Obesity and its related metabolic diseases have become a major global public health threat, and its rising incidence significantly increases the risk of cardiovascular and cerebrovascular diseases, diabetes and other complications. Pancreatic lipase is a key enzyme that converts food-borne lipids into triglycerides and fatty acids, and the effective inhibition of its activity has become an important strategy for the treatment of obesity. This paper discusses the screening methods of pancreatic lipase inhibitors, and summarizes and reviews the basic principles, advantages and disadvantages and application status of traditional screening methods, modern new screening methods and virtual screening methods. In view of the problems faced by the screening methods of pancreatic lipase inhibitors, future research urgently needs to move towards a collaborative innovation path of multi-technology integration, intelligent screening and complex systematization of traditional Chinese medicine, so as to open up new research paradigms.

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.

Monogenic hereditary cerebral small vessel disease （CSVD） is a group of genetic disorders characterized by cerebrovascular lesions， including cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy， cerebral autosomal recessive arteriopathy with subcortical infarcts and leukoencephalopathy， COL4A1 and COL4A2-related CSVD， and other rare types such as retinal vasculopathy with cerebral leukoencephalopathy and systemic manifestations and leukoencephalopathy with calcifications and cysts. These diseases are often caused by specific gene mutations and exhibit highly heterogeneous pathological mechanisms and clinical manifestations， including inflammatory response， abnormal gene expression， and microangiopathy. The advances in imaging findings and biomarkers have provided new methods for early diagnosis， while treatment strategies include stem cell therapy， immunotherapy，gene editing， and molecular targeted therapy. However， further studies are needed to develop individualized treatment regimens for different subtypes. This article reviews the important advances in the pathogenesis， clinical features， diagnostic methods， and treatment modalities of monogenic hereditary CSVD in recent years， in order to provide guidance for future research and clinical practice.

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 establish anin vitromodel of ferroptosis induced by Erastin and RAS-selective lethal 3(RSL3) in hepatoma cells, and to provide theoretical basis for the development of novel therapeutic strategies for HCC. Methods: Hepatoma cells(HCCLM3, HepG2, Hep3B, Huh7 and PLC/PRF/5) in logarithmic growth phase were treated with Erastin(0-40 μmol/L) and RSL3(0-10 μmol/L) at double concentrations respectively. After 24 h, CCK-8 method was used to detect cell viability, draw growth curve, calculate IC50, and HCC cells sensitive to inducers were selected for follow-up experiments. The effect of inducer on the state of hepatoma cells was observed under light microscope, and immunoblotting and flow cytometry were used to verify whether the ferroptotic modelin vitrowas successfully constructed. Results: Huh7, Hep3B and HepG2 cells were sensitive to Erastin and RSL3, but HCCLM3 and PLC/PRF/5 were insensitive to Erastin and RSL3. When the concentration of Erastin and RSL3 reached the maximum, the survival rate was still above 65%. Huh7, Hep3B and HepG2 cells were selected for subsequent experiments. Compared with the control group, the expression of Glutathione peroxidase 4(GPX4), a ferroptotic marker, was down-regulated in a concentration-dependent manner. In Huh7, Hep3B and HepG2 cells, lipid reactive oxygen species(ROS) levels significantly increased after 24 h treatment with 10 μmol/L and 20 μmol/L Erastin, respectively; in Huh7 cells, lipid ROS levels significantly increased after 24 h treatment with 0.5 μmol/L and 1 μmol/L RSL3, respectively; in Hep3B and HepG2 cells, lipid ROS levels significantly increased after 24 h treatment with 1 μmol/L and 2 μmol/L RSL3, respectively, compared with control group. Conclusion Huh7, Hep3B and HepG2 cells are highly sensitive to Erastin and RSL3. Huh7, Hep3B and HepG2 cells treated with 10 μmol/L Erastin for 24 h are good models for simulating ferroptosis induced by Erastinin vitro, Huh7 cells treated with 0.5 μmol/L RSL3 for 24 h and Hep3B and HepG2 cells treated with 1 μmol/L RSL3 for 24 h are good models for simulating ferroptosis induced by RSL3in vitro.

