ObjectiveTo investigate the effects and underlying mechanisms of Shenqi Wenfei prescription （SQWF） on chronic obstructive pulmonary disease （COPD）. MethodsA rat model of COPD with lung Qi deficiency was established using lipopolysaccharide （LPS） combined with cigarette smoke. Forty-eight SD rats were randomly divided into a blank group， a model group， low-， medium-， and high-dose SQWF groups （2.835， 5.67， 11.34 g·kg^-1）， and a Yupingfeng group （1.35 g·kg^-1）. Drug administration began on day 29 after modeling and continued for 2 weeks. The general condition of the rats was observed， and the lung function in each group was assessed. Hematoxylin-eosin （HE） staining was used to observe pathological changes in lung tissue. The proportion of inflammatory cells in bronchoalveolar lavage fluid （BALF） was measured. Apoptosis in lung tissue was examined by terminal deoxynucleotidyl transferase-mediated dUTP nick end-labeling （TUNEL） staining. The release level of lactate dehydrogenase （LDH） in BALF was detected by a microplate assay. Reactive oxygen species （ROS） levels in lung tissue were detected using fluorescent probes. The levels of malondialdehyde （MDA）， total superoxide dismutase （SOD）， and reduced glutathione （GSH） in BALF were measured by biochemical methods. Ultrastructural changes in lung cells were observed via transmission electron microscopy. Double immunofluorescence staining was performed to detect the expression of thioredoxin-interacting protein （TXNIP） and nucleotide-binding oligomerization domain-like receptor protein 3 （NLRP3） in lung tissue. Western blot analysis was used to detect the protein expression of TXNIP， NLRP3， apoptosis-associated speck-like protein containing a CARD （ASC）， cysteinyl aspartate-specific protease-1 （Caspase-1）， Caspase-1 p20， gasdermin D （GSDMD）， GSDMD N-terminal active fragment （GSDMD-N）， interleukin-1β （IL-1β）， and IL-18 in lung tissue. Serum IL-1β and IL-18 levels were measured by ELISA. ResultsCompared with the blank group， the model group showed lassitude， fatigue， tachypnea， and audible phlegm sounds， and lung function significantly declined （P0.01）. Pulmonary emphysema and inflammatory cell infiltration were obvious. The level of inflammatory cells in BALF increased significantly （P0.05）. The number of TUNEL-positive cells increased （P0.01）. Levels of LDH， ROS， and MDA in BALF increased significantly （P0.01）， while GSH and SOD activities decreased significantly （P0.01）. Lung tissue cells showed irregular morphology， swollen mitochondria， disrupted cell membranes， and abundant vesicles， i.e.， pyroptotic bodies. Protein levels of TXNIP， NLRP3， ASC， Caspase-1， Caspase-1 p20， GSDMD， GSDMD-N， IL-1β， and IL-18 in lung tissue were significantly elevated （P0.01）， and serum IL-1β and IL-18 levels also increased significantly （P0.01）. Compared with the model group， each medication group showed alleviation of qi deficiency symptoms and improved lung function （P0.01）. Pulmonary emphysema and inflammatory cell infiltration were reduced. Inflammatory cell levels decreased （P0.05）. The number of TUNEL-positive cells decreased significantly （P0.01）. Levels of LDH， ROS， and MDA decreased significantly （P0.05）， while GSH and SOD activities significantly increased （P0.01）. Morphological and structural damage in lung tissue was improved to varying degrees. Protein levels of TXNIP， NLRP3， ASC， Caspase-1， Caspase-1 p20， GSDMD， GSDMD-N， IL-1β， and IL-18 in lung tissue significantly decreased （P0.01）， and serum IL-1β and IL-18 levels also decreased significantly （P0.05）. ConclusionSQWF can improve lung function and alleviate inflammatory responses in COPD rats. Its mechanism may be related to regulating the ROS/TXNIP/NLRP3 pathway and inhibiting pyroptosis.

