ObjectiveType 2 diabetes mellitus (T2DM) often causes severe hepatic metabolic complications, dominated by metabolic associated fatty liver disease (MAFLD). Persistent hepatic steatosis and oxidative stress further trigger steatohepatitis and progressive liver damage, increasing the mortality risk of diabetic patients. Aerobic exercise effectively improves hepatic lipid metabolism and antioxidant capacity, but poor patient adherence restricts its long-term clinical application. Mitochondrial-derived mitochondrial open reading frame of the 12S rRNA type-c (MOTS-c) is a key peptide regulating insulin sensitivity and hepatic redox homeostasis. This study aimed to explore the protective mechanism of MOTS-c against T2DM-related liver injury and its combined beneficial effect with aerobic exercise via the NRF2/PPARγ signaling axis. This study aimed to investigate whether MOTS-c cooperates with aerobic exercise to alleviate T2DM-associated hepatic oxidative stress and metabolic dysfunction by activating the NRF2/PPARγ axis, and to clarify the molecular and transcriptomic characteristics of their combined intervention. MethodsStable MOTS-c overexpression and knockdown HepG2 cell lines were constructed using lentiviral transfection. An oleic acid-induced cellular lipid accumulation model and NRF2-knockout cell model were applied to verify the NRF2-dependent mechanism ofMOTS-c. Intracellular lipid deposition, triglyceride levels, antioxidant enzyme activities, and the expression of NRF2/PPARγ pathway-related genes and proteins were detected. In vivo, a T2DM rat model with obvious hepatic steatosis was established via a high-fat and high-sucrose diet combined with streptozotocin injection. Model rats received aerobic exercise, MOTS-c intraperitoneal injection, or combined intervention. We detected systemic glycolipid metabolic indicators, hepatic histopathological changes, and the expression of core proteins in the hepatic NRF2/PPARγ axis. Hepatic transcriptomic sequencing was performed to screen differentially expressed genes (DEGs) and enrich key pathways co-regulated by MOTS-c and aerobic exercise. ResultsCellular results showed that MOTS-c overexpression significantly reduced oleic acid-induced lipid deposition, enhanced antioxidant enzyme activity, and upregulated NRF2 and PPARγ expression. Conversely, MOTS-c knockdown aggravated hepatic lipid accumulation and oxidative damage and inhibited NRF2/PPARγ pathway activation. NRF2 knockout completely eliminated the protective effects of MOTS-c on lipid metabolism and redox balance, confirming its NRF2-dependent regulatory mechanism. In T2DM rats, both MOTS-c supplementation and aerobic exercise effectively improved insulin resistance, corrected glycolipid metabolic disorders, and alleviated hepatic steatosis, while consistently activating the hepatic NRF2/PPARγ axis. Compared with single intervention, the combined treatment showed a better improvement trend in hepatic metabolic and oxidative injury, without definitive synergistic effects. Transcriptomic analysis revealed that the co-regulated DEGs of MOTS-c and aerobic exercise were primarily enriched in lipid metabolism and PPAR signaling pathways, with multiple antioxidant and lipid-regulating genes significantly modulated by combined intervention. ConclusionMOTS-c exhibits obvious exercise-mimetic hepatoprotective effects in T2DM. It activates the hepatic NRF2/PPARγ axis to strengthen antioxidant defense, stabilize lipid metabolism, and relieve T2DM-associated hepatic steatosis and oxidative damage. Furthermore, MOTS-c produces additive beneficial effects with aerobic exercise, showing a superior intervention trend on diabetic liver dysfunction. This study identifies the NRF2/PPARγ axis as the core mechanism of MOTS-c-regulated hepatic protection, elucidates the transcriptomic basis of combined intervention, and provides a reliable theoretical basis and potential therapeutic target for clinical intervention in T2DM-complicated MAFLD.

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.

