Objective To introduce the causes of accidents and the diagnosis and treatment of two patients with radiation-induced skin injury admitted to our hospital in 2023, and to provide a reference for the clinical treatment of subsequent radiation-induced skin injury. Methods The clinical treatment process of two patients with acute skin injury caused by external radiation exposure were summarized and analyzed. Results The exposure history of the two patients was reconstructed, the flaw detection scenario was simulated, the biological dose and hand skin exposure dose were estimated, and the infrared thermal imaging device was used for dynamic monitoring. A comprehensive analysis was conducted based on clinical manifestations and other data. The diagnosis of “Xie” was excessive exposure combined with acute radiation-induced skin injury on both hands (Grade IV for the right hand palm, index finger, and middle finger and Grade II for the left hand little finger). The diagnosis of “Hao” was acute radiation-induced skin injury on both hands (Grade I). The two patients received different clinical treatment measures: “Xie” was treated with both local and systemic therapies, while “Hao” was mainly treated with systemic therapy. Conclusion After systematic and effective treatment, the radiation-induced skin injuries healed in both patients.

To summarize the clinical experience of Professor LIU Jinmin in treatment for epilepsy. It is believed that main pathogenesis of epilepsy is yangming failure to close and vital activity loss control， so a therapeutic approach focused on restoring the closure of yangming and regaining vital activity was proposed for the treatment of epilepsy. For excess syndrome， the treatment focuses on draining excess and descending qi， promoting purgation and restoring spirit. When yangming dryness-heat predominates， the approach involves unblock the bowels and regulating the spirit， descending qi and reducing fire， with modified Chengqi Decoction （承气汤） as prescription； when yangming phlegm-fire predominates， the treatment focuses on clearing heat and resolving phlegm， calming mind and suppressing fright， with modified Qingxin Wendan Decoction （清心温胆汤） as prescription； when yangming blood stasis predominates， the approach involves breaking up blood stasis and promoting purgation， eliminating stasis and awakening the mind， with Taoren Chengqi Decoction （桃核承气汤） as prescription. For deficiency syndrome， the treatment emphasizes tonifying deficiency and raising qi， strengthening the stomach and nourishing the spirit. When center qi deficiency and sinking of clear qi of the nutrients from food， the approach involves replenishing and uplifting qi while nourishing vital activity， with modified Liujunzi Decoction （六君子汤） as prescription； when yin deficiency and fluid consumption， the treatment focuses on nourishing stomach and tonifying yin， promoting fluid production and calming the spirit， with modified Maimendong Decoction （麦门冬汤） combined with Yiwei Decoction （益胃汤） as prescriptions. In clinical situations of deficiency-excess complex， it is essential to distinguish the primary condition from the secondary， applying both supplementing and draining methods flexibly to achieve optimal treatment.

Long-term spaceflight exposes astronauts to multiple extreme environmental factors, such as cosmic radiation, microgravity, social isolation, and circadian rhythm disruption, that markedly increase the risk of depressive symptoms, posing a direct threat to mental health and mission safety. However, the underlying biological mechanisms remain complex and incompletely understood. The potential mechanisms of spaceflight-induced depressive symptoms involve multiple domains, including alterations in brain structure and function, dysregulation of neurotransmitters and neurotrophic factors, oxidative stress, neuroinflammation, neuroendocrine system imbalance, and gut microbiota disturbances. Collectively, these changes may constitute the biological foundation of depressive in astronauts during spaceflight. Space-related stressors may increase the risk of depressive symptoms through several pathways: impairing hippocampal neuroplasticity, suppressing dopaminergic and serotonergic system function, reducing neurotrophic factor expression, triggering oxidative stress and inflammatory responses, activating the hypothalamic-pituitary-adrenal axis, and disrupting gut microbiota homeostasis. Future research should integrate advanced technologies such as brain-computer interfaces to develop individualized monitoring and intervention strategies, enabling real-time detection and effective prevention of depressive symptoms to safeguard astronauts' psychological well-being and mission safety.
Space Flight ; Humans ; Astronauts/psychology* ; Depression/physiopathology* ; Gastrointestinal Microbiome ; Weightlessness/adverse effects* ; Oxidative Stress ; Brain/physiopathology* ; Hypothalamo-Hypophyseal System ; Neuronal Plasticity ; Pituitary-Adrenal System

