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.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

OBJECTIVE To identify the active components of Desmodium styracifolium （Osb.） Merr. extract （DME） against cholestatic liver injury （CLI）， and to verify its target and molecular mechanism， so as to provide scientific evidence for the clinical application of D.styracifolium （Osb.） Merr. and the development of new hepatoprotective agents.METHODS High-performance liquid chromatography was applied to establish fingerprints of 19 batches of DME， followed by similarity evaluation and identification of common peaks. An in vitro CLI model was constructed by lithocholic acid （LCA）-induced injury in HepG2 cells to evaluate the in vitro protective effect of DME against CLI. Spearman correlation analysis， grey relational analysis and partial least-squares regression analysis were adopted to investigate the spectrum-effect relationship of DME against CLI and preliminarily screen the core active components. Molecular docking and surface plasmon resonance technology were used to predict and verify the binding capacity between core active components and farnesoid X receptor （FXR）. qRT-PCR， Western blot and immunofluorescence staining tests were performed to validate the influences of core active components on the expression of molecules related to FXR/bile salt export pump （BSEP） pathway in CLI model cells.RESULTS A total of 12 common peaks were calibrated in the fingerprints of 19 batches of DME， and the similarity values were all above 0.990. Four common peaks were identified， namely peak 6 （schaftoside）， peak 7 （isoorientin）， peak 11 （isoschaftoside） and peak 12 （isovitexin）. DME at 80 μg/mL exerted the optimal protective effect on CLI-model cells， and the cell viability reached （75.66±4.60）% after 24 h of treatment. Spectrum-effect analysis revealed that schaftoside possessed the strongest correlation with the anti-CLI activity of DME and served as the core active component. Target prediction and validation results showed that the binding energy between schaftoside and FXR was －8.1 kcal/mol， and the equilibrium dissociation constant was 27.3 μmol/L. Mechanistic experiments demonstrated that 100 μmol/L schaftoside significantly elevated the expression levels of FXR and BSEP， and mRNA of their encoded genes Nr1h4 ， Abcb11 in CLI-model cells （ P ＜0.05）.CONCLUSIONS Schaftoside may be the core active component of DME against CLI， and its mechanism may be related to the activation of FXR/BSEP pathway.

Background Pulmonary heart disease (PHD) is a critical cardiopulmonary disease in high-altitude areas, with pulmonary hypertension (PH) as its central pathological basis. Cold and hypoxia are vital environmental characteristics of high-altitude regions; however, their joint effect on the hospitalization risk for PHD and the underlying biological mechanisms remain unclear. Objective To evaluate the associations of cold, hypoxia, and their joint exposure with PHD hospitalization risk, and to investigate PH-related pathological changes induced by combined cold and hypoxic exposure and the intervention effects of γ-aminobutyric acid (GABA) in rats. Methods Based on hospitalization data for 92986 PHD cases from 333 hospitals in Gansu Province (2018–2022), a generalized additive model (GAM) with a quasi-Poisson distribution was used to assess the associations between daily mean temperature, atmospheric oxygen content (AOC) and the daily number of PHD hospitalizations. Four joint exposure categories were constructed using the fifth percentile of temperature (P₅, −7.90℃) and AOC grades (high or low) to assess the associations between different exposure combinations and daily PHD hospital admissions. To further investigate PH-related pathological changes and the intervention effects of GABA, 24 specific-pathogen-free male Sprague–Dawley rats were randomly assigned to four groups (n=6): normal temperature and normoxia control group (NC), combined cold and hypoxia exposure group (CH), combined exposure plus low-dose GABA intervention group (CHL), and combined exposure plus high-dose GABA intervention group (CHH). After 5 weeks, pulmonary hemodynamics and vascular remodeling were evaluated. Gut microbiota and inflammatory cytokines in lung tissue were assessed using 16S rRNA sequencing and enzyme-linked immunosorbent assay (ELISA), respectively. Results Each 1 g·m⁻³ decrease in AOC and each 1 ℃ decrease in daily mean temperature were associated with 2.6% (RR=1.026, 95%CI: 1.024, 1.027) and 1.8% (RR=1.018, 95%CI: 1.015, 1.020) increases in PHD hospitalization risk, respectively. Compared with the non-low-temperature and high-AOC group, the low-temperature and low-AOC group had the highest risk estimate (RR=1.673, 95%CI: 1.567, 1.785). Animal experiments demonstrated that, compared with the NC group, rats in the CH group showed shortened pulmonary artery acceleration time (PAT) and increased mean pulmonary artery pressure (MPAP), right ventricular hypertrophy index (RVHI), pulmonary arterial wall thickness, and α-smooth muscle actin (α-SMA) expression (P<0.05). The Observed Species and Chao1 indices of the gut microbiota were significantly lower in the CH group than in the NC group (P<0.05), while levels of tumor necrosis factor-alpha (TNF-α) and interleukin-1beta (IL-1β) in lung tissue were elevated (P<0.05). GABA intervention improved selected hemodynamic, vascular remodeling, and inflammatory indices. Conclusion Decreases in daily mean temperature and AOC are associated with an increased risk of PHD hospitalization, with the highest risk estimate observed in the low-temperature and low-AOC group. Animal experiments suggest that combined cold and hypoxic exposure induce PH-related pathological changes accompanied by alterations in the gut microbiota and pulmonary inflammation. GABA may partially ameliorate these changes.

