With the rapid development of deep learning(DL)technology,its potential applications in the medical field have become increasingly prominent.As a refractory disease,osteonecrosis of the femoral head(ONFH)has certain limitations in traditional diagnostic and therapeutic approaches.The application of DL technology is expected to overcome these limitations and improve diagnosis and treatment outcomes.At present,the applications of DL models-including enhancing image clarity,improving diagnostic accuracy and efficiency,conducting prognostic evaluations,optimizing preoperative planning,assisting intraoperative imaging,and customizing personalized treatment plans-have fully demonstrated their tremendous potential in the diagnosis and treatment of ONFH.This review summarizes the current application status of DL in ONFH diagnosis and treatment,aiming to provide references and insights for future related research.

Objective To explore the association between aspartate aminotransferase(AST)/alanine aminotransferase(ALT)ratio and metabolic syndrome(MS)in elderly hypertensive patients,and to provide reference for early detection and prevention of MS in elderly hypertensive patients.Methods A questionnaire survey and physical examination were conducted among 616 elderly hypertensive patients at community health service centers.Participants were divided into two groups based on MS status:MS group(n=334)and non-MS group(n=282).According to AST/ALT levels,participants were divided into four groups:q1 group(AST/ALT ≤0.88,n=156),q2 group(0.88＜AST/ALT ≤ 1.10,n=155),q3 group(1.10＜AST/ALT ≤ 1.37,n=154),and q4 group(AST/ALT＞1.37,n=151).Blood biochemical parameters including triglycerides(TG),high-density lipoprotein cholesterol(HDL-C),AST,ALT,and blood glucose were measured.The impact of AST/ALT levels on MS was analyzed using a Logistic regression model,while the risk prediction for MS occurrence was evaluated through receiver operating characteristic(ROC)curves.Results MS group showed higher body mass index(BMI),TG,ALT levels,abnormal glucose levels,female proportion,and abdominal obesity rate compared to non-MS group.HDL-C and AST/ALT values of MS group were lower than those in non-MS patients(P＜0.05).Logistic regression analysis revealed that after adjusting for BMI,smoking,alcohol consumption,physical activity,education level,marital status,TG,HDL-C,and glucose levels,both q3 and q4 groups demonstrated reduced MS risk compared to group q1 group(P＜0.05).ROC curve analysis indicated that the area under the curve for AST/ALT in MS was 0.638(P＜0.05).Conclusion The level of AST/ALT was negatively correlated with MS in elderly hypertensive patients,and AST/ALT has certain predictive value for the risk of MS in elderly hypertensive patients.

Polygonati Rhizoma demonstrates significant potential for addressing both chronic and hidden hunger. The supply of high-quality seedlings is a primary factor influencing the development of the Polygonati Rhizoma industry. Warm water soaking is often used in agriculture to promote the rapid germination of seeds, while its application and molecular mechanism in Polygonati Rhizoma have not been reported. To rapidly obtain high-quality seedlings, this study treated Polygonatum kingianum var. grandifolium seeds with sand storage at low temperatures, warm water soaking, and cultivation temperature gradients. The results showed that the culture at 25 ℃ or sand storage at 4 ℃ for 2 months rapidly broke the seed dormancy of P. kingianum var. grandifolium, while the culture at 20 ℃ or sand storage at 4 ℃ for 1 month failed to break the seed dormancy. Soaking seeds in 60 ℃ warm water further increased the germination rate, germination potential, and germination index. Specifically, the seeds soaked at 60 ℃ and cultured at 25 ℃ without sand storage treatment(Aa25) achieved a germination rate of 78. 67%±1. 53% on day 42 and 83. 40%±4. 63% on day 77. The seeds pretreated with sand storage at 4 ℃ for 2 months, soaked in 60 ℃ water, and then cultured at 25 ℃ achieved a germination rate comparable to that of Aa25 on day 77. Transcriptomic analysis indicated that warm water soaking might promote germination by triggering reactive oxygen species( ROS), inducing the expression of heat shock factors( HSFs) and heat shock proteins( HSPs), which accelerated DNA replication, transcript maturation, translation, and processing, thereby facilitating the accumulation and turnover of genetic materials. According to the results of indoor controlled experiments and field practices, maintaining a germination and seedling cultivation environment at approximately 25 ℃ was crucial for the one-year seedling cultivation of P. kingianum var. grandifolium.
Germination ; Seedlings/genetics* ; Water/metabolism* ; Seeds/metabolism* ; Polygonatum/genetics* ; Temperature ; Plant Proteins/genetics* ; Plant Dormancy

