Objective:To explore the effects of a collaborative care model based on family-community- professional team on the oral health-related quality of life in older adults, and in order to provide reference basis for oral health management of the elderly.Methods:Using one-group pretest-posttest design study, 110 cases of older adults who participated in health checkups at the Yuyang Community Health Center in Yichang City from May 1 to June 30, 2023 were selected by convenience sampling method as study subjects. A oral health intervention program was constructed through literature review, Delphi expert consultation, and pilot trials and implemented for 6 months to compare the differences in oral health self-efficacy level, oral health-related quality of life before and after the intervention of the study subjects.Results:Finally, 108 study subjects completed the intervention including 49 males, 59 females, and 58 were 60-69 years old, 45 were 70-79 years old, and 5 were aged 80 and over; the total oral health self-efficacy score of older adults after the intervention was (59.19 ± 3.43) points, which was higher than (55.05 ± 5.10) points before the intervention, and the difference was statistically significant ( t = - 7.69, P<0.05); the total score of oral health-related quality of life after the intervention was (46.11 ± 5.14) points, which was higher than that before the intervention (41.39 ± 4.06), and the difference was statistically significant ( t = -7.02, P<0.05). Conclusions:The collaborative care model based on family-community- professional team can improve the level of oral health self-efficacy and oral health-related quality of life of the elderly, and provide a reference point for oral health management in the elderly.

Objective:To investigate the prevalence of albuminuria in Chinese residents aged >35 years and its potential association with cardiovascular disease (CVD).Methods:A total of 34 647 Chinese subjects aged ≥35 years were selected by stratified multi-stage random sampling from 2012 to 2015. Data were collected through questionnaires, physical examinations, and laboratory tests. Albuminuria was categorized into 3 types according to urinary albumin-to- creatinine ratio: normal (<30 mg/g), microalbuminuria (MAU, 30-300 mg/g), and macroalbuminuria (≥300 mg/g). Measurement data were expressed as xˉ±s, and t-tests were used for comparisons between indicators. Qualitative data were expressed as rate or constituent ratio, and the χ2 test or Kruskal-Wallis test was used to examine differences. Logistic regression was used for multivariate analyses. SAS 9.4 software was used for statistical analyses, and P<0.05 was considered statistically significant. Results:The prevalence of abnormal albuminuria was 19.1%; the prevalence was 17.2% for MAU and lower in males (13.8%) than females (20.1%, P<0.01). The risk of CVD was higher among subjects with MAU ( OR=1.23, 95% CI 1.12-1.35) and macroalbuminuria ( OR=1.86, 95% CI 1.50-2.32). When MAU was complicated by hypertension and diabetes mellitus, the CVD risk was 1.76 times higher. Conclusions:The prevalence of MAU is high among Chinese subjects aged 35 years and over. Those with MAU have higher CVD risk, especially those with hypertension and diabetes mellitus.

In China, the current standard for cosmetic adverse reactions related skin disease (GB/T 17149.1-1997) was jointly issued by the Ministry of Health and the State Bureau of Technical Supervision in 1997, cosmetic-allergic adverse reactions include allergic contact dermatitis and photo-allergic contact dermatitis according to this standard. The increasing use and changes in cosmetic ingredients or formula lead to a significant increase for the incidence of adverse reactions as the cosmetics industry is developing rapidly in the last 20 years. In the meantime, the clinical manifestations have become more diverse. In recent years, there have been many reports on the special manifestations for cosmetic allergy and allergen test, which provide a reference for the subsequent improvement of the diagnosis and prevention.
Humans ; Patch Tests/adverse effects* ; Dermatitis, Allergic Contact/therapy* ; Cosmetics/adverse effects* ; China ; Incidence ; Allergens/adverse effects*