Schizophrenia is a chronic, severe, and highly heterogeneous psychiatric disorder. Current antipsychotic medications show limited effectiveness in treating negative symptoms and cognitive deficits. Accumulating evidence suggests that dysfunction of inhibitory γ-aminobutyric acid (GABA) neurons, leading to inhibitory circuit dysregulation, plays a pivotal role in the pathophysiology of the disorder. Recent advances in induced pluripotent stem cells (iPSCs) and brain organoid technologies have provided more accurate human-based models of schizophrenia, offering new avenues to investigate the complex neurodevelopmental mechanism of schizophrenia and to explore cell replacement therapies. Preclinical studies have demonstrated that transplantation of specific types of GABAergic interneuron precursors into the brain can selectively improve negative symptoms and cognitive deficits in animal models, highlighting considerable translational potential. However, the transition from bench to bedside still faces multiple technical and ethical challenges, enhancing cell differentiation efficiency, ensuring long-term safety of transplanted cells, achieving precise control and functional integration of neuronal subtypes, understanding circuit-specific contributions to different symptom domains, and establishing rigorous ethical and regulatory frameworks. In summary, inhibitory GABAergic interneuron-based cell therapy provides a novel theoretical and perspective foundation for improving negative and cognitive symptoms of schizophrenia. Despite significant challenges ahead, its prospects remain highly promising.

Objective:To explore the cardioprotective effects of icariin (ICA) against radiation-induced cardiac disease (RICD) in C57BL/6 mice.Methods:A total of 48 female C57BL/6J mice aged 6-8 weeks were randomly divided into three groups: the control group (CON), the irradiation group (IR), and the irradiation combined with icariin group (IR+ ICA), with 16 mice in each group. The IR and IR+ ICA groups received a single cardiac irradiation at a dose of 30 Gy, while the CON group received no radiation treatment. The IR+ ICA group was treated with ICA (70 mg·kg -1·d -1) two weeks before irradiation until the end of the experiment through intragastric administration. In contrast, the CON and IR groups were treated with an equal volume of vehicle solution (0.5% sodium carboxymethyl cellulose, NaCMC) via intragastric administration. The mice′s mental status, food intake, body weight, and survival rates were monitored during the experiment. At two weeks post-irradiation, the venous blood of the mice was collected and serum was separated for the enzyme-linked immunosorbent assays (ELISA) of creatine kinase MB isoenzyme (CK-MB) and cardiac troponin T (cTnT/TNNT2). At 12 weeks post-irradiation, the cardiac function of the mice was assessed using echocardiography. After the mice were euthanized under anesthesia, the histopathological changes and fibrosis degree of their myocardial tissues were assessed using hematoxylin and eosin (HE) and Masson′s trichrome staining, followed by the calculation of collagen volume fraction (CVF). The differential gene expression of brain natriuretic peptide (BNP), transforming growth factor-β (TGF-β), and interleukin-6 (IL-6) in the cardiac tissues of the mice was detected using real-time reverse transcription-polymerase chain reaction (RT-PCR). Apoptosis-related proteins and proteins associated with the phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) pathway were determined using Western blotting. The survival curves of the mice were plotted using Kaplan-Meier, and the survival differences of the mice among various groups were compared using the log-rank test. Results:After irradiation, the mice in the IR group showed lethargy, as well as decreased food intake and activity, while these symptoms in the IR+ ICA group were significantly alleviated. At two weeks post-irradiation, the CK-MB and cTnT levels of the IR group were significantly elevated compared with the CON group ( t = 5.28, 8.89, P < 0.01). At 12 weeks post-irradiation, the mice in the IR group exhibited significantly decreased body weight ( t = 2.47, P < 0.05) and decreased survival rates ( HR = 8.25, 95% CI: 1.157-58.770, P < 0.05) compared with the CON group. Echocardiography revealed that the IR group featured decreased left ventricular ejection fraction (EF), decreased fractional shortening (FS), and increased left ventricular end-diastolic diameter (LVDD) compared with the CON group ( t = 7.02, 4.45, P < 0.05). Histopathological examination revealed that the IR group suffered from cardiomyocyte edema, disordered arrangement, and increased fibrosis, with an elevated CVF. The IR group exhibited significantly upregulated gene expression of BNP, TGF-β, and IL-6 in cardiac tissues compared with the CON group ( t = 4.23, 6.39, 4.61, P < 0.05). After-irradiation, the IR group exhibited upregulated apoptosis-related proteins Cleaved Caspase-3 and Bax ( t = 6.29, 9.54, P < 0.05), decreased Bcl-2 expression ( t = 8.20, P < 0.001), and decreased phosphorylation levels of PI3K and Akt ( t = 6.47, 3.42, P < 0.001). The symptoms of the mice were partially ameliorated after treatment with ICA. Specifically, the mice in the IR+ ICA group exhibited higher body weight ( t = 5.13, P < 0.001) and significantly higher survival rates ( HR = 0.121, 95% CI: 0.017-0.864, P < 0.05) than the IR group. Compared to the IR group, the IR+ ICA group showed elevated cardiac function indicators EF and FS( t = 3.23, 3.05, P < 0.05), and reduced LVDD ( t = 3.02, P < 0.05). The histopathological analysis revealed mitigated edema and disordered arrangement of cardiomyocytes in the IR+ ICA group. Furthermore, the IR+ ICA group exhibited significantly lower BNP, TGF-β, and IL-6 expression levels than the IR group ( t = 2.83, 4.15, 2.96, P < 0.05). The expression of apoptosis-related proteins Cleaved Caspase-3 and Bax was lower ( t = 3.23, 3.24, P < 0.05), Bcl-2 expression was higher ( t = 5.92, P < 0.001), and restored phosphorylation levels of PI3K and Akt ( t = 2.89, 8.35, P < 0.001). Conclusions:Icariin has protective effects against the RICD. It alleviates cardiomyocyte apoptosis possibly by upregulating the phosphorylation levels of PI3K and Akt.