OBJECTIVES: To investigate the synergistic mechanism of the traditional Chinese medicine Rosa laevigata Michx. (RLM) for treatment of pulmonary arterial hypertension (PAH). METHODS: Network pharmacological analysis was carried out to screen the active ingredients of RLM and PAH disease targets and construct the "component-target-disease" interaction network, followed by gene enrichment analysis and molecular docking studies. In the cell experiments, primary cultures of rat pulmonary arterial smooth muscle cells were exposed to hypoxia for 24 h and treated with solvent or 100, 200 and 300 mg/mL RLM, and the changes in cell proliferation were detected using Western blotting for PCNA and immunofluorescence staining. In the animal experiment, male SD rats were randomized into 5 control group, monocrotaline (MCT) solvent group, and MCT with RLM (100, 200 and 300 mg/mL) treatment groups. HE staining and immunofluorescence staining were used to observe histopathological changes in the pulmonary blood vessels of the rats. RESULTS: Seven core active ingredients (including β-sitosterol and kaempferol) in RLM and 39 key disease targets were identified, and molecular docking showed that SRC was a high-affinity target. KEGG enrichment analysis showed that the differential genes were significantly enriched in calcium signaling and PI3K-AKT pathways. In rat pulmonary arterial smooth muscle cells, hypoxic exposure significantly up-regulated cellular expression of PCNA and phosphorylation levels of Src and AKT1, which were obviously lowered by RLM treatment. In RLM-treated rat models, the mean pulmonary artery pressure and right ventricular hypertrophy index (Fulton index) were significantly reduced, the tricuspid annular plane systolic excursion (TAPSE) was improved, and pulmonary vascular wall thickening and fibrosis were obviously ameliorated. CONCLUSIONS RLM inhibits pulmonary arterial smooth muscle cell proliferation in rat models of hypertension possibly by regulating the Src-AKT1 axis, suggesting the potential of RLM as a new natural drug for treatment of pulmonary hypertension.
Animals ; Cell Proliferation/drug effects* ; Proto-Oncogene Proteins c-akt/metabolism* ; Rats, Sprague-Dawley ; Pulmonary Artery/cytology* ; Male ; Rats ; Myocytes, Smooth Muscle/cytology* ; Hypertension, Pulmonary/pathology* ; Drugs, Chinese Herbal/pharmacology* ; Signal Transduction/drug effects* ; Muscle, Smooth, Vascular/cytology* ; src-Family Kinases/metabolism* ; Cells, Cultured

OBJECTIVE: To explore the effectiveness of arthroscopic release of elbow joint assisted by medial small incision ulnar nerve release in the treatment of non-traumatic elbow stiffness. METHODS: The clinical data of 15 patients with non-traumatic elbow stiffness treated with arthroscopic release of elbow joint assisted by medial small incision ulnar nerve release between April 2019 and September 2023 were retrospectively analyzed. There were 6 males and 9 females with an average age of 46 years ranging from 34 to 56 years. The causes included rheumatoid arthritis in 3 cases, gouty arthritis in 2 cases, loose bodies in 3 cases, and elbow osteoarthritis in 7 cases. There were 4 cases with ulnar neuritis and 3 cases with synovial osteochondromatosis. The duration of elbow stiffness ranged from 6 to 18 months, with an average of 10 months. The operation time and intraoperative blood loss were recorded. The effectiveness was evaluated by visual analogue scale (VAS) score, range of elbow motion (maximum flexion, maximum extension, and total flexion and extension), Mayo score, and Hospital for Special Surgery (HSS) elbow score. RESULTS: The operation time was 60-90 minutes, with an average of 65 minutes, and the intraoperative blood loss was 40-100 mL, with an average of 62 mL. All patients were followed up 13-18 months, with an average of 14 months. There was no complication such as vascular and nerve injury, poor wound healing, collateral ligament injury, elbow joint space narrowing, osteophyte proliferation, or loose body formation around the joint. At last follow-up, the elbow range of motion (maximum flexion, maximum extension, and total flexion and extension), VAS score, and Mayo score significantly improved when compared with those before operation ( P<0.05). The HSS elbow score was 85-95, with an average of 92; 12 cases were excellent, 3 cases were good, and the excellent and good rate was 100%. CONCLUSION Arthroscopic release of elbow joint assisted by medial small incision ulnar nerve release is an effective way to treat non-traumatic elbow stiffness, which has the advantages of small trauma, short operation time, and good effectiveness. It can carry out early elbow rehabilitation training and significantly improve elbow function.
Humans ; Male ; Female ; Arthroscopy/methods* ; Adult ; Middle Aged ; Elbow Joint/physiopathology* ; Retrospective Studies ; Range of Motion, Articular ; Treatment Outcome ; Ulnar Nerve/surgery* ; Operative Time

