ObjectiveTo systematically compare the effects of diverse electromagnetic stimulation protocols on hand function and activities of daily living (ADL) in stroke patients using network meta-analysis (NMA), and screen the optimal stimulation strategy for post-stroke hand dysfunction rehabilitation. MethodsNMA was performed in accordance with the PRISMA-NMA statement. Databases of CNKI, Wanfang data, VIP, CBM, PubMed, Web of Science and Embase were searched from database inception to April, 2026 for eligible randomized controlled trials (RCTs) comparing different electromagnetic stimulation protocols for post-stroke hand impairment. The Cochrane Risk of Bias tool and PEDro scale were used to assess methodological quality of included studies, while the GRADE system was adopted to grade evidence quality of primary outcomes of Fugl-Meyer Assessment-Upper Extremities (FMA-UE) and modified Barthel Index (MBI). After literature screening, data extraction and bias evaluation, RevMan 5.4 and Stata 17.0 were used for meta-analysis and NMA. ResultsA total of 22 RCT involving 17 electromagnetic stimulation protocols were finally included. The PEDro scores ranged from six to ten. The top five protocols for improving FMA-UE score were repetitive peripheral magnetic stimulation (rPMS) + repetitive transcranial magnetic stimulation (rTMS), intermittent theta-burst stimulation (iTBS) + rPMS, iTBS + transcranial direct current stimulation (tDCS), transcutaneous electrical acupoint stimulation (TEAS) and contralaterally controlled functional electrical stimulation (CCFES). tDCS was the most effective on MBI, followed by TEAS and iTBS+rPMS. Evidence quality for FMA-UE and MBI was moderate. Funnel plots suggested low risk of publication bias, and consistency tests verified good coherence between direct and indirect comparisons in network models. ConclusionElectromagnetic stimulation significantly facilitates upper limb and hand functional recovery, and improves ADL in stroke patients. The combined central-peripheral magnetic stimulation protocol may be the most effective on motor rehabilitation, whereas tDCS on ADL.

Against the backdrop of the "New Medical Education" initiative by the Ministry of Education, higher medical education faces an urgent need to reconstruct its talent cultivation system. Taking the Laboratory Animal Science course at Shandong University of Traditional Chinese Medicine as an example, this paper systematically explores how to construct a teaching system featuring deep integration of scientific research and education, aiming to address the disconnection between theory and practice and the lack of innovative thinking among students in traditional teaching. The construction of this system is based on three pillars: first, the establishment of a high-level, interdisciplinary faculty team that strongly supports teaching innovation; second, reliance on the Laboratory Animal Center of Shandong University of Traditional Chinese Medicine and the Shandong Provincial Engineering Research Center for Prevention and Treatment of Major Brain Diseases with Traditional Chinese Medicine to provide the necessary facilities; third, a systematic restructuring of teaching content and modes through the "multidisciplinary, multi-format, and multilevel" integration approach. The reform has yielded remarkable results, particularly evident in the increase in students' scientific research and innovation capabilities: the proportion of student projects approved at the provincial level or above in undergraduate innovation training programs significantly increased from 11.1% before the reform to 41.6%. Furthermore, student teams have won gold and silver awards in national competitions such as the "National Undergraduate Innovation Forum for Basic Medical Sciences and Experimental Design" and the "National College Students' Medical Innovation Competition". Additionally, the teaching team's faculty members serving as chief editors and editorial board members of the national planning textbook Laboratory Animal Science published by People's Medical Publishing House mark the nationwide recognition of the course construction achievements. Practice has shown that this integrated system effectively transforms scientific research resources into educational advantages, providing an effective pathway for cultivating top-notch talents in traditional Chinese medicine with solid practical skills and advanced innovative capabilities. It also offers a replicable model for teaching reforms in peer institutions.

