobin (Hb) as key feature variables for predicting intraoperative blood transfusion risk. In model evaluation, the SVM model outperforms the other three models across multiple metrics, including the area under the receiver operating characteristic curve (AUC), recall, recall gain, accuracy, precision, F1 score, and the area under the precision-recall curve (PRC-AUC). The SVM model, interpreted and visualized based on SHAP values, effectively predicted intraoperative blood transfusion risk in patients with hip fracture. A visual online application was developed based on the SVM model (https://pbo-nomogram.shinyapps.io/blood/). Conclusion: Preoperative low ALB and Hb levels, prolonged APTT, general anesthesia, and intertrochanteric fractures are risk factors for intraoperative blood transfusion in hip fracture patients. The risk prediction model for intraoperative blood transfusion constructed based on the SVM algorithm has optimal performance, which provides new ideas and methods for the clinical early identification of hip fracture patients with high transfusion risk and the implementation of targeted interventions.

Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.

Background/Aims: This study assessed the long-term efficacy and safety of tenofovir alafenamide (TAF) in real-world settings. Methods: Patients who were candidates for TAF treatment and were followed up at 12-week intervals over 192 weeks were enrolled in this study. Results: One hundred and forty-four patients (50 treatment-naive and 94 treatment-experienced) were included in this study. The cumulative incidence rates of cirrhosis and hepatocellular carcinoma at 192 weeks were 3.9% and 0.7%, respectively. In treatment-naive patients, the rates of a virological response, HBeAg conversion, and HBsAg loss at 192 weeks were 100%, 33.3%, and 2%, respectively. The treatment-naive patients exhibited higher baseline HBsAg levels than the treatment-experienced patients (4.31 log10IU/mL vs. 3.97 log10IU/mL). A significant decrease in the HBsAg levels from the baseline was observed at 144 and 192 weeks in the treatment-naive patients (p=0.01). The baseline body mass index (BMI) <25 kg/m2 (p=0.02) and HBsAg <3.3 log10IU/mL (p=0.04) were identified as predictive factors for a decrease in HBsAg ≥0.5 log10IU/mL at 48 weeks. The eGFR levels were consistently lower in the treatment-experienced patients throughout the study. Although the treatment-naive patients showed no abnormal increases in urinary URBP, the treatment-experienced patients showed elevated urinary β2MG and NAG levels at the baseline, which decreased over the treatment course. The total cholesterol, triglyceride, and low-density lipoprotein levels were similar in both groups. Conclusions Prolonging the TAF treatment duration enhances the virological response rate. The decline in HBsAg levels was more significant in the treatment-naive patients than in the treatment-experienced patients. The baseline BMI <25 kg/m2 and HBsAg <3.3 log10IU/mL were predictive factors for a significant decline in HBsAg at 48 weeks. TAF has high renal safety and no significant impact on lipid levels.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

OBJECTIVE: To evaluate the clinical effect and safety of acupuncture manipulation on treatment of intractable facial paralysis (IFP), and verify the practicality and precision of the Anzhong Facial Paralysis Precision Scale (Eyelid Closure Grading Scale, AFPPS-ECGS). METHODS: A multicentre, single-blind, randomized controlled trial was conducted from October 2022 to June 2024. Eighty-nine IFP participants were randomly assigned to an ordinary acupuncture group (OAG, 45 cases) and a characteristic acupuncture group (CAG, 44 cases) using a random number table method. The main acupoints selected included Yangbai (GB 14), Quanliao (SI 18), Yingxiang (LI 20), Shuigou (GV 26), Dicang (ST 4), Chengjiang (CV 24), Taiyang (EX-HN 5), Jiache (ST 6), Fengchi (GB 20), and Hegu (LI 4). The OAG patients received ordinary acupuncture manipulation, while the CAG received characteristic acupuncture manipulation. Both groups received acupuncture treatment 3 times a week, with 10 times per course, lasting for 10 weeks. Facial recovery was assessed at baseline and after the 1st, 2nd and 3rd treatment course by AFPPS-ECGS and the House-Brackmann (H-B) Grading Scale. Infrared thermography technology was used to observe the temperature difference between healthy and affected sides in various facial regions. Adverse events and laboratory test abnormalities were recorded. The correlation between the scores of the two scales was analyzed using Pearson correlation coefficient. RESULTS: After the 2nd treatment course, the two groups showed statistically significant differences in AFPPS-ECGS scores (P<0.05), with even greater significance after the 3rd course (P<0.01). Similarly, H-B Grading Scale scores demonstrated significant differences between groups following the 3rd treatment course (P<0.05). Regarding temperature measurements, significant differences in temperatures of frontal and ocular areas were observed after the 2nd course (P<0.05), becoming more pronounced after the 3rd course (P<0.01). Additionally, mouth corner temperature differences reached statistical significance by the 3rd course (P<0.05). No safety-related incidents were observed during the study. Correlation analysis revealed that the AFPPS-ECGS and the H-B Grading Scale were strongly correlated (r=0.86, 0.91, 0.93, and 0.91 at baseline, and after 1st, 2nd, and 3rd treatment course, respectively, all P<0.01). CONCLUSIONS Acupuncture is an effective treatment for IFP, and the characteristic acupuncture manipulation enhances the therapeutic effect. The use of the AFPPS-ECGS can more accurately reflect the recovery status of patients with IFP. (Trial registration No. ChiCTR2200065442).
Humans ; Acupuncture Therapy/methods* ; Facial Paralysis/therapy* ; Female ; Male ; Middle Aged ; Adult ; Treatment Outcome ; Acupuncture Points ; Aged