ObjectiveTo investigate the effects and underlying mechanisms of Shenqi Wenfei prescription （SQWF） on chronic obstructive pulmonary disease （COPD）. MethodsA rat model of COPD with lung Qi deficiency was established using lipopolysaccharide （LPS） combined with cigarette smoke. Forty-eight SD rats were randomly divided into a blank group， a model group， low-， medium-， and high-dose SQWF groups （2.835， 5.67， 11.34 g·kg^-1）， and a Yupingfeng group （1.35 g·kg^-1）. Drug administration began on day 29 after modeling and continued for 2 weeks. The general condition of the rats was observed， and the lung function in each group was assessed. Hematoxylin-eosin （HE） staining was used to observe pathological changes in lung tissue. The proportion of inflammatory cells in bronchoalveolar lavage fluid （BALF） was measured. Apoptosis in lung tissue was examined by terminal deoxynucleotidyl transferase-mediated dUTP nick end-labeling （TUNEL） staining. The release level of lactate dehydrogenase （LDH） in BALF was detected by a microplate assay. Reactive oxygen species （ROS） levels in lung tissue were detected using fluorescent probes. The levels of malondialdehyde （MDA）， total superoxide dismutase （SOD）， and reduced glutathione （GSH） in BALF were measured by biochemical methods. Ultrastructural changes in lung cells were observed via transmission electron microscopy. Double immunofluorescence staining was performed to detect the expression of thioredoxin-interacting protein （TXNIP） and nucleotide-binding oligomerization domain-like receptor protein 3 （NLRP3） in lung tissue. Western blot analysis was used to detect the protein expression of TXNIP， NLRP3， apoptosis-associated speck-like protein containing a CARD （ASC）， cysteinyl aspartate-specific protease-1 （Caspase-1）， Caspase-1 p20， gasdermin D （GSDMD）， GSDMD N-terminal active fragment （GSDMD-N）， interleukin-1β （IL-1β）， and IL-18 in lung tissue. Serum IL-1β and IL-18 levels were measured by ELISA. ResultsCompared with the blank group， the model group showed lassitude， fatigue， tachypnea， and audible phlegm sounds， and lung function significantly declined （P0.01）. Pulmonary emphysema and inflammatory cell infiltration were obvious. The level of inflammatory cells in BALF increased significantly （P0.05）. The number of TUNEL-positive cells increased （P0.01）. Levels of LDH， ROS， and MDA in BALF increased significantly （P0.01）， while GSH and SOD activities decreased significantly （P0.01）. Lung tissue cells showed irregular morphology， swollen mitochondria， disrupted cell membranes， and abundant vesicles， i.e.， pyroptotic bodies. Protein levels of TXNIP， NLRP3， ASC， Caspase-1， Caspase-1 p20， GSDMD， GSDMD-N， IL-1β， and IL-18 in lung tissue were significantly elevated （P0.01）， and serum IL-1β and IL-18 levels also increased significantly （P0.01）. Compared with the model group， each medication group showed alleviation of qi deficiency symptoms and improved lung function （P0.01）. Pulmonary emphysema and inflammatory cell infiltration were reduced. Inflammatory cell levels decreased （P0.05）. The number of TUNEL-positive cells decreased significantly （P0.01）. Levels of LDH， ROS， and MDA decreased significantly （P0.05）， while GSH and SOD activities significantly increased （P0.01）. Morphological and structural damage in lung tissue was improved to varying degrees. Protein levels of TXNIP， NLRP3， ASC， Caspase-1， Caspase-1 p20， GSDMD， GSDMD-N， IL-1β， and IL-18 in lung tissue significantly decreased （P0.01）， and serum IL-1β and IL-18 levels also decreased significantly （P0.05）. ConclusionSQWF can improve lung function and alleviate inflammatory responses in COPD rats. Its mechanism may be related to regulating the ROS/TXNIP/NLRP3 pathway and inhibiting pyroptosis.

