BACKGROUND:There is still no consensus on the optimal internal fixation for the treatment of Pauwels Ⅲ femoral neck fracture,and most of the related finite element analyses have been performed using a single simplified loading condition,and the biomechanical properties of commonly used internal fixation devices need to be further investigated. OBJECTIVE:To analyze the biomechanical characteristics of Pauwels Ⅲ femoral neck fractures treated with cannulated compression screw,dynamic hip screw,and femoral neck system by finite element method under different loading conditions of single-leg standing loads and sideways fall loads. METHODS:The DICOM data of healthy adult femur were obtained by CT scanning,imported into Mimics 15.0 software to obtain the rough model of bone tissue.The data exported from Mimics were optimized by Geomagics software,and then three internal fixation models were built and assembled with the femur model according to the parameters of the clinical application of the cannulated compression screw,dynamic hip screw,and femoral neck system by using Pro/E software.Finally,the three internal fixation models were imported into Ansys software for loading and calculation to analyze the stress distribution and displacement of the femur and the internal fixation under different working conditions of single-leg standing loads and sideways fall loads,as well as the stress characteristics of the calcar femorale and Ward's triangle. RESULTS AND CONCLUSION:(1)Under the single-leg standing load and the sideways fall load,the proximal femoral stress of the three internal fixation models was mainly distributed above the fracture end of the femoral neck.The peak stress of the proximal femoral end,fracture end,Ward triangle,and calcar femorale of the three internal fixation models were the smallest in the femoral neck system model and the largest in the cannulated compression screw model.(2)Under the single-leg standing load and the sideways fall load,the peak displacement of the proximal femur of the three internal fixation models was all located at the top of the femoral head,and the peak displacement was the smallest in the femoral neck system model and the largest in the cannulated compression screw model.(3)The peak displacement of the three internal fixation models was all located at the top of the internal fixation device under the single-leg standing and sideways fall loading conditions,and the peak displacement values were the smallest in the femoral neck system internal fixation model and the largest in the cannulated compression screw internal fixation model.(4)The internal fixation stress of the three internal fixation models was mainly distributed in the area near the fracture end of the internal fixation device under the single-leg standing and sideways fall loads,and the peak value of internal fixation stress was the smallest in the femoral neck system model and the largest in the cannulated compression screw model.(5)These results suggest that the mechanical stability of the femoral neck system is the best,but there may be a risk of stress shielding of the fracture end and calcar femorale.The stress of the internal fixation device of the femoral neck system is more dispersed,and the risk of internal fixation break is lower.

Background Staff in tertiary hospitals are a high-risk group for occupational burnout. Timely identification and precise intervention are crucial for improving healthcare service quality. However, comparative studies on perceived stress and occupational burnout among hospital staff in different positions are lacking. Objective To describe the status of perceived stress and occupational burnout among hospital staff in different positions and compare the differences, explore the relationship between perceived stress and occupational burnout, and identify the influencing factors of occupational burnout. Methods In May 2022, 1526 hospital staff members were selected by convenience sampling from six tertiary hospitals in Guangzhou. Data were collected using a general information questionnaire, the Chinese Perceived Stress Scale (CPSS), and the Maslach Burnout Inventory-Human Services Survey (MBI-HSS) to assess demographic characteristics, perceived stress, and occupational burnout. Chi-square test, one-way ANOVA, and Kruskal-Wallis H test were used to compare differences in perceived stress and occupational burnout among staff in different positions. Pearson correlation analysis was used to explore possible correlation between perceived stress and occupational burnout. Multiple linear regression was conducted to identify influencing factors of occupational burnout. Results A total of 1388 valid questionnaires were collected, with an effective response rate of 90.96%. Among them, 437 nurses (57.0%), 273 physicians (58.6%), 24 pharmacists (57.1%), and 62 administrators (54.9%) reported positive perceived health risk stress (P=0.892). Additionally, 392 