Objective To explore the relationship between dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI)and clinical pathological features of invasive breast cancer and lymphovascular invasion(LVI).Methods Imaging and clinical pathological data were retrospectively collected from 508 patients with invasive breast cancer who underwent breast DCE-MRI at the First Medical Center of Chinese PLA General Hospital from January 2019 to August 2021.Patients were divided into the LVI-positive(LVI+)group(n=79)and LVI-negative(LVI-)group(n=429)based on postoperative pathological results.Univariate and multivariate logistic regression analyses were used to identify risk factors for LVI.Results Compared with LVI-group,LVI+group had a higher proportion of patients aged<45 years(44.3%vs.27.0%,P=0.002),non-mass-like enhancement(NME)(31.7%vs.17.7%,P=0.004),Ki-67 expression rate(40.0%vs.30.0%,P<0.001),high Ki-67 expression(94.9%vs.78.1%,P=0.001),Luminal B subtype(76.0%vs.60.1%,P=0.008),and positive axillary lymph nodes rate(72.2%vs.31.5%,P<0.001),while the proportion of Luminal A subtype was lower(2.5%vs.21.5%,P<0.001).Univariate and multivariate logistic regression analyses showed that age≥45 years(OR=0.468,95%CI 0.280-0.783,P=0.004)was an independent protective factor for LVI,while NME(OR=1.987,95%CI 1.126-3.444,P=0.016)was an independent risk factor.Compared with Luminal A subtype,patients with Luminal B subtype(OR=10.482,95%CI 3.164-64.923,P=0.001),HER-2 overexpression subtype(OR=11.571,95%CI 2.755-79.341,P=0.003)and triple-negative subtypes(OR=8.433,95%CI 1.985-57.908,P=0.009)had a higher risk of LVI.Conclusions Age≥45 years is an independent protective factor for LVI,while NME is an independent risk factor.Among molecular subtypes,patients with Luminal B,HER-2 overexpression and triple-negative subtypes have a higher risk of LVI compared with the Luminal A subtype.

Objective To investigate the therapeutic potential and prophylactic value of concomitant administration of nonsteroidal anti-inflammatory drug(NSAID)and antimicrobial agents in mitigating the incidence and severity of trauma-induced sepsis.Methods A retrospective cohort study encompassed the collection of clinical records from trauma patients managed in the department of intensive care unit(ICU)of Daping Hospital,Army Medical University(Third Military Medical University)from June 2008 to June 2024.Based on administered therapeutic protocols,patients were stratified into a control group(receiving antibiotic monotherapy)and a experimental group(undergoing adjunctive therapy with NSAID in conjunction with antimicrobial agents).Intergroup comparisons were performed to elucidate differences in baseline clinical characteristics and laboratory indices pertinent to therapeutic outcomes.Results A total of 268 trauma patients were included,with 72 patients in the control group and 196 patients in the experimental group.The majority of cases involved open trauma(67.5%)and injuries sustained from traffic accidents(44.0%),reflecting the principal mechanisms of injury.The respiratory tract was the most common site of infection(67.5%),with Acinetobacter baumannii(A.baumannii)emerging as the leading causative microorganism(18.0%).Among therapeutic agents,ibuprofen represented the most frequently employed NSAID(59.8%),whereas cephalosporins constituted the predominant class of antimicrobials(30.5%).Following intervention,the lymphocyte percentage(LYM%)was markedly elevated in the experimental group relative to control group[0.14(0.09,0.20)vs.0.12(0.09,0.15),P<0.01].In contrast,the levels of white blood cell count(WBC),neutrophil percentage(NEU%),D-dimer,glucose(Glu),and lactic acid(Lac)were significantly reduced[WBC(×109/L):8.82(6.36,12.96)vs.12.10(7.78,15.54);NEU%:0.76(0.67,0.81)vs.0.78(0.72,0.83);D-dimer(μg/L):2208.0(889.5,3301.5)vs.2943.9(1735.4,4997.6);Glu(mmol/L):6.8(6.2,7.9)vs.7.7(6.6,9.2);Lac(mmol/L):0.9(0.6,1.2)vs.1.1(0.8,1.5),all P<0.05].The experimental group demonstrated a significantly reduced incidence of traumatic sepsis compared with the control group[15.8%(31/196)vs.26.4%(19/72),P<0.05].Conclusion The combination of NSAID and antimicrobial agents exerts its protective effect by attenuating inflammatory and stress responses,reestablishing immune homeostasis,correcting coagulopathy,and enhancing tissue perfusion,thereby significantly decreasing the incidence of traumatic sepsis and contributing to improved prognostic outcomes in injured patients.

AIM To explore the effects of Hofmeister series ions on encapsulation efficiencies of cinnamaldehyde,paeonol,and ligustilide in inclusion complex of volatile oils from Wenjing Decoction.METHODS The volatile oils were extracted,after which the β-cyclodextrin inclusion complex was prepared,the thermal stability was evaluated,and encapsulation efficiencies and inclusion complex constants of various volatile components in Na2SO4,NaH2PO4,NaCl,NaI,NaSCN solutions were determined.RESULTS The β-cyclodextrin inclusion complex demonstrated good thermal stability within 10 d.After the addtion of Hofmeister series ions,various volatile components displayed increased encapsulation efficiencies and inclusion complex constants,and concentration-dependent manner was observable in the latter.CONCLUSION Hofmeister series ions can affect the binding affinities of volatile components and β-cyclodextrin in volatile oils from Wenjing Decoction,thus regulate their encapsulation efficiencies.