To analyze the in vitro antibacterial effects of colistin (COL) or tigecycline (TGC) in combination with imipenem (IPM), amikacin (AMK), and cefoperazone-sulbactam (CSL) against carbapenem-resistant Acinetobacter baumannii(CRAB), so as to provide evidence for screening effective combination regimens for clinical microbial infections.

The shaoyang meridian is an important pivot between the internal organs and meridians system， with the functions of regulating qi and blood， balancing yin and yang， and coordinating the ascending and descending movement of qi. Dysfunction of the shaoyang pivot can lead to spleen and kidney deficiency， impaired liver and gallbladder qi regulation， and stagnation of qi and blood. It is believed that the onset and progression of Crohn's disease are closely related to shaoyang pivot dysfunction， with the core pathogenesis characterized by shaoyang disharmony， spleen deficiency， dampness retention， and blood stasis. Based on this understanding， the treatment principle centers on harmonizing the shaoyang pivot， supplemented by methods such as warming and nourishing the spleen and stomach， tonifying shaoyang， and soothing the liver and benefiting the gallbladder. Acupuncture is employed to target key acupoints along the shaoyang meridian to restore its regulatory functions， improve spleen and stomach transformation and transportation， facilitate liver and gallbladder qi flow， and promote the circulation of qi and blood. This provides a practical therapeutic approach for acupuncture-based treatment of Crohn's disease.

Objective To conduct a scoping review of research on the relationship between 24-hour movement behaviours and cognitive function in the elderly,so as to provide references for future research.Methods Totally 8 Chinese and English databases were systematically searched.The search period spanned from the establishment of databases until November 30,2024.According to the scoping review framework,2 researchers independently screened the studies,extracted the data of the included studies,and collaborated on the final analysis.Results A total of 12 papers were included,and the distribution of 24-hour movement behaviors in the elderly was as follows:3.0-5.4 h/d for light physical activity,0.6-1.5 h/d for moderate vigorous physical activity,8.9-12.3 h/d for sedentary behaviour and 6.7-8.4 h/d for sleep.Measures included objective,subjective and subject-objective measures.There are complex interactions among physical activity,sedentary behavior,sleep and cognitive function,which jointly affect cognitive function in the elderly.Conclusion Despite current differences in the measurement of 24-hour movement behaviours,the decreased physical activity,the increased sedentary time,and insufficient or excessive sleep are common problems among the elderly.By increasing physical activity,reducing sedentary behavior and ensuring adequate sleep,the overall cognitive function,executive function of the elderly can be improved.In the future,we should pay attention to the time allocation of 24-hour movement behaviours of the elderly,develop accurate and standardized measurement methods,and promote research in this field.

Objective To analyze the risk of bias during the experimental process and the shortcomings of the research report by evaluating the methodological and reporting quality of animal experimental studies on the prevention and treatment of precancerous lesions of gastric cancer(PLGC)using TCM compounds.To provide reference for improving the quality of animal experimental research on the prevention and treatment of PLGC with TCM compounds.Methods Experimental literature about the prevention and treatment of PLGC with TCM compounds was retrieved from CNKI,Wanfang Data,VIP,CBM,PubMed,Cochrane Library,Web of science and Embase from January 1,2014 to February 23,2024.SYRCLE assessment tool and ARRIVE 2.0 guideline were used to score the included literature and calculate the"low-risk"compliance rate for each item.Results Totally 213 articles were finally included,including 189 Chinese articles and 24 English articles.The SYRCLE tool score was(12.86±1.29)points,and the"low risk"compliance rate was 32.79％.The score of the necessary items of the ARRIVE 2.0 guideline was(24.15±2.80)points,and the"low risk"compliance rate was 49.08％;the score of the recommended items was(11.28±3.40)points,and the"low risk"compliance rate was 30.27％.In the SYRCLE tool evaluation,144(67.61％)studies did not elaborate on the method of generating the allocation sequence.All studies did not describe the adequacy of allocation concealment and the blinding method in the implementation of bias.Only 51 studies(23.94％)explicitly proposed the success criteria for PLGC modeling,only 66 studies(30.96％)provided detailed information on the statistical methods used,29 studies(13.62％)provided complete ethical statements,and 22 studies(10.33％)reported conflicts of interest.Conclusion There are many problems in the methodological quality and reporting quality of animal experimental literature on the prevention and treatment of PLGC with TCM compounds published from 2014 to 2024,especially the implementation of the random blinding strategy during the experimental process,the calculation details of the sample size,and the reporting of inclusion and exclusion criteria,etc.There are many deficiencies in this aspect.It is recommended to refer to the SYRCLE evaluation tool and the ARRIVE 2.0 guideline list to design and report the research plan,thereby improving the credibility and standardization of the PLGC animal experimental research results.