OBJECTIVE: To investigate the clinical efficacy and advantages of robot-assisted total knee arthroplasty (TKA) in patients with varus knee osteoarthritis. METHODS: Between October 2022 and June 2023, a total of 59 patients with severe knee osteoarthritis resulting in varus were treated with total knee arthroplasty, aged from 59 to 81 years with an average (70.90±4.63) years, including 19 mals and 40 females. The patients were divided into two groups based on the surgical method used:28 patients in the robot group and 31 patients in the traditional group. The robot group consisted of 8 males and 20 femalse patients, with an average age of (70.54±4.80) years and an average disease duration of (14.89±8.72) months. The traditional group consisted of 11 males and 20 females patients, with an average age of (71.39±4.5) years and an average disease duration of (12.32±6.73) months. The operative duration, amount of bleeding during the operation, postoperative activity time after the operation, hip-knee-ankle angle (HKA), lateral distal femoral angle (LDFA), medial proximal tibial angle (MPTA), and complications were compared between the two groups before and after the operation. Lateral tibia component (LTC), frontal tibia component (FTC), frontal femoral component (FFC) and lateral femoral component (LFC) were measured 6 months after operation Additionally, the degree of knee joint motility, American Knee Society score (KSS), and visual analogue scale(VAS) were compared before and after the operation. RESULTS: All patients had gradeⅠwound healing without any complications, and all patients were followed up for 6 to 8 months, with an average of (6.5±1.5) months. There were no significant differences preoperative imaging evaluation indexes (including HKA, LDFA, and MPTA), preoperative knee mobility, preoperative VAS, and preoperative KSS between the two groups (P>0.05). Comparing the operation time (109.11±7.16) min vs. (83.90±7.85) min, length of the incision (16.60±2.33) cm vs. (14.47±1.41) cm, intraoperative bleeding (106.93±6.15) ml vs. (147.97±7.62) ml, postoperative activity time (17.86±1.84) h vs. (21.77±2.68) h, between the two groups showed statistically significant differences (P<0.05). There were significant differences in FFC (88.96±0.84)° vs. (87.93±1.09)° and LFC (88.57±1.10)° vs. (87.16±1.2)° between the two groups at 6 months after operation (P<0.05). The robotic group 1, 3, 6 months after KSS (75.96±3.96), (81.53±3.78), (84.50±3.29) scores, VAS (3.68±0.67), (2.43±0.79), (0.54±0.64), knee joint mobility (113.32±4.72) °, (123.93±3.99) °, (135.36±2.34) °;Traditional group KSS (73.77±4.18), (76.48±3.60), (80.19±3.28) scores, VAS (4.16±1.04), (3.03±0.75), (1.42±0.76) scores, knee joint mobility (109.19±6.95) °, (119.94±6.08) °, (134.48±2.14) °. Compared to before surgery, both groups showed significant improvement in KSS, VAS and knee mobility during the three follow-up visits (P<0.001). Additionally, postoperative HKA (180.39±1.95)° vs. (178.52±2.23)°, LDFA (89.67±0.63) ° vs. (89.63±0.63)°, and MPTA (89.44±0.55)° vs. (89.29±0.60)° were significantly improved in both groups compared to before surgery (P<0.001). The robotic group had higher KSS than the traditional group at 1, 3, and 6 months after surgery (P<0.05). The robotic group also had lower VAS than the traditional group at 1, 3, and 6 months after surgery (P<0.05). Furthermore, knee mobility was higher in the robotic group than those in the traditional group at 1 and 6 months after surgery (P<0.05), but there was no significant difference between the two groups at 6 months after surgery. CONCLUSION Robot-assisted total knee arthroplasty is a safe and effective method for total knee replacement. The use of robotics can improve the limb axis and prosthesis alignment for patients with preoperative varus deformity, resulting in better clinical and imaging outcomes compared to the conventional group.
Humans ; Female ; Male ; Arthroplasty, Replacement, Knee/methods* ; Aged ; Middle Aged ; Osteoarthritis, Knee/physiopathology* ; Aged, 80 and over ; Robotic Surgical Procedures/methods*

