Through a comprehensive analysis combining network pharmacology prediction and transcriptomics, this study systematically explained the multi-target mechanism of Cyanotis arachnoidea(CA) Gel in improving melasma. A melasma model was induced in female SD rats by progesterone injection combined with ultraviolet B(UVB) irradiation for 40 consecutive days, while the blank control group was only fed routinely. After successful model establishment, the rats were randomly divided into five groups and administered different doses of CA ethanol extract gel(high, medium, and low doses) or arbutin Gel(positive control), which were applied once daily for 28 consecutive days. Subsequently, the levels of superoxide dismutase(SOD), malondialdehyde(MDA), and tyrosinase(TYR) in the skin, serum, and liver tissues were measured. Hematoxylin-eosin(HE) staining and Masson-Fontana staining were used to observe the pathological changes in the tissues. Network pharmacology combined with transcriptomics was employed to identify core targets and pathways, and the differential gene expression was validated by quantitative real-time PCR(qPCR). Pharmacodynamic experiments showed that CA Gel significantly increased SOD activity and decreased MDA and TYR levels in the skin, serum, and liver of model rats. It also improved epidermal thickening, inflammatory infiltration, collagen loss, and melanin deposition. Network pharmacology analysis showed that CA mainly regulated core targets such as signal transducer and activator of transcription 3(STAT3), epidermal growth factor receptor(EGFR), and interleukin-6(IL-6), and modulated the phosphatidylinositol 3-kinase(PI3K)-protein kinase B(AKT) and interleukin-17(IL-17) signaling pathways. Transcriptomic analysis showed that CA Gel significantly downregulated the gene expression of heat shock protein 90β family member 1(Hsp90b1), heat shock protein 90α family member 1(Hsp90aa1), and the key steroid synthesis enzyme cytochrome P450 family 17 subfamily A member 1(Cyp17a1), while upregulating thioredoxin 1(Txn1). qPCR results confirmed that CA Gel regulated oxidative stress and inflammatory response by inhibiting the IL-17 signaling pathway and steroid hormone synthesis. This study, for the first time, reveals the molecular mechanism of CA Gel in improving melasma through multi-target synergistic regulation of oxidative stress, inflammatory response, and hormone metabolism pathways, providing a scientific basis for the treatment of pigmentation diseases with traditional Chinese medicine.
Animals ; Rats ; Female ; Rats, Sprague-Dawley ; Network Pharmacology ; Drugs, Chinese Herbal/administration & dosage* ; Melanosis/metabolism* ; Transcriptome/drug effects* ; Humans ; Superoxide Dismutase/genetics* ; Signal Transduction/drug effects* ; Malondialdehyde/metabolism*

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

Hypoxemia is a common pathological state characterized by low oxygen saturation in the blood. This condition compromises mucosal barrier integrity particularly in the gut and oral cavity. However, the mechanisms underlying this association remain unclear. This study used periodontitis as a model to investigate the role of platelet activation in oral mucosal immunopathology under hypoxic conditions. Hypoxia upregulated methyltransferase-like protein 4 (METTL4) expression in platelets, resulting in N⁶-methyladenine modification of mitochondrial DNA (mtDNA). This modification impaired mitochondrial transcriptional factor A-dependent cytosolic mtDNA degradation, leading to cytosolic mtDNA accumulation. Excess cytosolic mt-DNA aberrantly activated the cGAS-STING pathway in platelets. This resulted in excessive platelet activation and neutrophil extracellular trap formation that ultimately exacerbated periodontitis. Targeting platelet METTL4 and its downstream pathways offers a potential strategy for managing oral mucosa immunopathology. Further research is needed to examine its broader implications for mucosal inflammation under hypoxic conditions.
DNA, Mitochondrial/metabolism* ; Mouth Mucosa/pathology* ; Hypoxia/immunology* ; Methyltransferases/metabolism* ; Blood Platelets/metabolism* ; Animals ; Periodontitis/immunology* ; Humans ; Platelet Activation ; Mice

