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.

ObjectiveThe widespread adoption of portable fundus cameras for primary care and community screening is hindered by limitations in current autofocus(AF) technologies. Image-based methods relying on sharpness evaluation require iterative searches, resulting in slow convergence, while projection-based techniques are susceptible to optical artifacts and calibration errors. To address these challenges, this study introduces a novel AF system based on direct wavefront sensing, designed to deliver simultaneous high speed, high precision, and operational robustness within the compact form factor essential for portable ophthalmic devices. MethodsOur approach fundamentally reimagines the AF process by directly measuring the ocular wavefront aberration. We developed a custom portable fundus camera integrating a miniaturized Shack-Hartmann wavefront sensor (SHWS) into the optical path. An 850 nm laser diode projects a point source onto the retina via oblique illumination to minimize corneal reflections. Light scattered from this spot carries the eye’s refractive error through the imaging optics and is directed to the SHWS, positioned at a plane optically conjugate to the primary color CMOS imaging sensor. A microlens array within the SHWS samples the incident wavefront, generating a pattern of focal spots on a CCD. Real-time centroid analysis of these spots provides a map of local wavefront slopes. These measurements are processed through a singular value decomposition (SVD) algorithm to fit a Zernike polynomial basis set, enabling real-time reconstruction of the wavefront phase. The defocus component (S) is extracted from the second-order Zernike coefficients, providing a direct, quantitative measure of the refractive error in diopters. This value serves as a precise error signal in a closed-loop control system, which commands a voice-coil actuated focusing lens to its null position in a single, deterministic step, eliminating the need for iterative search algorithms. ResultsComprehensive evaluation demonstrated the system’s high performance. Testing on a calibrated model eye (OEMI-7) established a highly linear relationship between the computed defocus S and the focusing lens position across a ±20 Diopter (D) compensation range, achievable within a 5 mm mechanical travel. The system achieved a focusing precision of 0.08 D, corresponding to an 18-fold improvement over a conventional projection spot-size method tested under identical conditions. The total focus acquisition time, encompassing wavefront measurement, computation, and lens actuation, averaged under 0.5 s. Clinical validation with 25 human volunteers (50 eyes, refractive range -15 D to +10 D) confirmed practical efficacy. The wavefront-sensing AF succeeded in 92% of attempts with a mean time of 0.5 s, substantially outperforming a projection-based benchmark which achieved only a 32% success rate with an average time of 4.25 s. The system provided instantaneous directional guidance and maintained stability during minor ocular movements. Objective assessment of image quality, via amplitude contrast of retinal vasculature, showed consistent and significant enhancement following AF correction across the entire tested diopter range. ConclusionThis work successfully implements and validates a direct wavefront-sensing autofocus paradigm for portable fundus cameras. By directly quantifying and compensating for the optical defocus aberration, this method bypasses the fundamental limitations of image-processing and projection-based techniques, enabling rapid, precise, and deterministic diopter compensation. The developed system delivers an exceptional combination of a wide operational range (±20 D), high accuracy (0.08 D), fast convergence (0.5 s), and a compact physical footprint. This technology provides a practical and high-performance focusing solution capable of enhancing the reliability, throughput, and diagnostic utility of portable retinal imaging in large-scale screening applications. Future efforts will be directed towards system cost optimization and performance adaptation for diverse ocular conditions.

