ObjectiveTo explore the characteristics of traditional Chinese medicine （TCM） syndromes in the patients with concurrent knee osteoarthritis （KOA） and postmenopausal osteoporosis （PMOP） and provide a scientific basis for precise TCM syndrome differentiation， diagnosis， and treatment of such concurrent diseases. MethodsA prospective， multicenter， cross-sectional clinical survey was conducted to analyze the characteristics of TCM syndromes in the patients with concurrent PMOP and KOA. Excel 2021 was used to statistically analyze the general characteristics of the included patients. Continuous variables were reported as x¯±s， and binary variables were reported as percentages. UCINET and Gephi were used to construct a complex "isease-syndrome-symptom" network for in-depth mining. Topological structure indicators， edge connection information between nodes， and weighted adjacency matrices were calculated by UCINET and Python. Gephi was used for complex network visualization. ResultsA total of 157 patients with concurrent PMOP and KOA from 12 TCM hospitals or community health service centers were selected for the collection of TCM syndrome and symptom information. A total of 4 main TCM syndromes were obtained， which were kidney-Yang deficiency （47.13%）， liver-kidney Yin deficiency （36.94%）， spleen-kidney Yang deficiency （8.92%）， and kidney Yin-Yang deficiency （7.01%）. In addition， 10 concurrent syndromes （mainly Qi stagnation and blood stasis， Qi and blood deficiency， spleen Yang deficiency， and cold-dampness） were identified. Based on the results of comprehensive frequency statistics and complex network analysis， as well as TCM theoretical knowledge and relevant guidelines， the general characteristics of concurrent PMOP and KOA and the main TCM syndromes in the dimensions of physical symptoms， pain， tongue and pulse manifestations， and defecation and urination were obtained. ConclusionThe main TCM syndromes in the patients with concurrent PMOP and KOA may be kidney Yang deficiency， liver-kidney Yin deficiency， spleen-kidney Yang deficiency， and kidney Yin-Yang deficiency， among which kidney Yang deficiency and liver-kidney Yin deficiency are the core TCM syndromes.

ObjectiveTo explore the characteristics of traditional Chinese medicine （TCM） syndromes in the patients with concurrent knee osteoarthritis （KOA） and postmenopausal osteoporosis （PMOP） and provide a scientific basis for precise TCM syndrome differentiation， diagnosis， and treatment of such concurrent diseases. MethodsA prospective， multicenter， cross-sectional clinical survey was conducted to analyze the characteristics of TCM syndromes in the patients with concurrent PMOP and KOA. Excel 2021 was used to statistically analyze the general characteristics of the included patients. Continuous variables were reported as x¯±s， and binary variables were reported as percentages. UCINET and Gephi were used to construct a complex "isease-syndrome-symptom" network for in-depth mining. Topological structure indicators， edge connection information between nodes， and weighted adjacency matrices were calculated by UCINET and Python. Gephi was used for complex network visualization. ResultsA total of 157 patients with concurrent PMOP and KOA from 12 TCM hospitals or community health service centers were selected for the collection of TCM syndrome and symptom information. A total of 4 main TCM syndromes were obtained， which were kidney-Yang deficiency （47.13%）， liver-kidney Yin deficiency （36.94%）， spleen-kidney Yang deficiency （8.92%）， and kidney Yin-Yang deficiency （7.01%）. In addition， 10 concurrent syndromes （mainly Qi stagnation and blood stasis， Qi and blood deficiency， spleen Yang deficiency， and cold-dampness） were identified. Based on the results of comprehensive frequency statistics and complex network analysis， as well as TCM theoretical knowledge and relevant guidelines， the general characteristics of concurrent PMOP and KOA and the main TCM syndromes in the dimensions of physical symptoms， pain， tongue and pulse manifestations， and defecation and urination were obtained. ConclusionThe main TCM syndromes in the patients with concurrent PMOP and KOA may be kidney Yang deficiency， liver-kidney Yin deficiency， spleen-kidney Yang deficiency， and kidney Yin-Yang deficiency， among which kidney Yang deficiency and liver-kidney Yin deficiency are the core TCM syndromes.