During long-duration manned space missions, the complex and extreme space environment exerts significant impacts on astronauts' physiological, psychological, and cognitive functions, thereby posing direct risks to mission safety and operational efficiency. As a key bridge between the brain and external devices, brain-computer interface (BCI) technology enables precise acquisition and interpretation of neural signals, offering a novel paradigm for human-machine collaboration in manned spaceflight. Non-invasive BCI technology shows broad application prospects across astronaut selection, mission training, in-orbit task execution, and post-mission rehabilitation. During mission preparation, multimodal signal assessment and neurofeedback training based on BCI can effectively enhance cognitive performance and psychological resilience. During mission execution, BCI can provide real-time monitoring of physiological and psychological states and enable intention-based device control, thereby improving operational efficiency and safety. In the post-mission rehabilitation phase, non-invasive BCI combined with neuromodulation may improve emotional and cognitive functions, support motor and cognitive recovery, and contribute to long-term health management. However, the application of BCI in space still faces challenges, including insufficient signal robustness, limited system adaptability, and suboptimal data processing efficiency. Looking forward, integrating multimodal physiological sensors with deep learning algorithms to achieve accurate monitoring and individualized intervention, and combining BCI with virtual reality and robotics to develop intelligent human-machine collaboration models, will provide more efficient support for space missions.
Brain-Computer Interfaces ; Humans ; Space Flight ; Astronauts/psychology* ; Neurofeedback ; Cognition ; Electroencephalography ; Man-Machine Systems

Objective:To explore the clinical, imaging, and pathological features of glottic squamous cell carcinoma of the larynx and their relationship with prognosis. Methods:A retrospective analysis was conducted on the clinical, imaging, and pathological data of 130 patients with glottic squamous cell carcinoma of the larynx who were treated at the First People's Hospital of Yinchuan and the General Hospital of Ningxia Medical University from January 2018 to March 2023. Imaging examinations （CT and MRI） were used to evaluate the lesion boundary clarity, density, enhancement nature, and enhancement degree. Postoperative pathological examination was used to determine the pathological nature, immunohistochemistry, etc. Statistical methods such as χ² test, Spearman correlation analysis, multivariate logistic regression analysis, and Kaplan-Meier method were used to analyze the data. Results:Among the 130 patients, 127 were male and 3 were female, with an average age of （61.92±9.595） years. There was a correlation between clinical, imaging, and pathological features. Multivariate analysis showed that heterogeneous MRI density （OR=12.414;P=0.019） and squamous cell carcinoma as a subtype were correlated. The initial symptom of non-hoarseness （HR=6.045;P=0.010） and unclear MRI boundary （HR=12.559; P=0.029） were independent risk factors for poor prognosis in patients with glottic squamous cell carcinoma of the larynx. Conclusion:There is a correlation between the clinical, imaging, and pathological features of patients with glottic squamous cell carcinoma of the larynx, and they can affect prognosis. The initial symptom of non-hoarseness and unclear MRI boundary of the tumor are independent risk factors for poor prognosis.
Humans ; Laryngeal Neoplasms/diagnosis* ; Prognosis ; Male ; Female ; Retrospective Studies ; Middle Aged ; Carcinoma, Squamous Cell/diagnosis* ; Magnetic Resonance Imaging ; Glottis/pathology* ; Tomography, X-Ray Computed ; Aged

Natural polyphenols are a group of components widely found in traditional Chinese medicines and have been demonstrated to delay or prevent the development of aging and age-related diseases in recent years. As far as we know, the studies of natural polyphenols in aging and aging-related diseases have never been extensively reviewed. In the present paper, we reviewed recent advances of natural polyphenols in aging and common age-related diseases and the current technological methods to improve the bioavailability of natural polyphenols. The results showed that natural polyphenols have the potential to prevent or treat aging and common age-related diseases through multiple mechanisms. Nanotechnology, structural modifications, and matrix processing could provide strong technical support for the development of natural polyphenols to prevent or treat aging and age-related diseases. In conclusion, natural polyphenols have important potential in the prevention and treatment of aging and age-related diseases.

