Objective To explore the clinical efficacy of transcranial combined peripheral magnetic stimu-lation on bladder and voiding ability in patients with NB after spinal cord injury.Methods From September 2023 to October 2024,60 patients with NB after spinal cord injury were chosen from the Department of Rehabilitation Medicine of the First Affiliated Hospital of Bengbu Medical University,and were separated into the regular group(n=15),M1 area stimulation group(n=15),sacral nerve root stimulation group(n=15),and combined stimulation group(n=15).The control group underwent conventional rehabilitation treatment,the M1 area stimu-lation group added repetitive transcranial magnetic stimulation(rTMS)of the M1 area of the motor cortex,the sacral nerve root stimulation group added repetitive peripheral magnetic stimulation(rPMS)of the sacral 3 nerve roots,and the co-stimulation group added rTMS of the M1 area and rPMS of the sacral 3 nerve roots,and the treat-ment was carried out for 4 weeks in total.Urodynamic indices,voiding diaries,and neurogenic bladder symptom scores(NBSS)were assessed before and after therapy in the four groups.Results Before therapy,the differences in maximum bladder capacity,bladder capacity at the time of the first urge to urinate,maximum urine flow rate,residual urine volume,average number of urination per day,average daily urinary output,and NBSS scores of the four groups were not statistically significant when compared with those of the pre-treatment group(P<0.05);after treatment,the maximum bladder capacity,bladder capacity at the time of the first urge to urinate,maximum urine flow rate,residual urine volume,average number of urination per day,average daily urinary output,and NBSS scores were all improved compared with those before treatment(P<0.05);in comparison between the groups,after treatment,the Urodynamic indices,voiding diaries,and NBSS scores of the combined group were better than those of the other three groups(P<0.05).Conclusion Transcranial combined peripheral bidirectional feedback magnetic stimulation therapy can improve urodynamic and voiding symptoms and promote the recovery of bladder and voiding function in patients with NB after spinal cord injury

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.

Diabetic cardiomyopathy (DCM) is a medical condition characterized by cardiac remodeling and dysfunction in individuals with diabetes mellitus. Sarcoplasmic reticulum (SR) and mitochondrial Ca²⁺ overload in cardiomyocytes have been recognized as biological hallmarks in DCM; however, the specific factors underlying these abnormalities remain largely unknown. In this study, we aimed to investigate the role of a cardiac-specific long noncoding RNA, D830005E20Rik (Trdn-as), in DCM. Our results revealed the remarkably upregulation of Trdn-as in the hearts of the DCM mice and cardiomyocytes treated with high glucose (HG). Knocking down Trdn-as in cardiac tissues significantly improved cardiac dysfunction and remodeling in the DCM mice. Conversely, Trdn-as overexpression resulted in cardiac damage resembling that observed in the DCM mice. At the cellular level, Trdn-as induced Ca²⁺ overload in the SR and mitochondria, leading to mitochondrial dysfunction. RNA-seq and bioinformatics analyses identified calsequestrin 2 (Casq2), a primary calcium-binding protein in the junctional SR, as a potential target of Trdn-as. Further investigations revealed that Trdn-as facilitated the recruitment of METTL14 to the Casq2 mRNA, thereby enhancing the m⁶A modification of Casq2. This modification increased the stability of Casq2 mRNA and subsequently led to increased protein expression. When Casq2 was knocked down, the promoting effects of Trdn-as on Ca²⁺ overload and mitochondrial damage were mitigated. These findings provide valuable insights into the pathogenesis of DCM and suggest Trdn-as as a potential therapeutic target for this condition.
Animals ; Diabetic Cardiomyopathies/pathology* ; RNA, Long Noncoding/genetics* ; Myocytes, Cardiac/metabolism* ; Mice ; Calsequestrin/genetics* ; Calcium/metabolism* ; Male ; Sarcoplasmic Reticulum/metabolism* ; Methyltransferases/metabolism* ; Mice, Inbred C57BL ; Mitochondria, Heart/metabolism* ; Disease Models, Animal ; Mitochondria/metabolism*