Progressive pulmonary fibrosis (PPF) is a progressive and lethal condition with few effective treatment options. Improvements in quality of life for patients with PPF remain limited even while receiving treatment with approved antifibrotic drugs. Traditional Chinese medicine (TCM) has the potential to improve cough, dyspnea and fatigue symptoms of patients with PPF. TCM treatments are typically diverse and individualized, requiring urgent development of efficient and precise design strategies to identify effective treatment options. We designed an innovative Bayesian adaptive two-stage trial, hoping to provide new ideas for the rapid evaluation of the effectiveness of TCM in PPF. An open-label, two-stage, adaptive Bayesian randomized controlled trial will be conducted in China. Based on Bayesian methods, the trial will employ response-adaptive randomization to allocate patients to study groups based on data collected over the course of the trial. The adaptive Bayesian trial design will employ a Bayesian hierarchical model with "stopping" and "continuation" criteria once a predetermined posterior probability of superiority or futility and a decision threshold are reached. The trial can be implemented more efficiently by sharing the master protocol and organizational management mechanisms of the sub-trial we have implemented. The primary patient-reported outcome is a change in the Leicester Cough Questionnaire score, reflecting an improvement in cough-specific quality of life. The adaptive Bayesian trial design may be a promising method to facilitate the rapid clinical evaluation of TCM effectiveness for PPF, and will provide an example for how to evaluate TCM effectiveness in rare and refractory diseases. However, due to the complexity of the trial implementation, sufficient simulation analysis by professional statistical analysts is required to construct a Bayesian response-adaptive randomization procedure for timely response. Moreover, detailed standard operating procedures need to be developed to ensure the feasibility of the trial implementation. Please cite this article as: Zhang C, Nie YS, Zhang CT, Yang HJ, Zhang HR, Xiao W, Cui GF, Li J, Li SJ, Huang QS, Yan SY. An adaptive Bayesian randomized controlled trial of traditional Chinese medicine in progressive pulmonary fibrosis: Rationale and study design. J Integr Med. 2025; 23(2): 138-145.
Female ; Humans ; Male ; Bayes Theorem ; Disease Progression ; Drugs, Chinese Herbal/therapeutic use* ; Medicine, Chinese Traditional/methods* ; Pulmonary Fibrosis/therapy* ; Quality of Life ; Randomized Controlled Trials as Topic ; Research Design ; Adaptive Clinical Trials as Topic

