Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

This case report describes a 68-year-old male patient diagnosed with primary hepatocellular carcinoma (HCC). After receiving Yttrium-90 microsphere selective internal radiation therapy (⁹⁰Y-SIRT), the tumor significantly reduced in size, and tumor markers alpha fetoprotein (AFP) and abnormal prothrombin (PIVKA-Ⅱ) decreased. Postoperative pathological results showed minimal residual tumor cells, indicating that ⁹⁰Y-SIRT has good efficacy and safety in downstaging and conversion of HCC, thereby facilitating subsequent surgical resection.

Objective:To analyze the reoperation rate and causes during the early adoption phase of unilateral biportal endoscopy (UBE).Methods:The clinical data of 180 patients who underwent UBE performed by a single surgeon at Beijing Friendship Hospital, Capital Medical University from October 2021 to June 2023 were retrospectively analyzed. Clinical and imaging data of patients who underwent reoperation were collected to analyze the causes of reoperation, and the clinical efficacy of the reoperations was also followed up. Measurement data were expressed as mean ± standard deviation ( ± s), and t-test was used before and after treatment. Results:A total of 180 patients who underwent UBE were included in this study, of which 6 patients underwent reoperation, and the reoperation rate was 3.33%. Among them, 3 cases occurred in the first 90 surgeries and the other 3 occurred in the subsequent 90 surgeries. The causes of reoperation were as follows: recurrent lumbar disc herniation at the same segment postoperatively in 2 cases, insufficient decompression in 2 cases, disc herniation following isolated decompression in 1 case, and immediate postoperative perianal numbness in 1 case. The time between the initial surgery and reoperation ranged from 0 to 187 days, with an average of 63.3 days. The average follow-up time after reoperation was 18.3 months. The visual analogue scale (VAS) and Oswestry disability index (ODI) scores of the patients at the last follow-up were significantly improved compared with those before operation (VAS score of low back pain: 5.2 ± 1.7 before operation, 1.2 ± 0.8 at the last follow-up, P<0.001; VAS score of leg pain: 7.2 ± 1.5 before operation, 1.2 ± 1.2 at the last follow-up, P<0.001; ODI score: 67.3 ± 5.7 before operation, 20.2 ± 8.2 at the last follow-up, P<0.001). The postoperative modified MacNab scores were generally satisfactory (4 cases were rated as excellent, accounting for 66.7%; 2 cases were rated as good, accounting for 33.3%). Except for one patient who experienced dural injury during open revision surgery, there were no serious complications such as nerve damage. Conclusions:In the early stages of UBE surgery, recurrent lumbar disc herniation and inadequate decompression are the primary reasons for reoperation, typically occurring within the first three months postoperatively. Reoperation does not significantly increase the risk of nerve injury. Enhanced early postoperative follow-up is recommended. For symptomatic patients, a second surgery with thorough decompression can yield satisfactory treatment outcomes.

Objective To investigate the predictive value of temperature gradients on the mortality of sepsis patients and their correlation with fluid input.Methods By means of a prospective observational method,154 patients with sepsis or septic shock admitted to the Department of Critical Care Medicine at Nanfang Hospital,Southern Medical University from November 2019 to November 2021 were included as research subjects.They were divided into a survivor group(n=118)and a non-survivor group(n=36)according to whether they survived within 28 days.The core-to-toe temperature gradient(CTTG)and toe-to-room temperature gradient(TRTG)were monitored and calculated immediately upon admission to the intensive care unit(ICU)and 6 hours after admission.Receiver operating characteristic(ROC)curve was used to explore the predictive value of temperature gradients on mortality,and multivariate Cox regression analysis was performed to explore the risk factors of 28-day mortality in sepsis patients.The results were verified through survival analysis.Correlation analysis and multivariate analysis of variance were used to explore the correlation between temperature gradients and fluid input,as well as noradrenaline doses.Results Among the 154 patients,118 survived within 28 days(survivor group),and 36 died(non-survivor group).ROC curve and multivariate Cox regression analysis showed that a toe-to-room temperature gradient of≤5.35℃within 6 hours after admission was a risk factor for 28-day mortality.Compared with patients with a high toe-to-room temperature gradient(>5.35℃),patients with a low toe-to-room temperature gradient(≤5.35℃)had a 2.74-fold increase in the risk of 28-day mortality(P=0.004,95%CI 1.54,9.12).The CTTG and TRTG upon admission to the ICU and 6 hours after admission were not significantly associated with fluid input or noradrenaline doses(P>0.05).Conclusions A toe-to-room temperature gradient of less than or equal to 5.35℃within 6 hours after ICU admission is a risk factor for 28-day mortality in sepsis patients.The improvement of temperature gradients at different time points is not associated with fluid input.

