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.

The gut microbiota regulates intestinal nutrient absorption, participates in modulating host glucolipid metabolism, and contributes to ameliorating glucolipid metabolism disorder. Dysbiosis of the gut microbiota can compromise the integrity of the intestinal mucosal barrier, induce inflammatory responses, and exacerbate insulin resistance and abnormal lipid metabolism in the host. Dangua Humai Oral Liquid, a hospital-developed formulation for regulating glucolipid metabolism, has been granted a national invention patent and demonstrates significant clinical efficacy. This study aimed to investigate the effects of Dangua Humai Oral Liquid on gut microbiota and the intestinal mucosal barrier in a mouse model with glucolipid metabolism disorder. A glucolipid metabolism disorder model was established by feeding mice a high-glucose and high-fat diet. The mice were divided into a normal group, a model group, and a treatment group, with eight mice in each group. The treatment group received a daily gavage of Dangua Humai Oral Liquid(20 g·kg~(-1)), while the normal group and model group were given an equivalent volume of sterile water. After 15 weeks of intervention, glucolipid metabolism, intestinal mucosal barrier function, and inflammatory responses were evaluated. Metagenomics and untargeted metabolomics were employed to analyze changes in gut microbiota and associated metabolic pathways. Significant differences were observed between the indicators of the normal group and the model group. Compared with the model group, the treatment group exhibited marked improvements in glucolipid metabolism disorder, alleviated pathological damage in the liver and small intestine tissue, elevated expression of recombinant claudin 1(CLDN1), occluding(OCLN), and zonula occludens 1(ZO-1) in the small intestine tissue, and reduced serum levels of inflammatory factors lipopolysaccharides(LPS), lipopolysaccharide-binding protein(LBP), interleukin-6(IL-6), and tumor necrosis factor-α(TNF-α). At the phylum level, the relative abundance of Bacteroidota decreased, while that of Firmicutes increased. Lipid-related metabolic pathways were significantly altered. In conclusion, based on the successful establishment of the mouse model of glucolipid metabolism disorder, this study confirmed that Dangua Humai Oral Liquid effectively modulates gut microbiota and mucosal barrier function, reduces serum inflammatory factor levels, and regulates lipid-related metabolic pathways, thereby ameliorating glucolipid metabolism disorder.
Animals ; Gastrointestinal Microbiome/drug effects* ; Mice ; Intestinal Mucosa/microbiology* ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Mice, Inbred C57BL ; Humans ; Glycolipids/metabolism* ; Lipid Metabolism/drug effects* ; Administration, Oral ; Disease Models, Animal

Aim To investigate the anti-acute lung injury(ALI)effect of Sterculiae Lychnophorae Semen(SLS)and its mechanism.Methods The main ac-tive components of SLS and their core targets and path-ways of action against ALI were obtained by network pharmacology methods.Subsequently,molecular doc-king technology and in vitro cellular experiments were applied for validation.Results A total of 19 core tar-gets were obtained,including HSP90AA1,CASP3,TNF,MAPK8 and MAPK14.The mechanisms may in-volve signaling pathways such as cancer,PI3K/Akt and MAPK.Molecular docking confirmed that the key targets of SLS formed a better binding activity with the relevant active ingredients.The in vitro results showed that SLS was able to protect the PM2.5-contaminated BEAS-2B cells,inhibit their NO,IL-1β and TNF-αlevels,and reduce the expression of p-p38 MAPK and p-JNK proteins.Conclusions The study successfully predicts the active ingredients,targets and signaling pathways of SLS against ALI,and in vitro experiments demonstrate that SLS might protect BEAS-2B cells from PM2.5 stimulus-induced inflammation and apoptosis by inhibiting the over-activation of p38 MAPK and JNK signaling pathways.

Objective:To explore the clinical value of combination of contrast-enhanced ultrasound(CEUS)and magnetic reso-nance imaging(MRI)in the diagnosis of parotid gland tumors.Methods:167 patients with parotid gland tumors were diagnosed by CEUS and MRI respectively and in combination.With postoperative pathological diagnosis result as the gold standard,the diagnos-tic value of CEUS combined with MRI(CEUS+MRI)was analyzed.Results:171 tumors were confirmed by postoperative pathology in 167 patients,including 143 benign tumors(83.63％)and 28 malignant tumors(16.37％).The benign tumors were mainly pleo-morphic adenoma(65 tumors,45.45％),Warthin tumor(40 tumors,27.97％)and basal cell adenoma(13 tumors,9.09％).Among the malignant tumors,mucoepidermoid carcinoma(7 tumors,25.00％),adenoid cystic carcinoma(6 tumors,21.43％)and acinic cell carcinoma(3 tumors,10.71％)were the most common.CEUS showed 39 cases of malignant parotid gland tumors and 132 cases of benign parotid gland tumors.The sensitivity,specificity and accuracy rate of CEUS were 57.14％,83.92％and 79.53％respectively.The MRI ADC values were manifested as pleomorphic adenoma＞malignant tumor＞Warthin tumor(P＜0.05).MRI showed 53 cases of malignant parotid gland tumors and 118 cases of benign parotid gland tumors,and the sensitivity,specifici-ty and accuracy rate of MRI diagnosis were 67.86％,76.22％and 74.85％respectively.CEUS+MRI revealed 33 cases of malig-nant parotid gland tumors and 138 cases of benign parotid gland tumors,the sensitivity,specificity and accuracy rate of CEUS+MRI diagnosis were 78.57％,92.31％and 90.06％respectively.The specificity and accuracy rate of CEUS+MRI were significantly higher than those of single examination(x2=4.806,13.951,7.348,13.664,allP＜0.05).Conclusion:Both CEUS and MRI have certain clinical value in the diagnosis of parotid gland tumors,and the specificity and accuracy rate of CEUS+MRI are significantly higher than those of single examination.

