ObjectiveZheng’s San Qi San (ZSQS) power, a classic traditional Chinese medicine (TCM) formula, is used for treating soft tissue injuries involving muscles, tendons, and ligaments. However, its underlying therapeutic mechanisms remain unclear. This study aimed to screen and identify pharmaceutically active ingredients and their candidate biomolecule targets, and further elucidate the molecular mechanism of ZSQS in the treatment of skeletal muscle injury. MethodsNetwork pharmacology was employed to construct “ZSQS-component-target”, “protein-protein interaction (PPI)” and “active ingredient-core protein-pathway” networks to predict the key active ingredients and potential core targets of ZSQS for skeletal muscle injury. The predicted results were then validated via microarray data from the GEO database. Molecular docking was then performed to assess the binding ability between the screened active ingredients of ZSQS and the candidate core targets. Moreover, liquid chromatography-mass spectrometry (LC-MS) was used for qualitative and quantitative analysis to verify the active components of the drug and ZSQS serum. Finally, an animal model of eccentric exercise-induced skeletal muscle injury and a myotube cell model of oxidative stress-induced injury were established to validate the effects of ZSQS and its interventional effects on the biological functions of critical targets, thereby demonstrating the potential therapeutic mechanism of ZSQS. ResultsAmong the 111 active components identified in ZSQS and their corresponding 204 targets related to the skeletal muscle injury repair process, 14 core targets (including AKT1) and 4 core active components (quercetin, luteolin, kaempferol, and β‑sitosterol) were screened out, while the corresponding metabolites of quercetin, luteolin and kaempferol were detected in the ZSQS serum. Among these targets, 5 candidate genes (IL-6, CASP3, HIF1A, STAT3, and JUN) overlapped with the differential expression screening results with GEO data, and IL-6 was confirmed to be enriched in the PI3K/AKT pathway. Combined with the prediction results of the AKT expression levels, these findings suggest that the phosphorylation level of AKT1 plays a core role in the therapeutic mechanism of ZSQS. Molecular docking analysis further revealed that the PH domain of AKT1 had high binding energy with all 4 core active components, as verified by LC-MS. Finally, animal model studies have shown the promoting effect of ZSQS administration on skeletal muscle injury repair and its possible antioxidant damage mechanism. Cell model studies further demonstrated that ZSQS-containing serum, core active ingredient combination therapy, and quercetin monomer could increase the phosphorylation level of AKT, promote the nuclear translocation of Nrf2, upregulate the expression of downstream antioxidant enzymes (SOD, GPx, and GR), and inhibit the expression of inflammatory factors (IL-6 and TNF-α), thereby alleviating oxidative stress and the inflammatory response. ConclusionZSQS alleviates skeletal muscle injury mainly by activating the AKT/Nrf2 signaling pathway, enhancing cellular antioxidant and anti-inflammatory capabilities. The results of this study provide a scientific basis for the clinical application and modernized development of ZSQS.

ObjectiveTo apply and systematically evaluate the care-need grading assessment tool for adults with disabilities in welfare institutions. MethodsFrom June to July, 2025, four disability care institutions in Shanghai were selected, and a total of 1 002 adults with disabilities were assessed using the self-developed care-need grading assessment tool for adults with disabilities in welfare institutions. The application effectiveness of the tool was evaluated by analyzing the classification results of care need grading and the reclassification in grade distribution. The application validity was assessed through score differences across functional dimensions, reduced-dimension clustering scatter plots for each grade, and external variables. The application efficiency was evaluated based on the average assessment duration and learning curves. The application utility value was assessed through the distribution characteristics and mapping relationships of service lists across different grades. ResultsThe distribution across disability levels was 84 in Level 1, 298 in Level 2, 92 in Level 3, 246 in Level 4, and 282 in Level 5, indicating a trend where individuals from higher levels in the original system shifted toward the middle and lower levels of the new system. The tool demonstrated strong discriminatory power across the four functional dimensions (P < 0.001), indicating favorable discriminant validity. The five classified levels exhibited clear clustering boundaries in the reduced-dimension space, reflecting robust structural validity. The classification results were consistent with theoretical expectations regarding external variables, including age, disability type, disability grade, number of comorbidities, and primary clinical diagnoses (P < 0.05), demonstrating sound external validity. The median assessment duration was 5.80 minutes, with a significant learning effect (P = 0.037), showcasing high efficiency. Finally, service lists tailored to different care levels were developed, where service content exhibited graded differences across care levels and accurately mapped the care-need characteristics of each grade, reflecting substantial utility value. ConclusionThis tool can classify the care needs of adults with disabilities into five levels, with sound validity and high assessment efficiency; while the resulting service lists for different care levels can be used to guide practical implementation, which can be used for the graded assessment of care needs among adults with disabilities.

