Objective To evaluate the efficacy and safety of CT-guided percutaneous radiofrequency ablation (RFA) as an alternative for video-assisted thoracoscopic surgery (VATS) in treating multiple pulmonary nodules. Methods A retrospective analysis was conducted on the clinical data of 113 patients with multiple pulmonary nodules admitted to Jiangsu Provincial Hospital of Traditional Chinese Medicine from October 2020 to October 2022. The patients were divided into the RFA group (n＝50) and the VATS group (n＝63) based on the treatment method. Perioperative indicators (operation time, intraoperative blood loss, postoperative length of hospital stay), oncological outcomes (recurrence-free survival [RFS], overall survival [OS]), and postoperative complication rates were compared between the two groups. Univariate and multivariate Cox regression analysis was performed to identify independent prognostic factors. Results The operation time in the RFA group was significantly shorter than that in the VATS group ([75.2±20.1] min vs [102.3±28.7]) min, P＜0.001). No statistically significant differences were observed in intraoperative blood loss and postoperative length of hospital stay. After follow-up of 24 (12, 30) months, no statistically significant differences were found in RFS (HR＝1.25, P＝0.445) or OS (HR＝1.42, P＝0.402) between the two groups. Mixed ground-glass nodules with high solid component and solid nodule were identified as independent risk factors for RFS (HR＝2.44, P＝0.023; HR＝2.97, P＝0.007) and OS (HR＝2.87, P＝0.022; HR＝3.43, P＝0.005) in patients with multiple pulmonary nodules. The total complication rate in the RFA group was lower than that in the VATS group (12.0% vs 34.9%, P＝0.009). Conclusions The efficacy of CT-guided RFA in treating multiple pulmonary nodules is comparable to that of VATS, with good safety, and it shows promise as an alternative to surgical treatment for multiple pulmonary nodules.

The superiority of magnetic resonance(MR)images in soft tissue imaging makes them indispensable for medical diagnosis and radiotherapy,but factors such as acquisition cost and contraindications limit their widespread application.In contrast,computed tomography(CT)scanning has the advantages of fast imaging speed and low cost.Herein,this review summarizes the research progress of generative deep learning models in the field of medical CT to MR image synthesis,and especially analyzes the technical characteristics,performance advantages,and challenges of various MR image synthesis methods from clinical scenarios such as spinal lesions,acute ischemic stroke,and tumor segmentation.Furthermore,the application value and future research prospects of medical image synthesis are discussed.

The superiority of magnetic resonance(MR)images in soft tissue imaging makes them indispensable for medical diagnosis and radiotherapy,but factors such as acquisition cost and contraindications limit their widespread application.In contrast,computed tomography(CT)scanning has the advantages of fast imaging speed and low cost.Herein,this review summarizes the research progress of generative deep learning models in the field of medical CT to MR image synthesis,and especially analyzes the technical characteristics,performance advantages,and challenges of various MR image synthesis methods from clinical scenarios such as spinal lesions,acute ischemic stroke,and tumor segmentation.Furthermore,the application value and future research prospects of medical image synthesis are discussed.

Traditional scientific research management suffers from problems such as scattered archives,lack of effective dynamic process supervision for projects,weak data analysis capabilities,and low sharing,making it difficult to meet the unified management of multiple hospital areas in medical groups and the independent management of each branch.The group has devel-oped an intelligent scientific research management system based on artificial big data by constructing the framework and designing the content of various demand modules for scientific research management.This system achieves full coverage management of sci-entific research activities,designing interrelated information data networks for scientific research project process management,a-chievement management,academic(specialized)construction management,postdoctoral management,etc.,realizing informa-tionization and refined management of multiple campuses within the group.Analyze the technological values of each hospital,de-partment,and personnel to provide powerful reference for decision-makers.The information-based scientific research manage-ment system is an important guarantee for hospital groups to intelligently manage and efficiently carry out scientific research work.