ObjectiveGastric hemorrhage is one of the most common and life-threatening emergencies of the upper digestive tract. Early identification and continuous monitoring are essential for reducing rebleeding rates and mortality, particularly within the critical early hours after onset. Although endoscopy and radiological imaging can accurately localize bleeding sites, these approaches are invasive, resource-intensive, and unsuitable for continuous bedside monitoring. Electrical impedance tomography (EIT), as a noninvasive and radiation-free functional imaging technique, offers real-time visualization of conductivity distribution and has the potential for detecting intragastric bleeding based on the electrical contrast between blood and surrounding gastric tissues. In this study, a three-dimensional gastric EIT (3D-gEIT) framework is proposed to achieve noninvasive, real-time, and dynamic monitoring of gastric hemorrhage, with emphasis on spatial localization and quantitative volume assessment. MethodsA three-dimensional upper-abdominal simulation model incorporating the stomach, gastric wall, gastric contents, and surrounding tissues was established. Three electrode configurations, namely the dual layer ring, the four layer staggered ring, and the opposed dual plane array, were designed and systematically compared to evaluate their influence on depth sensitivity and spatial resolution. Based on the Tikhonov-Noser hybrid regularization scheme, a region-clustering constraint was introduced to develop the TK-Noser-RCC algorithm. This approach aggregates spatially adjacent elements with similar conductivity variations, thereby enhancing structural continuity and suppressing isolated noise artifacts. To validate the proposed framework, an upper-abdominal physical phantom was constructed using agar to simulate background tissue conductivity. Hemispherical high-conductivity inclusions with volumes ranging from 10 ml to 50 ml were attached to the inner gastric wall to mimic localized bleeding under different gastric filling states. Boundary voltages were acquired under a 120 kHz excitation current and reconstructed using the TK-Noser-RCC algorithm. Furthermore, an in vivo animal experiment was performed using a porcine model with adult-scale abdominal dimensions. A total of 100 ml of autologous blood was injected incrementally into the stomach to simulate progressive gastric hemorrhage, and time-difference EIT reconstruction was conducted at each injection stage to assess the dynamic system response under physiological conditions. ResultsSimulation results demonstrated that the opposed dual-plane electrode array achieved superior depth sensitivity distribution and spatial resolution. For a 40 ml hemorrhage model, the average ICC and SSIM improved by 55.9% and 38.8% compared with the dual-layer ring configuration, and by 64.0% and 39.5% compared with the four-layer staggered configuration. The proposed region-clustering constraint significantly enhanced reconstruction stability. Under added Gaussian noise of 40 dB and 30 dB, ICC values remained approximately 0.85, indicating effective artifact suppression and preservation of boundary integrity. In physical phantom experiments, reconstructed hemorrhage volumes increased approximately linearly with the preset hemispherical volumes, and the reconstructed high-conductivity regions closely matched the actual bleeding locations. Both empty-stomach and full-stomach conditions were evaluated, demonstrating that the opposed dual-plane configuration maintained stable imaging performance across varying gastric contents. In the animal experiment, reconstructed low-impedance regions expanded progressively with increasing injected blood volume. The spatial localization of the hemorrhage remained stable throughout the procedure, and no significant artifacts were observed. Quantitative analysis showed that reconstructed volume and average conductivity variation exhibited an approximately linear growth trend with injected blood volume, confirming the sensitivity of the system to dynamic intragastric conductivity changes. ConclusionThe proposed 3D-gEIT framework enables quantitative reconstruction of gastric hemorrhage volume and spatial distribution with improved depth sensitivity, structural continuity, and noise robustness compared with conventional EIT approaches. By integrating optimized electrode configuration and a region-clustering-constrained reconstruction algorithm, the system provides stable dynamic monitoring under both controlled phantom conditions and in vivo physiological environments. This method offers a noninvasive, real-time, and low-cost imaging strategy for early diagnosis, postoperative monitoring, and bedside surveillance of gastric bleeding.

In recent years， repetitive transcranial magnetic stimulation （rTMS） has garnered significant attention as a therapeutic approach for sleep disorders in the elderly. However， the prevailing rTMS protocols are predominantly developed based on normative neurophysiological data derived from young adults and fail to incorporate individualized parameters tailored to the brain characteristics of the elderly. To address this gap， the consensus development group synthesized the latest evidence from 2010 to 2025 and established a standardized rTMS protocol specifically for elderly patients with sleep disorders. Adhering to the Appraisal of Guidelines for Research and Evaluation II （AGREE II） framework， systematically screened randomized controlled trials （RCTs） and systematic reviews regarding rTMS in the treatment of sleep disorders across various conditions. Meanwhile， the Grading of Recommendations Assessment， Development and Evaluation （GRADE） system was employed to rigorously grade the quality of evidence and the strength of recommendations. This consensus guideline delineates precise rTMS protocols for the management of sleep disorders in the elderly， highlights the adjustment of stimulation intensity according to scalp-cortex distance recommends either MRI‑guided neuronavigation or the Beam F3/F4 heuristic approach for accurate target localization， thereby providing precise rTMS intervention protocol for sleep disorders in the elderly， aiming to enhance clinical efficacy while ensuring treatment safety. ［Funded by National Key Research and Development Program （number， 2023YFC3603200）； General Program of Shenzhen Science and Technology Innovation Commission （number， JCYJ20240813112859008， JCYJ20240813112900002）； Youth Program of Shenzhen Kangning Hospital （number， KN2023A004）； www.guidelines-registry.cn number， PREPARE-2026CN530］