Objective To explore the clinical value of artificial intelligence (AI) quantitative parameters in distinguishing pathological grades of stageⅠ invasive adenocarcinoma (IAC). Methods Clinical data of patients with clinical stageⅠ IAC admitted to Yantaishan Hospital Affiliated to Binzhou Medical University from October 2018 to May 2023 were retrospectively analyzed. Based on the 2021 WHO pathological grading criteria for lung adenocarcinoma, IAC was divided into gradeⅠ, grade Ⅱ, and grade Ⅲ. The differences in parameters among the groups were compared, and logistic regression analysis was used to evaluate the predictive efficacy of AI quantitative parameters for grade Ⅲ IAC patients. Parameters were screened using least absolute shrinkage and selection operator (LASSO) regression analysis. Three machine learning models were constructed based on these parameters to predict grade Ⅲ IAC and were internally validated to assess their efficacy. Nomograms were used for visualization. Results A total of 261 IAC patients were included, including 101 males and 160 females, with an average age of 27-88 (61.96±9.17) years. Six patients had dual primary lesions, and different lesions from the same patient were analyzed as independent samples. There were 48 patients of gradeⅠ IAC, 89 patients of grade Ⅱ IAC, and 130 patients of grade Ⅲ IAC. There were statitical differences in the AI quantitive parameters such as consolidation/tumor ratio (CTR), ect among the three goups. (P<0.05). Univariate analysis showed that the differences in all variables except age were statistically significant (P<0.05) between the group gradeⅠ+grade Ⅱand the group grade Ⅲ . Multivariate analysis suggested that CTR and CT standard deviation were independent risk factors for identifying grade Ⅲ IAC, and the two were negatively correlated. Grade Ⅲ IAC exhibited advanced TNM staging, more pathological high-risk factors, higher lymph node metastasis rate, and higher proportion of advanced structure. CTR was positively correlated with the proportion of advanced structures in all patients. This correlation was also observed in grade Ⅲ but not in gradeⅠand grade ⅡIAC. CTR and CT median value were selected by using LASSO regression. Logistic regression, random forest, and XGBoost models were constructed and validated, among which, the XGBoost model demonstrated the best predictive performance. Conclusion Cautious consideration should be given to grade Ⅲ IAC when CTR is higher than 39.48% and CT standard deviation is less than 122.75 HU. The XGBoost model based on combined CTR and CT median value has good predictive efficacy for grade Ⅲ IAC, aiding clinicians in making personalized clinical decisions.

Objective To develop a deep learning method for volumetric assessment of traumatic intracerebral hemorrhage(TICH)using the Trans-UNet model and to compare its performance with traditional formula-based methods.Methods CT data from 141 TICH patients admitted to Army Medical Center of PLA between May 2018 and May 2023 were collected.A deep learning method based on the Trans-UNet model was established.Manual delineation via picture archiving and communication system(PACS)was served as the gold standard for comparing the accuracy,consistency,and time efficiency of our method against 10 different formula-based methods for measuring the amount of TICH.Results The median volume of TICH,as manual delineation via PACS,was 1.167 mL,with a median measurement time of 135 s per patient.The median percentage error in volume between the deep learning method and manual delineation via PACS was 3.59％.Spearman correlation coefficient was 0.999(P＜0.001),and a median measurement time was only 4.38 s per patient.In contrast,in the formula-based methods,the lowest median percentage error in volume was 16.451％,the highest Spearman correlation coefficient was 0.986(P＜0.001),and the lowest median measurement time was 20 s for a single patient.The statistical differences were observed in percentage error in volume and measurement time between the 2 types of methods(all P＜0.001).Conclusion Our developed deep learning method for volumetric assessment of TICH is superior to the formula-based methods in terms of measurement accuracy and time efficiency.

Endodontic diseases are a kind of chronic infectious oral disease.Common endodontic treatment concepts are based on the removal of inflamed or necrotic pulp tissue and the replacement by gutta-percha.However,it is very essential for endodontic treatment to debride the root canal system and prevent the root canal system from bacterial reinfection after root canal therapy(RCT).Recent research,encompassing bacterial etiology and advanced imaging techniques,contributes to our understanding of the root canal system's anatomy intricacies and the technique sensitivity of RCT.Success in RCT hinges on factors like patients,infection severity,root canal anatomy,and treatment techniques.Therefore,improving disease management is a key issue to combat endodontic diseases and cure periapical lesions.The clinical difficulty assessment system of RCT is established based on patient conditions,tooth conditions,root canal configuration,and root canal needing retreatment,and emphasizes pre-treatment risk assessment for optimal outcomes.The findings suggest that the presence of risk factors may correlate with the challenge of achieving the high standard required for RCT.These insights contribute not only to improve education but also aid practitioners in treatment planning and referral decision-making within the field of endodontics.