Objective To explore the value of support vector machine(SVM)model based on gray matter volume(GMV)for identifying amyotrophic lateral sclerosis(ALS),also to analyze the relevant brain regions.Methods MR 3D T1WI data of 60 ALS patients(ALS group)and 60 healthy volunteers(control group)were retrospectively analyzed.Taken GMV of each brain region obtained by voxel-based morphometry as the input features.F-score analysis was used to select feature with the highest classification accuracy to construct SVM model.Receiver operating characteristic curve was drawn to evaluate the efficacy of SVM model for identifying ALS,and top 10％was used as the weight threshold to obtain gray matter brain regions contributed the most to this model.Results SVM model constructed based on the top 40％GMV features had the highest classification accuracy(82.50％),with sensitivity,specificity and area under the curve(AUG)of 85.05％,80.40％and 0.890,respectively.The left precentral gyrus,left anterior cingulate gyrus and paracingulate gyrus,right middle temporal gyrus,opercular part of left inferior frontal gyrus,right dorsolateral superior frontal gyrus,left temporal pole:middle temporal gyrus,right superior occipital gyrus,orbital part of right middle frontal gyrus,right calcarine fissure and surrounding cortex,right fusiform gyrus were the top 1-10 gray matter brain regions contributed to this model.Conclusion ALS had specific GMV change pattern.SVM model based on GMV could be used to effectively identify ALS,while the left precentral gyrus was the most contributive brain region to this model.

Background Occupational stress has emerged as a critical public health concern affecting the physical and mental well-being of workers in the manufacturing sector. However, researchers typically evaluate its core driver—cumulative fatigue—using a crude binary “present/absent” variable, thereby overlooking the high-dimensional complexity and heterogeneity inherent in fatigue characteristics. This oversimplification constrains both the precision and predictive performance of occupational stress risk assessment model. Objective Leveraging a data-driven approach, to survey data on cumulative fatigue among manufacturing employees, and then use this new classification to develop and validate an occupational stress prediction model, with an ultimate aim of enhancing the accuracy and effectiveness of occupational stress assessment. Methods A set of cross-sectional survey data on 3871 manufacturing employees in 2021 were derived from the “Long working hours exposure and its adverse health effect risk assessment” program of the National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention. Occupational stress was assessed using the Core Occupational Stress Measurement Scale, while cumulative fatigue was evaluated via the Worker’s Self-Diagnostic Questionnaire for Fatigue Accumulation. Boruta method was applied to screen core variables from 20 occupational stress influencing factors. Dimensionality reduction of cumulative fatigue features was performed using a Bayesian sparse autoencoder (BASE), followed by comparison and application of clustering methods to achieve multi-class classification of the reduced features. Six machine learning classification models were then selected including logistic regression, support vector machine, decision tree, random forest, adaptive boosting, and lightweight gradient boosting machine (LightGBM) to construct and compare two occupational stress prediction models involving cumulative fatigue combined with ten other core variables: one utilizing the original binary cumulative fatigue label as a core variable, and another employing the novel fatigue classification proposed herein as a core variable. Results The positive rate of occupational stress among the manufacturing employees was 38.9%. The Boruta method identified 11 core variables of occupational stress: depressive symptoms, cumulative fatigue, age, length of service, tenure in current position, average weekly working hours, average daily overtime hours, average monthly income, low levels of exercise, life satisfaction, and sleep quality. The BSAE reduced the original cumulative fatigue factors to 12 dimensions, while the K-means clustering grouped the reduced fatigue features into three categories: no fatigue, moderate fatigue, and sever fatigue. Six occupational stress prediction models were constructed using the three-category labels of cumulative fatigue and ten additional factors. The results indicated that the LightGBM model performed best, achieving an area under the curve (AUC) of 0.78, an accuracy of 0.77, and an F1 score of 0.72. Compared with the model incorporating the traditional binary labels for cumulative fatigue, the best prediction AUC (0.72), accuracy (0.66), and F1 score (0.65) improved by 6%, 11%, and 7%, respectively. Conclusion Cumulative fatigue is a significant predictor of occupational stress among manufacturing employees. Applying data dimensionality reduction combined with three-class cluster analysis to characterize cumulative fatigue improves the performance of occupational stress prediction models. From a data-driven perspective, machine learning methods demonstrate strengths in processing complex datasets, capturing nonlinear relationships, and generating predictions based on key variables. This study therefore confirms that refined processing of core factors substantially enhances the predictive capability of machine learning models in assessing occupational stress risk in the manufacturing workforce.

