Objective To analyze the effect of releasing the lower pulmonary ligament on right residual lung expansion after right upper lobe resection under different body mass index (BMI) levels. Methods The clinical data of patients who underwent thoracoscopic right upper lobe resection in the First Affiliated Hospital with Nanjing Medical University from 2021 to 2022 were retrospectively analyzed. Patients were divided into a group A (17 kg/m2＜BMI≤23 kg/m2), a group B (23 kg/m2＜BMI≤29 kg/m2) and a group C (BMI＞29 kg/m2) according to BMI. The presence of residual cavity was judged by chest X-ray at 7-10 days after operation, the degree of compensation change of the right main bronchus angle was measured, and the changes in lung volume were determined by CT three-dimensional reconstruction. Results A total of 157 patients who underwent thoracoscopic right upper lobe resection were included, including 71 males and 86 females, with an average age of (59.7±11.2) years. There were 50 patients in the group A, 75 patients in the group B, and 32 patients in the group C. In the group A, compared with those without releasing the lower pulmonary ligament, patients with releasing had a lower incidence of postoperative residual cavity (P=0.016), greater changes in bronchus angle (P<0.001), and smaller changes in lung volume (P<0.001). In the group B and C, there was no significant effect of releasing the lower pulmonary ligament on postoperative residual cavity, bronchus angle, and lung volume changes (P>0.05). Conclusion For patients with thin and long body shape and low BMI, releasing the lower pulmonary ligament is helpful to promote the expansion of the residual lung after right upper lobe resection and reduce the occurrence of postoperative residual cavity in patients.

Background Long working hours, as a common risk factor for occupational stress, is closely related to the occurrence of depressive symptoms. Understanding how long working hours affect occupational stress and depressive symptoms will inform occupational health interventions. Objective To quantify the impact of long working hours exposure on occupational stress and depressive symptoms among Internet industry employees, translate black-box outputs into actionable insights, and demonstrate the value of interpretable machine learning for early-warning occupational-health surveillance. Methods A dataset was derived from a cross-sectional survey involving 2866 internet industry employees in China. This survey was part of the project Risk Assessment Of Long Working Hour Exposure And Its Adverse Health Effects, conducted by the National Institute for Occupational Health and Poisoning Control, Chinese Center for Disease Control and Prevention, from 2021 to 2023. Working hours, occupational stress and depressive symptoms were quantified with a set of structured questionnaires including the Core Occupational Stress Scale and the Patient Health Questionnaire. Pairwise associations were screened by Mantel tests and variance-inflation factors. Key predictors identified through feature selection were fed into six machine-learning risk-prediction models. Visual interpretation was provided by feature importance, Shapley additive explanations (SHAP) and local interpretable model-agnostic explanations (LIME), while directed causal effects and intervention impacts of prolonged working hours exposure on occupational stress and depressive symptoms were dissected with causal explanation of features techniques. Results The positive rates of occupational stress and depressive symptoms among internet employees were 12.9% and 77.8% respectively. Twelve core features for occupational stress and nine for depressive symptoms were retained after selection. After these features were supplied to six predictive algorithms and evaluated on five metrics, the Light Gradient Boosting Machine (LGBM) achieved the highest accuracy—0.89 for occupational stress and 0.79 for depressive symptoms on the hold-out test set. The feature-importance rankings converged on fatigue accumulation and life satisfaction as dominant drivers for both outcomes, whereas weekly working hours and daily overtime emerged as the principal exposure-related predictors. The SHAP summary plots revealed that longer weekly hours and daily overtime systematically elevated the probability of occupational stress. The causal feature explanation further quantified that ascending one category in weekly working hours increased the probability of occupational stress by 7.04%. Conclusion Exposure to long working hours is associated with both occupational stress and depressive symptoms among internet industry employees. Interpretable machine-learning frameworks translate these associations into transparent, defensible drivers, enabling precise identification of the pivotal factors and their interplay. This evidence base equips occupational-health practitioners with actionable insights for designing targeted prevention and intervention strategies.

