A multi-modal dental dataset for semi-supervised deep learning image segmentation.

In response to the increasing prevalence of dental diseases, dental health, a vital aspect of human well-being, warrants greater attention. Panoramic X-ray images (PXI) and Cone Beam Computed Tomography (CBCT) are key tools for dentists in diagnosing and treating dental conditions. Additionally, deep learning for tooth segmentation can focus on relevant treatment information and localize lesions.

Prognosis prediction of head and neck squamous cell carcinoma through the basement membrane-related lncRNA risk model.

Background: Head and neck squamous cell carcinoma (HNSCC) ranks among the most widespread and significantly heterogeneous malignant tumors globally. Increasing evidence suggests that the basement membrane (BM) and associated long non-coding RNAs (lncRNA) are correlated with the onset of HNSCC and its prognosis. Our study aims to construct a basement membrane-associated lncRNAs (BMlncRNAs) marker to accurately predict the prognosis of HNSCC patients and find novel immunotherapy targets.

A novel nerol-segmented waterborne polyurethane coating for the prevention of dental erosion.

Dental erosion is a common problem in dentistry, and it refers to the chronic pathological loss of dental hard tissues due to nonbacterially produced acids, primarily caused by the exposure of teeth to exogenous acids. Dietary factors play a pivotal part in the pathogenesis of dental erosion, with a high intake of acidic beverages leading to an increased prevalence of dental erosion in adolescents. Fluoride is mainly used in clinical practice to prevent dental erosion.

Developmental relationship between junctional epithelium and epithelial rests of Malassez.

(K17) is thought to be a candidate target gene for regulation by Lymphoid Enhancer Factor-1 (Lef-1) K17 is a marker that distinguishes junctional epithelium (JE) from epithelial rests of Malassez (ERM). However, the relationship of Lef-1 to K17 is not clear in this context. Moreover, the expression of other keratins such as K5, K6, K7 and K16 is not reported.

The metabolic reprogramming of γ-aminobutyrate in oral squamous cell carcinoma.

Oral squamous cell carcinoma (OSCC) is the most common head and neck malignancy. The oncometabolites have been studied in OSCC, but the mechanism of metabolic reprogramming remains unclear. To identify the potential metabolic markers to distinguish malignant oral squamous cell carcinoma (OSCC) tissue from adjacent healthy tissue and study the mechanism of metabolic reprogramming in OSCC.

Children's dental panoramic radiographs dataset for caries segmentation and dental disease detection.

When dentists see pediatric patients with more complex tooth development than adults during tooth replacement, they need to manually determine the patient's disease with the help of preoperative dental panoramic radiographs. To the best of our knowledge, there is no international public dataset for children's teeth and only a few datasets for adults' teeth, which limits the development of deep learning algorithms for segmenting teeth and automatically analyzing diseases. Therefore, we collected dental panoramic radiographs and cases from 106 pediatric patients aged 2 to 13 years old, and with the help of the efficient and intelligent interactive segmentation annotation software EISeg (Efficient Interactive Segmentation) and the image annotation software LabelMe.

MicroRNA-141-3p inhibits the progression of oral squamous cell carcinoma via targeting PBX1 through the JAK2/STAT3 pathway.

Oral squamous cell carcinoma (OSCC), which is the most common epithelial malignant neoplasm in the head and neck, is characterized by local infiltration and metastasis of lymph nodes. The five-year survival rate of OSCC remains low despite the advances in clinical methods. miR-141-3p has been shown to activate or inhibit tumorigenesis.

[TAN Bayesian network modeling of online learning decision making of dental undergraduates during the COVID-19 pandemic].

Purpose: To perceive the dental undergraduate's policy of coping with online learning and their decision-making laws during the COVID-19 pandemic.

Methods: For dental undergraduate students from the 2016 grade to 2018 grade of Lishui University, two prospective questionnaire surveys were conducted before the online course starting and four weeks later. SPSS Modeler18.

The lncRNA H19 mediates breast cancer cell plasticity during EMT and MET plasticity by differentially sponging miR-200b/c and let-7b.

Metastasis is a multistep process by which tumor cells disseminate from their primary site and form secondary tumors at a distant site. The pathophysiological course of metastasis is mediated by the dynamic plasticity of cancer cells, which enables them to shift between epithelial and mesenchymal phenotypes through a transcriptionally regulated program termed epithelial-to-mesenchymal transition (EMT) and its reverse process, mesenchymal-to-epithelial transition (MET). Using a mouse model of spontaneous metastatic breast cancer, we investigated the molecular mediators of metastatic competence within a heterogeneous primary tumor and how these cells then manipulated their epithelial-mesenchymal plasticity during the metastatic process.