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.

Large language models (LLMs) offer a modern approach to help inherit traditional Chinese medicine (TCM). This article discussed the progress of LLM applications in TCM and proposed future development directions by reviewing the existing research. We have found that LLMs and related technologies have excellent applications and performance in the management of TCM knowledge and data. They are often applied in information extraction, knowledge graph construction, and data standardization processing. However, data quality and security issues need to be given more attention. In clinical diagnosis and treatment, LLMs can imitate the thinking of TCM by disassembling and reconstructing its diagnostic process and can achieve functions such as prescription recommendation and question and answer (Q&A). However, this approach involves LLMs making inferences and predictions based on existing corpora and thus may not flexibly handle complex environments and tasks. Moreover, the current evaluation criteria for TCM LLMs can be summarized into 3 categories: general evaluation metrics, technical framework evaluation, and evaluation criteria for the characteristics of TCM (such as consistency rates of prescriptions and diagnostic suggestions). However, the lack of a unified and standardized evaluation system hinders the clinical application of TCM LLMs. The future progress of TCM LLMs should focus on the 3 aforementioned critical aspects to achieve technological breakthroughs. In addition, we are promoting the research on vertical TCM LLMs and application terminals. We believe this will bring new ideas to the research on TCM LLMs.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

ObjectiveMigraine is a leading neurological disorder and the fourth most common cause of years lived with disability worldwide, affecting nearly 116 million individuals. Although pharmacological treatments are available, their efficacy is often limited by side effects and variable response rates. Repetitive transcranial magnetic stimulation (rTMS) over the dorsolateral prefrontal cortex (DLPFC) offers a safe, non-invasive alternative for migraine management. However, the neurophysiological mechanisms, particularly how rTMS modulates local cortical excitability and distributed pain-related circuits, remain poorly understood. Elucidating these mechanisms is essential for optimizing treatment protocols and improving clinical outcomes. MethodsThis study employed concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG) to investigate neuroplastic and neurocircuitry mechanisms of DLPFC-rTMS in migraine. Study 1 compared 30 migraineurs and 28 healthy controls to identify abnormalities in TMS-evoked potentials (TEPs) and significant current density (SCD) within sensory-discriminative regions including the primary somatosensory cortex (S1) and posterior insula (pINS), cognitive-affective regions including the anterior insula (aINS) and midcingulate cortex (MCC), and a descending modulatory region, the periaqueductal gray (PAG). Study 2 used a single-blind, crossover, sham-controlled design in 34 healthy participants. Each participant received both active (10 Hz, 80% RMT, 1 500 pulses) and sham DLPFC-rTMS in counterbalanced order. TMS-EEG and cold pain tolerance were assessed before and after each session. ResultsIn Study 1, migraineurs showed a significantly less negative N120 amplitude compared to healthy controls (P=0.027, Cohen’s d=0.60), indicating local intracortical disinhibition. No group differences were observed for N40, P60, or P180 components. At the source level, migraineurs exhibited significantly higher SCD in the S1, pINS, aINS, and MCC (allQ<0.05), but not in the ventroposterior thalamus (vpTHAL), mediodorsal thalamus (mdTHAL), or PAG. In Study 2, active rTMS significantly reduced SCD from pre- to post-stimulation in the S1, aINS, and MCC (all Q<0.05). Sham stimulation also reduced SCD in the S1 (Q<0.05) but not in the aINS or MCC. Although no significant group-level analgesic effect was observed between active and sham conditions (P=0.107), correlation analyses revealed that greater SCD reductions in the S1 and MCC were significantly associated with higher post-rTMS pain tolerance (R=-0.487 and -0.495, both Q<0.01) and larger improvements in pain tolerance(R=-0.487 and -0.451, both Q<0.05). No such correlations were found following sham stimulation, suggesting that the behavioural relevance of neural changes is specific to active rTMS. ConclusionThis study provides novel evidence that migraineurs exhibit both local neuroplastic abnormalities (reduced N120 amplitude) and hyperactivity in key pain-processing regions (S1, pINS, aINS, MCC). A single session of DLPFC-rTMS reduced hyperactivity in the aINS, MCC, and S1. Notably, greater reductions in the S1 and MCC were associated with improved pain tolerance. These findings identify distinct cortical circuitries, particularly within the cognitive-affective pain network, that may serve as potential biomarkers for optimizing rTMS treatment in migraine and other chronic pain conditions. Future studies should validate these results in patient populations experiencing spontaneous migraine attacks and explore multi-session or accelerated rTMS protocols.