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

OBJECTIVE To establish a population pharmacokinetic(PopPK)model to predict the PK characteristics of GLS-010 in humans.METHODS Fifty-eight cynomolgus monkeys were used,18 of which were randomly divided into three groups and received a single intravenous infusion of GLS-010 at doses of 2,6,and 18 mg·kg-1,respectively.The rest were randomly assigned to four groups and received multiple intravenous infusions of GLS-010 at doses of 0,5,25,and 100 mg·kg-1,respectively,once a week(quaque week,qw)for five consecutive weeks.Blood samples were collected before and after administration.The concentrations of GLS-010 in the monkey serum were measured using a validated enzyme-linked immunosorbent assay,while those of anti-drug antibodies(ADA)in the cynomolgus monkey serum were determined by ultra-sensitive electrochemiluminescence immunoassay.The PK data on GLS-010 in cynomolgus monkeys was obtained,and the drug-time curves were plotted.A PopPK model was constructed using non-compartmental analysis and evaluated by goodness-of-fit plots and visual predictive checks.The constructed PopPK model was used to predict the PK characteristics in humans,which were finally compared with actual Phase Ⅰ clinical study results for validation.RESULTS The predictive results of the PopPK model were highly consistent with the actual Phase Ⅰ clinical study results.The model was able to predict the human PK characteristics under various dosing regimens,including 1 mg·kg-1 quaque 2 weeks(q2w),4 mg·kg-1(q2w),240 mg(q2w),240 mg(q3w),and 10 mg·kg-1(q2w).The predicted maximum plasma concentrations(Cmax)were 24.8,99.1,85.0,85.0,and 247.8 mg·L-1,respectively,and the AUC0-336h was 4 902.0,20 060.0,17 147.7,22 145.7(AUC0-504h),and 50 817.6 mg·h·L-1,respectively.The safety risks for the corresponding dosing regimens were 47.3,11.6,13.5,10.5,and 4.6,respectively.The predicted receptor occupancy at steady state(ROss)at Cmax,average plasma concentration(Cavg),and minimum plasma concentration(Cmin)were 38.8％,72.7％,69.4％,64.1％and 87.2％,29.1％,63.8％,60.0％,49.8％and 82.1％,21.9％,55.5％,51.3％,36.3％and 76.7％,respectively.CONCLUSION The PopPK model can effectively predict the human PK characteristics under different dosing regimens with high consistency with actual Phase Ⅰ clinical study results,which can serve as an important reference for selection of safe and effective doses for first-in-human research.

Objective To explore the clinical efficacy of transcranial combined peripheral magnetic stimu-lation on bladder and voiding ability in patients with NB after spinal cord injury.Methods From September 2023 to October 2024,60 patients with NB after spinal cord injury were chosen from the Department of Rehabilitation Medicine of the First Affiliated Hospital of Bengbu Medical University,and were separated into the regular group(n=15),M1 area stimulation group(n=15),sacral nerve root stimulation group(n=15),and combined stimulation group(n=15).The control group underwent conventional rehabilitation treatment,the M1 area stimu-lation group added repetitive transcranial magnetic stimulation(rTMS)of the M1 area of the motor cortex,the sacral nerve root stimulation group added repetitive peripheral magnetic stimulation(rPMS)of the sacral 3 nerve roots,and the co-stimulation group added rTMS of the M1 area and rPMS of the sacral 3 nerve roots,and the treat-ment was carried out for 4 weeks in total.Urodynamic indices,voiding diaries,and neurogenic bladder symptom scores(NBSS)were assessed before and after therapy in the four groups.Results Before therapy,the differences in maximum bladder capacity,bladder capacity at the time of the first urge to urinate,maximum urine flow rate,residual urine volume,average number of urination per day,average daily urinary output,and NBSS scores of the four groups were not statistically significant when compared with those of the pre-treatment group(P<0.05);after treatment,the maximum bladder capacity,bladder capacity at the time of the first urge to urinate,maximum urine flow rate,residual urine volume,average number of urination per day,average daily urinary output,and NBSS scores were all improved compared with those before treatment(P<0.05);in comparison between the groups,after treatment,the Urodynamic indices,voiding diaries,and NBSS scores of the combined group were better than those of the other three groups(P<0.05).Conclusion Transcranial combined peripheral bidirectional feedback magnetic stimulation therapy can improve urodynamic and voiding symptoms and promote the recovery of bladder and voiding function in patients with NB after spinal cord injury