Objective To investigate how deubiquitinase OTU domain-containing protein 3(OTUD3)suppresses the progression of hepatocellular carcinoma via gut-liver axis metabolic remodeling and microbiome dynamics.Methods A total of 24 male 2-week-old littermate C57BL/6J mice(12 wild-type and 12 Otud3-/-)were divided into two differential genotype groups before 6 mice from each group were randomly chosen to receive intraperitoneal injections of N-nitrosodieth-ylamine(DEN)for hepatocellular carcinoma(HCC)induction.The mice were divided into four groups(n=6/group):Otud3+/+control(WT CON),Otud3-/-control(KO CON),Otud3+/+DEN-induced HCC(WT DEN),and Otud3-/-DEN-induced HCC(KO DEN).At 40 weeks of age,liver tissues were collected for metabolomic profiling,and fecal samples were obtained for 16S rRNA sequencing.Results Multivariate analyses,including principal component analysis(PCA),partial least squares-discriminant analysis(PLS-DA),sparse partial least squares-discriminant analysis(sPLS-DA),and orthogonal partial least squares-discriminant analysis(OrthoPLS-DA),demonstrated complete intergroup separability.Fifty-four differential metabolites were identified between the WT DEN and KO DEN groups through metabolomic profiling,with gut-liver axis-associated pathways such as cholesterol metabolism and fatty acid biosynthesis revealed by KEGG pathway analysis.Microbiome analysis indicated an upregulation of Bacteroides at the genus level in the KO DEN group compared to WT DEN.Pearson correlation analysis highlighted amino acids and derivatives as predominant metabolite classes and revealed Bacteroidetes and Firmicutesas the dominant gut microbial phyla.Conclusion OTUD3 suppresses HCC progression by modulating gut-liver axis metabolism,potentially mediated by elevated betaine and increased abundance of Odoribacter,Alistipes,and Lachnoclostridium.

Peri-implant keratinized mucosa (PIKM) augmentation refers to surgical procedures aimed at increasing the width of PIKM. Consensus reports emphasize the necessity of maintaining a minimum width of PIKM to ensure long-term peri-implant health. Currently, several surgical techniques have been validated for their effectiveness in increasing PIKM. However, the selection and application of PIKM augmentation methods may present challenges for dental practitioners due to heterogeneity in surgical techniques, variations in clinical scenarios, and anatomical differences. Therefore, clear guidelines and considerations for PIKM augmentation are needed. This expert consensus focuses on the commonly employed surgical techniques for PIKM augmentation and the factors influencing their selection at second-stage surgery. It aims to establish a standardized framework for assessing, planning, and executing PIKM augmentation procedures, with the goal of offering evidence-based guidance to enhance the predictability and success of PIKM augmentation.
Humans ; Consensus ; Dental Implants ; Mouth Mucosa/surgery* ; Keratins

Paclitaxel (PTX), a valuable natural product derived from Taxus species, exhibits remarkable anti-cancer properties. It penetrates nanopores in microtubule walls, interacting with tubulin on the lumen surface and disrupting microtubule dynamics, thereby inducing cytotoxic effects in cancer cells. PTX and its derivatives have gained approval for treating various diseases due to their low toxicity, high efficiency, and broad-spectrum application. The widespread success and expanding applications of PTX have led to increased demand, raising concerns about accessibility. Consequently, researchers globally have focused on developing alternative production methods and applying nanocarriers in PTX delivery systems to enhance bioavailability. This review examines the challenges and advancements in PTX sourcing, production, physicochemical properties, anti-cancer mechanisms, clinical applications, trials, and chemo-immunotherapy. It aims to provide a comprehensive reference for the rational development and effective utilization of PTX.
Humans ; Paclitaxel/pharmacology* ; Antineoplastic Agents, Phytogenic/pharmacology* ; Neoplasms/drug therapy* ; Animals ; Taxus/chemistry*

