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.

BACKGROUND:At present,osteoarthritis has become a major disease affecting the quality of life of the elderly,and the therapeutic effect is poor,often focusing on preventing the disease process,and the pathogenesis of osteoarthritis is still not fully understood.Bioinformatics analysis was carried out to explore the main pathogenesis of osteoarthritis and related mechanisms of gene coding regulation. OBJECTIVE:To screen core differential genes with a major role in osteoarthritis by gene expression profiling. METHODS:Datasets were downloaded from the Gene Expression Omnibus(GEO):GSE114007,GSE117999,and GSE129147.Differential genes in the GSE114007 and GSE117999 data collections were screened using R software,performing differential genes to weighted gene co-expression network analysis.The module genes most relevant to osteoarthritis were selected to perform protein interaction analysis.Candidate core genes were selected using the cytocape software.The candidate core genes were subsequently subjected to least absolute shrinkage and selection operator regression and COX analysis to identify the core genes with a key role in osteoarthritis.The accuracy of the core genes was validated using an external dataset,GSE129147. RESULTS AND CONCLUSION:(1)A total of 477 differential genes were identified,265 differential genes associated with osteoarthritis were obtained by weighted gene co-expression network analysis,and 8 candidate core genes were identified.The least absolute shrinkage and selection operator regression analysis finally yielded a differential gene ASPM with core value that was externally validated.(2)It is concluded that abnormal gene ASPM expression screened by bioinformatics plays a key central role in osteoarthritis.

BACKGROUND:Studies have shown that patients with premature ovarian failure have changes in the structure of intestinal flora and that imbalance of intestinal microbiota may be one of the important mechanisms in the development of premature ovarian failure. OBJECTIVE:To investigate the effect of Liuwei Dihuang Wan on oxidative stress and intestinal microbiota in premature ovarian failure mice induced by cyclophosphamide. METHODS:Forty-five female ICR mice were randomized into three groups:blank group(normal mice),model group(premature ovarian failure mice),and Liuwei Dihuang Wan group.A mouse model of premature ovarian failure was prepared by one-time intraperitoneal injection of cyclophosphamide(120 mg/kg)in the latter two groups.After successful modeling,the Liuwei Dihuang Wan group was intragastrically administered for 28 continuous days,and the other two groups were intragastrically administered with the same amount of normal saline for 28 days.Mouse body mass was recorded weekly and ovarian index was calculated.The development of mouse follicles was observed using hematoxylin-eosin staining.ELISA method was used to detect serum levels of anti-Mullerian hormone,estradiol,follicle stimulating hormone,superoxide dismutase,glutathione peroxidase,and malondialdehyde.Meanwhile,the gut microbiome of all mice was detected through 16S rDNA sequencing. RESULTS AND CONCLUSION:The mice in the model group had loose hair,decreased vigor and grip strength,almost no increase in body mass,and decreased ovarian index.Whereas,the mouse body mass and ovarian index were increased after treatment with Liuwei Dihuang Wan(P<0.05).The estrous cycle of mice in the model group was disorganized;Liuwei Dihuang Wan could restore the estrous cycle and reduce the number of atretic follicles in mice with premature ovarian failure.The serum levels of follicle stimulating hormone and malondialdehyde in the model group significantly increased(P<0.01),while the levels of estradiol,anti-Mullerian hormone,superoxide dismutase,and glutathione peroxidase significantly decreased(P<0.01).Liuwei Dihuang Wan could significantly decrease the serum levels of follicle stimulating hormone and malondialdehyde(P<0.01),and increase the levels of estradiol,anti-Mullerian hormone,superoxide dismutase,and glutathione peroxidase.According to the 16S rDNA sequencing results,Liuwei Dihuang Wan could regulate the abundance and diversity of intestinal microbiota,and increase the relative abundance of beneficial bacteria.KEGG pathway analysis showed that the intestinal microbiota and metabolic pathways,biosynthesis of secondary metabolites,microbial metabolism in different environments,and biosynthesis of amino acids were regulated by Liuwei Dihuang Wan.To conclude,the changes in the structure of intestinal microbiome may be one of the potential mechanisms of Liuwei Dihuang Wan in treating premature ovarian failure.Liuwei Dihuang Wan can regulate the structure of intestinal microbiome,increase the number of beneficial bacteria,reduce the number of harmful bacteria,and thus improve the balance of intestinal microbiota.This regulatory effect helps to reduce oxidative stress levels and further inhibit ovarian oxidative stress in mice with premature ovarian failure.

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.

ObjectiveTo dynamically observe the clinical symptoms and pathological changes in a rat model of vinorelbine-induced phlebitis via injection into the dorsalis pedis vein. MethodsTwenty-eight 11-week-old male SPF-grade SD rats were randomly divided into a model group (n=20) and a control group (n=8). The model group received a single injection of 0.1 mL vinorelbine solution (4 mg/mL) via the right hind limb dorsalis pedis vein, while the control group received an equal volume of normal saline via the same method. The occurrence and grading of phlebitis in both groups were observed and recorded daily. The volume of the injured limb was measured by the drainage method to calculate the swelling rate. The weight-bearing ratio of the injured limb was assessed using a bipedal balance pain meter, and the skin temperature of the injured limb was measured by infrared thermal imaging. These measurements were conducted for 9 consecutive days. Starting from day 1, three rats from the model group were euthanized every other day. A 1-cm segment of the vein extending proximally from the injection site was collected. Pathological changes in the vein tissue were examined by hematoxylin-eosin staining, and ultrastructural changes of the vascular endothelium were observed using scanning electron microscopy. ResultsCompared to the control group, the injected hindlimb of model rats showed redness and swelling on day 1, with the swelling rate peaking at (81.89±15.75) % on day 3 (P<0.001), then gradually alleviating and decreasing to (15.41±0.33) % by day 9 (P<0.01). Pain was observed in the affected limbs of model rats on day 1 and worsened markedly on day 3, with the weight-bearing ratio decreasing to (36.35±4.91)% (P<0.001). Meanwhile, the skin temperature of the lesion site increased, reaching (36.36±0.40) ℃ on day 5 (P<0.001). Both pain and fever returned to near normal levels by day 9. Phlebitis grading in the model group showed that 75.0% of rats were grade Ⅱ on day 1; grade Ⅲ and Ⅳ each accounted for 37.5% on day 3; from days 5 to 9, most rats exhibited cord-like veins, predominantly grade III. Venous tissue showed peripheral edema and inflammatory cell infiltration on day 1, which gradually progressed to intimal rupture, vessel wall thickening, and even lumen narrowing from day 3 to 9. The venous intima exhibited destruction of tight junctions between endothelial cells and adhesion of blood cells, progressing to roughened, wrinkled, and protruding intimal surfaces. ConclusionThe vinorelbine-induced phlebitis of dorsal foot vein in rat model is characterized by local redness, swelling, warmth, and pain from days 3 to 5, which largely resolve by day 9, although cord-like veins can still be observed. With disease progression, venous tissue develops edema, vessel wall thickening, and lumen narrowing. The venous intima shows rupture, roughening, and in some cases, complete loss.