[Objective] To analyze the distribution of Rh blood group phenotype in some ethnic groups in China, so as to provide references for accurate blood transfusion. [Methods] The data of CNKI, Wanfang data and VIP were retrieved using "Rh blood group" and "nationality", and the search of PubMed database was conducted with the keywords "Rh blood group", "nationalities", "ethnic groups" and "China", with retrieval time until September 19, 2024 Data were extracted from eligible studies and the literature quality was evaluated using the criteria for cross-sectional studies in STROBE statement. Meta analysis was performed using Stata 11.0 software. [Results] A total of 350 relevant literature were retrieved, of which 26 were included. The total sample size for Rh phenotype distribution detection were 31 432, and the total population for RhD negative screening was 47 227, covering 26 ethnic groups. Meta-analysis revealed that the Rh blood groups phenotype distribution in certain ethnic populations in China was mainly CCDee 46.7% (95%CI=46.2%-47.2%), CcDEe 30.1% (95%CI=29.5%-30.6%), and CcDee 9.0% (95%CI=8.7%-9.3%). Analysis of the RhD-negative phenotype indicated an negative rate of RhD of 0.3% (95%CI=0.2%-0.3%), with the main phenotype distributions of ccdee at 0.2% (95%CI=0.1%-0.2%) and ccdEe at 0.2% (95%CI=0.0%-0.4%). The meta-analysis results of the distribution of common phenotypes among different ethnic groups showed that the CCDee phenotype was mainly distributed as Hani>Dong>Buyi>Miao>Tujia>Hui>Zang>Kazakh>Mongol>Uygur; the CcDEe phenotype: Zang>Mongol>Hui; the CcDee phenotype: Uygur>Kazakh>Mongol>Zang>Hui>Dong>Miao>Tujia>Buyi; the ccDEE phenotype: Zang>Hui=Mongol. The results of this study are similar to those of Qingdao population in China, but differ from studies conducted in North India, German individuals of European ancestry and Saudi Arabian populations. [Conclusion] The distribution of Rh blood group phenotypes in some ethnic groups in China shows no significant difference compared to the Han population, but there are differences when compared to populations in other countries and regions.

Objective:To investigate and validate the performance of a dosiomics model that utilized 3D dose distribution to forecast radiation-induced temporal lobe injury (RTLI) in nasopharyngeal carcinoma (NPC) patients following intensity-modulated radiotherapy (IMRT).Methods:Clinical data of 3578 patients diagnosed with NPC admitted to Jiangsu Cancer Hospital from January 2011 to December 2021 were retrospectively analyzed. According to the inclusion and exclusion criteria, 97 NPC patients who developed RTLI were assigned into the case group. A 1:1 propensity score matching (PSM) method was used to match 97 NPC patients without RTLI as the control group. Patients were assigned into the training cohort ( n=135) and the validation cohort ( n=59) at a 7:3 ratio by simple random method. Dosiomics features were extracted from the patients' three-dimensional dose distribution maps. Spearman rho and the least absolute shrinkage and selection operator regression were used to select dosiomics features. Clinical features were collected and screened by univariate and multivariate analyses. Eight machine learning classifiers were then trained to build dosiomics models and clinical models, respectively. The area under the ROC curve (AUC), sensitivity, and specificity were calculated to compare the predictive performance of the dosiomics and clinical models. Multivariate analysis was conducted using logistic regression to assess the influencing factors, while comparisons of the ROC curves between two different models were performed using the DeLong test. Results:A total of 1130 dosiomics features were extracted from the three-dimensional dose distribution maps, and 14 features were retained for model building after feature selection. The model based on the support vector machine (SVM) classifier achieved the highest AUC value of 0.977 (95% CI: 0.949-1.000) in the validation cohort, with an AUC of 1.000 (95% CI: 1.000-1.000) in the training cohort. By conducting univariate and multivariate analyses of the patients' clinical features, 2 clinical features were retained to build the clinical model. The model based on the SVM classifier achieved the optimal AUC value of 0.667 (95% CI: 0.523-0.810) in the validation cohort, with an AUC of 0.804 (95% CI: 0.730-0.878) in the training cohort. DeLong test showed that the difference between the dosiomics and clinical models was statistically significant ( P<0.05). Conclusion:The dosiomics model based on 3D dose distribution yields high predictive performance for RTLI in NPC patients after IMRT, which surpasses the clinical feature model, providing a new approach for early clinical prediction of RTLI.

Due to advances in treatment methods, the survival rate and quality of life of cancer patients have been improved. Radiation-induced vascular injury (RIVI) is a common adverse reaction following radiotherapy, mainly manifested as capillary injury and atherosclerosis in the irradiated area. Radiotherapy induces RIVI in the cerebral vessels, carotid arteries, coronary arteries, and large arteries through mechanisms such as endothelial cell injury and senescence, oxidative stress and inflammatory responses, angiogenesis, and vascular remodeling. In this review research progress in the pathological features, pathophysiological mechanisms, clinical manifestations, prevention and treatment strategies of RIVI was summarized, aiming to provide insights for future research on RIVI.

