Machado-Joseph disease, or spinocerebellar ataxia type 3 (SCA3), represents the most common autosomal dominant cerebellar ataxia worldwide. Despite its progressive and debilitating nature, disease-modifying therapies remain elusive. Repetitive transcranial magnetic stimulation (rTMS) has emerged as a promising non-invasive intervention; however, its clinical application has been hindered by inconsistent protocols and a lack of mechanistic understanding. A recent landmark study published in Brain Stimulation by Chen et al. addressed these challenges by combining a high-dose intermittent theta-burst stimulation (iTBS) protocol with concurrent transcranial magnetic stimulation-electroencephalography (TMS-EEG). This commentary provides an in-depth analysis of their findings, highlighting the restoration of cerebello-cortical inhibition (CBI) as a key therapeutic mechanism. Furthermore, we discuss the broader implications of this work, proposing that future translational research should integrate accelerated iTBS (aiTBS) paradigms, cortical response measurements (CRM), and individualized neuro-navigation to establish a new era of precision neuromodulation for ataxia.

Machado-Joseph disease, or spinocerebellar ataxia type 3 (SCA3), represents the most common autosomal dominant cerebellar ataxia worldwide. Despite its progressive and debilitating nature, disease-modifying therapies remain elusive. Repetitive transcranial magnetic stimulation (rTMS) has emerged as a promising non-invasive intervention; however, its clinical application has been hindered by inconsistent protocols and a lack of mechanistic understanding. A recent landmark study published in Brain Stimulation by Chen et al. addressed these challenges by combining a high-dose intermittent theta-burst stimulation (iTBS) protocol with concurrent transcranial magnetic stimulation-electroencephalography (TMS-EEG). This commentary provides an in-depth analysis of their findings, highlighting the restoration of cerebello-cortical inhibition (CBI) as a key therapeutic mechanism. Furthermore, we discuss the broader implications of this work, proposing that future translational research should integrate accelerated iTBS (aiTBS) paradigms, cortical response measurements (CRM), and individualized neuro-navigation to establish a new era of precision neuromodulation for ataxia.

Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

In recent years,the market share of food and medicine homology substances has continued to grow,and various types of contamination issues have become the focus of attention both inside and outside the industry.The contamination not only affects the original medicinal quality,but also leads to the accumulation of toxic substances in the human body,causing acute and chronic severe hazards such as vomiting,poisoning and cancer.Therefore,the development of biosensors that can conveniently,accurately and sensitively detect various pollutants in food and medicine homology substances has become a research hotspot.Aptasensors based on metal-organic frameworks(MOFs)with advantages such as strong specificity,rapid response and simple operation,have been widely used in detection of various pollutants.This review focused on the research progress of aptasensors based on MOFs for detection of food and medicine homology contamination in the past few years,and provided a detailed comparison and analysis for detection of chemical pollutants(such as pesticide residues,heavy metal residues,mycotoxins,etc.)and microbial contamination in food and medicine homology substances.Besides,the development trend and possible challenges of MOFs aptasensors in detection of food and medicine homology substances in the future were discussed,which was anticipated to provide a reference for the development of new MOFs aptasensors.

Objective:To investigate the correlation between triglyceride-glucose-body mass index (TyG-BMI index) and the outcome of young patients with acute ischemic stroke (AIS).Methods:Consecutive young patients with first-ever AIS (aged 18-45 years) admitted to Pingyi County People's Hospital and Qingdao Municipal Hospital from January 2020 to December 2023 were included retrospectively. The demographic data, vascular risk factors, baseline blood pressure, baseline laboratory tests, classification of stroke etiology, baseline National Institutes of Health Stroke Scale (NIHSS) scores, and main treatment methods were collected. At 3 months after the onset of stroke, the modified Rankin Scale was used for outcome evaluation. A score of 0-2 was defined as good outcome and >2 were defined as poor outcome. Multivariate logistic regression analysis was used to identify independent factors associated with poor outcome in young patients with AIS. Results:A total of 253 young patients with AIS were enrolled, including 196 males (77.5%), aged 38.65±5.34 years; baseline NIHSS score 3.03±2.88. At 90 days after onset, 206 patients (81.4%) had good outcome, while 47 (18.6%) had poor outcome. The poor outcome group had significantly higher systolic blood pressure, triglycerides, fasting blood glucose, triglyceride glucose (TyG) index, body mass index (BMI), TyG-BMI index, and baseline NIHSS score than those of the good outcome group (all P<0.05). Multivariate logistic regression analysis showed that after adjusting for gender, systolic blood pressure, baseline NIHSS score, and antiplatelet drug use, the TyG-BMI index was significantly independently associated with the poor outcome in young patients with AIS (odds ratio 1.039, 95% confidence interval 1.021-1.057; P<0.001). Conclusion:A higher baseline TyG-BMI index is independently associated with the poor outcome in young patients with AIS.

Objective To propose a high-precision deep learning-based image assessment method of osteosarcoma chemotherapy efficacy for clinical treatment,as existing methos have low accuracy of osteosarcoma assessment.Methods The low incidence of osteosarcoma led to the small scale of its imaging data and the problem of imbalance in data categories.This study combined deep learning with clinical medical information,combined the bone sarcoma generation module of BoneGAN and the scale lesion information capture module,and proposed OMLA-Net,a deep learning assessment network for chemotherapy effect of bone sarcoma based on multi-scale lesion attention network,which achieved computer-aided bone tumor assessment with integrated data augmentation and focused lesion information through pre-training and generalized loss training.Results In this study,40 cases of osteosarcoma MRI data were used as the basis for the comparison test on the generated dataset,and the OMLA-Net assessment outperformed the SOTA method Conv-LSTM-GAN in terms of the assessment effects such as accuracy and F1 scores,and the difference was statistically significant(Bootstrap statistical method P＜0.05);the subsequent K-fold cross-validation ablation experiments further demonstrated the effectiveness of each module proposed by OMLA-Net.Conclusion OMLA-Net can effectively perform the impact assessment of chemotherapy effect on osteosarcoma,which provides a new idea for subsequent clinical application.