This study aimed to comprehensively examine the association of gallstones, cholecystectomy, and cancer risk. Multivariable logistic regressions were performed to estimate the observational associations of gallstones and cholecystectomy with cancer risk, using data from a nationwide cohort involving 239 799 participants. General and gender-specific two-sample Mendelian randomization (MR) analysis was further conducted to assess the causalities of the observed associations. Observationally, a history of gallstones without cholecystectomy was associated with a high risk of stomach cancer (adjusted odds ratio (aOR)=2.54, 95% confidence interval (CI) 1.50-4.28), liver and bile duct cancer (aOR=2.46, 95% CI 1.17-5.16), kidney cancer (aOR=2.04, 95% CI 1.05-3.94), and bladder cancer (aOR=2.23, 95% CI 1.01-5.13) in the general population, as well as cervical cancer (aOR=1.69, 95% CI 1.12-2.56) in women. Moreover, cholecystectomy was associated with high odds of stomach cancer (aOR=2.41, 95% CI 1.29-4.49), colorectal cancer (aOR=1.83, 95% CI 1.18-2.85), and cancer of liver and bile duct (aOR=2.58, 95% CI 1.11-6.02). MR analysis only supported the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer. This study added evidence to the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer, highlighting the importance of cancer screening in individuals with gallstones.
Humans ; Mendelian Randomization Analysis ; Gallstones/complications* ; Female ; Male ; Cholecystectomy/statistics & numerical data* ; Middle Aged ; Risk Factors ; Aged ; Adult ; Neoplasms/etiology* ; Stomach Neoplasms/epidemiology*

Objective:To characterize the epidemiology of respiratory syndrome across healthcare facilities of different types and tiers in Beijing City, to compare pathogen-testing modalities and their associations with adverse outcomes, and to identify key factors associated with progression to severe illness, thereby informing regional prevention, control, and clinical optimization.Methods:The multicenter observational cohort study was performed using outpatient and emergency department data from five sentinel hospitals in Beijing (Beijing Xiaotangshan Hospital, Beijing Chaoyang District Shuangqiao Hospital, Beijing Haidian Hospital, Beijing You′an Hospital, Capital Medical University (Beijing You′an Hospital), and Beijing Ditan Hospital, Capital Medical University (Beijing Ditan Hospital)) from October 1st, 2023 to April 9th, 2025. Dual-target (two-plex) and triple-target (three-plex) respiratory specimens were collected. Demographic characteristics, visit information, pathogen-testing modalities and results were collected, and the epidemiologic features of patients who progressed to severe illness between the influenza high-incidence season (December to May) and the non-influenza season (June to November) were compared. Categorical variables were analyzed using the chi-square test. Multivariable logistic regression was used to estimate associations between covariates and risk of progression to severe illness.Results:Among the 192 131 cases, patients visited at Beijing You′an Hospital were concentrated in the 16 to 44 year age group, accounting for 66.79%(32 532/48 708). Beijing Xiaotangshan Hospital had a broad age distribution, with older adults comprising up to 22.35% (885/3 960). Of the 47 349 respiratory specimens across the five hospitals, Beijing You′an Hospital had the highest positivity rate for dual-target testing (46.76%(1 585/3 390)), while Beijing Haidian Hospital conducted the largest number of this tests ( n=12 514). For triple-target testing, Beijing You′an Hospital again had the highest positivity rate (45.03%(2 835/6 296)), whereas Beijing Ditan Hospital tested the most specimens ( n=12 011; positivity rate was 29.73%(3 571/12 011)). The influenza season within the same period (November 2023 to January 2024) exhibited a bimodal pattern, with alternating circulation of influenza viruses and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Among 32 744 outpatients/emergency patients who progressed to severe illness, significant seasonal differences were observed by sex, age, comorbidity status, and infection type ( χ2=6.60, 189.24, 32.71 and 189.99, respectively; all P<0.05). After adjustment for sex, age group, comorbidities, and infection type, testing modality remained significantly associated with risk of progression (dual-target testing, odds ratio ( OR)=0.116, 95% confidence interval ( CI) 0.111 to 0.122, P<0.001); no testing, OR=0.063, 95% CI 0.060 to 0.065, P<0.001). Conclusions:The epidemiological pattern of respiratory pathogens undergo significant changes after October 2023, which is characterized by alternating waves of influenza viruses and SARS-CoV-2 with pronounced seasonality and diversity. Substantial inter-hospital differences are observed in testing modalities and positivity rates. Risk of progression to severe illness varies significantly by sex, age, comorbidity burden, and infection type, and is closely associated with the testing modality. These findings support strengthening multiplex pathogen testing and targeted surveillance of high-risk groups to improve early identification and precise control of febrile-respiratory syndromes.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To explore the association between the systemic immune-inflammation index (SII) and obesity metabolic phenotypes, as well as metabolic features in children and adolescents.Methods:A cross-sectional study was conducted using the random cluster sampling method from March 2023 to May 2024. Children and adolescents aged 9-17 years in Guangzhou were surveyed through questionnaires, physical measurements, and blood tests. According to BMI and metabolic status, participants were classified into normal-weight groups [metabolically healthy normal weight (MHNW) and metabolically unhealthy normal weight (MUNW)] and overweight/obese groups [metabolically healthy overweight/obese (MHO/O) and metabolically unhealthy overweight/obese (MUO/O)]. After natural log-transformation of SII values (lnSII), multinomial logistic regression was used to assess the association between SII and obesity metabolic phenotypes, while binary logistic regression was applied to assess the relationship between SII and metabolic phenotypes in the overweight/obese subgroup. Linear regression model and restricted cubic spline (RCS) were employed to examine the relationship between SII and metabolic features among the entire population.Results:A total of 3 749 participants were included. After adjusting for covariates, for every unit increase in lnSII, the risk of MHO/O and MUO/O increased by 93% ( OR=1.93, 95% CI: 1.56-2.40, P<0.001) and 156% ( OR=2.56, 95% CI: 2.02-3.25, P<0.001), respectively. In the overweight/obesity subgroup, for every unit increase in lnSII, the risk of MUO/O increased by 37% ( OR=1.37, 95% CI: 1.01-1.87, P=0.045). Linear regression model and RCS showed that lnSII was positively correlated with systolic blood pressure (SBP) and diastolic blood pressure (DBP) (SBP: β=1.39, 95% CI: 0.67-2.11, P<0.001; DBP: β=1.27, 95% CI: 0.79-1.75, P<0.001). lnSII also had a non-linear relationship with triglyceride ( Pnonlinear=0.032) and high-density lipoprotein cholesterol ( Pnonlinear=0.002). Conclusion:Elevated SII levels are associated with unfavorable obesity metabolic phenotypes, higher blood pressure, and altered lipid profiles in children and adolescents. SII may be a potential driving factor for metabolic heterogeneity in children and adolescents.