ObjectiveTo examine the influencing mechanisms and regional differences in accessible facility utilization behavior among residents in eastern and central-western China. MethodsData were collected through the online questionnaire administered to residents across China using snowball sampling. Descriptive analysis and chi-square tests were conducted to compare the basic characteristics of respondents between the two regions. Welch's t test was used to compare accessible facility utilization behavior and its influencing factors. Multigroup structural equation modeling (SEM) was applied to compare the influencing mechanisms of accessible facility utilization behavior between eastern and central-western China. ResultsA total of 1 039 valid responses were obtained, including 604 from the eastern region and 435 from the central-western region. Residents in eastern regions scored significantly higher than those in central-western regions on both facility-seeking (t = 4.057, P < 0.001) and actual-using (t = 4.551, P < 0.001) behavior. The structural equation models for both regions showed identical and satisfactory goodness-of-fit indices (GFI = 0.950, AGFI = 0.932, IFI = 0.947, CFI = 0.947, RMSEA = 0.028), and all measurement and structural invariance tests met the recommended criteria. Facility configuration showed no significant direct effect on utilization behavior in eastern China, whereas a negative direct effect was observed in central-western China (β = -0.171, P = 0.047), with its influence mainly exerted indirectly through social cognition and user experience. Social cognition and user experience had significant positive effects on utilization behavior (P < 0.001). Meanwhile, social cognition indirectly influences utilization behavior through the mediating path of usage experience. The direct effects of social cognition (β = 0.406) and user experience (β = 0.510) in central-western China were greater than those in eastern China (β = 0.369 and β = 0.335, respectively). The chain mediation effect of "configuration-cognition-experience-behavior" was statistically significant in both regions (P < 0.05), with larger indirect effects observed in central-western China. ConclusionFacility configuration has a limited direct effect on accessible facility utilization, whereas social cognition and user experience play a central role, particularly in central-western China. It is recommended that the construction and renovation of accessible facility be guided by population needs, accompanied by strengthened promotion of accessibility concepts and policies, and that a transition from hardware-oriented construction to service- and management-oriented governance of accessible environments should be promoted in central-western China.

The recombinant human thyroid-stimulating hormone (rhTSH) can be used for differentiated thyroid cancer (DTC) preparation before ¹³¹I therapy, and follow-up. Since its approval by the American Food and Drug Administration (FDA) in 1998, rhTSH has been clinically used in European countries, the United States, and other countries for nearly 30 years. In April 2024, China’s first independently developed rhTSH agent was approved. Based on clinical experience and evidence from domestic and international studies, an expert consensus on the application of rhTSH has been developed following thorough consultations among experts. The consensus offers evidence-based recommendations to guide the appropriate use of rhTSH in clinical practice.

AIM To study the chemical constituents from Radix Puerariae Lobatae from Anhui province and their in vitro lipid-lowering activity.METHODS D101 macroporous resin,silica gel,MCI,and semi-preparative HPLC were used for isolation and purification,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The lipid accumulation model was established by palmitic acid-induced hepatocyte AML12,and the in vitro lipid-lowering activity was evaluated.RESULTS Twenty-one compounds were isolated and identified as carboxymethyl isoferulate(1),methyl(E)feruloylglycolate(2),ariscucurbin-A(3),trans-p-coumaroygly colic acid(4),indole-3-carboxaldehyde(5),β-sitosterol(6),puerol A(7),pueroside C(8),cumoestrol(9),dihydrofurocoumarin(10),decuroside V(11),psoralen dimer(12),bergapten dimer(13),isoliquiritigenin(14),neoliquiritin(15),calycosin(16),daidzein(17),3,4,7-trihydroxyisoflavone(18),ononin(19),genistein(20),genistin(21).Compounds 1-4、7-10、13 and 17-19 significantly inhibited lipid accumulation in AML12 cells,and compound 9 inhibited PPAR-γ expression.CONCLUSION Compounds 1-6,10-13 are isolated from Pueraria genus for the first time.Compounds 1-4,7-10,13 and 17-19 have good lipid-lowering activity.