OBJECTIVE: Varied acupoint selections represent a potential cause of the uncertainty surrounding the efficacy of acupuncture for knee osteoarthritis (OA). Skin temperature, a guiding factor for acupoint selection, may help to address this issue. This study explored thermal sensitization of acupoints used for the treatment of knee OA. METHODS: This cross-sectional case-control study enrolled cases aged 45-75 years with symptomatic knee OA and age- and gender-matched non-knee OA controls in a 1:1 ratio. All participants underwent infrared thermographic imaging. The primary outcome was the relative skin temperature of acupoint (STA), and the secondary outcome was the absolute STA of 11 acupoints. The Z test was used to compare the relative and absolute STAs between the groups. Principal component analysis was used to extract the common factors (CFs, acupoint cluster) in the STAs. A general linear model was used to identify factors affecting the STA in the knee OA cases. For the group comparisons of relative STA, P < 0.0045 (adjusted for 11 acupoints through Bonferroni correction) was considered to indicate statistical significance. For other analyses, P < 0.05 was used as the threshold for statistical significance. RESULTS: The analysis included 308 participants, consisting of 151 cases (mean age: [64.58 ± 6.67] years; male: 25.83%; mean body mass index: [25.70 ± 3.16] kg/m²) and 157 controls (mean age: [63.37 ± 5.96] years; male: 26.11%; mean body mass index: [24.47 ± 2.84] kg/m²). The relative STAs of ST34 (P = 0.0001), EX-LE2 (P < 0.0001), EX-LE5 (P = 0.0006), SP10 (P < 0.0001), BL40 (P = 0.0012) and GB39 (P = 0.0037) were higher in the knee OA group. No difference was found in the STAs of ST35, ST36, SP9, GB33 and GB34. Four CFs were identified for relative STA in both groups. The acupoints within each CF were consistent between the groups. The mean values of the relative STAs across each CF were higher in the knee OA group. In the knee OA cases, no factors were observed to affect the relative STA, while age and gender were found to affect the absolute STA. CONCLUSION Among patients with knee OA, thermal sensitization occurs in the acupoints of the lower extremity, exhibiting localized and regional thermal consistencies. The thermally sensitized acupoints that we identified in this study, ST34, SP10, EX-LE2, EX-LE5, GB39 and BL40, may be good choices for the acupuncture treatment of knee OA. Please cite this article as: Tu JF, Wang XZ, Yan SY, Wang YR, Yang JW, Shi GX, Zhang WZ, Jing LN, Yang LS, Liu DH, Wang LQ, Mi BH. Thermal sensitization of acupoints in patients with knee osteoarthritis: A cross-sectional case-control study. J Integr Med. 2025; 23(3): 289-296.
Humans ; Osteoarthritis, Knee/physiopathology* ; Male ; Cross-Sectional Studies ; Middle Aged ; Female ; Acupuncture Points ; Case-Control Studies ; Aged ; Skin Temperature ; Acupuncture Therapy

Objective:To explore the effectiveness of a hysteroscopic endometrial lesion diagnosis model de-veloped based on deep learning(DL)algorithm combined with gradient-weighted class activation mapping(Grad-CAM)visualization technology.Methods:303 hysteroscopy videos(4781 images)of 291 patients who un-derwent hysteroscopy examination in the Department of Gynecology,Renmin Hospital of Wuhan University from June 1,2021 to December 31,2022 were selected.The dataset was divided into a training set(3703 images)and a test set(1078 images)by weight sampling method.After the training set was used for model learning and train-ing,two model architectures,residual neural network(ResNet18)and efficient neural network(EfficientNet-B0),were selected to verify the model in the test set by five-class and two-class classification tasks,respectively.Tak-ing histopathology as the gold standard,the diagnostic efficacy was evaluated to select the optimal model,and the Grad-CAM layer was embedded in the optimal model to output hysteroscopy images of Grad-CAM.Results:①In the five-class classification tasks,the accuracy of EfficientNet-B0 model(93.23％)was higher than that of Res-Net18 model(84.23％);the area under the curve(AUC)of EfficientNet-B0 model in the diagnosis of five disea-ses,including atypical endometrial hyperplasia,endometrial polyps,endometrial cancer,endometrial atypical hy-perplasia,and submucous myoma,was slightly higher than that of ResNet18 model,and the AUC of both models was almost above 0.980.②In the binary classification task of accuracy and the evaluation of specificity,the two models were similar,both above 93.00％,and the sensitivity of EfficientNet-B0 model(91.14％)was significantly better than that of ResNet18 model(77.22％).③EfficientNet-B0 model combined with Grad-CAM algorithm could identify the abnormal areas in the image.After biopsy and pathological examination,it was confirmed that about 95％of the marked areas in the model's output heatmap were lesion areas.Conclusions:The hysteroscopy di-agnostic model developed by EfficientNet-B0 model combined with Grad-CAM has high diagnostic accuracy,sen-sitivity,and specificity,and has application value in the diagnosis of endometrial lesions.