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

OBJECTIVE To establish a population pharmacokinetic(PopPK)model to predict the PK characteristics of GLS-010 in humans.METHODS Fifty-eight cynomolgus monkeys were used,18 of which were randomly divided into three groups and received a single intravenous infusion of GLS-010 at doses of 2,6,and 18 mg·kg-1,respectively.The rest were randomly assigned to four groups and received multiple intravenous infusions of GLS-010 at doses of 0,5,25,and 100 mg·kg-1,respectively,once a week(quaque week,qw)for five consecutive weeks.Blood samples were collected before and after administration.The concentrations of GLS-010 in the monkey serum were measured using a validated enzyme-linked immunosorbent assay,while those of anti-drug antibodies(ADA)in the cynomolgus monkey serum were determined by ultra-sensitive electrochemiluminescence immunoassay.The PK data on GLS-010 in cynomolgus monkeys was obtained,and the drug-time curves were plotted.A PopPK model was constructed using non-compartmental analysis and evaluated by goodness-of-fit plots and visual predictive checks.The constructed PopPK model was used to predict the PK characteristics in humans,which were finally compared with actual Phase Ⅰ clinical study results for validation.RESULTS The predictive results of the PopPK model were highly consistent with the actual Phase Ⅰ clinical study results.The model was able to predict the human PK characteristics under various dosing regimens,including 1 mg·kg-1 quaque 2 weeks(q2w),4 mg·kg-1(q2w),240 mg(q2w),240 mg(q3w),and 10 mg·kg-1(q2w).The predicted maximum plasma concentrations(Cmax)were 24.8,99.1,85.0,85.0,and 247.8 mg·L-1,respectively,and the AUC0-336h was 4 902.0,20 060.0,17 147.7,22 145.7(AUC0-504h),and 50 817.6 mg·h·L-1,respectively.The safety risks for the corresponding dosing regimens were 47.3,11.6,13.5,10.5,and 4.6,respectively.The predicted receptor occupancy at steady state(ROss)at Cmax,average plasma concentration(Cavg),and minimum plasma concentration(Cmin)were 38.8％,72.7％,69.4％,64.1％and 87.2％,29.1％,63.8％,60.0％,49.8％and 82.1％,21.9％,55.5％,51.3％,36.3％and 76.7％,respectively.CONCLUSION The PopPK model can effectively predict the human PK characteristics under different dosing regimens with high consistency with actual Phase Ⅰ clinical study results,which can serve as an important reference for selection of safe and effective doses for first-in-human research.

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.

In recent years， the incidence of pulmonary nodules has kept rising. To give full play to the advantages of traditional Chinese medicine （TCM） in the treatment of pulmonary nodules and identify the breakthrough points of integrating TCM with Western medicine， the China Association of Chinese Medicine organized medical experts in TCM and western medicine to carry out in-depth discussion regarding this disease. The discussion encompassed the modern medical advances， TCM theories of etiology and pathogenesis， the role and advantages of TCM in the whole course management of pulmonary nodules， contents and methods of research on pulmonary nodules， and science popularization work， aiming to provide a reference for clinical practice and scientific research. After discussion， the experts concluded that the occurrence of pulmonary nodules was rooted in the deficiency of the lung and spleen and triggered by phlegm dampness， blood stasis， and Qi stagnation. TCM can treat pulmonary nodules by controlling and reducing nodules， improving physical constitution， ameliorating multi-system nodular diseases， reducing anxiety and avoiding excessive diagnosis and treatment， and serving as an alternative for patients who are unwilling or unfit for surgical treatment. At present， the optimal diagnosis and treatment strategy for pulmonary nodules has not been formed， which needs to be further studied from multiple perspectives such as clinical epidemiology， biology， and evidence-based medicine. The primary task of current research is to find out the advantages， effective prescriptions， and target populations and determine the effective outcomes of TCM in the treatment of pulmonary nodules. At the same time， basic research should be carried out to explore the etiology and biological behaviors of pulmonary nodules. The expert consensus on the diagnosis and treatment of pulmonary nodules with integrated TCM and Western medicine needs to be continuously revised to guide clinicians to conduct standardized， scientific， and accurate effective diagnosis and treatment.