ObjectiveThis study aimed to elucidate the mechanistic role of Staphylococcus aureus in the pathogenesis of atopic dermatitis (AD), a chronic inflammatory skin disorder characterized by pruritus and barrier dysfunction. A key focus was screening traditional Chinese medicine (TCM) active components with dual antibacterial and antipruritic efficacy, followed by systematic evaluation of their in vitro antibacterial activity. Additionally, a novel drug delivery system was constructed to enable localized efficient drug delivery, inhibiting S. aureus proliferation and alleviating its induced pruritus, thereby providing new strategies for targeted AD therapy. MethodsMale C57BL/6J mice aged 6-8 weeks (body weight 18-22 g) were used to establish an AD model via repeated oxazolone sensitization. On day 14, microbial samples were collected from the lesional area (1 cm²) using sterile cotton swabs, followed by vortex mixing, serial dilution, and plating on 5% sheep blood agar plates (incubated at 37°C for 24 h). Single colonies with complete transparent β-hemolytic zones were isolated and identified as vancomycin-intermediate S. aureus (VISA) via 16S rRNA sequencing. An S. aureus mono-infection animal model was then established by applying gauze saturated with bacterial suspension (McFarland turbidity 0.1) to the nape and back skin of mice. The pruritic phenotype and inflammatory cell infiltration induced by S. aureus were evaluated using comprehensive approaches including behavioral assays (e.g., scratching frequency recording), hematoxylin-eosin (HE) staining, and toluidine blue staining. The in vitro antibacterial efficacy of the TCM monomer pseudolaric acid B (PAB) and double network hydrogel (DN) was separately assessed by disk diffusion assay, while the minimum inhibitory concentration (MIC) of PAB was determined via broth dilution method. Further validation of the pharmacodynamic characteristics of the composite system (PAB@DN, composed of PAB and DN) was conducted through behavioral assays, HE staining, and dermatitis scoring, with its drug release profile evaluated by mass spectrometry analysis. Based on scratching behavioral analysis and dermatitis scoring, the optimal ratio and concentration of PAB@DN were optimized. ResultsThe S. aureus load in AD lesional tissues was significantly higher than in normal skin ((5.3±0.33)×10⁶ CFU vs. (3.6±0.26)×10⁷ CFU, P<0.001). In the S. aureus mono-infection group, mice exhibited a 6.7-fold increase in scratching frequency compared to the control group. HE staining revealed marked epidermal thickening ((10.4±2.39) μm vs. (85.6±1.95) μm, P<0.000 1), and toluidine blue staining showed a 23-fold increase in mast cell degranulation. Pseudolaric acid B exhibited a significant concentration-dependent inhibitory effect onS. aureus growth, with its in vitro antibacterial effect being 57% that of the antibiotic cefepime (inhibition zone diameter: PAB (1.885±0.036) cm vs. cefepime (3.636±0.005) cm, P<0.000 1) and a minimum inhibitory concentration (MIC) of 1 g/L. The carrier double network hydrogel (DN) itself lacked direct antibacterial activity (no significant difference in inhibition zone diameter compared to the control) but effectively ameliorated the dry symptoms of AD-like lesions. The PAB@DN composite system demonstrated a synergistic effect compared to individual components, resulting in a 50% reduction in scratching behavior, an 86% decrease in dermatitis score, and a 60% reduction in epidermal thickening. It also reduced the S. aureus load in mouse skin by approximately 34%, with the optimal effective formulation being PAB at 1 g/L loaded onto DN. ConclusionS. aureus colonization plays a critical driving role in the onset and progression of AD. Using an S. aureus infection model, this study confirmed that the pseudolaric acidB-hydrogel composite delivery system (PAB@DN) can effectively alleviate S. aureus-induced pruritus and skin damage, providing experimental evidence for microbiota-targeted therapy of AD.