Objective To develop an automated system that can accurately determine the relationship between the mandibular third molar and the mandibular nerve canal from panoramic images.Methods A dataset consisting of 600 panoramic images of the oral cavi-ty was selected,and the positions of the mandibular third molar and the mandibular nerve canal were accurately labeled.We compared the research designed TI-YOLOv5 with PANet,Faster R-CNN,Mask R-CNN,ResNeSt-101,and the original YOLOv5 in image seg-mentation tasks,with evaluation metrics of AP and AP50.Results TI-YOLOv5 achieved AP(average precision)54.0％and AP5094.9％,an increase of 4.9 and 6.7 percentage points respectively compared to the original YOLOv5(AP 49.1％,AP50 88.2％),and surpassed other SOTA methods such as Mask R-CNN(AP 45.1％,AP50 84.2％).Conclusion TI-YOLOv5 is significantly superior to mainstream networks in automatic positioning and relationship classification of mandibular wisdom teeth and neural tubes,with high de-tection accuracy and discrimination accuracy,and can provide reliable technical support for preoperative risk assessment of mandibular wisdom tooth extraction.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To investigate the pathogen distribution characteristics and related risk factors for postoperative infection in liver transplant recipients.Method:A retrospective analysis was conducted on the clinical data of 153 recipients who underwent liver transplantation and received postoperative treatment in the intensive care unit (ICU) of China-Japan Friendship Hospital from January 2019 to December 2023. According to whether postoperative infection occurred, the recipients were divided into the infection group (33 cases) and the non-infection group (120 cases). Pathogen-related data were collected from multiple postoperative body fluid sites of liver transplant recipients. Univariate analysis and multivariate logistic regression analysis were performed to identify independent risk factors.Result:Among the 153 recipients, 105 were male and 48 were female, with a mean age of (52.2 ± 9.5) years. During the ICU stay after liver transplantation, 33 recipients developed infections, including 15 cases of single-pathogen infection and 18 cases of mixed-pathogen infection. The most common site of infection was the lung, accounting for 22 cases (66.67%). Eleven recipients (33.33%) in the infection group died, with septic shock being the leading cause of death (7 cases, 63.63%), and the median survival time was 14 days. Infected recipients had Gram-negative bacteria (171 strains), mainly Stenotrophomonas maltophilia[54 strains (31.57%)] and Pseudomonas aeruginosa[52 strains (30.41%)]. Gram-positive bacteria (47 strains) were dominated by Enterococcus faecalis[25 strains (53.19%)]. Multivariate regression analysis showed that postoperative mechanical ventilation for more than 48 hours was an independent risk factor for infection in liver transplant recipients ( OR=10.878, 95% CI: 3.632-32.580, P<0.001). Conclusion:It is necessary to prevent ventilator-associated pneumonia in liver transplant recipients. Early removal of the tracheal tube and strengthening hospital infection prevention and control are of great significance in reducing the risk of postoperative infection in liver transplant recipients.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective To evaluate the effects of transcatheter aortic valve replacement(TAVR)on left ventricular reverse remodeling(LVRR)and outcomes in patients with mixed aortic valve disease(MAVD)and predominant aortic stenosis(AS).Methods Patients undergoing TAVR at our center between January 2020 and December 2022 were enrolled consecutively.Propensity score matching(PSM)(1∶1 ratio)was used to reduce selection bias.Transthoracic echocardiography(TTE)was used to monitor left ventricular ejection fraction(LVEF)and other structural parameters over time.The study outcome was a composite of cardiovascular death and rehospitalization due to cardiovascular causes.Linear mixed-effects models and logistic regression were utilized for comparing echocardiographic changes across groups and identifying independent risk factors for no-LVRR,respectively.Results After PSM,126 patients were included.MAVD group exhibited larger structural parameters(left ventricular end-systolic/end-diastolic diameter and volume,left ventricular mass index)and a lower left ventricular ejection fraction(LVEF)(all P＜0.05).However,more pronounced improvements in left ventricular structure and hemodynamics were observed during follow-up.Multivariate logistic regression analysis indicated that the left ventricular mass index(LVMI)was an independent predictor of left ventricular reverse remodeling(LVRR)after TAVR,whereas persistent moderate or greater mitral regurgitation(MR)and paravalvular leak(PVL)significantly reduced the incidence of LVRR.During a median follow-up period of 23 months,a total of 31 endpoint events occurred,and there was no statistically significant difference in long-term prognosis between the two groups(Log-rank P=0.330).Conclusions Compared to patients in the AS group,those in the MAVD group exhibited more severe left ventricular remodeling before TAVR.However,more significant LVRR was observed during postoperative follow-up.Additionally,the long-term prognosis was comparable between the two groups.