Objective:To explore the effectiveness of a hysteroscopic endometrial lesion diagnosis model de-veloped based on deep learning(DL)algorithm combined with gradient-weighted class activation mapping(Grad-CAM)visualization technology.Methods:303 hysteroscopy videos(4781 images)of 291 patients who un-derwent hysteroscopy examination in the Department of Gynecology,Renmin Hospital of Wuhan University from June 1,2021 to December 31,2022 were selected.The dataset was divided into a training set(3703 images)and a test set(1078 images)by weight sampling method.After the training set was used for model learning and train-ing,two model architectures,residual neural network(ResNet18)and efficient neural network(EfficientNet-B0),were selected to verify the model in the test set by five-class and two-class classification tasks,respectively.Tak-ing histopathology as the gold standard,the diagnostic efficacy was evaluated to select the optimal model,and the Grad-CAM layer was embedded in the optimal model to output hysteroscopy images of Grad-CAM.Results:①In the five-class classification tasks,the accuracy of EfficientNet-B0 model(93.23％)was higher than that of Res-Net18 model(84.23％);the area under the curve(AUC)of EfficientNet-B0 model in the diagnosis of five disea-ses,including atypical endometrial hyperplasia,endometrial polyps,endometrial cancer,endometrial atypical hy-perplasia,and submucous myoma,was slightly higher than that of ResNet18 model,and the AUC of both models was almost above 0.980.②In the binary classification task of accuracy and the evaluation of specificity,the two models were similar,both above 93.00％,and the sensitivity of EfficientNet-B0 model(91.14％)was significantly better than that of ResNet18 model(77.22％).③EfficientNet-B0 model combined with Grad-CAM algorithm could identify the abnormal areas in the image.After biopsy and pathological examination,it was confirmed that about 95％of the marked areas in the model's output heatmap were lesion areas.Conclusions:The hysteroscopy di-agnostic model developed by EfficientNet-B0 model combined with Grad-CAM has high diagnostic accuracy,sen-sitivity,and specificity,and has application value in the diagnosis of endometrial lesions.

Objective:To explore the effectiveness of a hysteroscopic endometrial lesion diagnosis model de-veloped based on deep learning(DL)algorithm combined with gradient-weighted class activation mapping(Grad-CAM)visualization technology.Methods:303 hysteroscopy videos(4781 images)of 291 patients who un-derwent hysteroscopy examination in the Department of Gynecology,Renmin Hospital of Wuhan University from June 1,2021 to December 31,2022 were selected.The dataset was divided into a training set(3703 images)and a test set(1078 images)by weight sampling method.After the training set was used for model learning and train-ing,two model architectures,residual neural network(ResNet18)and efficient neural network(EfficientNet-B0),were selected to verify the model in the test set by five-class and two-class classification tasks,respectively.Tak-ing histopathology as the gold standard,the diagnostic efficacy was evaluated to select the optimal model,and the Grad-CAM layer was embedded in the optimal model to output hysteroscopy images of Grad-CAM.Results:①In the five-class classification tasks,the accuracy of EfficientNet-B0 model(93.23％)was higher than that of Res-Net18 model(84.23％);the area under the curve(AUC)of EfficientNet-B0 model in the diagnosis of five disea-ses,including atypical endometrial hyperplasia,endometrial polyps,endometrial cancer,endometrial atypical hy-perplasia,and submucous myoma,was slightly higher than that of ResNet18 model,and the AUC of both models was almost above 0.980.②In the binary classification task of accuracy and the evaluation of specificity,the two models were similar,both above 93.00％,and the sensitivity of EfficientNet-B0 model(91.14％)was significantly better than that of ResNet18 model(77.22％).③EfficientNet-B0 model combined with Grad-CAM algorithm could identify the abnormal areas in the image.After biopsy and pathological examination,it was confirmed that about 95％of the marked areas in the model's output heatmap were lesion areas.Conclusions:The hysteroscopy di-agnostic model developed by EfficientNet-B0 model combined with Grad-CAM has high diagnostic accuracy,sen-sitivity,and specificity,and has application value in the diagnosis of endometrial lesions.