OBJECTIVE: This study aimed to evaluate the association between susceptibility genes and non-alcoholic fatty liver disease (NAFLD) in children with obesity. METHODS: We conducted a two-step case-control study. Ninety-three participants were subjected to whole-exome sequencing (exploratory set). Differential genes identified in the small sample were validated in 1,022 participants using multiplex polymerase chain reaction and high-throughput sequencing (validation set). RESULTS: In the exploratory set, 14 genes from the NAFLD-associated pathways were identified. In the validation set, after adjusting for sex, age, and body mass index, ECI2 rs2326408 (dominant model: OR = 1.33, 95% CI: 1.02-1.72; additive model: OR = 1.22, 95% CI: 1.01-1.47), C6orf201 rs659305 (dominant model: OR = 1.30, 95% CI: 1.01-1.69; additive model: OR = 1.21, 95% CI: 1.00-1.45), CALML5 rs10904516 (pre-ad dominant model: OR = 1.36, 95% CI: 1.01-1.83; adjusted dominant model: OR = 1.40, 95% CI: 1.03-1.91; and pre-ad additive model: OR = 1.26, 95% CI: 1.04-1.66) polymorphisms were significantly associated with NAFLD in children with obesity ( P < 0.05). Interaction analysis revealed that the gene-gene interaction model of CALML5 rs10904516, COX11 rs17209882, and SCD5 rs3733228 was optional ( P < 0.05), demonstrating a negative interaction between the three genes. CONCLUSION In the Chinese population, the CALML5 rs10904516, C6orf201 rs659305, and ECI2 rs2326408 variants could be genetic markers for NAFLD susceptibility.
Humans ; Non-alcoholic Fatty Liver Disease/genetics* ; Child ; Male ; Female ; Genetic Predisposition to Disease ; Case-Control Studies ; Exome Sequencing ; Adolescent ; Polymorphism, Single Nucleotide ; Obesity/complications* ; Pediatric Obesity/complications* ; China

AIM To investigate the effects of Congrong San on neuronal apoptosis and the Bax/Bcl-2/Caspase3 signaling pathway in a rat model of Alzheimer's disease(AD).METHODS A total of 60 2-month-old SD male rats were randomly divided into the blank group,the model group,the memantine hydrochloride group(0.025 g/kg)and low-dose,medium-dose and high-dose Congrong San groups(4.62,9.24,18.48 g/kg).All groups except the control group received stereotactic intracerebral injection of Aβ1-42 to establish AD models.Following the successful modeling,each group received its corresponding intragastric administration once daily for 28 consecutive days.After the administration,the rats had their learning and memory ability detected by the morris water maze test;their hippocampal neuronal morphology observed with HE and Nissl staining;their hippocampal neuronal apoptosis observed with TUNEL staining;and their hippocampal expressions of amyloid precursor protein(APP),β-site APP-cleaving enzyme 1(BACE1),and apoptosis-related proteins Bax,Bcl-2 and Caspase3 detected with Western blot assay.RESULTS Compared with the model group,the groups intervened with medium-dose and high-dose Congrong San exhibited improved learning and memory performance,alleviated hippocampal neuronal damage,increased Nissl body count(P＜0.01),reduced hippocampal apoptosis rate(P＜0.05,P＜0.01),decreased protein expressions of APP,BACE1,Bax and cleaved-Caspase3/Caspase3 ratio(P＜0.05,P＜0.01),and elevated Bcl-2 expression(P＜0.01).CONCLUSION Congrong San mitigates cognitive impairment,hippocampal neuronal damage,and apoptosis in AD rats,probably through inhibition of the Bax/Bcl-2/Caspase3 signaling pathway activation.