Bismuth iodide(BiOI)with different crystal plane ratios of(110)to(001)was synthesized,and typeⅡheterojunction formed between(001)and(110)crystal planes of BiOI was used to improve the separation efficiency of photogenerated electrons and holes.Then the BiOI(001)/(110)was composited with nitrogen-doped graphene quantum dots(N-GQDs)to prepare a ternary composites,which could enhance the range and intensity of light absorption,and prolonged the lifetime of photogenerated electrons due to the formation of Z-scheme heterojunctions between BiOI and N-GQDs,thereby leading to the excellent photoelectric performance of the BiOI/N-GQDs for generating sensitive photoelectric response signals.A photoelectrochemical sensor for sensitive detection of chlorpyrifos(CPF)was designed with BiOI/N-GQDs-modified FTO electrode as a photocathode.The S and N atoms contained in CPF were coordinated with Bi(Ⅲ)on the surface of BiOI,which reduced the photocurrent of BiOI/N-GQDs.The photocurrent change was linear with logarithm of concentration of CPF in the range of 1.5×10-12-5.0×10-9 mol/L,and the detection limit was 1.5×10-12 mol/L.The sensor was highly sensitive,selective and stable,and could be used for determination of trace CPF in environmental and food samples.

Objective:To evaluate whether the mechanism by which mesenchymal stem cell-derived exosomes (MSC-exo) mitigated endotoxin-induced lung injury was related to the heme oxygenase-1 (HO-1)/mitochondrial signaling pathway in alveolar macrophages of mice.Methods:In vivo experiment Eighteen C57BL/6 wild-type (WT) mice were divided into 3 groups ( n=6 each) using a random number table method: control group (C group), lipopolysaccharide (LPS) group (L group) and LPS + MSC-exo group (LM group). Six HO-1 conditional knockout mice (HO-1 -/-) were selected and served as HO-1 -/- + MSC-exo + LPS group (HML group). The model of endotoxin-induced lung injury was prepared by injection of LPS 15 mg/kg. MSC-exo (2×10 11 particles) was intravenously injected at 1 h before injection of LPS in LM group. MSC-exo (2×10 11 particles) was intravenously injected and 1 h later LPS was injected in HML group. The expression of HO-1 in macrophages was detected using immunofluorescence, lung injury was assessed following hematoxylin-eosin staining, the wet/dry weight ratio (W/D ratio) was determined, and the mitochondrial morphology was observed with a transmission electron microscope. Cell experiment Alveolar macrophages (MH-S) were divided into 4 groups ( n=20 each) using a random number table method: control group (C group), LPS+ phosphate buffer solution group (LP group), LPS+ MSC-exo group (LM group), and LPS+ MSC-exo+ HO-1 small-interfering RNA group (LMS group). Cells were incubated for 12 h with LPS 10 μg/ml in LP, LM and LMS groups. In addition, LM group was incubated with MSC-exo 100 μg/ml, LP group was incubated with the equal volume of phosphate buffer solution, and the alveolar macrophages were transfected with HO-1 small interfering RNA and incubated with MSC-exo 100 μg/ml in LMS group at the same time. The concentrations of interleukin-1beta (IL-1β) and tumor necrosis factor-alpha (TNF-α) in supernatant were measured by enzyme-linked immunosorbent assay, HO-1 expression was detected by Western blot, the mitochondrial membrane potential was measured using JC-1 staining, and the expression of reactive oxygen species (ROS) was detected by fluorescence. Results:In vivo experiment Compared to C group, the lung injury score and W/D ratio were significantly increased ( P<0.05), the fluorescence signal of HO-1 in macrophages was enhanced, and the damage to mitochondria was aggravated in L group. Compared to L group, the lung injury score and W/D ratio were significantly decreased ( P<0.05), the fluorescence signal of HO-1 in macrophages was enhanced, and the damage to mitochondria was reduced in LM group. Compared to LM group, the lung injury score and W/D ratio were significantly increased ( P<0.05), macrophages had no HO-1 fluorescence signal, and the damage to mitochondria was aggravated in HML group. Cell experiment Compared to C group, the concentrations of IL-1β and TNF-α in supernatant were significantly increased, the expression of HO-1 was up-regulated ( P<0.05), and the mitochondria predominantly exhibited green JC-1 fluorescence, accompanied by an enhanced ROS fluorescence signal in LP group. Compared to LP group, the concentrations of IL-1β and TNF-α in supernatant were significantly decreased, the expression of HO-1 was up-regulated ( P<0.05), and the mitochondria predominantly exhibited red JC-1 fluorescence, accompanied by a weakened ROS fluorescence signal in LM group. Compared to LM group, the concentrations of IL-1β and TNF-α in supernatant were significantly increased, the expression of HO-1 was down-regulated ( P<0.05), and the mitochondria predominantly exhibited green JC-1 fluorescence, accompanied by an enhanced ROS fluorescence signal in LMS group. Conclusions:The mechanism by which MSC-exo attenuates endotoxin-induced lung injury may be related to up-regulation of HO-1 expression in alveolar macrophages and reduction of mitochondrial damage in mice.