Hypertrophic scar (HS) affects the function and beauty of patients, and brings a heavy psychological burden to patients. However, the specific pathogenesis mechanism of HS in molecular biology level is not yet clear, and this disease is still one of the clinical diseases difficult to prevent and cure. MicroRNA (miR) is a family of single-stranded endogenous noncoding RNAs that can regulate gene expression. The abnormal transcription of miR in hypertrophic scar fibroblasts can affect the transduction and expression of downstream signal pathway or protein, and the exploration of miR and its downstream signal pathway and protein helps deeply understand the occurrence and development mechanism of scar hyperplasia. This article summarized and analyzed how miR and multiple signal pathways involve in the formation and development of HS in recent years, and further outlined the interaction between miR and target genes in HS.
Humans ; MicroRNAs/genetics* ; Cicatrix, Hypertrophic/genetics* ; Fibroblasts ; Hyperplasia

Polymyxin B, which is a last-line antibiotic for extensively drug-resistant Gram-negative bacterial infections, became available in China in Dec. 2017. As dose adjustments are based solely on clinical experience of risk toxicity, treatment failure, and emergence of resistance, there is an urgent clinical need to perform therapeutic drug monitoring (TDM) to optimize the use of polymyxin B. It is thus necessary to standardize operating procedures to ensure the accuracy of TDM and provide evidence for their rational use. We report a consensus on TDM guidelines for polymyxin B, as endorsed by the Infection and Chemotherapy Committee of the Shanghai Medical Association and the Therapeutic Drug Monitoring Committee of the Chinese Pharmacological Society. The consensus panel was composed of clinicians, pharmacists, and microbiologists from different provinces in China and Australia who made recommendations regarding target concentrations, sample collection, reporting, and explanation of TDM results. The guidelines provide the first-ever consensus on conducting TDM of polymyxin B, and are intended to guide optimal clinical use.
Humans ; Anti-Bacterial Agents/therapeutic use* ; China ; Drug Monitoring/methods* ; Polymyxin B ; Practice Guidelines as Topic

The twenty-first century has already recorded more than ten major epidemics or pandemics of viral disease, including the devastating COVID-19. Novel effective antivirals with broad-spectrum coverage are urgently needed. Herein, we reported a novel broad-spectrum antiviral compound PAC5. Oral administration of PAC5 eliminated HBV cccDNA and reduced the large antigen load in distinct mouse models of HBV infection. Strikingly, oral administration of PAC5 in a hamster model of SARS-CoV-2 omicron (BA.1) infection significantly decreases viral loads and attenuates lung inflammation. Mechanistically, PAC5 binds to a pocket near Asp49 in the RNA recognition motif of hnRNPA2B1. PAC5-bound hnRNPA2B1 is extensively activated and translocated to the cytoplasm where it initiates the TBK1-IRF3 pathway, leading to the production of type I IFNs with antiviral activity. Our results indicate that PAC5 is a novel small-molecule agonist of hnRNPA2B1, which may have a role in dealing with emerging infectious diseases now and in the future.
Animals ; Mice ; Antiviral Agents/pharmacology* ; COVID-19 ; Hepatitis B virus ; Interferon Type I/metabolism* ; SARS-CoV-2/drug effects* ; Heterogeneous-Nuclear Ribonucleoprotein Group A-B/antagonists & inhibitors*