Objective To explore the role of the protein kinase R-like endoplasmic reticulum kinase(PERK)-mediated endoplasmic reticulum stress pathway in a model of lipopolysaccharide(LPS)-induced microglia inflammation.Methods To investigate its effects on endoplasmic reticulum(ER)stress,an inflammation model of microglia was established by stimulating with LPS at gradient concentrations for 24 hours and with 1 mg/L LPS for different durations.Cell viability was assessed by the CCK-8 assay;The mRNA and protein expression levels of related inflammatory factors were measured by Real-time PCR and ELISA kits.Cellular oxidative stress was evaluated by detecting reactive oxygen species(ROS),and Real-time PCR and Western blotting were used to examine the mRNA and protein expression levels of ER stress pathway markers associated with inflammation.Results 1.The effects of different concentrations of LPS on cell viability and morphology were not statistically significant after acting on BV-2 cells for 24 hours(P＞0.05);2.1 mg/L LPS incubated with BV-2 cells for different times and the cell viability decreased with the increase of time;3.Compared with the 0 hour group,the levels of pro-inflammatory cytokine interleukin(IL)-1β,tumor necrosis factor-α(TNF-α)mRNA and protein expression increased significantly(P＜0.05)in the LPS-stimulated 9 hours,12 hours,and 24 hours groups,and the inflammation model was successfully established;4.Compared with the 0 hour group,the protein and mRNA expression levels of the endoplasmic reticulum stress pathway-related indexes in the LPS-stimulated 9 hours,12 hours,and 24 hours groups increased significantly(P＜0.01),which showed the time-dependence;5.After adding the PERK inhibitor GSK2606414,the mRNA and protein expression levels of endoplasmic reticulum stress-related indicators in the PERK inhibitor group were significantly reduced compared with those in the LPS group(P＜0.05);6.The mRNA and protein expression levels of pro-inflammatory cytokines and the fluorescence intensity of ROS in the PERK inhibitor group were significantly reduced compared with those in the LPS group(P＜0.01).Conclusion Targeting PERK-mediated endoplasmic reticulum stress inhibits LPS-induced inflammatory responses in microglia.

Objective To investigate the expression of myelin transcription factor 1-like(MYT1L)during amyotrophic lateral sclerosis(ALS)progression and its association with neuronal degeneration through bioinformatics analysis combined with in vivo and in vitro experiments.Methods Bioinformatics analysis of the GSE106803 dataset from the Gene Expression Omnibus(GEO)database revealed significant down-regulation of MYT1L in spinal cords of ALS transgenic mice carrying the human superoxide dismutase 1 mutant gene(hSOD1G93A)compared to the wild-type(WT)mice.hSOD1G93A transgenic mice and their WT littermates were selected to analyze MYT1L mRNA and protein changes in spinal cord tissues at different disease stages using Real-time PCR and Western blotting.Double immunofluorescent staining was used to determine the distribution and cellular localization of MYT1L in the spinal cord of mice at the middle stage of the disease.An ALS cellular model was established using hSOD1G93A mutant NSC34 cells,with hSOD1WT NSC34 cells as controls.MYT1L expression and distribution were assessed in these cells via Real-time PCR,Western blotting,and immunofluorescent staining.Based on the GSE76220 dataset from the GEO database,differentially expressed genes(DEGs)between MYT1L high-and low-expression groups in lumbar spinal motor neurons of ALS patients were identified,followed by Gene Ontology(GO)functional enrichment analysis.MYT1L overexpression was induced in the ALS cellular model to evaluate alterations in cell viability and neurite outgrowth.Results In the GSE106803 dataset,MYT1L expression was significantly down-regulated in the spinal cord of ALS mice.Animal experiments confirmed progressive reductions in MYT1L mRNA and protein levels in spinal cord tissues of ALS mice during mid-and late-disease stages.Compared to the WT group,MYT1L expression decreased in motor neurons of the lumbar spinal cord gray matter anterior horn in ALS mice,while it increased in astrocytes.In vitro,hSOD1G93Amutant NSC34 cells exhibited significantly reduced MYT1L expression than controls,with MYT1L localized to both the cytoplasm and nucleus.DEGs between MYT1L high-and low-expression groups in lumbar spinal cord motor neurons of ALS patients(GSE76220 dataset)were enriched in synaptic-related functions through GO analysis.Overexpression of MYT1L in hSOD1G93A mutant NSC34 cells enhanced cell viability and promoted neurite outgrowth.Conclusion Aberrantly low expression of MYT1L is closely associated with ALS pathogenesis.Overexpression of MYT1L promotes neurite growth and exerts protective effects on ALS motor neurons,suggesting its therapeutic potential.