Objective:To develop and validate a prediction model for medication adherence among patients receiving allergen sublingual immunotherapy (SLIT).Methods:A prospective cross-sectional study was conducted, and a total of 288 patients who received SLIT treatment at an allergy center in the First Affiliated Hospital with Nanjing Medical University (Jiangsu Province Hospital) from December 2023 to July 2024 were assigned to the modeling group. Additionally, 122 patients from August to October 2024 were assigned to the validation group. Data of patients′ general information, medication beliefs, anxiety levels, social support, disease perception, and medication adherence were collected. Single-factor analysis and LASSO regression were utilized to identify potential predictors, and a prediction model for medication adherence was constructed using multifactorial logistic regression. A nomogram was then developed based on the model. The model′s discriminatory ability was evaluated using receiver operating characteristic curve (ROC), the area under curve (AUC), sensitivity, and specificity. The model was then validated in the validation cohort.Results:Single-factor analysis and LASSO regression identified a total of nine predictive factors. Logistic regression revealed that medical belief tendency [ OR (95% CI) =2.420 (1.116-5.248), P=0.025], the somatic control dimension in self-rating anxiety scales [ OR (95% CI)=1.404 (1.241-1.589), P<0.001], the subjective support dimension in social support assessment [ OR (95% CI)=0.784 (0.725-0.847), P<0.001], and the cognitive dimension in illness perception [ OR (95% CI)=0.725 (0.647-0.813), P<0.001] were independent predictors of medication adherence in patients undergoing SLIT. The AUC value of the model was 0.899 (95% CI=0.863-0.934) in the modeling group and 0.882 (95% CI=0.820-0.944) in the validation group, indicating good discriminatory ability. The optimal cutoff value of the model was 0.493, with a sensitivity of 81.1% and specificity of 85.7% in the modeling group, and a sensitivity of 87.3% and specificity of 82.5% in the validation group. Conclusion:The medication adherence prediction model developed in this study for patients undergoing SLIT exhibits good predictive performance and provides valuable guidance for early intervention by clinical healthcare professionals.

