Objective:To develop an artificial intelligence system using fully convolutional neural networks（FCN）to assist echocardiographers in the quantitative assessment of mitral regurgitation（MR）severity.Methods:From August 2021 to June 2024，echocardiographic images of 441 patients with MR were prospectively collected from Renmin Hospital of Wuhan University and the Central Hospital of Wuhan. After screening，a total of 269 patients（4 917 frames）were included in the study. Of these，3 644 frames（128 patients）of apical four-chamber color Doppler MR flow convergence images from Renmin Hospital of Wuhan University were selected as the training/validation set，while images from 121 patients（813 frames）were used as the internal test set. Additionally，images from 20 patients（460 frames）from the Central Hospital of Wuhan were selected as the external test set. The FCN algorithm was employed to capture features and segment the MR color region on the left atrial side，simultaneously outputting the regurgitant radius（r）for the calculation of the effective regurgitant orifice area and regurgitant volume. The severity of MR was then classified according to the 2017 guidelines of the American Society of Echocardiography. The segmentation and classification performance of the model was evaluated，and the measurement results of the AI system was compared with that of both senior and junior physicians.Results:In the internal test set，the accuracy of r identification for cases classified as Grade Ⅰ to Ⅳ was 0.48，0.81，0.86，and 0.87，respectively. In the external test set，the accuracy of r identification for cases classified as Grade Ⅰ to Ⅳ was 0.60，0.77，0.64，and 0.77，respectively. The average accuracy of MR classification in the internal and external test sets was 0.91 and 0.88，respectively.Conclusions:The FCN model is capable of segmenting the left atrial side regurgitant areas in apical four-chamber heart color Doppler images，aiding physicians in obtaining quantitative assessment parameters for MR，and assisting junior physicians in accurately assessing the severity of MR.

A tertiary public general hospital in Guangdong has innovated its inpatient bed scheduling system by integra-ting multiple models,including"Hospital-Wide Bed Pooling,"outpatient chemotherapy,day surgery,pre-admission,and pre-discharge programs.Supported by policy guidance,this initiative optimizes clinical operations,enhances patient admission struc-tures and processes,and improves bed utilization efficiency through a multi-dimensional centralized bed management approach.By rationally allocating hospital-wide bed resources and maximizing their operational effectiveness,the hospital advances high-quality development in healthcare delivery.

A tertiary public general hospital in Guangdong has innovated its inpatient bed scheduling system by integra-ting multiple models,including"Hospital-Wide Bed Pooling,"outpatient chemotherapy,day surgery,pre-admission,and pre-discharge programs.Supported by policy guidance,this initiative optimizes clinical operations,enhances patient admission struc-tures and processes,and improves bed utilization efficiency through a multi-dimensional centralized bed management approach.By rationally allocating hospital-wide bed resources and maximizing their operational effectiveness,the hospital advances high-quality development in healthcare delivery.

Objective:To develop an artificial intelligence system using fully convolutional neural networks（FCN）to assist echocardiographers in the quantitative assessment of mitral regurgitation（MR）severity.Methods:From August 2021 to June 2024，echocardiographic images of 441 patients with MR were prospectively collected from Renmin Hospital of Wuhan University and the Central Hospital of Wuhan. After screening，a total of 269 patients（4 917 frames）were included in the study. Of these，3 644 frames（128 patients）of apical four-chamber color Doppler MR flow convergence images from Renmin Hospital of Wuhan University were selected as the training/validation set，while images from 121 patients（813 frames）were used as the internal test set. Additionally，images from 20 patients（460 frames）from the Central Hospital of Wuhan were selected as the external test set. The FCN algorithm was employed to capture features and segment the MR color region on the left atrial side，simultaneously outputting the regurgitant radius（r）for the calculation of the effective regurgitant orifice area and regurgitant volume. The severity of MR was then classified according to the 2017 guidelines of the American Society of Echocardiography. The segmentation and classification performance of the model was evaluated，and the measurement results of the AI system was compared with that of both senior and junior physicians.Results:In the internal test set，the accuracy of r identification for cases classified as Grade Ⅰ to Ⅳ was 0.48，0.81，0.86，and 0.87，respectively. In the external test set，the accuracy of r identification for cases classified as Grade Ⅰ to Ⅳ was 0.60，0.77，0.64，and 0.77，respectively. The average accuracy of MR classification in the internal and external test sets was 0.91 and 0.88，respectively.Conclusions:The FCN model is capable of segmenting the left atrial side regurgitant areas in apical four-chamber heart color Doppler images，aiding physicians in obtaining quantitative assessment parameters for MR，and assisting junior physicians in accurately assessing the severity of MR.