Objective To explore the prevalence of depressive symptoms in postoperative patients with ovarian cancer and to analyze its influencing factors from multiple dimensions, including clinical characteristics, psychological factors, and laboratory indicators. Methods A cross-sectional study was conducted, which enrolled 235 postoperative patients with ovarian cancer. Depressive status was assessed using the patient health questionnaire, and the demographic, pathological, and medical record data of the patients were collected using the generalized anxiety disorder scale, Pittsburgh sleep quality index, European organization for research and treatment of cancer quality of life questionnaire core 30, and ECOG performance status score. Peripheral blood tumor marker (CA125), routine blood test, lymphocyte subsets, and serum cytokine levels were measured. Univariate and multivariate binary logistic regression analysis were used for statistical analysis. Results The prevalence of depression in postoperative patients with ovarian cancer was 39.15% (92/235). Univariate analysis showed that ECOG score ≥ 2 points, pain, anxiety, poor sleep quality, low quality of life, low life satisfaction, tumor recurrence, six or more cycles of chemotherapy, as well as higher levels of CA125, NLR, and NAR, and lower hemoglobin levels were significantly associated with depression (all P<0.05). Multivariate binary Logistic regression analysis showed that anxiety (OR=1.975, 95%CI: 1.231-3.170), sleep efficiency (OR=4.181, 95%CI: 1.211-14.43), sleep latency (OR=34.806, 95%CI: 4.258-284.542), ECOG performance status score, cognitive function (OR=0.918, 95%CI: 0.868-0.97), and life satisfaction were independent risk factors for depression (all P<0.05). Laboratory indicators were not independent influencing factors in the multivariate Logistic regression model. Conclusion Depression in postoperative patients with ovarian cancer is influenced by physiological, psychological, and social factors. Clinical management should focus on patients with anxiety, sleep disorders, poor physical condition, and low life satisfaction, and a comprehensive prevention and treatment strategy centered on psychological intervention and taking into account symptom management and social support should be implemented.

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.

The mental health management of laboratory animals is a critical factor in ensuring the reliability of scientific research data. However, due to the subtle nature of mental state alterations and the limitations of current assessment methods, the mental health of laboratory animals is often overlooked by researchers. Therefore, there is an urgent need to explore a new, objective, simple, and practical method for evaluating mental health. Stress, as a primary factor inducing alterations in the mental state of animals, can influence experimental results across multiple research fields through the neuroendocrine-immune network. This paper first elucidates the necessity of mental health management in laboratory animals from three perspectives: factors contributing to stress, neural mechanisms of stress, and research areas affected by stress. It highlights that excluding animals with abnormal mental states before experiments can enhance the efficiency and reproducibility of biomedical studies. Second, this paper briefly summarizes existing methods for assessing the health of laboratory animals, pointing out that approaches such as behavioral tests and metabolomics have many limitations in evaluating stress responses. Existing methods struggle to meet the demand for simple, objective, and non-invasive assessment methods in animal management. Therefore, this paper focuses on hair, a biological sample with the advantages of cumulative information and non-invasive collection, and systematically describes the theoretical basis and technological advances in using hair characteristics as indicators of stress responses from three perspectives: hair traits, the levels of substances in hair, and artificial intelligence (AI). It proposes and supports an innovative technical pathway that combines hair traits with AI-based image analysis, with the aim of offering an improved solution for non-invasive and objective stress assessment, while providing theoretical support for improving the health management system of laboratory animals.

