Molecular cloning and preliminary functional analysis of six RING-between-ring (RBR) genes in grass carp (Ctenopharyngodon idellus)

Ubiquitination is a post-translational modification of proteins that is widely present in eukaryotic cells. There is increasing evidence that ubiquitinated proteins play crucial roles in the immune response process. In mammals, RING-between-RING (RBR) proteins play a key role in regulating immune signaling as the important E3 ubiquitin ligases during ubiquitination. However, the function of RBR in fish is still unclear. In the present study, six RBR genes (RNF19A, RNF19B, RNF144AA, RNF144AB, RNF144B and RNF217) of grass carp (Ctenopharyngodon idellus) were cloned and characterized. Similar to mammals, all six members of RBR family contained RING, inbetween-ring (IBR) and transmembrane (TM) domains. These genes were constitutively expressed in all studied tissues, but the relative expression level differed. Following grass carp reovirus(GCRV) infection, the expression of six RBR genes in liver, gill, spleen and intestine significantly altered. Additionally, their expression in Ctenopharyngodon idellus kidney (CIK) cells was significantly increased after GCRV infection. And deficiency of RNF144B in CIK with small interference RNA (siRNA) up-regulated polyinosinic:polycytidylic acid poly(I:C))- induced inflammatory cytokines production, including 1FN-I, TNF-alpha, IL-6, and transcription factor IRF3, which demonstrated that RNF144B was a negative regulator of inflammatory cytokines. Our results suggested that the RBR might play a vital role in regulating immune signaling and laid the foundation for the further mechanism research of RBR in fishes

Application of Machine Learning Algorithms to Predict Central Lymph Node Metastasis in T1-T2, Non-invasive, and Clinically Node Negative Papillary Thyroid Carcinoma

Purpose: While there are no clear indications of whether central lymph node dissection is necessary in patients with T1-T2, non-invasive, clinically uninvolved central neck lymph nodes papillary thyroid carcinoma (PTC), this study seeks to develop and validate models for predicting the risk of central lymph node metastasis (CLNM) in these patients based on machine learning algorithms. Methods: This is a retrospective study comprising 1,271 patients with T1-T2 stage, non-invasive, and clinically node negative (cN0) PTC who underwent surgery at the Department of Endocrine and Breast Surgery of The First Affiliated Hospital of Chongqing Medical University from February 1, 2016, to December 31, 2018. We applied six machine learning (ML) algorithms, including Logistic Regression (LR), Gradient Boosting Machine (GBM), Extreme Gradient Boosting (XGBoost), Random Forest (RF), Decision Tree (DT), and Neural Network (NNET), coupled with preoperative clinical characteristics and intraoperative information to develop prediction models for CLNM. Among all the samples, 70% were randomly selected to train the models while the remaining 30% were used for validation. Indices like the area under the receiver operating characteristic (AUROC), sensitivity, specificity, and accuracy were calculated to test the models' performance. Results: The results showed that ~51.3% (652 out of 1,271) of the patients had pN1 disease. In multivariate logistic regression analyses, gender, tumor size and location, multifocality, age, and Delphian lymph node status were all independent predictors of CLNM. In predicting CLNM, six ML algorithms posted AUROC of 0.70–0.75, with the extreme gradient boosting (XGBoost) model standing out, registering 0.75. Thus, we employed the best-performing ML algorithm model and uploaded the results to a self-made online risk calculator to estimate an individual's probability of CLNM (https://jin63.shinyapps.io/ML_CLNM/). Conclusions: With the incorporation of preoperative and intraoperative risk factors, ML algorithms can achieve acceptable prediction of CLNM with Xgboost model performing the best. Our online risk calculator based on ML algorithm may help determine the optimal extent of initial surgical treatment for patients with T1-T2 stage, non-invasive, and clinically node negative PTC

DeePMD-kit v2: A software package for Deep Potential models

DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials (MLP) known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, Deep Potential - Range Correction (DPRc), Deep Potential Long Range (DPLR), GPU support for customized operators, model compression, non-von Neumann molecular dynamics (NVNMD), and improved usability, including documentation, compiled binary packages, graphical user interfaces (GUI), and application programming interfaces (API). This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, the article benchmarks the accuracy and efficiency of different models and discusses ongoing developments.Comment: 51 pages, 2 figure

The prevalence and common risk indicators of root caries and oral health service utilization pattern among adults, a cross-sectional study