ObjectiveTo investigate the expression characteristics of serum HBV RNA in patients with low-level viremia （LLV） and its value in the diagnosis of LLV. MethodsA total of 402 chronic hepatitis B （CHB） patients who attended Affiliated Hospital of Zunyi Medical University from December 2023 to May 2025 were enrolled， and according to their viral load， they were divided into complete virologic response （CVR） group （190 patients with HBV DNA <20 IU/mL） and LLV group （212 patients with an HBV DNA level of ≥20 IU/mL and <2 000 IU/mL）. The two groups were analyzed in terms of age， sex， disease type， serum HBV RNA， HBeAg， alanine aminotransferase （ALT）， aspartate aminotransferase （AST）， and total bilirubin （TBil）， and according to HBeAg status， the patients in the LLV group were further divided into HBeAg-negative group with 140 patients and HBeAg-positive group with 72 patients. The chi-square test was used for comparison of categorical data between two groups， and the Mann-Whitney U test was used for comparison of continuous data between two groups. A multivariate Logistic regression analysis was used to investigate the influencing factors for LLV in CHB patients， and a Spearman’s rank correlation analysis was used to analyze the correlation of HBV RNA with HBV DNA， ALT， AST， and TBil in the LLV group. The receiver operating characteristic （ROC） curve was plotted to evaluate the efficacy of HBV RNA in the diagnosis of LLV. ResultsCompared with the CVR group， the LLV group had a significantly higher serum level of HBV RNA ［3 （1　—　5） log₁₀ copies/mL vs 2 （1　—　3） log₁₀ copies/mL， Z=-2.346， P=0.019］ and a significantly higher proportion of patients with hepatitis B cirrhosis （31.13% vs 22.11%， χ²=4.155， P=0.042） or hepatocellular carcinoma （9.91% vs 4.74%， χ²=3.876， P=0.049）. The multivariate Logistic regression analysis showed that HBV RNA （odds ratio=1.163， 95% confidence interval： 1.058　—　1.278， P=0.002） was an independent risk factor for the onset of LLV in CHB patients. Among the patients with LLV， HBeAg-positive patients had a significantly higher level of HBV RNA than HBeAg-negative patients ［6 （4　—　7） log₁₀ copies/mL vs 2 （1　—　3） log₁₀ copies/mL， Z=-9.962， P<0.001］. The correlation analysis showed that HBV RNA level had no significant correlation with HBV DNA， ALT， AST， or TBil in the patients with LLV （all P>0.05）. The ROC curve analysis showed that HBV RNA had an AUC of 0.567 for the diagnosis of LLV （P=0.021）， with an optimal cut-off value of 4.5 log₁₀ copies/mL， a sensitivity of 30.7%， and a specificity of 85.8%. ConclusionSerum HBV RNA level is an independent risk factor for the development of LLV in CHB patients， and there is a significant increase in the expression of HBV RNA in HBeAg-positive patients. Therefore， it may serve as a potential biomarker for clinical risk assessment.

ObjectiveTo investigate the mechanism of action of Jiedu Huayu granules in improving liver injury in mice with acute liver failure （ALF） by observing its effect on a mouse model of ALF after prophylactic administration， and to provide a basis for clinical medication. MethodsA total of 60 specific pathogen-free male C57BL/6J mice were divided into normal group， model group， Jiedu Huayu granules group （JDHY group）， and farnesoid X receptor （FXR） agonist （GW4064） group using a random number table， with 15 mice in each group. The model of ALF was induced by a single intraperitoneal injection of D-galactosamine combined with lipopolysaccharide. The mice in the JDHY group were given prophylactic administration of 0.3 g/mL drug solution of Jiedu Huayu granules by gavage for 3 days before modeling， those in the normal group and the model group were given 0.9% NaCl solution by gavage， and those in the GW4064 group were given intraperitoneal injection of GW4064 for 3 consecutive days before modeling. The mice were sacrificed after modeling， and serum and liver tissue samples were collected. A veterinary automatic biochemical analyzer was used to measure the serum levels of total bilirubin （TBil）， total bile acids （TBA）， gamma-glutamyl transferase （GGT）， alanine aminotransferase （ALT）， and aspartate aminotransferase （AST） in mice from each group； HE staining was used to observe liver pathological changes； RT-PCR was used to measure the mRNA expression levels of FXR， fibroblast growth factor 15 （FGF15）， fibroblast growth factor receptor 4 （FGFR4）， small heterodimer partner （SHP）， and bile salt export pump （BSEP） in mice， and Western blot was used to measure the protein expression levels of FXR， FGF15， FGFR4， SHP， and BSEP. A one-way analysis of variance was used for comparison between groups， and the Dunett method was used for further comparison between two groups. ResultsCompared with the normal group， the model group had significant increases in the serum levels of TBil， ALT， AST， TBA， and GGT （all P<0.01）， and compared with the model group， the JDHY group and the GW4064 group had significant reductions in the serum levels of TBil， ALT， AST， TBA， and GGT （all P <0.01）. HE staining showed that compared with the model group， the JDHY group and the GW4064 group had milder pathological injury， a reduction in the area of hepatocyte necrosis， and alleviation of cellular swelling and edema. Compared with the normal group， the model group had significant reductions in the mRNA and protein expression levels of FXR， FGF15， FGFR4， SHP， and BSEP in liver tissue （all P <0.01）， and compared with the model group， the JDHY group and the GW4064 group had significant increases in the mRNA and protein expression levels of FXR， FGF15， FGFR4， SHP， and BSEP in liver tissue （all P <0.05）. ConclusionJiedu Huayu granules may alleviate liver injury in mice with ALF through the FXR/SHP axis.