Objective To enhance the gamma spectrometry analysis and detection capabilities of personnel in measuring radionuclides in bio-ash, and ensure the accuracy and precision of gamma spectrometer in our laboratory for the analysis of radionuclides in bio-ash. Methods The laboratory participated in the 2024 national interlaboratory comparison for radionuclide measurement in bio-ash. Radionuclides ²⁴¹Am, ¹³⁷Cs, and ⁴⁰K in four different bio-ash samples were measured. Based on the measurement methods specified in GB/T 16145—2022, sample measurement, result calculation, and uncertainty evaluation were performed using spectrometry analysis software and sourceless efficiency calibration software. The measurement results and performance evaluation of the laboratory in the comparison were analyzed, and factors affecting gamma-spectrometry measurement and result interpretation were discussed. Results The relative deviation (D) of the measurement results for radionuclides ²⁴¹Am and ¹³⁷Cs in the four bio-ash samples ranged from −10.2% to 2.0% and −1.7% to 0.3%, respectively. The P statistic ranged from 7.0% to 12.5% and 5.0% to 10.8%, respectively. These results met the criteria of |D| ≤ 20% (MARB), |D| ≤ 2.58P, and P ≤ 20% (MARB). The ζ-scores for the measurement of ⁴⁰K in the four bio-ash samples ranged from 0.8 to 1.3, satisfying the criterion of |ζ| < 2. All measurement results in this laboratory in the comparison were satisfactory. Conclusion The laboratory uses a high-purity germanium gamma spectrometer to measure radionuclides in bio-ash. The self-absorption correction method, analysis method, and uncertainty evaluation are appropriate, which can ensure the accuracy and precision of the measurement results. The measurement results are accurate and reliable.