Objective To observe and analyze the clinical efficacy and safety of carvedilol combined with dual-wavelength pulsed dye laser in the treatment of rosacea.Methods A retrospective analysis was per-formed on 50 patients with rosacea mainly characterized by flushing,erythema,and telangiectasia who were treated with dual-wavelength pulsed dye laser in the Department of Dermatology of this hospital from October 2023 to October 2024.They were divided into the observation group and the control group according to differ-ent treatment methods,with 25 cases in each group.The control group received dual-wavelength pulsed dye la-ser treatment,while the observation group received carvedilol combined with dual-wavelength pulsed dye laser treatment.The clinical erythema assessment(CEA)scale and physician global assessment(PGA)were used to evaluate the efficacy of the two groups,and the occurrence of adverse reactions was recorded.Results After treatment,the CEA scores of both groups were lower than those before treatment.The CEA score of the ob-servation group was lower than that of the control group,and the PGA score was higher than that of the con-trol group,with statistically significant differences(P<0.05).No singnifcant adverse reactions occurred in ei-ther group.Conclusion Carvedilol combined with dual-wavelength pulsed dye laser is more effective than sin-gle dual-wavelength pulsed dye laser in the treatment of rosacea,and the treatment method is safe.

Objective To develop an ultra-sensitive nanoparticle contrast agent for magnetic resonance angiography(MRA),to establish a highly sensitive imaging method for complicated vascular structures,and to provide imaging evidence for precision diagnosis,treatment,prognosis,and individualized treatment of ischemic stroke.Methods A dual-modality MRA contrast agent was prepared through ligand exchange of ultra-small NaGdF4 nanocrystals synthesized via a high temperature method,with biocompatible polyethylene glycol(PEG-dp)ligands.The basic structure,morphology,size distribution,and relaxation rate of the NaGdF4 nano contrast agent were characterized using transmission electron microscopy(TEM),a particle size potential analyzer,and a 7.0 T small-animal MRI scanner.A total of 6 healthy male SPF-grade BALB/c mice were selected and randomly divided into two groups,a NaGdF4 group and a Gd-DTPA group.The mice in the two groups were injected with NaGdF4 nanoparticle contrast agent or clinical Gd-DTPA contrast agent(0.1 mmol Gd3+/kg)via the tail vein.MRA images were obtained using a 7.0 T small animal magnetic resonance imaging system before and after the injection.A total of 6 healthy male SPF-grade Sprague Dawley(SD)rats were selected to establish a right middle cerebral artery occlusion(rMCAO)model to simulate ischemic stroke.The rats were injected with NaGdF4 nano-contrast agent(0.1 mmol Gd3+/kg)via the tail vein.Before and after the injection,brain MRI images of the rats were obtained using a 7.0 T small animal magnetic resonance imaging system.The in vitro and in vivo biological safety of the nano contrast agent was verified through cytotoxicity and hemolysis experiments and HE staining.Results Uniform spherical oil-phase NaGdF4 nanocrystals with an average particle size of approximately(4.43±0.46)nm were successfully prepared.After ligand exchange,biocompatible water-phase nanocrystals were obtained with a hydrodynamic size of 16.1 nm and a surface potential of-1.9 mV.The relaxation performance of this nanocrystal contrast agent was significantly superior to that of the clinical contrast agent Gd-DTPA.The longitudinal molar relaxivity rate(r1)of the NaGdF4 nano contrast agent was 8.84 mM-1s-1,while the transverse molar relaxivity rate(r2)was 27.36 mM-1s-1,which were 1.96 times(4.52 mM-1s-1)and 3.37 times(8.13 mM-1s-1)those of Gd-DTPA,respectively.It also demonstrated excellent biocompatibility.NaGdF4-enhanced MRA achieved high-resolution vascular imaging and effectively enabled the differentiation of the ischemic area,infarct core,and ischemic penumbra in an animal model of ischemic stroke.Conclusion The multi-parameter MRA based on NaGdF4 nanoparticles provides critical imaging evidence for the clinical diagnosis and prognosis of ischemic stroke.