ObjectiveTo construct an automatic measurement model for palmar tilt and radial inclination suitable for traditional Chinese medicine （TCM） clinical scenarios， and to validate its accuracy and efficiency in TCM manipulative reduction settings. MethodsData on anteroposterior （AP） and lateral X-rays of distal radius fractures were collected from patients admitted to 18 TCM/ integrated TCM and western medicine hospitals in Jiangsu province between September 1st， 2023， and September 1st， 2024， via the Jiangsu Diagnosis and Treatment Big Data Platform for TCM Dominant Diseases. A medical image segmentation framework based on multi-scale feature fusion and edge-awareness was employed， combined with anatomical knowledge specific to TCM orthopedics， to optimize the feature extraction strategy of an artificial intelligence （AI） model. This framework enabled automatic segmentation of fracture regions and measurement of distal radius palmar tilt and radial inclination. The accuracy of the AI model in measuring radial inclination and volar tilt was validated， and the measurement time and average time gain rate of the AI model were compared to those of manual measurement. ResultsA total of 15,444 AP and lateral X-ray images of distal radius fractures were collected， and were divided into a training set （11,144 images， 5066 AP and 6078 lateral）， a validation set （3700 images， 1840 AP and 1860 lateral）， and an independent test set （600 images， 300 AP and 300 lateral） after preprocessing. In the measurement of 300 AP X-rays in the independent test set for radial inclination， when the degree error between AI measurement and manual measurement was ＜3° and ＜5°， AI measurement accuracy was 83% and 93%， respectively. In 300 lateral X-rays in the test set for palmar tilt， when AI measurements had an error of ＜3° and ＜5° compared to manual measurements， corresponding accuracy rate was 78% and 90%， respectively. For 50 X-ray images， AI measurement time was （1.37±0.05） min for radial inclination while manual measurement time was （22.57±2.52） min （P＜0.001）； in terms of palmar tilt， the AI measurement time was （1.33±0.14） min， shorter than （23.70±2.80） min for manual measurement time （P＜0.001）. Average time gain rates for manual and AI measurements were 93.93% and 94.39% respectively. ConclusionAn automatic measurement model for palmar tilt and radial inclination in distal radius fractures has been established， enabling more accurate and efficient assessment as well as providing a tool to support the quantitative evaluation of the efficacy of TCM manipulative reduction and large-sample clinical research.

Objective:To investigate the associations of onset age, diabetes duration, and glycated hemoglobin (HbA1c) levels with ischemic stroke risk in type 2 diabetes patients.Methods:The participants were from Comprehensive Research on the Prevention and Control of the Diabetes in Jiangsu Province. The study used data from baseline survey from December 2013 to January 2014 and follow-up until December 31, 2021. After excluding the participants who had been diagnosed with stroke at baseline survey and those with incomplete information on onset age, diabetes duration, and HbA1c level, a total of 17 576 type 2 diabetes patients were included. Cox proportional hazard model was used to calculate the hazard ratio ( HR) and 95% CI of onset age, diabetes duration, and HbA1c level for ischemic stroke. Results:During the median follow-up time of 8.02 years, 2 622 ischemic stroke cases were registered. Multivariate Cox proportional risk regression model showed that a 5-year increase in type 2 diabetes onset age was significantly associated with a 5% decreased risk for ischemic stroke ( HR=0.95, 95% CI: 0.92-0.99). A 5-year increase in diabetes duration was associated with a 5% increased risk for ischemic stroke ( HR=1.05, 95% CI: 1.02-1.10). Higher HbA1c (per 1 standard deviation increase: HR=1.17, 95% CI: 1.13-1.21) was associated with an increased risk for ischemic stroke. Conclusion:The earlier onset age of diabetes, longer diabetes duration, and high levels of HbA1c are associated with an increased risk for ischemic stroke in type 2 diabetes patients.