Background Occupational stress has emerged as a critical public health concern affecting the physical and mental well-being of workers in the manufacturing sector. However, researchers typically evaluate its core driver—cumulative fatigue—using a crude binary “present/absent” variable, thereby overlooking the high-dimensional complexity and heterogeneity inherent in fatigue characteristics. This oversimplification constrains both the precision and predictive performance of occupational stress risk assessment model. Objective Leveraging a data-driven approach, to survey data on cumulative fatigue among manufacturing employees, and then use this new classification to develop and validate an occupational stress prediction model, with an ultimate aim of enhancing the accuracy and effectiveness of occupational stress assessment. Methods A set of cross-sectional survey data on 3871 manufacturing employees in 2021 were derived from the “Long working hours exposure and its adverse health effect risk assessment” program of the National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention. Occupational stress was assessed using the Core Occupational Stress Measurement Scale, while cumulative fatigue was evaluated via the Worker’s Self-Diagnostic Questionnaire for Fatigue Accumulation. Boruta method was applied to screen core variables from 20 occupational stress influencing factors. Dimensionality reduction of cumulative fatigue features was performed using a Bayesian sparse autoencoder (BASE), followed by comparison and application of clustering methods to achieve multi-class classification of the reduced features. Six machine learning classification models were then selected including logistic regression, support vector machine, decision tree, random forest, adaptive boosting, and lightweight gradient boosting machine (LightGBM) to construct and compare two occupational stress prediction models involving cumulative fatigue combined with ten other core variables: one utilizing the original binary cumulative fatigue label as a core variable, and another employing the novel fatigue classification proposed herein as a core variable. Results The positive rate of occupational stress among the manufacturing employees was 38.9%. The Boruta method identified 11 core variables of occupational stress: depressive symptoms, cumulative fatigue, age, length of service, tenure in current position, average weekly working hours, average daily overtime hours, average monthly income, low levels of exercise, life satisfaction, and sleep quality. The BSAE reduced the original cumulative fatigue factors to 12 dimensions, while the K-means clustering grouped the reduced fatigue features into three categories: no fatigue, moderate fatigue, and sever fatigue. Six occupational stress prediction models were constructed using the three-category labels of cumulative fatigue and ten additional factors. The results indicated that the LightGBM model performed best, achieving an area under the curve (AUC) of 0.78, an accuracy of 0.77, and an F1 score of 0.72. Compared with the model incorporating the traditional binary labels for cumulative fatigue, the best prediction AUC (0.72), accuracy (0.66), and F1 score (0.65) improved by 6%, 11%, and 7%, respectively. Conclusion Cumulative fatigue is a significant predictor of occupational stress among manufacturing employees. Applying data dimensionality reduction combined with three-class cluster analysis to characterize cumulative fatigue improves the performance of occupational stress prediction models. From a data-driven perspective, machine learning methods demonstrate strengths in processing complex datasets, capturing nonlinear relationships, and generating predictions based on key variables. This study therefore confirms that refined processing of core factors substantially enhances the predictive capability of machine learning models in assessing occupational stress risk in the manufacturing workforce.

Objective:To summarize the early clinical outcomes of aortic valve replacement(AVR) using the Perceval sutureless aortic valve.Methods:This retrospective study included 50 patients who underwent AVR with the Perceval sutureless prostheses at Beijing Anzhen Hospital between June 2023 and January 2025. Surgical parameters, early clinical outcomes, valve function, and hemodynamic performance were evaluated to summarize clinical effectiveness.Results:The mean age of patients was(63.5±9.1) years, predominantly female(36/50). Severe aortic stenosis was present in 43 cases(86.0%). A preoperative aortic annulus dimension of 20.0(19.0, 21.0) mm measured in both anteroposterior and transverse diameters. Preoperative peak transvalvular gradient was(92.7±31.0)mmHg(1 mmHg=0.133 kPa), with a mean gradient of (58.0±21.2) mmHg. All procedures were successfully completed using the Perceval sutureless prostheses. Isolated AVR was performed in 20 patients(40.0%), with cardiopulmonary bypass and aortic cross-clamp times of 75.0(50.5, 99.5) min and 50.5(29.5, 71.5) min, respectively. Postoperative transesophageal echocardiography revealed an immediate reduction in the peak transvalvular gradient to 11.0(8.0, 18.0) mmHg, significantly lower compared to preoperative measurements( P<0.001). Two cases of paravalvular leakage and one case requiring permanent pacemaker implantation were reported postoperatively. All patients completed the 3-month follow-up, with one death during the follow-up period; the remaining patients exhibited normal prosthetic valve function without major adverse cardiovascular events. Significant postoperative reductions were observed in left ventricular end-diastolic diameter(45.8 mm vs. 43.2 mm, P=0.003) and left atrial diameter(53.9 mm vs. 44.6 mm, P<0.001) compared with baseline. Conclusion:AVR using the Perceval sutureless prostheses demonstrated safe and effective early clinical outcomes with excellent hemodynamic performance and low incidence of postoperative paravalvular leakage and permanent pacemaker implantation. The sutureless technique represents a viable alternative strategy, particularly advantageous for patients with small aortic annuli or complex surgical conditions, warranting broader clinical adoption.