Chemical cleaning and disinfection are crucial steps for eliminating infection in root canal treatment.However,irrigant selection or irrigation procedures are far from clear.The vapor lock effect in the apical region has yet to be solved,impeding irrigation efficacy and resulting in residual infections and compromised treatment outcomes.Additionally,ambiguous clinical indications for root canal medication and non-standardized dressing protocols must be clarified.Inappropriate intracanal medication may present side effects and jeopardize the therapeutic outcomes.Indeed,clinicians have been aware of these concerns for years.Based on the current evidence of studies,this article reviews the properties of various irrigants and intracanal medicaments and elucidates their effectiveness and interactions.The evolution of different kinetic irrigation methods,their effects,limitations,the paradigm shift,current indications,and effective operational procedures regarding intracanal medication are also discussed.This expert consensus aims to establish the clinical operation guidelines for root canal irrigation and a position statement on intracanal medication,thus facilitating a better understanding of infection control,standardizing clinical practice,and ultimately improving the success of endodontic therapy.

Objective:To understand the epidemiological characteristics of human respiratory syncytial virus (HRSV) among acute respiratory infection (ARI) cases in 16 provinces of China from 2009 to 2023.Methods:The data of this study were collected from the ARI surveillance data from 16 provinces in China from 2009 to 2023, with a total of 28 278 ARI cases included in the study. The clinical specimens from ARI cases were screened for HRSV nucleic acid from 2009 to 2023, and differences in virus detection rates among cases of different age groups, regions, and months were analyzed.Results:A total of 28 278 ARI cases were enrolled from January 2009 to September 2023. The age of the cases ranged from<1 month to 112 years, and the age M ( Q1, Q3) was 3 years (1 year, 9 years). Among them, 3 062 cases were positive for HRSV nucleic acid, with a total detection rate of 10.83%. From 2009 to 2019, the detection rate of HRSV was 9.33%, and the virus was mainly prevalent in winter and spring. During the Corona Virus Disease 2019 (COVID-19) pandemic, the detection rate of HRSV fluctuated between 6.32% and 18.67%. There was no traditional winter epidemic peak of HRSV from the end of 2022 to the beginning of 2023, and an anti-seasonal epidemic of HRSV occurred from April to May 2023. About 87.95% (2 693/3 062) of positive cases were children under 5 years old, and the difference in the detection rate of HRSV among different age groups was statistically significant ( P<0.001), showing a decreasing trend of HRSV detection rate with the increase of age ( P<0.001). Among them, the HRSV detection rate (25.69%) was highest in children under 6 months. Compared with 2009-2019, the ranking of HRSV detection rates in different age groups changed from high to low between 2020 and 2023, with the age M (Q1, Q3) of HRSV positive cases increasing from 1 year (6 months, 3 years) to 2 years (11 months, 3 years). Conclusion:Through 15 years of continuous HRSV surveillance analysis, children under 5 years old, especially infants under 6 months old, are the main high-risk population for HRSV infection. During the COVID-19 pandemic, the prevalence and patterns of HRSV in China have changed.

This study focuses on the cases(mainly characterized by respiratory symptoms such as cough, runny nose, fever, sore throat, and nasal congestion)of an outbreak of upper respiratory tract infections in a kindergarten in Jingyuan County, Baiyin City, Gansu Province, in May 2023. The epidemiological data were collected, and pharyngeal swab specimens were also obtained from the patients. The specimens of the research participants were subjected to respiratory multi-pathogen testing, and the positive specimens were further analyzed by sequencing the second hypervariable region (HRV2) of the G gene of respiratory syncytial virus (RSV) and constructing a phylogenetic tree. A total of 90 patients were collected, with an incidence rate of 22.84% (90/394), and the highest incidence was observed in the junior class group at 29.55%. Among the 17 pharyngeal swab specimens collected, 16 specimens were identified with the A subtype of respiratory syncytial virus. Sequencing analysis confirmed that it was the A subtype ON1 genotype. Based on the aforementioned testing results, it can be concluded that the current epidemic was primarily caused by infection with the A subtype of respiratory syncytial virus. Following the implementation of intervention measures, the epidemic has been effectively controlled.