Objective To modify the YOLOv5 algorithm with similarity attention mechanism(SimAM)to enhance the recognition and segmentation accuracy of CT images for cerebral hemorrhage.Methods A basic framework was established with a YOLOv5 algorithm consisting of a backbone network(Backbone),a neck module(Neck)and a head module(Head),and then SimAM was introduced at the end of Backbone to form a YOLOv5-Sim-B algorithm and at the end of Neck to construct a YOLOv5-Sim-N algorithm.The YOLOv5-Sim-B and YOLOv5-Sim-N algorithms were trained and validated using the CT image dataset for cerebral hemorrhage publicly available on the Kaggle competition platform,and compared with the traditional YOLOv5 algorithm for recognizing and segmenting cerebral hemorrhagic lesions in CT images.Results In case the value of IoU-T was 0.6,the mean average precision(mAP)was 0.967 for YOLOv5-Sim-B algorithm,0.960 for the YOLOv5-Sim-N algorithm and 0.964 for the traditional YOLOv5 algorithm during the recognition and segmentation of cerebral hemorrhagic lesions in CT images.Conclusion The proposed algorithm gains advantages in detection accuracy and robustness,and can efficiently identify and segment cerebral hemorrhage foci in CT images.[Chinese Medical Equipment Journal,2025,46(5):1-8]

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To propose an improved YOLOv8 algorithm based on polarized self-attention(PSA)and deformable attention(DAT)so as to enhance the detection of pulmonary nodules in CT images.Methods A basic framework was established with a YOLOv8 model consisting of a backbone network(Backbone),a neck module(Neck)and a head module(Head).PSA was introduced into the end of the spatial pyramid pooling-fast(SPPF)of Backbone to construct a YOLOv8-PSA algorithm,and DAT was involved in the medium-scale feature layer P4 in Head to form a YOLOv8-DAT algorithm.The YOLOv8-PSA and YOLOv8-DAT algorithms were trained and validated using the CT image dataset of pulmonary nodules from public platforms,and compared with the original YOLOv8 algorithm for the detection of pulmonary nodule lesions in CT images.Results When used for pulmonary module detection of CT images,the YOLOv8-DAT algorithm had the mean average precision(mAP)in case of intersection over union threshold of 0.5(mAP50),mAP in case of intersection over union threshold of 0.5 to 0.95(mAP50-95)and precision ratio being 0.918,0.588 and 0.960 respectively,which gained advantages over the YOLOv8-PSA algorithm with mAP50,mAP50-95 and precision ratio being 0.914,0.583 and 0.945 respectively,and over the original YOLOv8 algorithm with mAP50,mAP50-95 and precision ratio being 0.911,0.564 and 0.952 respectively.Conclusion The YOLOv8-DAT algorithm detects pulmonary modules in CT images effectively,and facilitates early screening and diagnosis of pulmonary modules clinically.[Chinese Medical Equipment Journal,2025,46(8):1-10]

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To propose an improved YOLOv8 algorithm based on polarized self-attention(PSA)and deformable attention(DAT)so as to enhance the detection of pulmonary nodules in CT images.Methods A basic framework was established with a YOLOv8 model consisting of a backbone network(Backbone),a neck module(Neck)and a head module(Head).PSA was introduced into the end of the spatial pyramid pooling-fast(SPPF)of Backbone to construct a YOLOv8-PSA algorithm,and DAT was involved in the medium-scale feature layer P4 in Head to form a YOLOv8-DAT algorithm.The YOLOv8-PSA and YOLOv8-DAT algorithms were trained and validated using the CT image dataset of pulmonary nodules from public platforms,and compared with the original YOLOv8 algorithm for the detection of pulmonary nodule lesions in CT images.Results When used for pulmonary module detection of CT images,the YOLOv8-DAT algorithm had the mean average precision(mAP)in case of intersection over union threshold of 0.5(mAP50),mAP in case of intersection over union threshold of 0.5 to 0.95(mAP50-95)and precision ratio being 0.918,0.588 and 0.960 respectively,which gained advantages over the YOLOv8-PSA algorithm with mAP50,mAP50-95 and precision ratio being 0.914,0.583 and 0.945 respectively,and over the original YOLOv8 algorithm with mAP50,mAP50-95 and precision ratio being 0.911,0.564 and 0.952 respectively.Conclusion The YOLOv8-DAT algorithm detects pulmonary modules in CT images effectively,and facilitates early screening and diagnosis of pulmonary modules clinically.[Chinese Medical Equipment Journal,2025,46(8):1-10]