Objective:To observe the tumor control and the degree of radiation-induced lung injury (RILI) between FLASH irradiation and conventional dose rate (CONV) irradiation, and compare the changes in plasma proteomic profiles of mice following whole-lung FLASH and CONV irradiation using proteomics method.Methods:A mouse model with metastatic lung cancer was established. After whole-lung irradiation, changes in normal lung capacity were monitored using CT scans. Then, a RILI model was constructed to examine pathological alterations in lung tissues following whole-lung CONV and FLASH irradiation. Plasma samples were collected from mice receiving whole-lung CONV irradiation ( n = 5) and whole-lung FLASH irradiation ( n = 5), followed by comparison with samples from the control group of healthy mice (also referred to as the healthy control group). These plasma samples were analyzed using isobaric tags for relative and absolute quantification (iTRAQ)-based proteomics, followed by the screening and identification of differentially expressed proteins using high-throughput bioinformatics. Moreover, protein-protein interaction (PPI) network analysis was conducted to identify hub genes using the STRING database and Cytoscape software. Results:Whole-lung FLASH and CONV irradiation produced consistent tumor control, with the former significantly reducing RILI compared to the latter. A total of 609 proteins were identified through proteomic analysis. Among them, 89 differentially expressed proteins were detected in the whole-lung FLASH group. Gene Ontology (GO) enrichment analysis indicated that up-regulated genes were primarily associated with stress and inflammatory responses, whereas down-regulated genes were related to ATP metabolism and angiogenesis regulation. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that up-regulated genes were predominantly enriched in unfolded protein response pathways, while down-regulated genes were mainly involved in metabolic pathways and oxidative phosphorylation. Integrated PPI analysis and subsequent validation via reverse transcription-polymerase chain reaction (RT-PCR) revealed four key genes.Conclusions:Compared to the whole-lung CONV irradiation, whole-lung FLASH irradiation reduces the RILI of normal lung tissues while maintaining equivalent tumor control in metastatic lung cancer. Proteomic analysis of differentially expressed proteins in plasma after whole-lung FLASH and CONV irradiation provides valuable insights into the molecular mechanisms underlying the FLASH effect.

To investigate the aging behavior of fluoroelastomer FM-1D in hot air,with compression set as a parameter for seal aging,aging tests were conducted on fluoroelastomer FM-1D under different initial compression rates in a hot air environment ranging from 60℃to 150℃.The aging kinetic equation relating compression set of FM-1D to temperature and time was established,in order to predict its aging life at 25℃.The test results indicated that when the initial compression rate was 30%,the compression set exhibited an Arrhenius relationship with both test temperature and time.However,at a initial compression rate of 50%,the compression set gradually conformed to the Arrhenius relationship as time extended.These findings provide a reference for determining accelerated testing methods and maintenance cycles for FM-1D rubber materials.

Objective:To explore the differences in the ability of different parts of the human skin to recognize vibration frequencies in order to provide data for physiological optimization of vibration parameters in pilots′ tactile vests.Methods:Ten healthy volunteers were selected and grouped by age as 20-40 years (6 cases) and 41-50 years (4 cases). All the subjects participated in 3 trials: ① identification test of frequency steps using cutaneous tactile perception: the back of the left hand was chosen as the test area, a dual-oscillator synchronous vibration system was adopted, and the frequency step was gradually increased (initially 0.1 Hz) to determine the threshold of frequency identification; ② maximum frequency threshold test of cutaneous tactile perception: the maximum frequency recognition thresholds in 7 parts of the trunk (the left waist, right waist, chest, back, left shoulder, right shoulder, neck) and the back of the hand were tested; ③ frequency discrimination test of cutaneous tactile perception: 5 equally spaced frequencies (covering the frequency recognition thresholds) were set to evaluate the accuracy of tactile frequency memory on the back of the hand after 3, 15 min and 24 h. The relationships between the adjacent step sizes of cutaneous tactile perception and the average value of the sum of adjacent frequencies were analyzed using simple linear regression. The highest identification thresholds of frequencies in different parts of the subjects as well as the accuracy of frequency discrimination during different periods were compared across the age groups.Results:The maximum thresholds of frequency identification of cutaneous tactile perception among the 10 subjects ranged from 16.20 to 33.55 Hz, while the range of adjacent step sizes was between 3.60 and 7.10 Hz. The adjacent step sizes were positively correlated with the average value of the sum of adjacent frequencies ( r=0.882, F=529.18, P<0.001). In the test on the maximum threshold of frequency identification of cutaneous tactile perception, there was a statistically significant difference in the main effect of an age group between the 2 groups ( F=15.87, P<0.001), but not in the main effect of the site ( P>0.05), or in the interactions between the group and age ( P>0.05). The accuracies of skin vibration frequency memory on the dorsal hand of the subjects at 3, 15 min and 24 h were 88%, 72% and 68% respectively. In the frequency discrimination test, there were no statistically significant differences in the main effect of the group, main effect of time or in their interactions between the 2 groups (all P>0.05). Conclusions:The ability of the human skin to identify vibration frequency is impacted by age, but there is no difference in sensitivity between the trunk and the back of the hand. It is recommended that the tactile vest for pilots be designed for general purposes to make it easy to adapt to vibration frequencies of multiple parts.