BACKGROUND:Pulsed electromagnetic fields,as an important physical therapy,are exactly effective in the treatment of osteoarthritis,but the mechanism has not been fully clarified. OBJECTIVE:To observe the effect of pulsed electromagnetic field on the degeneration of knee joint cartilage in aged rats. METHODS:Eight 6-month-old Sprague-Dawley rats were selected as the young group and were subjected to normal diet with no treatment.Sixteen 22-month-old Sprague-Dawley rats were randomly divided into old group(n=8)and pulsed electromagnetic field group(n=8).The rats in the pulsed electromagnetic field group were subjected to a pulsed electromagnetic field intervention,once a day,5 days per week for continuous 8 weeks.The rats in the old group were given no treatment.All rats were anesthetized and executed after 8 weeks for the detection of relevant indexes. RESULTS AND CONCLUSION:Compared with the young group,serum type Ⅱ collagen C-terminal peptide level was increased in the old group(P<0.05);compared with the old group,serum type Ⅱ collagen C-terminal peptide level was decreased in the pulsed electromagnetic field group(P<0.05).Micro-CT showed that the bone volume fraction,bone mineral density,and number of bone trabeculae decreased(P<0.05)and the trabecular separation increased(P<0.05)in the tibia of rats in the aged group compared with the young group;and the bone volume fraction,bone density,and number of trabeculae increased(P<0.05)and the trabecular separation decreased(P<0.05)in the tibia of rats in the pulsed electromagnetic field group compared with the aged group.The tibial plateau Safranin O-fast green staining showed that the articular cartilage structure of rats in the aged group was disorganized,and the number of chondrocytes was obviously reduced,and the tidal line could not be distinguished.The above results were improved in the pulsed electromagnetic field group.RT-qPCR and western blot assay showed that the mRNA and protein expression levels of matrix metalloproteinase 1,matrix metalloproteinase 13,P53 and P21 in the articular cartilage and subchondral bone of rats were elevated in the aged group compared with the young group(P<0.05)and decreased in the pulsed electromagnetic field group compared with the old group(P<0.05).To conclude,pulsed electromagnetic fields may improve osteoarthritis in aged rats by inhibiting chondrocyte senescence,alleviating articular cartilage degradation and inhibiting subchondral bone osteoporosis through suppressing the expression of P53/P21.

Evolution and natural selection have endowed animal venoms, including scorpion venoms, with a wide range of pharmacological properties. Consequently, scorpions, their venoms, and/or their body parts have been used since time immemorial in traditional medicines, especially in Africa and Asia. With respect to their pharmacological potential, bioactive peptides from scorpion venoms have become an important source of scientific research. With the rapid increase in the characterization of various components from scorpion venoms, a large number of peptides are identified with an aim of combating a myriad of emerging global health problems. Moreover, some scorpion venom-derived peptides have been established as potential scaffolds helpful for drug development. In this review, we summarize the promising scorpion venoms-derived peptides as drug candidates. Accordingly, we highlight the data and knowledge needed for continuous characterization and development of additional natural peptides from scorpion venoms, as potential drugs that can treat related diseases.
Animals ; Scorpion Venoms/pharmacology* ; Peptides/pharmacology* ; Scorpions ; Drug Development ; Medicine, Traditional

Objective     To evaluate the effect of mediastinal drainage tube placed in the left thoracic cavity after partial resection of the mediastinum pleura in robot-assisted McKeown esophagectomy for esophageal carcinoma, and to compare it with the traditional method of mediastinal drainage tube placed in mediastinum. Methods    We retrospectively analyzed clinical data of 96 patients who underwent robot-assisted McKeown esophagectomy for esophageal carcinoma by the surgeons in the same medical group in our department between July 2018 and March 2021. There were 78 males and 18 females, aged 52-79 years. Left mediastinum pleura around the carcinoma during operation was resected in all patients. Patients were divided into two groups according to the method of mediastinal drainage tube placement: a control group (placed in mediastinum) and an observation group (placed through the mediastinal pleura into the left thoracic cavity with several side ports distributed in the mediastinum). The incidence of left thoracentesis or catheterization after surgery, anastomotic fistula and anastomotic healing time, other complications such as pneumonia and postoperative pain score were also compared between the two groups. Results     There was no statistical difference in baseline data or surgical parameters between the two groups. The percentage of patients in the observation group who needed re-thoracentesis or re-catheterization postoperatively due to massive pleural effusion in the left thoracic cavity was significantly lower than that in the control group (5.6% vs. 21.4%, P=0.020). The incidence of anastomotic leakage (3.7%vs. 7.1%, P=0.651) and the healing time of anastomosis (18.56±4.27 d vs. 24.33±5.48 d, P=0.304) were not statistically different between the two groups, and there was no statistical difference in other complications such as pulmonary infection. Moreover, the postoperative pain score was also similar between the two groups. Conclusion     For patients whose mediastinal pleura is removed partially during robot-assisted McKeown esophagectomy for esophageal carcinoma, placing the drainage tube through the mediastinal pleura into the left thoracic cavity can reduce the risk of left-side thoracentesis or catheterization, which may promote the postoperative recovery of patients.

There are direct and indirect interactions between gut microbiota and host immune response, which can have a multifaceted impact on host health. Dysbiosis caused by disturbances in the gut microbiota is associated with susceptibility to many diseases, especially immune-related diseases. Based on the research results in recent years, this paper introduced the mechanism of the interaction between gut microbiota and host immunity, and expounded the role of gut microbiota in the occurrence and development of immune-related diseases, including intestinal system diseases such as inflammatory bowel disease and other systemic diseases such as rheumatoid arthritis, and summarized disease treatment strategies targeting gut microbiota. A better understanding of the research progress of gut microbiota and immune-related diseases will help us in the prevention and management of such diseases, and broaden our path to discover disease intervention targets.
Gastrointestinal Microbiome/physiology* ; Humans ; Inflammatory Bowel Diseases ; Intestines

Key requirements of successful animal behavior research in the laboratory are robustness, objectivity, and high throughput, which apply to both the recording and analysis of behavior. Many automatic methods of monitoring animal behavior meet these requirements. However, they usually depend on high-performing hardware and sophisticated software, which may be expensive. Here, we describe an automatic infrared behavior-monitor (AIBM) system based on an infrared touchscreen frame. Using this, animal positions can be recorded and used for further behavioral analysis by any PC supporting touch events. This system detects animal behavior in real time and gives closed-loop feedback using relatively low computing resources and simple algorithms. The AIBM system automatically records and analyzes multiple types of animal behavior in a highly efficient, unbiased, and low-cost manner.