Objective:To evaluate the efficacy of lamb′s tripe extract and vitamin B 12 capsule (LTEVB 12C) on chronic atrophic gastritis (CAG) at different locations (antrum lesser curvature, antrum greater curvature, gastric angle, corpus lesser curvature, and corpus greater curvature). Methods:From August 2011 to January 2013, 715 patients with CAG in a multicenter, randomized, double-blind, placebo-controlled trial were enrolled from 16 tertiary first-class hospitals across the country, including the First Affiliated Hospital of Air Force Medical University, Nanfang Hospital of Southern Medical University, the First Hospital of Jilin University, West China Hospital of Sichuan University, etc., there were 476 cases in the LTEVB 12C group and 239 cases in the placebo group. The patients of the LTEVB 12C group received LTEVB 12C, and the patients of placebo group received LTEVB 12C mimetic, all the medications were taken 3 capsules each time and 3 times a day after meals, and the treatment course of 2 groups were both 6 months. The efficacy evaluation criteria included the effective rate (a decrease of ≥1 in histopathological score compared with baseline after 6 months of treatment) and the reversal rate (a decrease of ≥ 2 in histopathological score compared with baseline after 6 months of treatment in the patients with moderate to severe CAG). The impact of lesion sites on the therapeutic effects of LTEVB 12C was analyzed by logistic regression analysis. The two-way unordered Cochran-Mantel-Haenszel chi-square test considering the center effect and Pearson chi-square test were used for statistical analysis. Results:The effective rates of chronic inflammation at the antrum greater curvature and corpus greater curvature (23.3%, 110/473 vs. 13.0%, 31/239; 20.3%, 96/472 vs. 12.6%, 30/239), the effective rates of atrophy at the antrum lesser curvature, antrum greater curvature, gastric angle, corpus lesser curvature, and the corpus greater curvature (27.0%, 118/437 vs. 15.7%, 34/216; 29.2%, 126/432 vs. 18.5%, 38/205; 27.8%, 121/435 vs. 16.7%, 36/216; 32.5%, 127/391 vs. 19.8%, 37/187; 33.0%, 119/361 vs. 21.8%, 39/179), and the effective rates of intestinal metaplasia at the antrum lesser curvature, antrum greater curvature, gastric angle, and the corpus lesser curvature (45.0%, 112/249 vs. 29.8%, 31/104; 53.8%, 86/160 vs. 33.9%, 21/62; 45.8%, 103/225 vs. 24.0%, 25/104; 51.9%, 83/160 vs. 28.3%, 17/60) of the LTEVB 12C group were all higher than those of the placebo group, and the differences were statistically significant ( χ2=10.76, 6.39, 9.69, 7.91, 11.05, 9.62, 8.57, 5.20, 7.11, 12.45, and 6.73; all P<0.05). The reversal rates of chronic inflammation at the corpus lesser curvature and corpus greater curvature (5.2%, 12/231 vs. 0, 0/123; 4.7%, 8/170 vs. 0, 0/88), the reversal rates of atrophy at the antrum lesser curvature, antrum greater curvature, corpus lesser curvature, and the corpus greater curvature (6.8%, 22/323 vs. 1.3%, 2/151; 9.2%, 29/315 vs. 1.4%, 2/144; 14.2%, 38/267 vs. 2.5%, 3/121; 20.8%, 35/168 vs. 5.8%, 4/69), and the reversal rates of intestinal metaplasia at the antrum lesser curvature, antrum greater curvature, gastric angle, and the corpus lesser curvature (29.8%, 39/131 vs. 9.1%, 4/44; 41.0%, 32/78 vs. 12.5%, 3/24; 33.3%, 44/132 vs. 4.8%, 3/63; 50.0%, 37/74 vs. 8.7%, 2/23) of the LTEVB 12C group were all higher than those of the placebo group, and the differences were statistically significant ( χ2=6.58, 5.12, 5.60, 8.61, 11.43, 6.59, 7.30, 4.95, 15.92, 7.62; all P<0.05). There were no statistically significant differences in the effective rates and reversal rates of active inflammation at different locations between the LTEVB 12C group and the placebo group (all P>0.05). The results of logistic regression analysis (taking the antrum lesser curvature as the reference) further confirmed that the reversal rates of chronic inflammation ( OR=0.22, 95% confidence interval (95% CI): 0.07 to 0.67; OR=0.24, 95% CI: 0.07 to 0.80), atrophy ( OR=0.28, 95% CI: 0.16 to 0.49; OR=0.28, 95% CI: 0.16 to 0.49), and intestinal metaplasia ( OR=0.42, 95% CI: 0.24 to 0.77; OR=0.20, 95% CI: 0.08 to 0.52) at the corpus lesser curvature and corpus greater curvature were all higher than those at the antrum lesser curvature, and the differences were statistically significant (all P<0.05). There were no statistically siginificant differences in the reversal rates of the aforementioned pathological features between the antrum greater curvature, gastric angle, and the antrum lesser curvature (all P>0.05). Conclusion:LTEVB 12C can achieve good efficacy in the treatment of CAG, and the chronic inflammation, atrophy, and intestinal metaplasia at multiple locations are improved, especially at the corpus lesser curvature and the corpus greater curvature.

