Invasive fungal infections (IFIs) have become prominent global health threats, escalating the burden on public health systems. The increasing occurrence of invasive fungal infections is due primarily to the extensive application of chemotherapy, immunosuppressive therapies, and broad-spectrum antifungal agents. At present, therapeutic practices utilize multiple categories of antifungal agents, such as azoles, polyenes, echinocandins, and pyrimidine analogs. Nevertheless, the clinical effectiveness of these treatments is progressively weakened by the emergence of drug resistance, thereby substantially restricting their therapeutic utility. Consequently, there is an imperative need to expedite the discovery of novel antifungal agents. This review seeks to present an exhaustive synthesis of novel antifungal drugs and candidate agents that are either under current clinical investigation or anticipated to progress into clinical evaluation. These emerging compounds exhibit unique benefits concerning their modes of action, antimicrobial spectra, and pharmacokinetic characteristics, potentially leading to improved therapeutic outcomes relative to conventional antifungal regimens. It is anticipated that these novel therapeutic agents will furnish innovative treatment modalities and enhance clinical outcomes in managing invasive fungal infections.

Objective:To investigate the risk factors associated with the development of venous thromboembolism with abdominal infection following pancreatic cancer surgery.Methods:A retrospective analysis was conducted on the clinical data of 70 patients with pancreatic cancer who underwent pancreaticoduodenectomy at the Department of Hepatobiliary Surgery of the First Affiliated Hospital of Air Force Medical University from March 2020 to August 2024, of which 31 were male and 39 were female, aged (58.5±6.8) years. Two groups were divided into two groups according to the occurrence of venous thromboembolism with abdominal infection in the postoperative period: the complication group ( n=28) and the non-complication group ( n=42). The general data, laboratory indexes and surgery-related indexes of the two groups were recorded, and logistic regression model was used to analyse the risk factors for the occurrence of venous thromboembolism with abdominal cavity infection after pancreaticoduodenectomy, and receiver operating characteristic (ROC) curve was used to assess the predictive value of the factors for the occurrence of venous thromboembolism with abdominal cavity infection after pancreatic cancer surgery. Results:Multifactorial analysis showed that the combination of diabetes mellitus ( OR=1.216, 95% CI: 1.225-1.657, P=0.035), occurrence of postoperative pancreatic fistula ( OR=1.292, 95% CI: 1.095-1.829, P=0.022), occurrence of postoperative biliary fistula ( OR=1.239, 95% CI: 1.171-2.618, P=0.005), high D-dimer ( OR=137.030, 95% CI: 3.214-5 843.128, P=0.010), prolonged operation time ( OR=1.058, 95% CI: 1.002-1.117, P=0.042), and low serum albumin ( OR=0.711, 95% CI: 0.508-0.995, P=0.046) in pancreatic cancer patients with a high risk of postoperative venous thromboembolism with the development of abdominal infection. ROC curve analysis showed that diabetes mellitus, pancreatic fistula, biliary fistula, D-dimer, duration of surgery, serum albumin, and co-prediction had certain predictive value for the occurrence of postoperative venous thromboembolism with abdominal infection after pancreatic cancer surgery, in which, the area under the curve for co-prediction in assessing the occurrence of postoperative venous thromboembolism with abdominal infection after pancreatic cancer surgery was 0.993 (95% CI: 0.982-1.000), with a sensitivity of 1.000 and a specificity of 0.929. Conclusion:Comorbid diabetes mellitus, pancreatic fistula, biliary fistula, D-dimer, prolonged duration of surgery, and serum albumin are independent risk factors for the development of postoperative venous thromboembolism with abdominal infection in patients with pancreatic cancer, all of which have diagnostic value and a high joint predictive value. The predictive value of co-prediction is relatively high.

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.

Interstitial cystitis/bladder pain syndrome (IC/BPS) is a refractory condition characterized by chronic inflammation of the bladder wall, disruption of the urothelial barrier, and neural sensitization. Current therapies, such as oral pentosan polysulfate sodium (PPS) or intravesical hyaluronic acid instillations, offer limited efficacy due to transient effects and an inability to reverse tissue fibrosis. Platelet-rich plasma (PRP), a regenerative medicine approach, has demonstrated significant therapeutic potential in urological disorders through the synergistic actions of its multiple growth factors. This review summarizes the latest advances in PRP therapy for IC/BPS, revealing that the underlying mechanisms primarily involve the release of diverse growth factors, suppression of inflammatory responses, restoration of the urothelial barrier, and modulation of nerve axonal regeneration. Clinically, PRP therapy significantly alleviates symptoms including pelvic/bladder pain, urinary frequency, nocturia episodes, and improves patients'quality of life. Furthermore, it offers advantages such as convenient administration, a favorable safety profile, and strong feasibility, presenting new therapeutic methods and options for the clinical treatment of IC/BPS.