Objective:To develop and validate a prediction model for medication adherence among patients receiving allergen sublingual immunotherapy (SLIT).Methods:A prospective cross-sectional study was conducted, and a total of 288 patients who received SLIT treatment at an allergy center in the First Affiliated Hospital with Nanjing Medical University (Jiangsu Province Hospital) from December 2023 to July 2024 were assigned to the modeling group. Additionally, 122 patients from August to October 2024 were assigned to the validation group. Data of patients′ general information, medication beliefs, anxiety levels, social support, disease perception, and medication adherence were collected. Single-factor analysis and LASSO regression were utilized to identify potential predictors, and a prediction model for medication adherence was constructed using multifactorial logistic regression. A nomogram was then developed based on the model. The model′s discriminatory ability was evaluated using receiver operating characteristic curve (ROC), the area under curve (AUC), sensitivity, and specificity. The model was then validated in the validation cohort.Results:Single-factor analysis and LASSO regression identified a total of nine predictive factors. Logistic regression revealed that medical belief tendency [ OR (95% CI) =2.420 (1.116-5.248), P=0.025], the somatic control dimension in self-rating anxiety scales [ OR (95% CI)=1.404 (1.241-1.589), P<0.001], the subjective support dimension in social support assessment [ OR (95% CI)=0.784 (0.725-0.847), P<0.001], and the cognitive dimension in illness perception [ OR (95% CI)=0.725 (0.647-0.813), P<0.001] were independent predictors of medication adherence in patients undergoing SLIT. The AUC value of the model was 0.899 (95% CI=0.863-0.934) in the modeling group and 0.882 (95% CI=0.820-0.944) in the validation group, indicating good discriminatory ability. The optimal cutoff value of the model was 0.493, with a sensitivity of 81.1% and specificity of 85.7% in the modeling group, and a sensitivity of 87.3% and specificity of 82.5% in the validation group. Conclusion:The medication adherence prediction model developed in this study for patients undergoing SLIT exhibits good predictive performance and provides valuable guidance for early intervention by clinical healthcare professionals.

Objective:To develop a deep learning-based system for real-time recognition and classification of portal hypertensive gastropathy (PHG) and evaluate its ability to assist junior endoscopists.Methods:A total of 2 848 gastroscopy images from 832 patients with liver cirrhosis were selected from Digestive Endoscopy Center databases of Renmin Hospital of Wuhan University, Wuhan Hospital of Traditional Chinese and Western Medicine, and the Second Hospital of Jingzhou from January 2015 to October 2023. This system referred to 3 endoscopic features of Baveno Ⅱ scoring system. Three models were developed respectively for gastric antral vascular ectasia (GAVE), mosaic-like pattern (MLP), and red marks (RM). The specific classification references were as follows: (1) GAVE model: 0 no, 1 yes; (2) MLP model: 0 no, 1 mild, 2 severe; (3) RM model: 0 no, 1 isolated, 2 fused. The classification results for endoscopic characteristics of PHG of 3 endoscopy experts were taken as the gold standard. The yolov8-m model was used for training. The training dataset, validation dataset, and test dataset were allocated at a ratio of 8∶1∶1. The test dataset was used to evaluate the performance of models and their auxiliary effects on endoscopists. The accuracy, recall, precision, specificity and Kappa coefficient were calculated. Results:The accuracy, recall, specificity of GAVE model were 96.0% (48/50), 87.5% (7/8) and 97.6% (41/42). There was no significant difference between its accuracy and the gold standard ( χ2=316.226, P=1.000). The precision of GAVE1 and GAVE0 were 87.5% (7/8) and 97.6% (41/42) respectively. The accuracy of MLP model was 84.1% (132/157), and there was no significant difference compared with the gold standard ( χ2=3.286, P=0.193). The precision and recall of MLP2 were 88.2% (15/17) and 75.0% (15/20). The precision and recall of MLP1 were 77.9% (60/77) and 88.2% (60/68). The precision and recall of MLP0 were 90.5% (57/63) and 82.6% (57/69). The accuracy of RM model was 87.9% (123/140), and there was no significant difference compared with the gold standard ( χ2=2.891, P=0.409). The precision and recall of RM2 were 94.7% (18/19) and 78.3% (18/23). The precision and recall of RM1 were 72.2% (26/36) and 81.3% (26/32). The precision and recall of RM0 were 92.9% (79/85) and 92.9% (79/85). The mean accuracy of the three junior endoscopists, with and without the assistance of the GAVE model, MLP model, and RM model, respectively increased from 95.3% to 99.3%, from 83.9% to 91.9%, and from 81.9% to 83.1%. The overall consistency analysis of the 3 junior endoscopists with the gold standard indicated that the consistency of the GAVE model before and after assistance was extremely strong (both an overall Kappa of 1.000); the consistency before assistance of the MLP model was moderate (with an overall Kappa of 0.601), which increased to extremely strong after assistance (with an overall Kappa of 0.964); and the consistency of the RM model before and after assistance was also relatively strong (with an overall Kappa of 0.792 before and 0.798 after). Conclusion:The deep learning system accurately identifies and classifies PHG features and significantly enhances diagnostic performance of junior endoscopists.