Objective To explore the predictive efficacy of several multimodal MRI-based machine learning models for the promoter methylation states of O6-methylguanine-DNA methyltransferase(MGMT)of glioblastoma muliforme(GBM)patients in terms of the GBM heterogeneity and the complexity of the tumor microenvironment.Methods Firstly,the multimodal MRI images of 317 GBM patients from The University of Pennsylvania Glioblastoma(UPENN-GBM)dataset were pre-processed,with four sequences involved in including T1-weighted imaging(T1WI)sequence,T1-weighted contrast-enhanced imaging(T1CE)sequence,T2-weighted imaging(T2WI)sequence and fluid-attenuated inversion recovery(FLAIR)sequence,and the radiomics features were extracted for two regions of interest(ROIs)such as the tumor core region and the tumor edema region.Secondly,the data of the 317 GBM patients were randomly divided into a training set(254 cases)and a test set(63 cases),which underwent normalization with Z-scores and feature selection and dimensionality reduction with Lasso regression.Finally,three models were established respectively with particle swarm optimization-support vector machine(PSO-SVM),C-support vector classification(C-SVC)and adaptive boosting(adaptive boosting(Adaboost)algorithms,and the predictive efficacy of the three models for glioblastoma multiforme MGMT promoter methylation states were evaluated in terms of accuracy and AUC.Results The Adaboost model based on T2WI sequence and radiomics features of the tumor core region had the highest predictive efficacy with accuracy and AUC values of 67％and 0.74,respectively,higher than those of other combinations of sequences,models and regions of interest.Conclusion The multimodal MRI-based machine learning models can be used for the prediction of glioblastoma multiforme MGMT promoter methylation states,which provides powerful support for personalized treatment and prognostic assessment of GBM.[Chinese Medical Equipment Journal,2025,46(6):7-13]

Central nervous system(CNS)degenerative disorders refer to a spectrum of pathological alterations triggered by struc-tural damage to cerebral neural tissues,clinically manifested as diverse neurological dysfunction syndromes,including multiple sclerosis(MS),neurodegenerative diseases(NDs),and ische-mic stroke.The hallmark pathological features of these disorders involve irreversible neuronal damage and decompensation of functional neural networks,ultimately leading to progressive neurological deficits.Notably,with the accelerating global popu-lation aging,the incidence of these diseases has surged signifi-cantly.According to WHO statistics,they now rank among the top three global causes of disability and mortality.Current re-search has confirmed that the pathogenesis of CNS degenerative disorders exhibits high heterogeneity,encompassing multifaceted pathophysiological processes such as genetic predisposition,oxi-dative stress,protein misfolding,and metabolic dysregulation.This intricate pathogenic network not only complicates clinical differential diagnosis but also poses substantial challenges to the development of precision therapeutic strategies.Importantly,re-cent studies have revealed that mitochondrial homeostasis disrup-tion-induced inflammatory cascades(termed mitochondrial in-flammation)play a pivotal regulatory role in neurodegenerative progression.Key molecular mechanisms include impaired mito-phagy,aberrant mitochondrial DNA(mtDNA)release and NL-RP3 inflammasome activation.This review systematically deci-phers the molecular regulatory network of mitochondrial inflam-mation,with a focus on its biological effects in critical pathologi-cal events such as blood-brain barrier disruption,microglial hy-peractivation and neuronal apoptosis.The overarching aim is to provide a theoretical foundation for developing innovative thera-peutic strategies targeting mitochondrial homeostasis restoration.