Objective To reveal the development characteristics of fat percentage and muscle mass in three nomadic populations in the Hexi Corridor of Gansu.Methods Bioelectrical impedance analysis was used to determine the values of 13 indexes of fat percentage and muscle mass in 263 cases of Gansu Kazakhs,400 cases of Gansu Mongols,and 362 cases of Yugu adults.Results In the three nomadic populations of the Hexi Corridor,visceral fat level of males was significantly positively correlated with age,while total body muscle mass and estimated bone mass were significantly negatively correlated with age.In females,percent body fat,visceral fat grade,percent left and right upper limb fat,percent right lower limb fat and percent trunk fat were all significantly positively correlated with age,while trunk muscle mass was significantly negatively correlated with age.The result of principal component analysis showed that the three nomadic populations in the Hexi Corridor were close to each other in terms of fat percentage and muscle mass characteristics,with high visceral fat grades in males and normal visceral fat grade in females.Among the 13 populations,three nomadic groups in the Hexi Corridor had high fat percentage and muscle mass.Overall,the nomadic population had greater fat percentage and muscle mass than the semi-agricultural and semi-pastoral population,and even more significantly greater than the agrarian population.The long-term integration of the historical Hexi Corridor populations result ed in the relative proximity of the genetic structure of three nomadic populations,which was a genetic factor for the proximity of their fat percentage and muscle mass.Higher per capita disposable income was a socio-economic factor for high fat percentage and muscle mass among Gansu Kazakhs and Gansu Mongolians.Low average annual temperature was an environmental factor for high muscle mass among Gansu Kazakhs and Yugus.Conclusion Gansu Kazakhs,Gansu Mongols,and Yugus have the fat percentage and muscle mass characteristic of northern Chinese populations.

The chemical constituents were systematically separated from the roots of Berberis polyantha by various chromatographic methods, including silica gel column chromatography, HP20 column chromatography, polyamide column chromatography, reversed-phase C_(18) column chromatography, and preparative high-performance liquid chromatography. The structures of the compounds were identified by physicochemical properties and spectroscopic techniques(1D NMR, 2D NMR, UV, MS, and CD). Four phenylpropanoids were isolated from the methanol extract of the roots of B. polyantha, and they were identified as(2R)-1-(4-hydroxy-3,5-dimethoxyphenyl)-1-propanone-O-β-D-glucopyranoside(1), methyl 4-hydroxy-3,5-dimethoxybenzoate(2),(+)-syringaresinol(3), and syringaresinol-4-O-β-D-glucopyranoside(4). Compound 1 was a new compound, and other compounds were isolated from this plant for the first time. The anti-inflammatory activity of these compounds was evaluated based on the release of nitric oxide(NO) in the culture of lipopolysaccharide(LPS)-induced RAW264.7 macrophages. At a concentration of 10 μmol·L~(-1), all the four compounds inhibited the LPS-induced release of NO in RAW264.7 cells, demonstrating potential anti-inflammatory properties.
Plant Roots/chemistry* ; Animals ; Mice ; Berberis/chemistry* ; RAW 264.7 Cells ; Macrophages/immunology* ; Drugs, Chinese Herbal/isolation & purification* ; Nitric Oxide/metabolism* ; Molecular Structure ; Anti-Inflammatory Agents/isolation & purification*