Objective: To analyze changes in tuberculosis infection among junior high school students before and after tuberculosis exposure, so as to provide a reference for improving school tuberculosis prevention and control measures and policy formulation. Methods: Retrospectively collect data on a tuberculosis outbreak that occurred in a grade of a junior high school in Chongqing in 2025, including tuberculosis screening records of students in this grade upon their enrollment in 2022 (1 156 students) and after two tuberculosis outbreaks in 2023 (206 students) and 2025 (171 students). The Wilcoxon signed rank test for paired design was used to compare the induration diameters of the subjects, and the Chi square test was adopted to analyze the rate of tuberculosis infection among students. Results: In the tuberculosis outbreak in 2023, the rate of tuberculosis infection among close contacts ( 11.84 %) and the rate of tuberculosis infection among freshrman at school enrollment (12.89%) showed no statistically significant difference ( χ 2=0.25, P >0.05). The rate of tuberculosis infection of close contacts in the 2025 tuberculosis outbreak (55.56%) was higher than that in the 2023 outbreak (11.84%) ( χ 2=30.42, P <0.01). Among the 106 students included in the cohort analysis, the median induration diameter was 3.50 (1.50, 7.50) mm in 2023 and 8.75 (4.25, 11.50) mm in 2025, with a statistically significant difference ( Z=-5.76, P <0.01). There was no statistically significant difference between the infection rate in 2022 (16.98%) and that in 2023 (10.38%) ( χ 2=1.96, P =0.16). The infection rate in 2025 (43.40%) was higher than those in 2022 and 2023 ( χ 2=17.55, 29.39, both P <0.017). The seroconversion rate of students in the same class in 2025 ( 58.00 %) was higher than that of students in different classes (16.07%), with a statistically significant difference ( χ 2=20.19, P <0.01). All 72 individuals with latent tuberculosis infections identified during the pandemic in 2023 and 2025 refused to undergo prophylactic treatment. Conclusions The lack of preventive treatment may be the underlying cause of the successive outbreaks during the epidemic. Early detection of infection sources and standardized outbreak management are crucial to controlling the spread of the epidemic.

As a key member of the insulin-like growth factor family， insulin-like growth factor-‍Ⅰ （IGF-‍Ⅰ） is mainly synthesized in the liver and is widely distributed in the human body， and it is involved in the physiological processes such as cell proliferation， differentiation， metabolism， and apoptosis. Studies have shown that the level of IGF-‍Ⅰ is negatively correlated with the severity of liver cirrhosis， and IGF-‍Ⅰ mainly affects the progression of liver cirrhosis by inhibiting liver fibrosis， promoting DNA damage repair， and regulating lipid metabolism. Monitoring of IGF-‍Ⅰ level is expected to provide an evaluation indicator for improving the prognosis of patients with liver cirrhosis， and stimulating the action pathway of IGF-‍Ⅰ or regulating its expression level may become a new method for the treatment of liver cirrhosis. This article reviews the research advances in IGF-‍Ⅰ in liver cirrhosis， in order to provide new ideas for the diagnosis and treatment of liver cirrhosis.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