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.

Aim To explore the mechanism of ligustil-ide(LIG)improving demyelination by inhibiting in-flammatory response in mice with distal middle cerebral artery occlusion(dMCAO)through AIM2/caspase-1 signal pathway.Methods Thirty C57BL/6N male mice were randomly divided into three groups:sham operation group(Sham group,n=10),model group(dMCAO group,n=10)and treatment group(LIG group,n=10).The dMCAO mouse model was estab-lished by electrocoagulation in dMCAO group and LIG group.The mice were scored by Longa after waking up,and the changes of cerebral blood flow were moni-tored by laser speckle blood flow imaging system after dMCAO.One hour after modeling,LIG(30 mg·kg-1·d-1)was injected intraperitoneally in LIG group,and the same amount of normal saline was injected in sham group and dMCAO group for one week until the end of the experiment.The mice in each group were stained with TTC,and the brain injury was observed pathologically.Fatigue turning bar test and open field test were used to evaluate the motor function and anxie-ty degree of mice,and then the brain tissues of mice were taken for black gold staining to compare the chan-ges of myelin sheath in each group.Immunofluores-cence staining was used to detect the average fluores-cence intensity of MBP,IBA1 and GFAP in CC,CPU and CX regions of mouse brains.ELISAwas used to de-tect the contents of TNF-α,IL-6,IL-1 β,IL-17A and BDNF in brain tissue proteins of mice.Western blot-ting was used to detect the protein expressions of AIM2,caspase-1 and ASC-in each group.Results Compared with the dMCAO group,the infarct area was reduced,the behavior was significantly improved and the demyelination was reduced in the LIG group.The expression of MBP protein in CC,CPU and CX regions increased(P＜0.05),the expression of IBA1 in CX decreased(P＜0.01),and the expression of GFAP in-creased in CC,CPU and CX regions(P＜0.01).The results of ELISA showed that the levels ofTNF-α(P＜0.01),IL-6(P＜0.01),IL-1β(P＜0.05)and IL-17A(P＜0.01)significantly decreased,while the ex-pression of BDNF increased(P＜0.05).The protein expression levels of AIM2,caspase-1 and ASC in mouse brain decreased after treatment(P＜0.01).Conclusion LIG has a protective effect on demyelina-tion in dMCAO mice,which may be related to the inhi-bition of AIM2/caspase-1 signaling pathway and in-flammation and to the promotion of BDNF secretion.