Airway assessment is an important prerequisite for airway management.Difficult airway(DA)is a major challenge in anes-thesia management,and failure to predict DA in advance may lead to serious adverse events such as failed intubation and hypoxemia.Accurate assessment and prediction of possible DA before surgery is of vital importance.Traditional assessment systems rely on the ex-perience of the physician experience for interpretation,with a low sensitivity and difficulties in identifying hidden anatomical abnor-malities.Relying on powerful learning and data analysis capabilities,artificial intelligence(AI)establishes a predictive model for DA by integrating multimodal data on the basis of machine learning and deep learning,thereby improving the efficiency and accuracy of identifying abnormal anatomical structures in the airway,which helps to significantly improve prediction efficiency,develop a targeted regimen,implement effective management,and ensure the safety and quality of anesthesia.This article reviews the research on the ap-plication of AI in predicting DA in recent years.

ObjectiveTo assess the efficiency of a Sophora flavescens Ait (S. flavescens, Ku Shen)-soluble microneedle (SFA-MN) for improving skin lesion symptoms in mice with psoriasis.MethodsSFA-MNs were prepared using a two-mold molding process with 20% w/v polyvinylpyrrolidone and 15% w/v polyvinyl alcohol. The SFA-MNs were assessed for morphology, mechanical properties, in vitro dissolution, identification of components, and skin lesion improvement in imiquimod-induced psoriasis mice.ResultsThe SFA-MNs demonstrated good mechanical properties for efficiently penetrating the dermis, facilitating efficient drug delivery. Furthermore, they effectively inhibited mast cell levels in the dorsal lesion area of psoriasis mice and reduced the expression of the T-lymphocyte factor cluster of differentiation 3 and tumor necrosis factor-α. In addition, this system alleviated skin inflammation, splenic swelling, and thymic atrophy in the psoriasis-like mouse model. Seven major components were detected from SFA-MNs by comparison of the mass-to-nucleus ratios (m/z) of the secondary fragments N-methylcytisine, 5α, 9α-dihydroxymatrine, sophoramine, matrine, oxysophocarpine, oxymatrine, and kushenol O.ConclusionThe drug delivery strategy combining traditional herbal S. flavescens with soluble microneedle technology provides more targeted and effective immune regulation for treating psoriasis-like mice models, enabling enhanced therapeutic effects compared with the control group.

Objective:To explore the prevalence and risk factors of insomnia in Chinese Air Force servicemen deployed to highland areas.Methods:A total of 718 Air Force servicemen deployed to Qinghai-Tibetan plateau were recruited at May 2024.Sleep quality was assessed with the Pittsburgh Sleep Quality Index.Social-demograph-ic,military service,and psychological characteristics were measured with a self-administered general question-naire.Bivariable and multivariable logistic regressions were performed to identify independent risk factors.Missing data were handled by the multiple imputation.Results:The average sleep duration was(6.9±1.2)h and the aver-age PSQI score was(5.9±4.1).Totally 53.8％of participants experienced clinically significant insomnia.The multivariable analysis revealed that age≥35(aOR=4.07,95％CI=1.11-17.76),stressful event(aOR=3.27,95％CI=2.00-5.49),dysfunctional sleep beliefs and attitudes(aOR=2.59,95％CI=1.75-3.85),and caffeine product usage(aOR=1.69,95％CI=1.17-2.43)were risk factors for insomnia,while Tibetan-indigenous ethnic(aOR=0.44,95％CI=0.20-0.91),higher perceived social support(aOR=0.96,95％CI=0.96-0.99),and positive coping style(aOR=0.96,95％CI=0.93-0.99)were protective factors.Conclusion:Air force service-men deployed to highland areas have sufficient sleep time,but reduced sleep quality.Age,exposed to stress event during deployment,dysfunctional sleep beliefs and attitudes,and caffeine product usage are risk factors for insomni-a,while Tibetan-indigenous ethnic,higher perceived social support and positive coping style act as protective fac-tors.

Objective:To explore the prevalence and risk factors of insomnia in Chinese Air Force servicemen deployed to highland areas.Methods:A total of 718 Air Force servicemen deployed to Qinghai-Tibetan plateau were recruited at May 2024.Sleep quality was assessed with the Pittsburgh Sleep Quality Index.Social-demograph-ic,military service,and psychological characteristics were measured with a self-administered general question-naire.Bivariable and multivariable logistic regressions were performed to identify independent risk factors.Missing data were handled by the multiple imputation.Results:The average sleep duration was(6.9±1.2)h and the aver-age PSQI score was(5.9±4.1).Totally 53.8％of participants experienced clinically significant insomnia.The multivariable analysis revealed that age≥35(aOR=4.07,95％CI=1.11-17.76),stressful event(aOR=3.27,95％CI=2.00-5.49),dysfunctional sleep beliefs and attitudes(aOR=2.59,95％CI=1.75-3.85),and caffeine product usage(aOR=1.69,95％CI=1.17-2.43)were risk factors for insomnia,while Tibetan-indigenous ethnic(aOR=0.44,95％CI=0.20-0.91),higher perceived social support(aOR=0.96,95％CI=0.96-0.99),and positive coping style(aOR=0.96,95％CI=0.93-0.99)were protective factors.Conclusion:Air force service-men deployed to highland areas have sufficient sleep time,but reduced sleep quality.Age,exposed to stress event during deployment,dysfunctional sleep beliefs and attitudes,and caffeine product usage are risk factors for insomni-a,while Tibetan-indigenous ethnic,higher perceived social support and positive coping style act as protective fac-tors.