nurses (51.1%), 213 physicians (45.7%), 19 pharmacists (45.2%), and 53 administrators (46.9%) reported positive occupational burnout (P=0.005). Perceived stress was positively correlated with occupational burnout among nurses, physicians, pharmacists, and administrators (r=0.5973, 0.5687, 0.5464, and 0.5276, respectively; P＜0.01). The multiple linear regression identified perceived stress (b=1.4587, P＜0.001), job satisfaction (b=−7.4195, P＜0.001), self-rated health (b=−2.0428, P＜0.001), working years (b=−0.1135, P=0.016), and being a nurse (compared with an administrators) (b=3.2435, P=0.045) as significant factors for occupational burnout (P<0.001). Conclusion Perceived health risk stress and occupational burnout are common among hospital staff, with nurses experiencing significantly higher levels of occupational burnout compared to other positions. Hospital managers should pay more attention to staff with higher perceived stress, lower job satisfaction, poorer self-rated health, and shorter working years, particularly nurses.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Background/Aims: Treatment indications for patients with chronic hepatitis B (CHB) remain contentious, particularly for patients with mild alanine aminotransferase (ALT) elevation. We aimed to evaluate treatment effects in this patient population. Methods: This rollover study extended a placebo-controlled trial that enrolled non-cirrhotic patients with CHB and ALT levels below two times the upper limit of normal. Following 3 years of randomized intervention with either tenofovir disoproxil fumarate (TDF) or placebo, participants were rolled over to open-label TDF for 3 years. Liver biopsies were performed before and after the treatment to evaluate histopathological changes. Virological, biochemical, and serological outcomes were also assessed (NCT02463019). Results: Of 146 enrolled patients (median age 47 years, 80.8% male), 123 completed the study with paired biopsies. Overall, the Ishak fibrosis score decreased in 74 (60.2%), remained unchanged in 32 (26.0%), and increased in 17 (13.8%) patients (p<0.0001). The Knodell necroinflammation score decreased in 58 (47.2%), remained unchanged in 29 (23.6%), and increased in 36 (29.3%) patients (p=0.0038). The proportion of patients with an Ishak score ≥ 3 significantly decreased from 26.8% (n=33) to 9.8% (n=12) (p=0.0002). Histological improvements were more pronounced in patients switching from placebo. Virological and biochemical outcomes also improved in placebo switchers and remained stable in patients who continued TDF. However, serum HBsAg levels did not change and no patient cleared HBsAg. Conclusions In CHB patients with minimally raised ALT, favorable histopathological, biochemical, and virological outcomes were observed following 3-year TDF treatment, for both treatment-naïve patients and those already on therapy.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

This study aims to systematically characterize the targeted effects of Quanduzhong Capsules on cartilage lesions in knee osteoarthritis by integrating spatial transcriptomics data mining and animal experiments validation, thereby elucidating the related molecular mechanisms. A knee osteoarthritis model was established using Sprague-Dawley(SD) rats, via a modified Hulth method. Hematoxylin and eosin(HE) staining was employed to detect knee osteoarthritis-associated pathological changes in knee cartilage. Candidate targets of Quanduzhong Capsules were collected from the HIT 2.0 database, followed by bioinformatics analysis of spatial transcriptomics datasets(GSE254844) from cartilage tissues in clinical knee osteoarthritis patients to identify spatially specific disease genes. Furthermore, a "formula candidate targets-spatially specific genes in cartilage lesions" interaction network was constructed to explore the effects and major mechanisms of Quanduzhong Capsules in distinct cartilage regions. Experimental validation was conducted through immunohistochemistry using animal-derived biospecimens. The results indicated that Quanduzhong Capsules effectively inhibited the degenerative changes in the cartilage of affected joints in rats, which was associated with the regulation of Quanduzhong Capsules on the thioredoxin-interacting protein(TXNIP)-NOD-like receptor family pyrin domain containing 3(NLRP3)-bone morphogenetic protein receptor type 2(BMPR2)-fibronectin 1(FN1)-matrix metallopeptidase 2(MMP2) signal axis in the articular cartilage surface and superficial zones, subsequently inhibiting cartilage matrix degradation leading to oxidative stress and inflammatory diffusion. In summary, this study clarifies the spatially specific targeted effects and protective mechanisms of Quanduzhong Capsules within pathological cartilage regions in knee osteoarthritis, providing theoretical and experimental support for the clinical application of this drug in the targeted therapy on the inflamed cartilage.