Soybean meal (SBM) prepared by soybean crushing is the most popular protein source in the poultry and livestock industries (Cai et al., 2015) due to its economic manufacture, high protein content, and good nutritional value. Despite these benefits, SBM contains various antigen proteins such as glycinin and β-conglycinin, which account for approximately 70% of the total proteins of the SBM and reduce digestibility and damage intestinal function (Peng et al., 2018). Treating SBM with proteases (neutrase, alcalase, and trypsin) or fermentation can eliminate these antigen proteins (Contesini et al., 2018). Because of its safety and rapid growth cycle, Bacillus strains are considered ideal for the fermentation industry (Yao et al., 2021). SBM fermented by Bacillus yields products with high nutritional value and low levels of antinutritional factors (ANFs), stimulating research in this area (Yuan et al., 2017). Kumari et al. (2023) demonstrated that fermentation with Bacillus species effectively degrades antigen proteins and increases crude protein content. The degradation of antigen proteins relies on protease hydrolysis. Low protease production is the major obstacle hindering the widespread use of microbial fermentation techniques.
Bacillus amyloliquefaciens/metabolism* ; Fermentation ; Glycine max/metabolism* ; Soybean Proteins/metabolism* ; Peptide Hydrolases/metabolism* ; Ribosomes/metabolism* ; Globulins ; Antigens, Plant ; Seed Storage Proteins

This consensus will introduce the characteristics of fillers used in the surgical cavities of domestic nasal surgery patients based on relevant literature and expert opinions. It will also provide recommendations for the selection of cavity fillers for different nasal diseases, with chronic sinusitis as a representative example.
Humans ; Nasal Cavity/surgery* ; Nasal Surgical Procedures ; China ; Consensus ; Sinusitis/surgery* ; Dermal Fillers

Objective: To summarize the laboratory findings of a case of hemolytic disease of the fetus and newborn (HDFN) caused by Rh system anti-c antibodies and to review the literature, so as to explore the characteristics of anti-c HDFN. Methods: The ABO blood type, Rh blood type, direct antiglobulin test (DAT) results, and the presence of unexpected antibodies and their titers were determined by serological methods. The cases of anti-c HDFN in our laboratory in China and abroad were statistically analyzed, and the incidence of severe HDFN caused by anti-c, anti-D and anti-E was compared. Results: The blood type of the child was B (Rh CcDee) with a positive DAT. Anti-c antibody was detected in both serum and eluate, with a serum antibody titer of 4. The mother’s blood type was AB (Rh CCDee) with a negative DAT, and anti-c antibody was detected in the serum with a titer of 128. Among 20 cases of anti-c HDFN, 17 were DAT positive, and 9 (45%, 9/20) underwent blood transfusion or exchange transfusion. The incidence of severe HDFN was 47.60% (10/21) for anti-c, 47.60% (10/21) for anti-D and 31.30% (5/16) for anti-E. Conclusion: Maternal pregnancy and/or blood transfusion are the main reasons for the production of Rh alloantibodies such as anti-c. The prevention and management of anti-c should be similar to that of anti-D. Rh antigen-matched (five antigens of Rh blood group) transfusion is necessary for women of childbearing age to avoid antibody production, and Rh typing and antibody screening during prenatal examination is recommended to ensure early detection, intervention and treatment.