Objective:To investigate the risk factors associated with the development of venous thromboembolism with abdominal infection following pancreatic cancer surgery.Methods:A retrospective analysis was conducted on the clinical data of 70 patients with pancreatic cancer who underwent pancreaticoduodenectomy at the Department of Hepatobiliary Surgery of the First Affiliated Hospital of Air Force Medical University from March 2020 to August 2024, of which 31 were male and 39 were female, aged (58.5±6.8) years. Two groups were divided into two groups according to the occurrence of venous thromboembolism with abdominal infection in the postoperative period: the complication group ( n=28) and the non-complication group ( n=42). The general data, laboratory indexes and surgery-related indexes of the two groups were recorded, and logistic regression model was used to analyse the risk factors for the occurrence of venous thromboembolism with abdominal cavity infection after pancreaticoduodenectomy, and receiver operating characteristic (ROC) curve was used to assess the predictive value of the factors for the occurrence of venous thromboembolism with abdominal cavity infection after pancreatic cancer surgery. Results:Multifactorial analysis showed that the combination of diabetes mellitus ( OR=1.216, 95% CI: 1.225-1.657, P=0.035), occurrence of postoperative pancreatic fistula ( OR=1.292, 95% CI: 1.095-1.829, P=0.022), occurrence of postoperative biliary fistula ( OR=1.239, 95% CI: 1.171-2.618, P=0.005), high D-dimer ( OR=137.030, 95% CI: 3.214-5 843.128, P=0.010), prolonged operation time ( OR=1.058, 95% CI: 1.002-1.117, P=0.042), and low serum albumin ( OR=0.711, 95% CI: 0.508-0.995, P=0.046) in pancreatic cancer patients with a high risk of postoperative venous thromboembolism with the development of abdominal infection. ROC curve analysis showed that diabetes mellitus, pancreatic fistula, biliary fistula, D-dimer, duration of surgery, serum albumin, and co-prediction had certain predictive value for the occurrence of postoperative venous thromboembolism with abdominal infection after pancreatic cancer surgery, in which, the area under the curve for co-prediction in assessing the occurrence of postoperative venous thromboembolism with abdominal infection after pancreatic cancer surgery was 0.993 (95% CI: 0.982-1.000), with a sensitivity of 1.000 and a specificity of 0.929. Conclusion:Comorbid diabetes mellitus, pancreatic fistula, biliary fistula, D-dimer, prolonged duration of surgery, and serum albumin are independent risk factors for the development of postoperative venous thromboembolism with abdominal infection in patients with pancreatic cancer, all of which have diagnostic value and a high joint predictive value. The predictive value of co-prediction is relatively high.

Objective:To observe the expression of interleukin-35(IL-35) in Hashimoto's thyroiditis(HT) patients, and evaluate its regulatory effect on the balance between regulatory T cells(Treg) and T helper 22(Th22) cells.Methods:Forty-two HT patients and eighteen controls were consecutively enrolled. Plasma and peripheral blood mononuclear cells(PBMC) were isolated. Treg were purified. Plasma IL-35 and IL-22 were detected with enzyme-linked immunosorbent assay. Treg and Th22 percentages were measured using flow cytometry. Real-time quantitative PCR was used to assess mRNA levels of forhead box protein 3(FoxP3) and aryl hydrocarbon receptor(AhR). Treg were stimulated with exogenous IL-35, and were co-cultured with autologous PBMC to induce Treg-to-Th22 phenotypic differentiation, evaluating the effect of IL-35 on Treg function and differentiation.Results:There was imbalance between Treg and Th22 cells in HT group. HT group had reduced Treg percentage, plasma IL-35 and FoxP3 mRNA( P<0.001), while had elevated Th22 percentage and AhR mRNA( P<0.001). There was no significant difference in plasma IL-22 level between two groups( P=0.775). The suppressive capacity of Tregs in the HT group was diminished( P=0.013), and secretion levels of IL-35 and IL-10 were lower than those in the control group( P<0.001). The ability of Tregs in the HT group to differentiate into Th22 cells was increased, with higher levels of CCR4, CCR6, CCR10, AhR mRNA, and IL-22 secretion compared to the control group( P<0.01). IL-35 stimulation induced elevation of Treg percentage, FoxP3 mRNA, and IL-35/IL-10 secretion( P<0.05), but did not affect Th22 percentage, AhR mRNA, or IL-22 secretion( P>0.05). IL-35 stimulation enhanced Treg function in HT group, increasing proliferation inhibition and secretion of IL-35 and IL-10( P<0.05). IL-35 stimulation reduced the differentiation of Treg to Th22 phenotype in HT group, with decreased levels of CCR4, CCR6 CCR10, AhR mRNA, and IL-22 secretion( P<0.05). Conclusion:IL-35 enhances the immunosuppression of Tregs in HT patients and inhibits its differentiation into Th22 cells, thus regulating the balance between Tregs and Th22 cells.