Objective:To compare the prevalence of frailty and related factors in middle-aged and elderly people aged ≥45 years in island and mountainous areas of Taizhou, Zhejiang Province.Methods:Based on cross-sectional design, stratified cluster sampling and quota sampling methods were adopted. One administrative district was randomly selected from each of six coastal and three inland administrative districts in Taizhou during July to August, representing two different geographical terrains. In the island area (Jiaojiang District), all residents aged ≥45 years were included by cluster sampling. In the mountainous area (Xianju County), participants were selected through quota sampling, with same gender and age distributions. Data about their demographic characteristics, lifestyle and health-related factors were collected through questionnaire surveys and laboratory examinations. The prevalence of frailty was assessed using the Fried frailty phenotype scale. Hierarchical analysis and multivariate logistic regression analysis were used to compare the influencing factors of frailty.Results:A total of 1 011 local residents were studied, in whom island and mountainous residents accounted for 48.1% (486/1 011) and 51.9% (525/1 011) respectively; men and women accounted for 45.9% (464/1 011) and 54.1% (547/1 011) respectively. Middle-aged (45-49 years), younger elderly (60-74 years), and older elderly (≥75 years) residents accounted for 38.6% (390/1 011), 44.6% (451/1 011), and 16.8% (170/1 011) respectively. The overall prevalence rate of frailty was 3.6% (36/1 011), the prevalence rate was 3.7% (17/464) in men and 3.5% (19/547) in women. The prevalence rates in age groups 45-59,60-74 years and ≥75 years were 0.3% (1/390), 2.2% (10/451), and 14.7% (25/170), respectively. The prevalence rates of frailty and pre-frailty in island area were 6.0% (29/486) and 39.1% (190/486), respectively, which was higher than those in mountainous area (1.3%, 7/525) and (30.9%, 162/525). After adjusting for potential confounding factors, the risk for frailty in island residents was significantly higher than that in mountainous residents (a OR=1.55,95% CI: 1.07-2.25, P=0.019). In island area, older age (60-74 years:a OR=2.52,95% CI: 1.56-4.13; ≥75 years:a OR=11.65,95% CI:5.38-26.70), being women (a OR=1.94,95% CI: 1.20-3.17), suffering from depression (a OR=1.09,95% CI:1.02-1.17) were associated with frailty symptoms. In mountainous area, older age was also associated with an increased risk of frailty symptoms, but the OR value was lower than those in island area (60-74 years: a OR=1.74,95% CI:1.04-2.94;≥75 years: a OR=4.78,95% CI:2.45-9.50). Polydrug use (a OR=2.08,95% CI: 1.14-3.80) and suffering from depression (a OR=1.10,95% CI: 1.02-1.18) had significant positive association with frailty symptoms. Higher education level had significant negative association with frailty symptoms (junior high school: a OR=0.40,95% CI: 0.21-0.75; senior high school and technical secondary school: a OR=0.29,95% CI: 0.15-0.53; college or above:a OR=0.22,95% CI: 0.11-0.42). Conclusions:The prevalence of frailty in middle-aged and elderly community residents was significantly higher in island area than in mountainous area in Taizhou. The frailty-related factors varied with area. The elderly people (≥75 years) and women in island area had higher risk for frailty. Older age and suffering from depression were the independent risk factors for frailty. It is necessary to pay attention to the health risk factors and special environment in island area, and take comprehensive intervention measures to delay the process of debilitation and improve the quality of life of middle-aged and elderly people.

Objective To investigate the mechanism of astragaloside Ⅰ,the active constituent of milkvetch root,in inhibiting podocyte injury and improving diabetic kidney disease.Methods According to the body weight,60 male db/db mice were randomly divided into the model group,astragaloside Ⅰ low-dose group(10 mg/kg),astragaloside Ⅰ medium-dose group(20 mg/kg),astragaloside Ⅰ high-dose group(40 mg/kg),and valsartan group(10mg/kg),with 12 mice per group.Twelve db/db littermate control db/m mice were used as the control group.The drug was administered by gavage for 8 weeks.Transmission electron microscope was used to observe the ultrastructure of the kidney;immunohistochemistry and Western blotting were used to detect the expression of nephrotic protein(nephrin),a marker of renal podocytes;enzyme-linked immunosorbent assay was used to detect the contents of interleukin-1β(IL-1β)and interleukin-18(IL-18)in the serum of mice;Western blotting was used to detect the protein expressions of NOD-like receptor thermoprotein domain-related protein 3(NLRP3),cysteinyl aspartate specific proteinase 1(Caspase-1),and Gasdermin D(GSDMD)in kidney tissue.Results Compared with the control group,the glomeruli of the model group showed obvious podocyte loss and foot process fusion;the protein expression of nephrin was decreased(P＜0.05);the contents of IL-1 β and IL-18 in serum were increased(P＜0.05);the protein expressions of NLRP3,Cleaved-Caspase-1,and GSDMD-N were increased(P＜0.05).Compared with the model group,the renal pathological damage in the astragaloside Ⅰ administration groups were alleviated;the protein expression of nephrin was increased(P＜0.05);the contents of IL-1β and IL-18 in serum were decreased(P＜0.05);the protein expressions of NLRP3,Cleaved-Caspase-1,and GSDMD-N were decreased(P＜0.05).Conclusion Astragaloside Ⅰ may play a role in intervening diabetic kidney disease by inhibiting pyroptosis and improving podocyte injury.