Objective To investigate the prevalence of pinworm infections among kindergarten children and the effectiveness of health interventions among teachers and parents in Gaoyou City, so as to provide insights into optimization of enterobiasis control strategies. Methods From September to November each year from 2023 to 2025, Gaoyou City’s 57 kindergartens were divided into five zones based on the five cardinal directions: east, west, south, north, and center. At least one kindergarten was randomly selected as a survey site in each zone, with a minimum of 200 children surveyed per site. The transparent adhesive tape anal swab method was used to detect pinworm infection in the surveyed children, while the transparent adhesive tape sticking method was employed to assess pinworm egg contamination in the children’s home and classroom environments. Concurrently, health education interventions were conducted for kindergarten teachers and parents. Additionally, self-administered questionnaires were administered to teachers and parents to evaluate children’s hygiene behaviors and the awareness rates of pinworm prevention knowledge among teachers and parents before and after the health education interventions. Results From 2023 to 2025, a total of 1 939 children from nine kindergartens in Gaoyou City were tested for pinworm infection, with two cases detected, resulting in an overall infection rate of 0.10% (2/1 939). No pinworm eggs were found in the samples from the children’s families or classroom environments. In public kindergartens, the proportions of children practicing the four hygiene habits, namely “handwashing after defecation” [96.10% (1 305/1 358) vs. 74.65% (212/284); χ² = 153.646, P < 0.05], “regular nail trimming” [92.93% (1 262/1 358) vs. 77.82% (221/284); χ² = 61.349, P < 0.05], “not biting toys or pencils” [88.14% (1 197/1 358) vs. 76.76% (218/284); χ² = 25.549, P < 0.05], and “showering twice or more per week” [89.03% (1 209/1 358) vs. 74.65% (212/284); χ² = 41.699, P < 0.05], were all higher than those in private kindergartens. Before health education intervention, the awareness rates of pinworm prevention knowledge among teachers in public and private kindergartens were 86.89% (53/61) and 75.00% (21/28), respectively, with no statistically significant difference (χ² = 1.935, P > 0.05). The awareness rates among parents of children in public and private kindergartens were 64.73% (879/1 358) and 57.39% (163/284), respectively, showing a statistically significant difference (χ² = 5.447, P < 0.05). After the intervention, the awareness rates among teachers in public and private kindergartens increased to 96.72% (59/61) and 82.14% (23/28), respectively, while those among parents rose to 88.95% (1 208/1 358) and 77.81% (221/284), both with statistically significant differences (χ² = 5.628 and 25.808, both P < 0.05). Among the questionnaire items, teachers [32.58% (29/89)] and parents [26.00% (427/1 642)] had the lowest overall awareness rate regarding the “main reasons for the difficulty in preventing and controlling pinworm disease”. After the intervention, these rates increased to 77.53% (69/89) and 70.77% (1 162/1 642), respectively. Conclusions The prevalence of pinworm infection in kindergarten children in Gaoyou City is at a low level. Health intervention can effectively improve the knowledge level of teachers and parents on the prevention and treatment of pinworm disease, but further efforts are needed to strengthen the health education and management of pinworm disease in private kindergartens.

Background Patients with pneumoconiosis often have limited disease-related knowledge, insufficient access to health education, and substantial health management needs. Health education may help improve rehabilitation outcomes and quality of life in this population. Objective To evaluate the effects of health education based on the Listen-Establish-Adopt-Reinforce-Name-Strength (LEARNS) model on rehabilitation outcomes, health-related behaviors, and quality of life among pneumoconiosis patients, and provide effective intervention strategies for the rehabilitation management of patients with pneumoconiosis. Methods A randomized controlled trial was conducted. A total of 120 pneumoconiosis patients treated in the Department of Occupational Diseases, Beijing Emergency General Hospital, from November 2024 to February 2025 were enrolled. Participants were randomly assigned to a control group or an intervention group using a random number table method, with 60 patients in each group. The control group received routine pharmacotherapy, whereas the intervention group received a 12-week LEARNS model-based health-education intervention in addition to routine treatment. The 6-Minute Walk Test (6MWT) was used to assess exercise tolerance, and the modified Medical Research Council dyspnoea scale (mMRC) was used to evaluate dyspnoea. The Self-Rating Anxiety Scale (SAS) and Self-Rating Depression Scale (SDS) were applied for psychological status assessment. Pulmonary function, including forced expiratory volume in one second (FEV₁) and forced vital capacity (FVC), was measured using spirometry. A self-designed scale was used to evaluate eight health-related behaviors targeted by the health education program. The 36-Item Short-Form Health Survey (SF-36) and Chronic Obstructive Pulmonary Disease (COPD) Assessment Test (CAT) were used to assess quality of life, and the Pittsburgh Sleep Quality Index (PSQI) was adopted to evaluate sleep quality. Results After the 12-week intervention, the control group showed no statistically significant changes from baseline in the measured outcomes(P＞0.05). In the intervention group, exercise tolerance improved significantly, with the 6-minute walking distance increasing from (382.55±19.52) m to (426.84±33.59) m (P＜0.001). Dyspnoea was also alleviated, with the mMRC score decreasing from 1.37±0.66 to 0.96±0.54 (P＜0.001). The CAT score decreased from 18.95±7.03 to 10.67±3.64 (P＜0.001). Significant improvements were observed in anxiety and depression symptoms (P＜0.001), with the SAS score decreasing from 38.85±6.24 to 34.27±2.27, and the SDS score decreasing from 49.01±3.25 to 45.49±3.44. Sleep quality improved significantly, with the PSQI score dropping from 7.89±4.35 to 4.05±2.31 (P＜0.001). All eight health-related behaviors in the intervention group improved significantly after the intervention (P＜0.001), including acquisition of disease-related knowledge (1.87±0.34 vs. 3.13±0.45), participation in health education activities (1.89±0.52 vs. 3.61±0.38), and regular physical exercise (2.37±0.41 vs. 4.17±0.33). All SF-36 domain scores increased significantly (P＜0.05), with the most prominent improvements observed in physical functioning, general health, and vitality. At week 12, all SF-36 domain scores were significantly higher in the intervention group than in the control group (P＜0.05). No statistically significant between-group differences were detected in pulmonary function parameters (P＞0.05). Conclusion LEARNS model-based health education could improve exercise tolerance, dyspnea, psychological status, sleep quality, health-related behaviors, and quality of life among patients with pneumoconiosis, and therefore may be a useful adjunctive strategy for rehabilitation management in patients with pneumoconiosis.