Objective:To compare the efficacy of hepatic artery infusion chemotherapy (HAIC) combined with targeted therapy and immunnotherapy and transarterial chemoembolization (TACE) combined with targeted therapy and immunnotherapy in the treatment of unresectable hepatocellular carcinoma HCC.Methods:We retrospectively analyzed the clinical data of 40 patients with unresectable HCC treated with HAIC combined with targeted therapy and immunnotherapy and TACE combined with targeted therapy and immunnotherapy in Tongde Hospital of Zhejiang Province and Zhejiang Provincial People's Hospital.The patients were divided into HAIC group ( n=14) and TACE group ( n=26) according to the different treatment methods. Baseline data, surgical conversion and intraoperative situation, tumor response, portal vein cancer thrombus control rate, leukocyte reduction rate, platelet reduction rate, incidence of liver function abnormalities, objective remission rate, and disease control rate were compared between the two groups. Results:The HAIC group had a later baseline tumor staging than the TACE group (higher percentage of portal vein cancer thrombus, CNLC stage Ⅲa).The surgical conversion rate of the HAIC and TACE groups were 28.6%(4/14) and 26.9%(7/26), respectively, with the difference of no statistical significance ( P>0.05);The operation time and intraoperative bleeding were (329.5±19.9) min vs.(413.4±26.4) min, (272.2±49.9) ml vs.(536.0±123.6) ml, and the differences were statistically significant ( P<0. 05); The maximum tumor diameter reduction rate [(30.7%±15.1%) vs.(7.2%±12.6%)] and portal vein cancer thrombus control rate [100% (12/12) vs. 64.3% (9/14)], the differences were statistically significant ( P<0.05);The incidences of leukocyte and platelet decrease in the two groups during the course of treatment were 71.4%(10/14) vs. 34.6%(9/26)、78.5%(11/14) vs. 38.5%(10/26), and the incidences of liver function abnormalities were 35.7%(5/14) vs. 69.2%(18/26), the differences were statistically significant ( P<0.05);The objective response rate and disease control rate were 57.1%(8/14) vs. 30.8% (8/26)、71.4% (10/14) vs. 53.8%(14/26), all statistically significant. Conclusion:HAIC combined with targeted therapy and immunnotherapy is a safe and effective treatment for middle and advanced HCC, especially suitable for patients with portal vein tumor thrombus(PVTT), large tumor, or poor liver function.

Objective:To evaluate the clinical efficacy of transoral robotic surgery (TORS) in the treatment of malignant tongue base tumors.Methods:A multicenter study was conducted to collect and analyze the clinical data of patients with malignant tongue base tumors who underwent TORS at five otolaryngology-head and neck surgery centers in China, including Eye Ear Nose and Throat Hospital of Fudan University, Sun Yat-sen University Cancer Center, Tongji Hospital of Huazhong University of Science and Technology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, and the First Affiliated Hospital of China Medical University between January 2017 and January 2023. Among the patients, 38 were males and 11 were females, with a mean age of 59.0±8.8 years. Baseline characteristics, complications, and follow-up data were compared between groups. Independent sample t-tests or Mann-Whitney U tests was used for comparisons of continuous variables; chi-square tests or Fisher′s exact tests was applied for categorical variables. Survival analysis was performed using the Kaplan-Meier method to calculate overall survival and disease-free survival, and differences between groups were compared using the log-rank test. Results:Among the 49 patients, 41 (83.7%) were diagnosed with squamous cell carcinoma (SCC), with a p16 positive rate of 51.2% (21/41). There were no statistically significant differences between the p16-positive group ( n=21) and the p16-negative group ( n=20) in age, sex, or postoperative bleeding (all P>0.05). However, there was a significant difference in TNM stage between the two groups ( χ2=14.556, P=0.020), with the p16-positive group predominantly in stage I (66.7%) and the p16-negative group primarily in stages Ⅲ and Ⅳ (40.0% and 30.0%, respectively). The postoperative tracheotomy rate was 30.6% (15/49), and the incidence of postoperative bleeding was 6.1% (3/49). The 1-year and 3-year overall survival rates were 98.0% and 92.5%, respectively, while, the 1-year and 3-year disease-free survival rates were 89.2% and 84.9%, respectively. No significant differences were observed between the p16-positive and p16-negative groups in 3-year overall survival (100% vs. 83.8%, χ2=1.093, P=0.518) or 3-year disease-free survival (68.2% vs. 88.9%, χ2=2.161, P=0.382). Conclusion:TORS for malignant tongue base tumors demonstrates high clinical safety and favorable oncological outcomes.