Objective: To analyze the epidemiological characteristics, associated factors, and vaccine effectiveness of two pertussis cluster outbreaks in two primary schools in Yangzhong City in 2025, so as to provide evidence for school based epidemic prevention and control. Methods: From August 26 to 30, 2025, a pertussis questionnaire was administered to the epidemic affected classes of two primary schools (school A and school B) in Yangzhong City. A descriptive epidemiological retrospective analysis was used to characterize the pertussis cluster outbreaks in Yangzhong City from March to July 2025. A 1∶5 matched case control study (79 cases, 395 controls) was performed. Multivariate Logistic regression was used to identify associated factors, and the clinical symptom incidence rates, types of pertussis containing vaccines, and timeliness of vaccination were compared between groups using Fisher s exact test. Results: From March to July 2025, a total of 79 pertussis cases were reported in the two schools, with attack rates of 1.33% and 1.01%, respectively. Cases were predominantly aged 7-8 years (85.37% in school A, 73.68% in school B), and the main clinical manifestation was productive cough (63.29%). The pneumonia incidence rate among hospitalized cases ( 57.14 %) was higher than that among nonhospitalized cases(4.17%)(Fisher s exact test, P <0.01). The interval from the last dose to onset was concentrated at 6 to <7 years (44 cases). Logistic regression showed that children exposed to secondhand smoke in daily life ( OR = 3.86 ), those whose desk mates or front/back desk mates took leave due to cough ( OR =4.67), and those whose dining table mates or front/back table mates took leave due to cough ( OR =3.67) had significantly higher risks of pertussis (all P <0.05). A high proportion of both the case group and the control group received the acellular DTaP vaccine (97.47% and 96.96%, respectively),while a low proportion received the pentavalent vaccine (1.27% and 3.04%, respectively). Additionally, one case received only three doses of the acellular DTaP vaccine.The difference in vaccine type distribution between the two groups was not statistically significant (Fisher s exact test, P =0.31). Conclusions The outbreaks represent breakthrough infections under high vaccine coverage. Close contact and secondhand smoke exposure are the main risk factors. A booster immunization strategy with diphtheria-tetanus-pertussis vaccine should be implemented for school aged children.

The paper introduces Professor LIU Xing's clinical experience and characteristics of integrative acupuncture and medication in treatment of primary trigeminal neuralgia (PTN). It is believed that the essential pathogenesis of PTN is pathogenic wind, and qi and blood obstruction results from invasion of pathogenic wind. Hence, dispelling wind is the key principle of treatment. Palpation is done at first in the neck, face and buccal mucosal region to detect the masses in treatment. Acupotomy is operated at the masses distributed at Shangguan (GB3), Xiaguan (ST7) and the white line of buccal mucosa, so as to release masses. Additionally, five-wind points (Fengfu [GV16], bilateral Fengchi [GB20], Yifeng [TE17], Bingfeng [SI12] and Fengmen [BL12]), three-nape points (bilateral Naokong [GB19], Tianzhu [BL10] and Jianjing [GB21]) and three-governor-vessel points (Baihui [GV20], Zhiyang [GV9] and Yintang [GV24⁺]) are selected to dispel wind and stop pain. Besides, herbal decoction (wu feng tang) and blood-letting at ear apex are administered in combination. The integration of acupuncture and medication obtains a holistic effect on PTN by dispelling wind pathogen, and promoting qi and blood circulation.
Humans ; Trigeminal Neuralgia/drug therapy* ; Acupuncture Therapy ; Acupuncture Points ; Female ; Male ; Middle Aged ; Drugs, Chinese Herbal/administration & dosage* ; Combined Modality Therapy ; Adult ; Aged

Accurate timing of myelination is crucial for the proper functioning of the central nervous system. Here, we identified a de novo heterozygous mutation in TMEM63A (c.1894G>A; p. Ala632Thr) in a 7-year-old boy exhibiting hypomyelination. A Ca²⁺ influx assay suggested that this is a loss-of-function mutation. To explore how TMEM63A deficiency causes hypomyelination, we generated Tmem63a knockout mice. Genetic deletion of TMEM63A resulted in hypomyelination at postnatal day 14 (P14) arising from impaired differentiation of oligodendrocyte precursor cells (OPCs). Notably, the myelin dysplasia was transient, returning to normal levels by P28. Primary cultures of Tmem63a^-/- OPCs presented delayed differentiation. Lentivirus-based expression of TMEM63A but not TMEM63A_A632T rescued the differentiation of Tmem63a^-/- OPCs in vitro and myelination in Tmem63a^-/- mice. These data thus support the conclusion that the mutation in TMEM63A is the pathogenesis of the hypomyelination in the patient. Our study further demonstrated that TMEM63A-mediated Ca²⁺ influx plays critical roles in the early development of myelin and oligodendrocyte differentiation.
Animals ; Cell Differentiation/physiology* ; Oligodendroglia/metabolism* ; Mice, Knockout ; Mice ; Male ; Myelin Sheath/metabolism* ; Humans ; Child ; Cells, Cultured ; Oligodendrocyte Precursor Cells/metabolism*