Objective To systematically review the evidence from systematic reviews on the effect of exercise on internet behavioral addictions.Methods Systematic reviews on exercise for internet behavioral addictions were searched in Web of Science,Scopus,EBSCO,PsycINFO,PubMed,Cochrane Library,Embase and CNKI,from January,2015 to January,2025.In ac-cordance with the PRISMA guidelines,the evidences about exercise on internet behavioral addiction,as well as the health benefits,were reported.Results Eleven English reviews were included,from China,Malaysia,Indonesia and Australia,involving 31 672 internet behavioral addiction aged ten to 30 years,covering internet addiction,mobile phone addiction and gaming addic-tion.The included literatures were all systematic reviews mainly from journals in psychology,psychiatry,public health,etc.Interventions included aerobic exercise,strength training,functional training,skill-based training and structured combination exercise,with programs ranging from 30 to 120 minutes per session,one to six times per week,for six to 24 weeks.Exercise significantly improved mental health,behavioral health,physical health and cognitive function.Moderate-intensity structured combination exercise(≥60 minutes persession,≥3 times per week,≥8 weeks)showed the best outcomes,especially for gaming addiction.Exercise combined with psycholog-ical therapy was more effective for severe addiction.Conclusion Exercise is effective on internet behavioral addictions,and moderate-intensity structured combination exer-cise is the most effective.It is recommended to use structured combination exercise for gaming addiction and combined exercise-psychological therapy for severe addiction.

Objective To develop a data-driven model for estimating tangential ground reaction force(GRFt)from lower limb kinematic data and select the most suitable input based on a balance between input quantity and estimation accuracy,with the aim of measuring GRFt in outdoor gait experiments.Methods Gait data from ten subjects walking at five different inclines(-10°,-5°,0°,5°,10°)were used to train two data-driven models,namely a backpropagation neural network(BPNN)-based model and a polynomial sparse identification(PSI)-based model.The performance of these models was evaluated using eight kinematic data combinations and the normal ground reaction force(GRFn)as inputs to determine the optimal model and input combination.Results Under the same input dimensionality,the combination of hip-knee joint angles proved more accurate in estimating GRF,than the knee-ankle joint angle combination.Specifically,the BPNN and PSI models based on the former combination predicted GRF,with errors of 1.61％BW(body weight)and 1.84％BW,respectively,while the latter combination resulted in errors of 2.82％BW and 3.15％BW.When GRFn and all joint angles were used as inputs,the model's prediction error was only 1.46％BW.Conclusions The combination of GRFn and hip-knee joint angles achieves an optimal balance between computational complexity and estimation accuracy.This study supports the accurate estimation of GRF,in outdoor gait testing.

Objective To develop a data-driven model for estimating tangential ground reaction force(GRFt)from lower limb kinematic data and select the most suitable input based on a balance between input quantity and estimation accuracy,with the aim of measuring GRFt in outdoor gait experiments.Methods Gait data from ten subjects walking at five different inclines(-10°,-5°,0°,5°,10°)were used to train two data-driven models,namely a backpropagation neural network(BPNN)-based model and a polynomial sparse identification(PSI)-based model.The performance of these models was evaluated using eight kinematic data combinations and the normal ground reaction force(GRFn)as inputs to determine the optimal model and input combination.Results Under the same input dimensionality,the combination of hip-knee joint angles proved more accurate in estimating GRF,than the knee-ankle joint angle combination.Specifically,the BPNN and PSI models based on the former combination predicted GRF,with errors of 1.61％BW(body weight)and 1.84％BW,respectively,while the latter combination resulted in errors of 2.82％BW and 3.15％BW.When GRFn and all joint angles were used as inputs,the model's prediction error was only 1.46％BW.Conclusions The combination of GRFn and hip-knee joint angles achieves an optimal balance between computational complexity and estimation accuracy.This study supports the accurate estimation of GRF,in outdoor gait testing.

