Caries lesions diagnosis with deep convolutional neural network in intraoral QLF images by handheld device.

Objectives: This study investigated the effectiveness of a deep convolutional neural network (CNN) in diagnosing and staging caries lesions in quantitative light-induced fluorescence (QLF) images taken by a self-manufactured handheld device.

Methods: A small toothbrush-like device consisting of a 400 nm UV light-emitting lamp with a 470 nm filter was manufactured for intraoral imaging. A total of 133 cases with 9,478 QLF images of teeth were included for caries lesion evaluation using a CNN model.

The association of HBV infection and head and neck cancer: a systematic review and meta-analysis.

Background: Hepatitis B virus (HBV) infections is an important public health problem worldwide and closely affect extrahepatic cancer. Several recent studies have investigated the relationship between HBV infection and head and neck cancer (HNC), but their findings were inconsistent.In order to address the limitations of small sample sizes, we conducted a meta-analysis to assess the association between HBV and HNC.

Identification of as a novel prognostic biomarker and potential therapeutic target for oral squamous cell carcinoma.

Background: The cyclin-dependent kinase subunit 2 () is recognized to have a substantial impact on the pathogenesis and advancement of several malignant neoplasms. Nevertheless, its biological function and prognostic significance in oral squamous cell carcinoma (OSCC) have yet to be thoroughly investigated. Our primary objective was to clarify the contribution of in the progression and prognosis of OSCC.

Integrative Analysis of N6-Methyladenosine-Related Enhancer RNAs Identifies Distinct Prognosis and Tumor Immune Micro-Environment Patterns in Head and Neck Squamous Cell Carcinoma.

At present, the prognostic value of N6-methyladenosine (m6A)-related enhancer RNAs (eRNAs) for head and neck squamous cell carcinoma (HNSCC) still remains unclear. Our study aims to explore the prognostic value of m6A-related eRNAs in HNSCC patients and their potential significance in immune infiltration and immunotherapy. We constructed a 5 m6A-related eRNAs risk model from The Cancer Genome Atlas (TCGA) HNSCC dataset, using univariate and multivariate Cox and least absolute shrinkage and selection operator (LASSO) regression analysis.

Magnetic Resonance Imaging-Based Radiomics Features Associated with Depth of Invasion Predicted Lymph Node Metastasis and Prognosis in Tongue Cancer.

Background: Adequate safe margin in tongue cancer radical surgery is one of the most important prognostic factors. However, the role of peritumoral tissues in predicting lymph node metastasis (LNM) and prognosis using radiomics analysis remains unclear.

Purpose: To investigate whether magnetic resonance imaging (MRI)-based radiomics analysis with peritumoral extensions contributes toward the prediction of LNM and prognosis in tongue cancer.

High Expression of Tomm34 and Its Correlations With Clinicopathology in Oral Squamous Cell Carcinoma.

Tomm34, as a member of the outer mitochondrial membrane proteins, is evenly distributed between the cytoplasm and the outer mitochondrial membrane. It is up-regulated in a variety of tumors and correlates with poor prognosis. This study aimed to investigate expression of Tomm34 and its correlations with clinicopathology in oral squamous cell carcinoma (OSCC).