To investigate the associations of serum gamma-glutamyl transferase (GGT) levels with the risk of cardiovascular disease (CVD) and its subtypes in patients with type 2 diabetes mellitus (T2DM) in Jiangsu Province.Methods:The participants were enrolled in the Comprehensive Research project regarding 'Prevention and Control of Diabetes' in Jiangsu Province. The baseline survey was conducted from 2013 to 2014, and follow-up until December 31, 2021. After excluding the participants who self-reported with chronic liver disease/stroke/coronary heart disease at baseline survey and those with incomplete information on GGT, a total of 16 147 T2DM patients were included in the final analysis. Cox proportional hazard regression models were used to calculate the hazard ratio ( HR) and their 95% CI of GGT for CVD, myocardial infarction, and stroke. Restricted cubic spline models were applied to analyze the dose-response relationship between GGT and the risk of CVD and its subtypes. Results:During the median follow-up time of 8.02 years, 2 860 CVD cases were registered, including 196 cases of myocardial infarction and 2 730 cases of stroke. Multivariate Cox proportional risk regression model indicated that compared to the lowest serum GGT level group, the highest GGT level group had a 24% increased risk of CVD ( HR=1.24, 95% CI: 1.09-1.41) and a 23% increased risk of stroke ( HR=1.23, 95% CI: 1.08-1.40). The restricted cubic spline model showed a nonlinear dose-response relationship between GGT and the risk of CVD, myocardial infarction, and stroke in T2DM patients. Conclusions:High levels of GGT may be associated with an increased risk of cardiovascular disease in T2DM patients, which needs further exploration and validation in future clinical practice.

The incidence rate of nonalcoholic fatty liver disease (NAFLD) is gradually increasing, and NAFLD has become the most important chronic liver disease in China. At present, the pathogenesis of NAFLD has not been fully elucidated and there are still no effective drugs. From the perspectives of pathogenesis, noninvasive diagnosis, and drug action and efficacy, this article introduces the research advances in metabolomics regarding endogenous small molecule metabolites in NAFLD, so as to provide new ideas and methods for further exploration of NAFLD.

OBJECTIVE: To analyze the effects of alterations in the expressions of methyltransferase on protein expression profiles in human nasopharyngeal carcinoma (NPC) cells and enrich the differential signaling pathways. METHODS: The total protein was extracted from -knockout cell line CNE1 and the wild-type cell line CNE1, and the differentially expressed proteins were screened by tandem mass tag (TMT) labeled protein quantification technique and tandem mass spectrometry. GO analysis was used to annotate and enrich the differentially expressed proteins, and the KEGG database was used to enrich and analyze the pathways of the differential proteins. RESULTS: With a fold change (FC)≥1.2 and < 0.05 as the screening standard, 2049 differentially expressed proteins were identified in CNE1 cells, among which 904 were up-regulated and 1145 were down-regulated. GO functional annotation results indicated that knockout caused characteristic changes in multiple biological processes (cell processes and regulation, cell movement, metabolic processes, and biosynthesis of cellular components), molecular functions (catalytic activity and molecular binding, transcription factor activity), and cellular components (cell membrane, organelle, macromolecular complex). KEGG analysis showed that the differentially expressed proteins were involved in an array of signaling pathways closely related to tumors, including MAPK, PI3K-Akt, Ras, Rap1, mTOR, Hippo, HIF-1, Wnt, AMPK, FoxO, ErbB, P53 and JAK-STAT. CONCLUSIONS knockout significantly changes the protein expression characteristics of NPC cells and affects a number of signal pathways closely related to tumors. The results provide evidence for investigation of the pathogenesis and therapeutic target screening of NPC.

Purpose　The aim is to study α-glucosidase inhibitor from Schisandra Chinensis(Turcz.)Baill.Methods　The inhibitor was purified by soaking,ultrafiltration,ion-exchange chromatography and Lead Acetate deposition.Results　A α-glucosidase inhibitor was obtained.Conclusion　The inhibitor was a kind of non-competition inhibitor with large molecular weight of over 5×105D.