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 evaluate the accuracy of a self-developed extraoral scanning system based on photogrammetry technology, and to provide evidence for advancing the development and clinical application evaluation of domestically produced scanning devices.Methods:This research group developed a photogrammetry-based implant extraoral scanning system with customized scan bodies. Two distinct edentulous implant resin models were designed and three-dimensional (3D)-printed by Center of Digital Dentistry, Peking University School and Hospital of Stomatology, containing 6 (Model 1) and 8 (Model 2) abutment analogs respectively. Reference data acquisition was performed using a high-precision denture 3D scanner with scan caps mounted on the analogs. Specialized scan bodies were then mounted on the analogs for 3D positional data acquisition using both the self-developed system (experimental group) and the clinically established system (control group). Each system conducted 10 repeated scans per model. Trueness was assessed through root mean square error (RMSE), linear deviation (LD), and angular deviation (AD) relative to reference data, while precision was determined through intra-group RMSE analysis. Systematic comparisons included inter-group performance on identical models and intra-group variability across different models.Results:For Model 1, the experimental group showed statistically significant advantages over controls in intra-group RMSE [(3.10±0.71) μm vs (4.61±1.51) μm, P<0.001], reference-data RMSE [(21.48±0.60) μm vs (32.50±0.63) μm, P<0.001], linear deviation [23.64 (32.35) μm vs 44.86 (55.73) μm, P<0.001], and angular deviation [0.29° (0.29°) vs 0.23° (0.33°), P<0.001]. In Model 2, significant improvements were observed in intra-group RMSE [(4.47±1.58) μm vs (6.21±2.07) μm, P<0.001], reference-data RMSE [(38.84±0.86) μm vs (43.69±1.34) μm, P<0.001], and linear deviation [37.95 (50.68) μm vs 49.71 (58.89) μm, P<0.001]. Both groups exhibited model-dependent variability, with RMSE of precision and trueness of both groups, linear deviation of experimental group, angular deviation of control group showing statistically significant increases (all P<0.001) corresponding to abutment analog quantity. Conclusions:The self-developed scanning system demonstrates superior accuracy in 3D positional acquisition of abutment analogs compared to the contral group system, with implant number identified as a critical determinant of extraoral scanning accuracy.

Objective:To develop an original-mirror alignment associated deep learning algorithm for intelligent registration of three-dimensional maxillofacial point cloud data,by utilizing a dynamic graph-based registration network model(maxillofacial dynamic graph registration network,MDGR-Net),and to provide a valuable reference for digital design and analysis in clinical dental applications.Methods:Four hundred clinical patients without significant deformities were recruited from Peking University School of Stomatology from October 2018 to October 2022.Through data augmentation,a total of 2 000 three-dimensional maxillofacial datasets were generated for training and testing the MDGR-Net algorithm.These were divided into a training set(1 400 cases),a validation set(200 cases),and an internal test set(200 cases).The MDGR-Net model constructed feature vectors for key points in both original and mirror point clouds(X,Y),established correspondences between key points in the X and Y point clouds based on these feature vectors,and calculated rotation and translation matrices using singular value decomposi-tion(SVD).Utilizing the MDGR-Net model,intelligent registration of the original and mirror point clouds were achieved,resulting in a combined point cloud.The principal component analysis(PCA)algorithm was applied to this combined point cloud to obtain the symmetry reference plane associated with the MDGR-Net methodology.Model evaluation for the translation and rotation matrices on the test set was performed using the coefficient of determination(R2).Angle error evaluations for the three-dimensional maxillofacial symmetry reference planes were constructed using the MDGR-Net-associated method and the"ground truth"iterative closest point(ICP)-associated method were conducted on 200 cases in the inter-nal test set and 40 cases in an external test set.Results:Based on testing with the three-dimensional maxillofacial data from the 200-case internal test set,the MDGR-Net model achieved an R2 value of 0.91 for the rotation matrix and 0.98 for the translation matrix.The average angle error on the internal and external test sets were 0.84°±0.55° and 0.58°±0.43°,respectively.The construction of the three-dimensional maxillofacial symmetry reference plane for 40 clinical cases took only 3 seconds,with the model performing optimally in the patients with skeletal Class Ⅲ malocclusion,high angle cases,and Angle Class Ⅲ orthodontic patients.Conclusion:This study proposed the MDGR-Net association method based on intelligent point cloud registration as a novel solution for constructing three-dimensional maxillo-facial symmetry reference planes in clinical dental applications,which can significantly enhance diagnos-tic and therapeutic efficiency and outcomes,while reduce expert dependence.

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.

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.

Objective:The influencing factors of intraoperative hypoxemia in patients with benign central airway stenosis were investigated by machine learning algorithm, and the prediction model of hypoxemia was constructed and verified.Methods:A case-control study was used in this study. The clinical data of 650 patients with benign central airway stenosis who who received surgical treatment in the First Affiliated Hospital of PLA Naval Medical University from June 2022 to April 2024 were retrospectively analyzed. And they were divided into a training set ( n=455) and a test set ( n=195) according to 7:3. The training set was used for establishing Logistic regression model and conducting internal verification, and the test set was used for external verification. The least absolute shrinkage and selection operator (LASSO) regression and Boruta algorithm were used to select the factors affecting intraoperative hypoxemia in patients with benign central airway stenosis. A Logistic regression prediction model was constructed, and the model was evaluated using area under the receiver operating characteristic curve (AUC), decision curve analysis (DCA) and calibration curve. Shapley additive interpretation (SHAP) were used to analyze the importance of influencing factors. Results:Among 650 patients, 279 were males and 371 were females, aged (37.86 ± 8.82) years. Nine feature variables were screened by LASSO regression, while 7 feature variables were screened by Boruta algorithm, the intersection of the two was operation time, complications, degree of airway stenosis, thermal ablation therapy, balloon dilation, and airway stent, respectively, based on this, a logistic regression prediction model was constructed.The AUC values of the training set, validation set and test set of the model were 0.928 (95% CI 0.903-0.954), 0.922 (95% CI 0.843-0.995) and 0.919 (95% CI 0.872-0.965), respectively. The calibration curve showed that the predicted results of the model were in good agreement with the actual results, and the DCA curve showed that the model had clinical application value. SHAP analysis showed that the importance of variables affecting intraoperative hypoxemia in benign central airway stenosis patients was ranked as operation time, thermal ablation therapy, degree of airway stenosis, comorbidification, balloon dilation, and airway stent. Conclusions:The Logistic regression prediction model of intraoperative hypoxemia built based on machine learning algorithm has good prediction efficiency, which is helpful to early identification of risk groups and prevention of hypoxemia.