Objective:To observe the effect of isokinetic sensorimotor training on the hand function of stroke survivors.Methods:Forty-two stroke survivors with hand dysfunction were randomly divided into an isokinetic group of 22 and a control group of 20. Both groups were given sensorimotor training in addition to routine drug treatment and rehabilitation therapy, but the isokinetic group was additionally provided with sensorimotor training based on isokinetic techniques for 45 minutes daily, 5 days a week for 4 consecutive weeks. Before and after the intervention, both groups were evaluated using the Semmes-Weinstein monofilament examination (SWME), their two-point discrimination (2-PD) was documented, proprioception of their wrist joints was quantified, and the Fugl-Meyer upper extremity assessment (FMA-UE) and the simplified upper limb function assessment (STEF) were applied.Results:In both groups after treatment, there was a significant improvement in the SWME scores and 2-PD distance of the index finger and the thenar, and there was a significant decrease in the angle of motion perception (at 30° of flexion). The average FMA-UE and STEF scores of both groups had improved. After the treatment, the SWME scores of the index finger and the thenar, as well as well as the average FMA-UE and STEF scores of the isokinetic group were significantly higher than the control group′s averages. Angle of motion perception was also significantly superior.Conclusions:Sensorimotor training based on isokinetic techniques can significantly improve touch, motion sense, gross motor function and the fine motor ability of stroke survivors.

Objective To design a combat rescue specialized physical training simulator to solve the problems of the existing combat rescue physical traing in multifunctionality and simulation vividness.Methods The simulator was divided into three types for stretcher handling,land combat rescue and marine rescue based on the application scenerio and functional positioning,and into three grades of basic level,intensive level and ultra intensive level based on the loaded mass and additional weight object.The main components of the simulator included a manikin,a bionic joint and addtional weight objects.The manikin was made up of outer skin,inner liner and skeleton;the bionic joint was made of stainless steel with surface electrophoresis treatment,and was composed of high-strength medal bearing shafts with multiple disc springs and damping mechanisms;the additional weight objects involued in high-intensity cast iron or lead blocks,which were pre-embedded,mounted or srtapped into the simulator.The simulator was verified with body shape and mass detection,drop test,waterproof test and drag test.Results It's proved the simulator gained advantages in vividness for body shape and mass,bionic joint structure and adaptability to training environments and could be used for graded physical training in typical combat rescue scenerios.Conclusion The simulator developed solves the problems of the combat rescue specialized physical training equipment,and facilitates the enhancement of physical training of combat rescue personnel.[Chinese Medical Equipment Journal,2025,46(1):33-37]

Progressive pulmonary fibrosis (PPF) is a progressive and lethal condition with few effective treatment options. Improvements in quality of life for patients with PPF remain limited even while receiving treatment with approved antifibrotic drugs. Traditional Chinese medicine (TCM) has the potential to improve cough, dyspnea and fatigue symptoms of patients with PPF. TCM treatments are typically diverse and individualized, requiring urgent development of efficient and precise design strategies to identify effective treatment options. We designed an innovative Bayesian adaptive two-stage