Objective: To establish a comprehensive diagnostic classification model of lateral cephalograms based on artificial intelligence (AI) to provide reference for orthodontic diagnosis. Methods: A total of 2 894 lateral cephalograms were collected in Department of Orthodontics, Capital Medical University School of Stomatology from January 2015 to December 2021 to construct a data set, including 1 351 males and 1 543 females with a mean age of (26.4± 7.4) years. Firstly, 2 orthodontists (with 5 and 8 years of orthodontic experience, respectively) performed manual annotation and calculated measurement for primary classification, and then 2 senior orthodontists (with more than 20 years of orthodontic experience) verified the 8 diagnostic classifications including skeletal and dental indices. The data were randomly divided into training, validation, and test sets in the ratio of 7∶2∶1. The open source DenseNet121 was used to construct the model. The performance of the model was evaluated by classification accuracy, precision rate, sensitivity, specificity and area under the curve (AUC). Visualization of model regions of interest through class activation heatmaps. Results: The automatic classification model of lateral cephalograms was successfully established. It took 0.012 s on average to make 8 diagnoses on a lateral cephalogram. The accuracy of 5 classifications was 80%-90%, including sagittal and vertical skeletal facial pattern, mandibular growth, inclination of upper incisors, and protrusion of lower incisors. The acuracy rate of 3 classifications was 70%-80%, including maxillary growth, inclination of lower incisors and protrusion of upper incisors. The average AUC of each classification was ≥0.90. The class activation heat map of successfully classified lateral cephalograms showed that the AI model activation regions were distributed in the relevant structural regions. Conclusions: In this study, an automatic classification model for lateral cephalograms was established based on the DenseNet121 to achieve rapid classification of eight commonly used clinical diagnostic items.
Male ; Female ; Humans ; Young Adult ; Adult ; Artificial Intelligence ; Deep Learning ; Cephalometry ; Maxilla ; Mandible/diagnostic imaging*

Objective: To develop a multi-classification orthodontic image recognition system using the SqueezeNet deep learning model for automatic classification of orthodontic image data. Methods: A total of 35 000 clinical orthodontic images were collected in the Department of Orthodontics, Capital Medical University School of Stomatology, from October to November 2020 and June to July 2021. The images were from 490 orthodontic patients with a male-to-female ratio of 49∶51 and the age range of 4 to 45 years. After data cleaning based on inclusion and exclusion criteria, the final image dataset included 17 453 face images (frontal, smiling, 90° right, 90° left, 45° right, and 45° left), 8 026 intraoral images [frontal occlusion, right occlusion, left occlusion, upper occlusal view (original and flipped), lower occlusal view (original and flipped) and coverage of occlusal relationship], 4 115 X-ray images [lateral skull X-ray from the left side, lateral skull X-ray from the right side, frontal skull X-ray, cone-beam CT (CBCT), and wrist bone X-ray] and 684 other non-orthodontic images. A labeling team composed of orthodontic doctoral students, associate professors, and professors used image labeling tools to classify the orthodontic images into 20 categories, including 6 face image categories, 8 intraoral image categories, 5 X-ray image categories, and other images. The data for each label were randomly divided into training, validation, and testing sets in an 8∶1∶1 ratio using the random function in the Python programming language. The improved SqueezeNet deep learning model was used for training, and 13 000 natural images from the ImageNet open-source dataset were used as additional non-orthodontic images for algorithm optimization of anomaly data processing. A multi-classification orthodontic image recognition system based on deep learning models was constructed. The accuracy of the orthodontic image classification was evaluated using precision, recall, F1 score, and confusion matrix based on the prediction results of the test set. The reliability of the model's image classification judgment logic was verified using the gradient-weighted class activation mapping (Grad-CAM) method to generate heat maps. Results: After data cleaning and labeling, a total of 30 278 orthodontic images were included in the dataset. The test set classification results showed that the precision, recall, and F1 scores of most classification labels were 100%, with only 5 misclassified images out of 3 047, resulting in a system accuracy of 99.84%(3 042/3 047). The precision of anomaly data processing was 100% (10 500/10 500). The heat map showed that the judgment basis of the SqueezeNet deep learning model in the image classification process was basically consistent with that of humans. Conclusions: This study developed a multi-classification orthodontic image recognition system for automatic classification of 20 types of orthodontic images based on the improved SqueezeNet deep learning model. The system exhibitted good accuracy in orthodontic image classification.
Humans ; Male ; Female ; Child, Preschool ; Child ; Adolescent ; Young Adult ; Adult ; Middle Aged ; Deep Learning ; Reproducibility of Results ; Radiography ; Algorithms ; Cone-Beam Computed Tomography