Animals ; Osteoarthritis, Knee/metabolism* ; Drugs, Chinese Herbal/administration & dosage* ; Rats, Sprague-Dawley ; Rats ; Male ; Humans ; Capsules ; Female ; Disease Models, Animal

Traditional Chinese medicine(TCM) capable of clearing heat and removing toxin is most commonly used in clinical practice and has the effect of removing fire-heat and toxin. Studies have shown that most of the Ilex plants have the effect of clearing heat and removing toxin, among which the varieties of I. cornuta, I. pubescens, I. rotunda, I. latifolia, and I. chinensis are most widely used. These plants generally contain triterpenoids and their glycosides, alkaloids, flavonoids, phenylpropanoids, and other chemical components, especially pentacyclic triterpenoids. According to their skeletons, pentacyclic triterpenoids can be divided into the oleanane type, the ursane type, the lupinane type, etc. Among them, ursane-type components are the most abundant, and 136 species have been found so far. These components have been proved to have pharmacological effects such as anti-inflammatory, anti-tumor, hypolipidemic, anti-thrombosis, cardiomyocyte-protective, antibacterial, and hepatoprotective effects. Therefore, this paper systematically reviews the domestic and foreign literature on Ilex plants with a focus on the research progress on pentacyclic triterpenoids and their pharmacological activities, aiming to provide reference for the development of TCM resources with the effect of clearing heat and removing toxin.
Ilex/chemistry* ; Plants, Medicinal/chemistry* ; Pentacyclic Triterpenes/pharmacology* ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/pharmacology* ; Humans ; Animals

This paper aimed to investigate the therapeutic effect and mechanism of action of the Yiqi Fumai Formula(YQFM), a kind of traditional Chinese medicine(TCM), on mice with experimental heart failure based on the "heart-gut axis" theory. Based on the network pharmacology integrated with the group collaboration algorithm, the active ingredients were screened, a "component-target-disease" network was constructed, and the potential pathways regulated by the formula were predicted and analyzed. Next, the model of experimental heart failure was established by intraperitoneal injection of adriamycin at a single high dose(15 mg·kg~(-1)) in BALB/c mice. After intraperitoneal injection of YQFM(lyophilized) at 7.90, 15.80, and 31.55 mg·d~(-1) for 7 d, the protective effects of the formula on cardiac function were evaluated using indicators such as ultrasonic electrocardiography and myocardial injury markers. Combined with inflammatory factors in the cardiac and colorectal tissue, as well as targeted assays, the relevant indicators of potential pathways were verified. Meanwhile, 16S rDNA sequencing was performed on mouse fecal samples using the Illumina platform to detect changes in gut flora and analyze differential metabolic pathways. The results show that the administration of injectable YQFM(lyophilized) for 7 d significantly increased the left ventricular end-systolic internal diameter, fractional shortening, and ejection fraction of cardiac tissue of mice with experimental heart failure(P<0.05). Moreover, markers of myocardial injury were significantly decreased(P<0.05), indicating improved cardiac function, along with significantly suppressed inflammatory responses in cardiac and intestinal tissue(P<0.05). Additionally, the species of causative organisms was decreased, and the homeostasis of gut flora was improved, involving a modulatory effect on PI3K-Akt signaling pathway-related inflammation in cardiac and colorectal tissue. In conclusion, YQFM can affect the "heart-gut axis" immunity through the homeostasis of the gut flora, thereby exerting a therapeutic effect on heart failure. This finding provides a reference for the combination of TCM and western medicine to prevent and treat heart failure based on the "heart-gut axis" theory.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Heart Failure/microbiology* ; Mice ; Mice, Inbred BALB C ; Male ; Disease Models, Animal ; Gastrointestinal Microbiome/drug effects* ; Heart/physiopathology* ; Humans ; Signal Transduction/drug effects*