Parkinson’s disease (PD) is a common neurodegenerative disorder that significantly impacts patients’ independence and quality of life, imposing a substantial burden on both individuals and society. Although dopaminergic replacement therapies provide temporary relief from various symptoms, their long-term use often leads to motor complications, limiting overall effectiveness. In recent years, non-invasive deep brain stimulation (DBS) techniques have emerged as promising therapeutic alternatives for PD, offering a means to modulate deep brain regions with high precision without invasive procedures. These techniques include temporal interference stimulation (TIs), low-intensity transcranial focused ultrasound stimulation (LITFUS), transcranial magneto-acoustic stimulation (TMAS), non-invasive optogenetic modulation, and non-invasive magnetoelectric stimulation. They have demonstrated significant potential in alleviating various PD symptoms by modulating neural activity within specific deep brain structures affected by the disease. Among these approaches, TIs and LITFUS have received considerable attention. TIs generate low-frequency interference by applying two slightly different high-frequency electric fields, targeting specific brain areas to alleviate symptoms such as tremors and bradykinesia. LITFUS, on the other hand, uses low-intensity focused ultrasound to non-invasively stimulate deep brain structures, showing promise in improving both motor function and cognition in PD patients. The other three techniques, while still in early research stages, also hold significant promise for deep brain modulation and broader clinical applications, potentially complementing existing treatment strategies. Despite these promising findings, significant challenges remain in translating these techniques into clinical practice. The heterogeneous nature of PD, characterized by variable disease progression and individualized treatment responses, necessitates flexible protocols tailored to each patient’s unique needs. Additionally, a comprehensive understanding of the mechanisms underlying these treatments is crucial for refining protocols and maximizing their therapeutic potential. Personalized medicine approaches, such as the integration of neuroimaging and biomarkers, will be pivotal in customizing stimulation parameters to optimize efficacy. Furthermore, while early-stage clinical trials have reported improvements in certain symptoms, long-term efficacy and safety data are limited. To validate these techniques, large-scale, multi-center, randomized controlled trials are essential. Parallel advancements in device design, including the development of portable and cost-effective systems, will improve patient access and adherence to treatment protocols. Combining non-invasive DBS with other interventions, such as pharmacological treatments and physical therapy, could also provide a more comprehensive and synergistic approach to managing PD. In conclusion, non-invasive deep brain stimulation techniques represent a promising frontier in the treatment of Parkinson’s disease. While they have demonstrated considerable potential in improving symptoms and restoring neural function, further research is needed to refine protocols, validate long-term outcomes, and optimize clinical applications. With ongoing technological and scientific advancements, these methods could offer PD patients safer, more effective, and personalized treatment options, ultimately improving their quality of life and reducing the societal burden of the disease.