This study aimed to characterize and identify the non-volatile components in aqueous and ethanolic extracts of the stems and leaves of Rhododendron tomentosum by using sensitive and efficient ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry(UHPLC-Q-TOF-MS) combined with a self-built information database. By comparing with reference compounds, analyzing fragment ion information, searching relevant literature, and using a self-built information database, 118 compounds were identified from the aqueous and ethanolic extracts of R. tomentosum, including 35 flavonoid glycosides, 15 phenolic glycosides, 12 flavonoids, 7 phenolic acids, 7 phenylethanol glycosides, 6 tannins, 6 phospholipids, 5 coumarins, 5 monoterpene glycosides, 6 triterpenes, 3 fatty acids, and 11 other types of compounds. Among them, 102 compounds were reported in R. tomentosum for the first time, and 36 compounds were identified by comparing them with reference compounds. The chemical components in the ethanolic and aqueous extracts of R. tomentosum leaves and stems showed slight differences, with 84 common chemical components accounting for 71.2% of the total 118 compounds. This study systematically characterized and identified the non-volatile chemical components in the ethanolic and aqueous extracts of R. tomentosum for the first time. The findings provide a reference for active ingredient research, quality control, and product development of R. tomentosum.
Rhododendron/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Mass Spectrometry/methods* ; Plant Leaves/chemistry*

As a new type of production factor that can empower the development of new quality productivity, the data element is an important engine to promote the high quality development of the industry. Traditional Chinese medicine(TCM) dispensing is the most basic work of TCM clinical pharmacy, and its quality directly affects the clinical efficacy of TCM. The integration of data elements and TCM dispensing can stimulate the innovation and vitality of the TCM dispensing industry and promote the high-quality and sustainable development of the industry. A large-scale, detailed, and systematic study on TCM dispensing was conducted. The innovative practice path of data fusion construction in the whole process of TCM dispensing was investigated by integrating the digital resources "nine full activities" of TCM dispensing, creating the digital dictionary of "TCM clinical information data elements", and exploring innovative applications of TCM dispensing driven by data and technology, so as to promote the standardized, digital, and intelligent development of TCM dispensing in medical health services. The research content of this project was successfully selected as the second batch of "Data element×" typical cases of National Data Administration in 2024, which is the only selected case in the field of TCM.
Medicine, Chinese Traditional/methods* ; Drugs, Chinese Herbal ; Humans

OBJECTIVE: To explore, identify, and develop novel blood-based indicators using machine learning algorithms for accurate preoperative assessment and effective prediction of postoperative complication risks in patients with rheumatoid arthritis (RA) undergoing total knee arthroplasty (TKA). METHODS: A retrospective cohort study was conducted including RA patients who underwent unilateral TKA between January 2019 and December 2024. Inpatient and 30-day postoperative outpatient follow-up data were collected. Six machine learning algorithms, including decision tree, random forest, logistic regression, support vector machine, extreme gradient boosting, and light gradient boosting machine, were used to construct predictive models. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), F1-score, accuracy, precision, and recall. SHapley Additive exPlanations (SHAP) values were employed to interpret and rank the importance of individual variables. RESULTS: According to the inclusion criteria, a total of 1 548 patients were enrolled. Ultimately, 18 preoperative indicators were identified as effective predictive features, and 8 postoperative complications were defined as prediction labels for inclusion in the study. Within 30 days after surgery, 453 patients (29.2%) developed one or more complications. Considering overall accuracy, precision, recall, and F1-score, the random forest model [AUC=0.930, 95% CI (0.910, 0.950)] and the extreme gradient boosting model [AUC=0.909, 95% CI (0.880, 0.938)] demonstrated the best predictive performance. SHAP analysis revealed that anti-cyclic citrullinated peptide antibody, C-reactive protein, rheumatoid factor, interleukin-6, body mass index, age, and smoking status made significant contributions to the overall prediction of postoperative complications. CONCLUSION Machine learning-based models enable accurate prediction of postoperative complication risks among RA patients undergoing TKA. Inflammatory and immune-related blood biomarkers, such as anti-cyclic citrullinated peptide antibody, C-reactive protein, and rheumatoid factor, interleukin-6, play key predictive roles, highlighting their potential value in perioperative risk stratification and individualized management.
Humans ; Arthroplasty, Replacement, Knee/adverse effects* ; Arthritis, Rheumatoid/blood* ; Machine Learning ; Postoperative Complications/blood* ; Female ; Male ; Retrospective Studies ; Middle Aged ; Aged ; Risk Factors ; Preoperative Period ; C-Reactive Protein/analysis* ; Risk Assessment