trial, hoping to provide new ideas for the rapid evaluation of the effectiveness of TCM in PPF. An open-label, two-stage, adaptive Bayesian randomized controlled trial will be conducted in China. Based on Bayesian methods, the trial will employ response-adaptive randomization to allocate patients to study groups based on data collected over the course of the trial. The adaptive Bayesian trial design will employ a Bayesian hierarchical model with "stopping" and "continuation" criteria once a predetermined posterior probability of superiority or futility and a decision threshold are reached. The trial can be implemented more efficiently by sharing the master protocol and organizational management mechanisms of the sub-trial we have implemented. The primary patient-reported outcome is a change in the Leicester Cough Questionnaire score, reflecting an improvement in cough-specific quality of life. The adaptive Bayesian trial design may be a promising method to facilitate the rapid clinical evaluation of TCM effectiveness for PPF, and will provide an example for how to evaluate TCM effectiveness in rare and refractory diseases. However, due to the complexity of the trial implementation, sufficient simulation analysis by professional statistical analysts is required to construct a Bayesian response-adaptive randomization procedure for timely response. Moreover, detailed standard operating procedures need to be developed to ensure the feasibility of the trial implementation. Please cite this article as: Zhang C, Nie YS, Zhang CT, Yang HJ, Zhang HR, Xiao W, Cui GF, Li J, Li SJ, Huang QS, Yan SY. An adaptive Bayesian randomized controlled trial of traditional Chinese medicine in progressive pulmonary fibrosis: Rationale and study design. J Integr Med. 2025; 23(2): 138-145.
Female ; Humans ; Male ; Bayes Theorem ; Disease Progression ; Drugs, Chinese Herbal/therapeutic use* ; Medicine, Chinese Traditional/methods* ; Pulmonary Fibrosis/therapy* ; Quality of Life ; Randomized Controlled Trials as Topic ; Research Design ; Adaptive Clinical Trials as Topic

OBJECTIVE: To investigate the associations between eight serum per- and polyfluoroalkyl substances (PFASs) and regional fat depots, we analyzed the data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 cycles. METHODS: Multiple linear regression models were developed to explore the associations between serum PFAS concentrations and six fat compositions along with a fat distribution score created by summing the concentrations of the six fat compositions. The associations between structurally grouped PFASs and fat distribution were assessed, and a prediction model was developed to estimate the ability of PFAS exposure to predict obesity risk. RESULTS: Among females aged 39-59 years, trunk fat mass was positively associated with perfluorooctane sulfonate (PFOS). Higher concentrations of PFOS, perfluorohexane sulfonate (PFHxS), perfluorodecanoate (PFDeA), perfluorononanoate (PFNA), and n-perfluorooctanoate (n-PFOA) were linked to greater visceral adipose tissue in this group. In men, exposure to total perfluoroalkane sulfonates (PFSAs) and long-chain PFSAs was associated with reductions in abdominal fat, while higher abdominal fat in women aged 39-59 years was associated with short-chain PFSAs. The prediction model demonstrated high accuracy, with an area under the curve (AUC) of 0.9925 for predicting obesity risk. CONCLUSION PFAS exposure is associated with regional fat distribution, with varying effects based on age, sex, and PFAS structure. The findings highlight the potential role of PFAS exposure in influencing fat depots and obesity risk, with significant implications for public health. The prediction model provides a highly accurate tool for assessing obesity risk related to PFAS exposure.