Objective To systematically review the evidence from systematic reviews on the effect of exercise on internet behavioral addictions.Methods Systematic reviews on exercise for internet behavioral addictions were searched in Web of Science,Scopus,EBSCO,PsycINFO,PubMed,Cochrane Library,Embase and CNKI,from January,2015 to January,2025.In ac-cordance with the PRISMA guidelines,the evidences about exercise on internet behavioral addiction,as well as the health benefits,were reported.Results Eleven English reviews were included,from China,Malaysia,Indonesia and Australia,involving 31 672 internet behavioral addiction aged ten to 30 years,covering internet addiction,mobile phone addiction and gaming addic-tion.The included literatures were all systematic reviews mainly from journals in psychology,psychiatry,public health,etc.Interventions included aerobic exercise,strength training,functional training,skill-based training and structured combination exercise,with programs ranging from 30 to 120 minutes per session,one to six times per week,for six to 24 weeks.Exercise significantly improved mental health,behavioral health,physical health and cognitive function.Moderate-intensity structured combination exercise(≥60 minutes persession,≥3 times per week,≥8 weeks)showed the best outcomes,especially for gaming addiction.Exercise combined with psycholog-ical therapy was more effective for severe addiction.Conclusion Exercise is effective on internet behavioral addictions,and moderate-intensity structured combination exer-cise is the most effective.It is recommended to use structured combination exercise for gaming addiction and combined exercise-psychological therapy for severe addiction.

Objective To explore the automated identification and diameter measurement methods for inferior vena cava (IVC) based on clinical ultrasound images of IVC. Methods An automated identification and localization method based on topology and automatic tracking algorithm was proposed. Tracking algorithm was used for identifying and continuously locating to improve the efficiency and accuracy of measurement. Tests were conducted on 18 sets of ultrasound data collected from 18 patients in intensive care unit (ICU),with clinicians' measurements as the gold standard. Results The recognition accuracy of the automated method was 94.44％ (17/18),and the measurement error of IVC diameter was within the range of±1.96s (s was the standard deviation). The automated method could replace the manual method. Conclusion The proposed IVC automated identification and localization algorithm based on topology and automatic tracking algorithm has high recognition success rate and IVC diameter measurement accuracy. It can assist clinicians in identifying and locating IVC,so as to improve the accuracy of IVC measurement.

Objective To analyze the independent influencing factors of intimate partner homicide(IPH)cases,construct an IPH prediction model,and provide a basis for criminal profiling.Methods A total of 476 convicted homicide cases in Guangdong Province from January 1,2014,to December 31,2020,were collected as modeling dataset.They were divided into the IPH group(n=180)and the non-intimate partner homicide(N-IPH)group(n=296)based on whether the offender and victim were intimate partners.Logistic regression was used to build the model,the model was evaluated through the receiver operating characteristic(ROC)curve analysis and a nomogram was drawn.Inter-nal validation was conducted using ten-fold cross-validation method.A total of 126 court judgments from outside Guangdong Province from January 1,2011,to December 31,2020,were randomly col-lected for external validation.Results Through multi-factor Logistic regression analysis,7 variables were ultimately selected for inclusion in the model.The Hosmer-Lemeshow goodness of fit test result of the model was χ2=13.158,P=0.068.The ROC area under the curve(AUC)of the model was 0.939(95%CI:0.919-0.959),the cut-off value was 0.292,the sensitivity was 0.900,and the specificity was 0.865.The calibration curve was close to the ideal curve.The ten-fold cross-validation showed the accuracy of 0.863 and a Kappa value of 0.708.The external validation results showed an AUC of 0.922(95%CI:0.872-0.971),a cut-off value of 0.292,a sensitivity of 0.890,and a specificity of 0.886.The calibration curve tended to the ideal curve.Conclusion The IPH prediction model based on forensic field indicators has good predictive ability,reliable accuracy and stability,and can provide a scientific method for criminal profiling.