OBJECTIVE: To investigate the effect of pachymic acid (PA) against TNBS-induced Crohn's disease (CD)-like colitis in mice and explore the possible mechanism. METHODS: Twenty-four C57BL/6J mice were randomized equally into control group, TNBS-induced colitis model group and PA treatment group. PA treatment was administered via intraperitoneal injection at the daily dose of 5 mg/kg for 7 days, and the mice in the control and model groups were treated with saline. After the treatments, the mice were euthanized for examination of the disease activity index (DAI) of colitis, body weight changes, colon length, intestinal inflammation, intestinal barrier function and apoptosis of intestinal epithelial cells, and the expressions of TNF-α, IL-6 and IL-1β in the colonic mucosa were detected using ELISA. The possible treatment targets of PA in CD were predicted by network pharmacology. String platform and Cytoscape 3.7.2 software were used to construct the protein-protein interaction (PPI) network. David database was used to analyze the GO function and KEGG pathway; The phosphorylation of PI3K/AKT in the colonic mucosal was detected with Western blotting. RESULTS: PA significantly alleviated colitis in TNBS-treated mice as shown by improvements in the DAI, body weight loss, colon length, and histological inflammation score and lowered levels of TNF-α, IL-6 and IL-1β. PA treatment also significantly improved FITC-dextran permeability, serum I-FABP level and colonic transepithelial electrical resistance, and inhibited apoptosis of the intestinal epithelial cells in TNBS-treated mice. A total of 248 intersection targets were identified between PA and CD, and the core targets included EGFR, HRAS, SRC, MMP9, STAT3, AKT1, CASP3, ALB, HSP90AA1 and HIF1A. GO and KEGG analysis showed that PA negatively regulated apoptosis in close relation with PI3K/AKT signaling. Molecular docking showed that PA had a strong binding ability with AKT1, ALB, EGFR, HSP90AA1, SRC and STAT3. In TNBS-treated mice, PA significantly decreased p-PI3K and p-AKT expressions in the colonic mucosa. CONCLUSION PA ameliorates TNBS-induced intestinal barrier injury in mice by antagonizing apoptosis of intestinal epithelial cells possibly by inhibiting PI3K/AKT signaling.
Animals ; Mice ; Mice, Inbred C57BL ; Crohn Disease ; Phosphatidylinositol 3-Kinases ; Proto-Oncogene Proteins c-akt ; Interleukin-6 ; Molecular Docking Simulation ; Tumor Necrosis Factor-alpha ; Colitis/chemically induced* ; Inflammation ; Apoptosis ; ErbB Receptors

BACKGROUND: Low-density computed tomography (LDCT) improved early lung cancer diagnosis but introduces an excess of false-positive pulmonary nodules data. Hence, accurate diagnosis of early-stage lung cancer remains challenging. The purpose of the study was to assess the feasibility of using circulating tumour cells (CTCs) to differentiate malignant from benign pulmonary nodules. METHODS: 122 patients with suspected malignant pulmonary nodules detected on chest CT in preparation for surgery were prospectively recruited. Peripheral blood samples were collected before surgery, and CTCs were identified upon isolation by size of epithelial tumour cells and morphological analysis. Laser capture microdissection, MALBAC amplification, and whole-exome sequencing were performed on 8 samples. The diagnostic efficacy of CTCs counting, and the genomic variation profile of benign and malignant CTCs samples were analysed. RESULTS: Using 2.5 cells/5 mL as the cut-off value, the area under the receiver operating characteristic curve was of 0.651 (95% confidence interval: 0.538-0.764), with a sensitivity and specificity of 0.526 and 0.800, respectively, and positive and negative predictive values of 91.1% and 30.3%, respectively. Distinct sequence variations differences in DNA damage repair-related and driver genes were observed in benign and malignant samples. TP53 mutations were identified in CTCs of four malignant cases; in particular, g.7578115T>C, g.7578645C>T, and g.7579472G>C were exclusively detected in all four malignant samples. CONCLUSIONS CTCs play an ancillary role in the diagnosis of pulmonary nodules. TP53 mutations in CTCs might be used to identify benign and malignant pulmonary nodules.
Humans ; Lung Neoplasms ; Exome Sequencing ; Multiple Pulmonary Nodules ; Carcinoma ; DNA Repair