Objective:To investigate the relationship between different states of cardiac function and their changes during the course of diabetic foot ulcers(DFU), and to evaluate their impact on patient prognosis.Methods:A retrospective analysis was conducted on 194 DFU patients who were rehospitalized at approximately 3-month intervals. Basic clinical data and cardiac function-related indicators were collected at baseline and follow-up. Patients were followed until death or until November 10, 2024. Outcomes including ulcer healing, recurrence, minor amputation, and death were recorded. Logistic regression models were used to analyze the effects of cardiac function status and its changes on these four outcomes. Results:After treatment, the proportion of patients with NYHA class Ⅱ-Ⅲ decreased significantly from 33.5% at baseline to 21.6%( P=0.009). Serum N-terminal pro-B-type natriuretic peptide(NT-proBNP) level also decreased after treatment compared with baseline [635.85(59.83, 453.28) pg/mL vs 728.67(81.48, 696.15) pg/mL, P=0.055]. Serum NT-proBNP level was significantly higher in the death group compared to the survival group( P=0.002). The proportion of DFU patients with baseline NYHA class Ⅱ-Ⅲ was significantly higher than that in those with class Ⅰ( P=0.012). Regression analysis showed that an improvement in NT-proBNP levels was associated with a lower risk of DFU recurrence( OR=0.378, 95% CI 0.183-0.779, P=0.008), and improvement in NYHA class was associated with a lower mortality risk( OR=0.074, 95% CI 0.020-0.275, P<0.001). Conclusion:Cardiac function status and its changes during the treatment of DFU patients have strong prognostic implications, particularly in predicting the risk of recurrence and death outcomes.

Oroxylin A (OA) is a natural flavonoid primarily derived from the plants Oroxylum indicum and Scutellaria baicalensis. Currently, OA is obtainable through chemical synthesis and exhibits polypharmacological properties, including anti-cancer, anti-inflammatory, anti-microbial, and multi-organ protective effects. The first-in-class drug OA tablets are presently undergoing phase Ib/IIa clinical trials for hepatocellular carcinoma (HCC) treatment. Substantial evidence suggests that OA demonstrates therapeutic potential against various hepatic and gastrointestinal (GI) disorders, including HCC, hepatic fibrosis, fatty liver disease, hepatitis, liver injury, colitis, and colorectal cancer (CRC). OA exerts its therapeutic effects primarily by modulating several crucial signaling pathways, including those associated with apoptosis, oxidative stress, inflammation, glucolipid metabolism, and fibrosis activation. The oral pharmacokinetics of OA is characterized by phase II metabolism, hydrolysis, and enterohepatic recycling. This review provides a comprehensive overview of the critical stages involved in the development of OA tablets, presenting a holistic perspective on the progression of this first-in-class drug from preclinical to clinical phases. It encompasses the synthesis of active pharmaceutical ingredients, pharmacokinetics, pharmacological efficacy, toxicology, drug delivery, and recent advancements in clinical trials. Importantly, this review examines the potential mechanisms by which OA may influence the gut-liver axis, hypothesizing that these interactions may confer health benefits associated with OA that transcend the limitations posed by its poor bioavailability.
Humans ; Flavonoids/pharmacokinetics* ; Tablets ; Animals ; Gastrointestinal Diseases/drug therapy* ; Liver Diseases/drug therapy* ; Drug Development ; Clinical Trials as Topic ; Scutellaria baicalensis/chemistry*

Obesity has become a major global public health issue,and the situation in China is also becoming increasingly severe.Adipose tissue is categorized into white adipose tissue(WAT)and brown adipose tissue(BAT),which regulates metabolic homeostasis by secreting various adipokines.Mitochondria,as the core organelles of energy metabolism,its dysfunction are closely related to obesity.In the state of obesity,mitochondrial dynamics imbalance,oxidative stress,and metabolic dysfunction can all lead to energy metabolism disorders and adipose tissue dysfunction.Moreover,mitochondrial dysfunction not only affects adipose tissue but also extends to multiple organs such as muscles and livers,thereby exacerbating obesity and related metabolic diseases.In recent years,although numerous therapeutic strategies targeting mitochondrial dysfunction have been actively explored,their clinical translation faces challenges.This review explores the association between mitochondrial dysfunction in adipose tissue and obesity,analyses its mechanism and existing treatment strategies,aiming to provide a new perspective for the diagnosis and treatment of obesity.