Background Root caries is a prevalent oral health concern among adults, yet there remains a need for a comprehensive understanding of its occurrence and associated risk indicators. The present study was aimed to investigate the prevalence of root caries and to determine significantly associated indicators with it among adults. Methods The residents aged 35–74 years old were enrolled in a cross-sectional study in which dental examination were taken and structured questionnaires were collected in Zhejiang Province, China. All data were recorded in an electronic system and analyzed. Results The prevalence of decayed and filled root caries in 1,076 respondents was 31.9%. Elder age, greater attachment loss, and exposed root surface were associated with higher odds of incidence for decayed/filled roots and decayed roots. In the last 12 months, 27.4% of adults with decayed or filled roots and 23.2% of others utilized oral health services. Carious adults who had a very poor/poor oral health status were 2.905 times likely to report dental visits. People with sound roots who were female (OR = 2.103, P < 0.001), perceived their oral health status as moderate (OR = 1.802, P = 0.015), or poor/very poor (OR = 4.103, P < 0.001) were more likely to visit a dentist in the past 12 months. Conclusions Age, attachment loss and root exposure were most significantly associated with the prevalence of root caries. Individuals who recognize their poor or very poor oral health status should feel encouraged to make use of oral health services

Research status of damage identification algorithm based on deep learning

One of the core tasks of computer vision is target detection. With the rapid development of deep learning, target detection technology based on deep learning has become the mainstream algorithm in this field. As one of the main application fields, damage identification has achieved important development in the past decade. This paper systematically summarizes the research progress of damage identification algorithm based on deep learning, analyzes the advantages and disadvantages of each algorithm and its detection results on voc2007, voc2012 and coco data sets. Finally, the main contents of this paper are summarized, and the research prospect of deep learning based damage identification algorithm is prospect

The correlation between periodontitis and uncontrolled hypertension is mediated by inflammatory markers: results from a cross-sectional study of urban elderly population in southeast China

Abstract Background Periodontal diseases is considered the most important global oral health burden according to the world health organization (WHO) (Oral health. https://www.who.int/news-room/fact-sheets/detail/oral-health#Overviewth (who.int). Accessed 21 Sep 2023). It is a common local inflammatory disease associated with hypertension, this study aims to explore the relationship between periodontitis and uncontrolled hypertension and whether inflammation indication such as white blood cell (WBC) count or neutrophil count is a mediator of this relationship. Methods One thousand four hundred eighty-eight elders attending annual physical and oral examinations in Zhejiang province were included in this study. The staging of Periodontitis was classified as none, mild-moderate and severe. Participants are categorized into two groups based on blood pressure: hypertensive( positive high blood pressure( HBP) history or underwent HBP medication or blood pressure( BP) ≥ 140/90 mmHg) and uncontrolled hypertensive (systolic blood pressure( SBP) ≥ 140 mmHg or distolic blood pressure( DBP) ≥ 90 mmHg). Peripheral blood samples were collected, information on hypertension history and potential confounders (age, sex, smoking, alcohol consumption, exercise frequency, diabetes) was collected in questionnaires. The correlation between periodontitis and hypertension was investigated using logistics regression analyses, mediation analysis was assessed for the effect of inflammation on hypertension. Results The study population includes 1,488 participants aged 55–90 years. Odds of uncontrolled hypertension increased significantly along with periodontitis in the regression models both in unadjusted model (odds ratio( OR): 1.407, 95% confidence intervals( CI): 1.037 ~ 1.910) and fully adjusted model (OR: 1.950, 95% CI: 1.127 ~ 3.373). Mediation analysis confirmed that WBC and neutrophic count function as a full mediator of the association between periodontitis and uncontrolled hypertension either in the unadjusted or the adjusted model. Conclusions In a study of urban elderly population in southeast China, periodontitis is found to be significantly associated with uncontrolled hypertension, such relation is mediated by WBC and neutrophil count. Periodontitis can increase the difficulty of controlling hypertension. Promotion of periodontal health strategies in the dental setting could help reduce the burden of hypertension and its complications

Additional file 3 of Assessment of life support skills of resident dentists using OSCE: cross-sectional survey

Additional file 3: Table S3. Questionnaire on self-assess competence and willingness of CPR

Structural Derivative and Electronic Property of Armchair Carbon Nanotubes from Carbon Clusters

The structural derivative and electronic property of carbon nanotubes from carbon clusters were investigated by density functional theory (DFT), including armchair single-walled carbon nanotubes (SWCNTs) and multiwalled carbon nanotubes (MWCNTs). Results show that the carbon nanotubes (CNTs) can be obtained through layer-by-layer growth from the initial structure. The structural derivative processes are quantitatively described by monitoring changes in local configuration. Electronic properties show the energy gaps of finite SWCNTs and double-walled CNTs (DWCNTs) depending on their lengths. However, the band structures of MWCNTs differ from those of SWCNTs; the band structures of DWCNTs (4, 4)@(8, 8), (5, 5)@(10, 10), and TWCNTs show metallicity, whereas those of (3, 3)@(6, 6) DWCNTs show a strong semiconductor characteristic. Analysis of the partial density of states shows that the diameters and walls of CNTs have no obvious effects on the distribution of total density of states near the Fermi level of SWCNTs and MWCNTs