Objective: To analyze the epidemiological characteristics and spatio-temporal clustering characteristics of pulmonary tuberculosis (PTB) in Yulin City, Shaanxi Province from 2007 to 2024, so as to provide the evidence for optimizing regional PTB prevention and control strategies. Methods: Registration data of PTB cases in Yulin City from 2007 to 2024 were collected from the Tuberculosis Management Information System of the China Disease Prevention and Control Information System. The average annual percent change (AAPC) and annual percent change (APC) were used to analyze the trends in PTB registration rates. Descriptive epidemiological methods were used to analyze the temporal, spatial and population distribution characteristics. Spatio-temporal scan analysis was used to analyze the spatio-temporal clustering characteristics. Results: A total of 35 874 PTB cases were registered in Yulin City from 2007 to 2024. The registered incidence decreased from 80.41/105 in 2007 to 38.53/105 in 2024 (AAPC=-3.916%, P<0.05). Downward trends were observed from 2007 to 2016 and from 2019 to 2022 (APC=-4.440%, -19.361%, both P<0.05). March used to be the peak of disease incidence, with a seasonal index of 1.78, while February used to be the trough, with a seasonal index of -1.38. The average annual registered incidence rates were relatively high in Zhouxian County, Wubu County, and Suide County, at 89.02/105, 82.52/105 and 79.61/105, respectively. There were 21 672 registered PTB cases among males, accounting for 60.41%, and 14 202 cases among females, accounting for 39.59%. The higher registered cases were observed in groups aged 15 to <25 years and ≥65 years, with 9 400 and 7 950 cases, accounting for 26.20% and 22.16%, respectively. The proportion of population aged ≥65 years increased from 16.97% in 2007 to 43.24% in 2024, with an increase of 154.80%. Farmers were the predominant occupation, with 24 477 cases, accounting for 68.23%. Spatio-temporal scan analysis showed that the primary clusters consistently included Qingjian County, Suide County, Zizhou County, and Wubu County from 2007 to 2015, 2016 to 2019, 2020 to 2022 and 2023 to 2024. Mizhi County was incorporated into the clusters from 2016 to 2019 and 2020 to 2022, while Jiaxian County was further added from 2023 to 2024. The specific cluster periods were from January 2007 to June 2011, November 2017 to August 2019, March 2020 to July 2021, and February 2023 to July 2024, respectively. Conclusions From 2007 to 2024, the registered incidence of PTB in Yulin City showed an overall declining trend. March marked the peak of disease onset. Males, the elderly aged ≥65 years and farmers were the high-incidence population. Persistent spatio-temporal clustering was observed in the southern regions, including Qingjian County, Suide County, Zizhou County, Wubu County, and Mizhi County.

With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.