Objective To investigate the anatomical and microscopic structures of interstitial fluid flow channels in the skin tissue of hand dorsum in human cadavers.Methods Totally 7 fresh cadavers within 12 hours post-mortem were included.MRI was used to observe the distribution of interstitial fluid flow from the first phalanx of the fingers to the wrist,precisely locating the flow channels.Based on imaging results,histological analyses were conducted to determine the histological characteristics of the flow channels.Furthermore,multi-immunofluorescence and microcomputed tomography(Micro-CT)techniques were employed to analyze the channels,and image post-processing was used to elucidate their anatomical structures at the microscopic level.Results After injecting a contrast agent into the first phalanx of ten finger specimens and applying repeated pressure,MRI image revealed centripetal long-range interstitial fluid flow along channels distinct from blood vessels and lymphatic vessels.Histological analysis and Micro-CT further confirmed that the flow primarily occurred within the fibrous connective tissue and adventitia of the skin.Conclusion The orderly fibrous connective tissue and adventitia in the skin form the interstitial fluid flow channels in the human hand dorsum skin,named as"stromal membrane channels"in the skin.

Objective:This study aimed to evaluate the value of CT-based radiomics machine learning models in predicting spread through air spaces(STAS)in lung adenocarcinoma(LUAD)and to determine the optimal peritumoral analysis region.Methods:Data from 378 pa-tients who underwent non-small cell lung cancer surgery at Zhejiang Cancer Hospital between January 2013 to January 2017 were retro-spectively analyzed.Logistic regression,random forest,and XGBoost models were constructed using regions extending 0,3,6,9,and 12 mm outward from the tumor margin.Results:The XGBoost model using the 6 mm peritumoral region performed best on the test set,with an AUC-ROC of 0.855(95%CI:0.756-0.950),followed by the XGBoost model using the 9 mm region.Decision curve analysis(DCA)indicated that the XGBoost models for the 6 mm and 9 mm regions had higher net clinical benefits.Feature analysis revealed that some wavelet trans-form features significantly contributed to STAS prediction.Conclusions:This preliminary study suggests that CT-based radiomics machine learning models have predictive value for STAS.The XGBoost model based on the 6 mm peritumoral region demonstrated the best perform-ance,and holds promise in assisting preoperative assessment.

OBJECTIVE To explore the effect of hydrogen peroxide disinfectant on terminal disinfection in wards of medical institutions.METHODS The surfaces of highly frequent contact objects of the wards of the First Affilia-ted Hospital of Nanchang University from which the public health center patients were discharged between Apr.2024 and Jun.2024 were respectively disinfected with 0.5％(low)and 5％(high)concentrations of hydrogen peroxide disinfecting wipes,totally 180 samples were randomly collected before and after the disinfection,and the pathogens were detected.The air of the wards from which the public health center patients were discharged be-tween Jul.2024 and Aug.2024 were disinfected with hydrogen peroxide dry mist disinfection device,and 90 sam-ples were respectively collected before and after the disinfection.Geobacillus stearothermophilus was used as the biological indicator and placed at various points within the air-disinfected wards to evaluate the disinfection level.The environmental sampling results and distribution of bacteria were observed and compared.RESULTS The qualified rates of disinfection of the object surfaces were 95.56％(86/90)and 98.89％(89/90)respectively for the low and high concentratioins of hydrogen peroxide disinfecting wipes,and there was no significant difference in the disinfection effect.Totally 120 strains of pathogens were isolated from unqualified samples before the disinfection,among which gram-negative bacteria(69.17％)were dominant,and the isolation rate of multidrug-resistant or-ganisms was 22.50％(27/120);only 1 strain of carbapenem-resistant Acinetobacter baumannii was isolated after the disinfection.The qualified rate of disinfection of air in the wards was 96.00％by 7.5％hydrogen peroxide dry mist disinfection device,the average bacterial colony counts in the air were 2 CFU/(5 min·vsl)after the dis-infection,and the killing rate of Geobacillus stearothermophilus was 100.00％by the air disinfection.CONCLUSION The hydrogen peroxide disinfectant can meet the requirement for terminal disinfection of the wards of the medical institutions,and it is portable and highly efficient.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disorder affecting multiple systems, characterized by the development of harmful autoantibodies and immune complexes that lead to damage in organs and tissues. Chinese medicine (CM) plays a role in mitigating complications, enhancing treatment effectiveness, and reducing toxicity of concurrent medications, and ensuring a safe pregnancy. However, CM mainly solves the disease comprehensively through multi-target and multi-channel regulation process, therefore, its treatment mechanism is often complicated, involving many molecular links. This review introduces the research progress of pathogenesis of SLE from the aspects of genetics, epigenetics, innate immunity and acquired immunity, and then discusses the molecular mechanism and target of single Chinese herbal medicine and prescription that are commonly used and effective in clinic to treat SLE.
Lupus Erythematosus, Systemic/immunology* ; Humans ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/pharmacology* ; Animals