To explore the anti-depression effect of Suanzaoren Decoction(SZRD), the regulatory effects on endogenous metabolites in the liver of rats with depression induced by chronic unpredictable mild stress(CUMS) were analyzed by using LC-MS metabolomics. The rats were randomly divided into normal control group, model group, low-dose SZRD group, high-dose SZRD group, and positive drug group. The CUMS depression model was replicated by applying a variety of stimuli, such as fasting and water deprivation, ice water swimming, hot water swimming, day and night reversal, tail clamping, and restraint for rats. Modeling and treatment were conducted for 56 days. The behavioral indexes of rats in each group, including body weight, open field test, sucrose preference test, and tail suspension test, were observed. Plasma samples and liver tissue samples were collected, and the contents of 5-hydroxytryptamine(5-HT), dopamine(DA), and norepinephrine(NE) in plasma were measured using enzyme-linked immunosorbent assay(ELISA). Meanwhile, the regulatory effects of SZRD on the liver metabolic profile of CUMS model rats were analyzed by the LC-MS metabolomics method. The results show that SZRD can significantly improve the depression-like behavior of CUMS model rats and increase the neurotransmitter levels of 5-HT, DA, and NE in plasma. A total of 24 different metabolites in the rats' liver are identified using the LC-MS metabolomics method, and SZRD can reverse 13 of these metabolites. Metabolic pathway analysis indicates that nine metabolic pathways are found to be significantly associated with depression, and in the low-dose SZRD group, four pathways can be regulated, including pentose phosphate pathway, purine metabolism, inositol phosphate metabolism, and sphingolipid metabolism. In the high-dose SZRD group, two metabolic pathways can be regulated, including sphingolipid metabolism and glycerol glycerophospholipid metabolism. Sphingolipid metabolism is a metabolic pathway that can be regulated by SZRD at different doses, so it is speculated that it may be the primary pathway through which SZRD can alleviate metabolic disturbances in the liver of CUMS model rats.
Animals ; Rats ; Drugs, Chinese Herbal/administration & dosage* ; Metabolomics ; Depression/metabolism* ; Male ; Liver/drug effects* ; Rats, Sprague-Dawley ; Antidepressive Agents/administration & dosage* ; Serotonin/blood* ; Humans ; Disease Models, Animal ; Behavior, Animal/drug effects*

Ecological cultivation is an important way for the sustainable production of traditional Chinese medicine in the context of the carbon peaking and carbon neutrality goals. Facility cultivation and simulative habitat cultivation modes have been developed and applied to develop the endangered Dendrobium huoshanense on the basis of protection. However, the differences in the greenhouse gas emissions and global warming potential of these cultivation modes remain unexplored, which limits the accurate assessment of carbon-friendly ecological cultivation modes of D. huoshanense. Greenhouse gas emission flux monitoring based on the static chamber method provides an effective way to solve this problem. Therefore, this study conducted a field experiment in the facility cultivation and simulative habitat cultivation modes at a D. huoshanense cultivation base in Dabie Mountains, Anhui Province. From April 2023 to March 2024, samples of greenhouse gases were collected every month, and the concentrations of CO_2, CH_4, and N_2O of the samples were then detected by gas chromatography. The greenhouse gas emission fluxes, cumulative emissions, and global warming potential were further calculated, and the following results were obtained.(1)The two cultivation modes of D. huoshanense showed significant differences in greenhouse gas emission fluxes, especially the CO_2 emission flux, with a pattern of facility cultivation>simulative habitat cultivation [(35.60±11.70)mg·m~(-2)·h~(-1) vs(2.10±4.59)mg·m~(-2)·h~(-1)].(2) The annual cumulative CO_2 emission flux in the case of facility cultivation was significantly higher than that of simulative habitat cultivation[(3 077.00±842.00)kg·hm~(-2) vs(221.00±332.00)kg·hm~(-2)], while no significant difference was found in annual cumulative CH_4 and N_2O emission fluxes.(3) The facility cultivation mode had a significantly higher global warming potential than the simulative habitat cultivation mode [(3 053.00±847.00)kg·hm~(-2) vs(196.00±362.00)kg·hm~(-2)]. Overall, the simulative habitat cultivation of D. huoshanense has obvious carbon-friendly characteristics compared with facility cultivation, which is in line with the concept of ecological cultivation of medicinal plants. This study is of great reference significance for the implementation and promotion of the ecological cultivation mode of D. huoshanense under carbon peaking and carbon neutrality goals.
Dendrobium/chemistry* ; Greenhouse Gases/metabolism* ; Carbon/analysis* ; Ecosystem ; Carbon Dioxide/metabolism* ; China ; Global Warming