Humans ; Fluorocarbons/blood* ; Female ; Adult ; Middle Aged ; Male ; Environmental Pollutants/blood* ; Abdominal Fat ; Nutrition Surveys ; Alkanesulfonic Acids/blood* ; Obesity ; Environmental Exposure

OBJECTIVE: To identify the key features of facial and tongue images associated with anemia in female populations, establish anemia risk-screening models, and evaluate their performance. METHODS: A total of 533 female participants (anemic and healthy) were recruited from Shuguang Hospital. Facial and tongue images were collected using the TFDA-1 tongue and face diagnosis instrument. Color and texture features from various parts of facial and tongue images were extracted using Face Diagnosis Analysis System (FDAS) and Tongue Diagnosis Analysis System version 2.0 (TDAS v2.0). Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for feature selection. Ten machine learning models and one deep learning model (ResNet50V2 + Conv1D) were developed and evaluated. RESULTS: Anemic women showed lower a-values, higher L- and b-values across all age groups. Texture features analysis showed that women aged 30-39 with anemia had higher angular second moment (ASM)and lower entropy (ENT) values in facial images, while those aged 40-49 had lower contrast (CON), ENT, and MEAN values in tongue images but higher ASM. Anemic women exhibited age-related trends similar to healthy women, with decreasing L-values and increasing a-, b-, and ASM-values. LASSO identified 19 key features from 62. Among classifiers, the Artificial Neural Network (ANN) model achieved the best performance [area under the curve (AUC): 0.849, accuracy: 0.781]. The ResNet50V2 model achieved comparable results [AUC: 0.846, accuracy: 0.818]. CONCLUSION Differences in facial and tongue images suggest that color and texture features can serve as potential TCM phenotype and auxiliary diagnostic indicators for female anemia.
Humans ; Female ; Tongue/diagnostic imaging* ; Adult ; Anemia/diagnosis* ; Middle Aged ; Face/diagnostic imaging* ; Young Adult ; Machine Learning

Objective:To investigate the association of blood lipids and body mass index (BMI) with hyperuricemia (HUA) in the elderly.Methods:It was a cross-sectional study. A total of 114 391 elderly individuals received health examinations at primary healthcare institutions in Wujin District from January to December in 2022. The health examination included questionnaire survey, physical examination and laboratory examination. The multivariate logistic regression and restricted cubic spline (RCS) plots were used to analyze the association and dose-response relationship of blood lipid and BMI with HUA. The mediating effect model was used to explore the mediation effect of BMI on the association between blood lipid and HUA.Results:Among the 112 415 subjects, 18 506 (16.46%) were checked with HUA. After adjusting for relevant confounders, total cholesterol (TC) ( OR=1.20, 95% CI: 1.16-1.23), triglyceride (TG) ( OR=1.46, 95% CI: 1.44-1.49), high density lipoprotein cholesterol (HDL-C) ( OR=0.74, 95% CI: 0.73-0.76), low density lipoprotein cholesterol (LDL-C) ( OR=1.14, 95% CI: 1.12-1.15) and BMI ( OR=1.42, 95% CI: 1.39-1.44) were all associated with HUA (all P0.05). The RCS analysis revealed that TG, HDL-C, and LDL-C each exhibited a nonlinear dose-response relationship with HUA, the inflection points was 3.00 mmol/L, 1.57 mmol/L and 2.50 mmol/L, respectively (all P-nonlinear0.001). The results of interaction showed that there were additive interaction between high TC( S=1.27 , 95% CI: 1.17-1.37), high TG( S=1.32 , 95% CI: 1.25-1.40), high LDL-C( S=1.23 , 95% CI: 1.14-1.34) and overweight/obesity with HUA (all P0.05). The results of mediation effect analysis showed that the mediation effect of BMI on the association between blood lipids (HDL-C, LDL-C, TG and TC) and HUA, from high to low, were as follows: 22.5% (95% CI: 20.8%-24.2%), 13.9% (95% CI: 12.0%-16.2%), 13.5% (95% CI: 12.7%-14.4%) and-3.9% (95% CI:-6.6%--1.8%). Conclusion:The blood lipid levels and BMI are positively correlated with HUA in the elderly.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.