Objective To investigate the protective effects and mechanism of Shuilian Fengkui Formula(SFF)of Yao medicine on sequelae pelvic inflammatory disease(SPID)in rats.Methods The SPID rat model was established by mechanical injury coupled with bacterial infection,and then the rats were randomly divided into:the SPID group,the positive drug(Fukeqianjin tablets)group,SFF groups at low,medium and high doses,and the sham-operation group,with 8 rats in each group;SPID group,SFF groups,TLR4 agonist CRX-527(CRX-527)group,SFF plus CRX-527 group,with 8 rats in each group.Corresponding drug intervention was given for 21 consecutive days.The indexes of uterus,spleen,thymus and other organs were calculated.The histopathological changes in rat uterus were observed by HE staining.The levels of interleukin-1β(IL-1β),interleukin-6(IL-6),tumor necrosis factor-α(TNF-α),immunoglobulin G(IgG),immunoglobulin M(IgM)in serum were detected by ELISA;The protein expression levels of Toll receptor 4(TLR4),myeloid differentiation factor(MyD88),nuclear factor kappa B p65(NF-κB p65),and phosphorylated nuclear factor kappa B p65(p-NF-κB p65)in rat uterine tissues were detected by Western blot.Results Compared with the sham operation group,the uterine index of SPID group significantly increased(P<0.01),the spleen index and thymus index significantly decreased(P<0.01),the pathological damage of uterine tissue was serious,the contents of IL-1β,IL-6,TNF-α in serum significantly increased(P<0.01),the contents of IgG and IgM significantly decreased(P<0.01),the TLR4,MyD88 protein and the ratio of p-NF-κB p65/NF-κB p65 protein in uterine tissue significantly increased(P<0.01).Compared with the SPID group,the uterine index of the positive drug group and the SFF groups significantly decreased(P<0.05),the spleen index and thymus index significantly increased(P<0.05),the pathological damage of uterine tissue significantly improved,the contents of IL-1β,IL-6 and TNF-α in serum were significantly lowered(P<0.05),the contents of IgG and IgM significantly increased(P<0.05),and the TLR4,MyD88 protein and the ratio of p-NF-κB p65/NF-κB p65 protein in uterine tissue significantly downregulated(P<0.01).However,CRX-527 significantly reversed the effects of SFF on SPID in rats.Conclusion SFF could improve SPID in rats by impeding the inflammatory response,and its mechanism might be attributed to inhibition of TLR4/MyD88/NF-κB signaling pathway.

Objective To explore the effect of rituximab on cellular immunity and cytokines in children with new-onset steroid-sensitive nephrotic syndrome(SSNS).Methods Clinical data of 60 children with new-onset SSNS treated at Xuzhou Children's Hospital from December 2021 to March 2023 were retrospectively analyzed.Children were allocated according to rituximab use into a control group(no rituximab)and an observation group(rituximab).The relapse rate,T-lymphocyte subsets and cytokines before and after treatment,and the incidence of adverse reactions were compared between groups.Results The relapse rate was lower in the observation group than in the control group(27%vs 73%,P<0.05).After treatment,CD3+and CD4+T-lymphocyte counts,the CD4+/CD8+ratio,and serum interleukin-2 increased in the observation group and were higher than in the control group(P<0.05).Interleukin-6 and tumor necrosis factor-α levels decreased after treatment in the observation group and were lower than in the control group(P<0.05).After treatment,CD8+T-lymphocyte counts decreased,interferon-γ increased,and interleukin-10 decreased in both groups,with no significant differences between the two groups(P>0.05).The incidence of adverse reactions did not differ significantly between the two groups(P>0.05).Conclusions Rituximab can reduce the relapse rate in children with new-onset nephrotic syndrome and shows good safety.Its therapeutic effect is achieved by regulating the number and function of T cells and by modulating the anti-inflammatory effects of cytokines.