Objective Based on the theoretical framework of International Classification of Functioning,Disability and Health(ICF),this paper compared the classification and grading methods of disability standards in four areas in China,focusing on definition,classification,grading,coding systems and assessment tools.Methods Four disability standards including Disability Assessment and Code for Life Insurance(insurance standard),Classification of Disability Degrees for Human Body Injury(judicial standard),Grading of Disability for Work-Related Injuries and Occupational Diseases(work-related injury standard),and Classification and Grading of Dis-abilities for Persons with Disabilities(disability eligibility standard)were systematically analyzed.Each standard was reviewed to identify core elements of disability definitions,classification,and grading methods.Content analysis was used to extract and compare the definitions,classification,grading,coding systems,and assessment tools.The strengths,weaknesses,and practical limitations of each standard were analyzed using the ICF frame-work.Results There were different in disability definitions,classification and grading,coding systems,and assessment tools across the standards.In terms of definitions,the insurance standard emphasized ICF's body structure and function impairments;the judicial standard defined disability as limitations in life and work capacity due to bodily injury,covering ICF's body structure and function,activity and participation;the work-related injury standard focused on loss of labor capacity due to work-related injuries,involving body structure and function,activity and partici-pation;the disability eligibility standard refered to the ICF model,defining disability as impairments in body function and structure,and activity limitations and participation restriction.Regarding classification and grading,the insurance standard divided disabilities into eight categories based on body structure and function,with ten grades of disability severity;the judicial standard first graded disabilities into ten levels and then classified as in-jury site;the work-related injury standard divided disabilities into five categories based on clinical disciplines,grading from one to ten;the disability eligibility standard divided disabilities into seven categories,each with four grades.For coding systems and assessment tools,the insurance standard used ICF coding system,while the disability standard for persons with disabilities used a numerical coding system other from ICF,and the other standards did not use coding systems.Assessment tools varied significantly.The use of World Health Organiza-tion Disability Assessment Schedule(WHODAS 2.0)was proposed but not applying it in grading.Conclusion This study has systematically compared and analyzed four typical disability-related standards in China using the ICF framework.Personal Insurance Disability Assessment and Coding,Grading of Disability Caused by Bodily Injury,and Classification and Grading of Disabilities for Persons with Disabilities are all promulgated af-ter 2011,and adopt ICF concepts and methods to define and classify disabilities,considering body function and structure,activity and participation,and environmental factors.However,due to different purposes,their grading methods and levels vary:except for Classification and Grading of Disabilities for Persons with Disabilities,which uses a four-level grading system,the other standards use a ten-level system,primarily based on body func-tion and structure.In disability assessment,the recommended methods differ by category,showing significant variability.Due to differing classification and grading methods,disability data from various standards are lack in comparability.The international trend advocates for a unified disability standard framework based on ICF and ICD-11 to enhance the comparability and exchangeability of disability data.

Background and purpose:Diffuse large B-cell lymphoma(DLBCL)is subclassified into germinal center B-cell-like(GCB)and non-GCB subtypes,which differ in prognosis and treatment response.However,current distinction still relies on invasive pathological assays.This study developed radiomics and deep-learning models based on multiparametric magnetic resonance imaging(MRI)to non-invasively differentiate the two subtypes preoperatively,thereby reducing dependence on histopathological examination.Methods:This study retrospectively included patients with pathologically confirmed DLBCL diagnosed at Huashan Hospital,Fudan University,and other institutions between March 2013 and December 2024.Using multiparametric MRI data,we developed DLBCL-subtype classification models that combined 4 radiomics-based machine-learning algorithms:support vector machine(SVM),logistic regression(LR),Gaussian process(GP)and Naive Bayes(NB),with 3 deep-learning architectures[densely-connected convolutional networks 121(DenseNet121),residual network 101(ResNet101)and EfficientNet-b5].Additionally,two radiologists with different experience levels independently classified DLBCL on MRI in a blinded fashion.Model and radiologist performance were quantified using the area under the receiver operating characteristic curve(AUC),accuracy(ACC),and F1-score to evaluate their ability to distinguish GCB from non-GCB subtypes.This study was approved by the Ethics Committee of Huashan Hospital of Fudan University(No.KY2024-663),and all patients signed informed consents.Results:A total of 173 patients were enrolled(55 with GCB subtype and 118 with non-GCB subtype).Radiomics and deep learning methods effectively distinguished DLBCL subtypes.Among these,the GP radiomics model(based on T1-CE+T2-FLAIR+ADC sequences)and DenseNet121 deep learning model(based on T1-CE+T2-FLAIR+ADC sequences)demonstrated optimal performance.Both achieved excellent results on the internal validation set(GP:AUC=0.900,ACC=0.896,F1=0.840;DenseNet121:AUC=0.846,ACC=0.854,F1=0.774)and maintained robustness on the external validation set.Furthermore,the classification efficacy of the optimal AI model surpassed that of experienced radiologists(highest physician AUC=0.678).Conclusion:Radiomics and deep-learning models based on multiparametric MRI features can effectively differentiate GCB from non-GCB subtypes of DLBCL.Among them,GP and DenseNet121 exhibit outstanding performance,especially when integrating multi-sequence feature sets for classifying DLBCL subtypes on complex imaging data.