Objective:To apply artificial intelligence（AI）in classifying ovarian tumors on ultrasound images，and compare the diagnostic results of several sonographers with varying seniority levels.Methods:A total of 645 patients diagnosed with adnexal masses via gynecological ultrasound examination at Qilu Hospital of Shandong University from January 2021 to December 2024 were enrolled. Three deep learning architectures，i.e.，Alexnet，Densenet121，and Resnet50 were developed and used to internally test the classification effectiveness of ovarian tumors，while the optimal model was selected for external testing. Two junior sonographers and two senior sonographers were recruited to independently diagnose ovarian tumors in the external test dataset. Subsequently，the benign and malignant results of the model's predictions were disclosed to each sonographer，and their revised diagnoses on the same external test data in combination with the best AI model were recorded.Results:The optimal model achieved an accuracy of 0.941，sensitivity of 0.936，and specificity of 0.944 on the internal test dataset，and maintained robust performance on the external test dataset with accuracy of 0.891，sensitivity of 0.880，and specificity of 0.907. Compared to junior sonographers，the optimal model demonstrated significantly higher sensitivity in discriminating benign from malignant ovarian tumors（0.880 vs. 0.723，0.602；all P<0.05）. No statistically significant difference was observed in diagnostic accuracy between the optimal model and senior sonographer 1（ P=0.05）. With assistance from the optimal model，junior sonographers achieved significant improvements in both sensitivity and specificity（sensitivity：0.723 vs. 0.843，0.602 vs. 0.819；specificity：0.778 vs. 0.833，0.685 vs. 0.741；all P<0.05）. Conclusions:The optimal model achieves comparable performance to that of senior sonographers in ovarian tumor classification. With model assistance，the diagnostic performance of junior sonographers is significantly improved.

OBJECTIVE To explore the value of healthcare failure mode and effect analysis mode(HFMEA)com-bined with enhanced management of link quality in centralized processing of rigid endoscopic instruments.METHODS Totally 80 pieces of rigid endoscopic instruments that were recycled by the endoscopy room of otolar-yngology department of The First Medical Center of PLA General Hospital from Jan.2022 to Dec.2022 were as-signed as the control group,and 70 pieces of rigid endoscopic instruments that were recycled under the HFMEA model combined with enhanced management of link quality from Jan.2023 to Dec.2023 were assigned as the ex-perimental group.The effect of the management and the qualified rate of instruments were compared between the two groups of instruments,compare the satisfaction under the different intervention modes.RESULTS The scores of instrument disassembly and assembly,cleaning procedures,cleaning quality,environmental management and packaging quality were higher in the experimental group than in the control group(P＜0.05).The unqualified rate of instruments of the experimental group was 10.00％,lower than 23.75％of the control group(x2=4.926,P=0.026).The staff's satisfaction with the work of the experimental group was 91.67％,higher than 66.67％of the control group(Z=2.026,P=0.043).CONCLUSION For the centralized management of rigid endoscopic in-struments,the implementation of the enhanced management of link quality under the HFMEA mode can effective-ly improve the effect of management of the instruments and reduce the unqualified rate of recycled instruments,demonstrating a positive effect on raising the staff's satisfaction with the recycle process of instruments.

Objective: To examine the mediating effect of frailty on social isolation and cognitive function among the elderly. Methods: Demographic information, smoking, alcohol consumption and cognitive function of the elderly at ages of 60 years and older were collected from the China Health and Retirement Longitudinal Study 2020. Social isolation and frailty were evaluated using social isolation index and frailty index, respectively. The mediating effect of frailty on social isolation and cognitive function was analyzed using the Process program, and the significance of the mediating role was tested using the Bootstrap test. Results: A total of 2 822 individuals were enrolled, including 1 483 males (52.55%) and 1 339 females (47.45%). There were 2 497 (88.48%) and 325 (11.52%) individuals at ages of 60-<75 years and ≥75 years, respectively. The median cognitive function score was 14 (interquartile range, 16) points. There were 432 cases with social isolation (15.31%), with a median social isolation index of 10 (interquartile range, 5) points. The median frailty index was 0.11 (interquartile range, 0.15). There were 1 111 individuals without frailty, accounting for 39.37%; 1 214 individuals with pre-frailty, accounting for 43.02%; and 497 individuals with frailty, accounting for 17.61%. Mediating effect analysis showed that social isolation affected cognitive function directly and negatively with the effect value of -0.773 (95%CI: -0.899 to -0.647), and also affected cognitive function by frailty indirectly and negatively with the effect value of -0.147 (95%CI: -0.188 to -0.110), with the mediating effect contributed 15.98% of the total effect. Conclusion Frailty can directly or indirectly affect cognitive function among elderly through social isolation.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.