Classification and detection of dental images using meta-learning.

Meta-learning of dental X-rays is a machine learning technique that can be used to train models to perform new tasks quickly and with minimal input. Instead of just memorizing a task, this is accomplished through teaching a model how to learn. Algorithms for meta-learning are typically trained on a collection of training problems, each of which has a limited number of labelled instances.

Exploring the interplay between Porphyromonas gingivalis KGP gingipain, herpes virus MicroRNA-6, and Icp4 transcript in periodontitis: Computational and clinical insights.

Background: Porphyromonas gingivalis, a major pathogen in periodontitis, produces KGP (Lys-gingipain), a cysteine protease that enhances bacterial virulence by promoting tissue invasion and immune evasion. Recent studies highlight microRNAs' role in viral latency, potentially affecting lytic replication through host mechanisms. Herpes virus (HSV) establishes latency via interactions between microRNA-6 (miRH-6) and the ICP4 transcription factor in neural ganglia.

HyperAttention and Linformer-Based β-catenin Sequence Prediction For Bone Formation.

Introduction Beta (β)-catenin, a pivotal protein in bone development and homeostasis, is implicated in various bone disorders. Peptide-based therapeutics offer a promising approach due to their specificity and potential for reduced side effects. Attention networks are widely used for peptide sequence prediction, specifically sequence-to-sequence models.

Graph Neural Network-Based Drug Gene Interactions of Wnt/β-Catenin Pathway in Bone Formation.

Introduction The Wnt/β-catenin pathway is crucial for bone formation and remodeling, regulating osteoblast differentiation, bone remodeling, and skeletal homeostasis. Dysregulation of the Wnt/β-catenin pathway is linked to bone-related diseases like osteoporosis, osteoarthritis, and osteosarcoma. The strategies to modulate this pathway include Wnt agonists, inhibitors, and small molecules.

Comparing Graph Sample and Aggregation (SAGE) and Graph Attention Networks in the Prediction of Drug-Gene Associations of Extended-Spectrum Beta-Lactamases in Periodontal Infections and Resistance.

Introduction: Gram-negative bacteria exhibit more antibiotic resistance than gram-positive bacteria due to their cell wall structure and composition differences. Porins, or protein channels in these bacteria, can allow small, hydrophilic antibiotics to diffuse, affecting their susceptibility. Mutations in porin protein genes can also impair antibiotic entry.

Gradient Boosting Prediction of Overlapping Genes From Weighted Co-expression and Differential Gene Expression Analysis of Wnt Pathway: An Artificial Intelligence-Based Bioinformatics Study.

Introduction The Wnt (wingless-related integration site) signalling pathway is crucial for bone formation and remodelling, regulating the commitment of mesenchymal stem cells (MSCs) to the osteoblastic lineage. It triggers the transcriptional activation of Wnt target genes and promotes osteoblast proliferation and survival. Weighted co-expression network analysis (WGCNA) and differential gene expression analysis help researchers understand gene roles.

Deep Learning Prediction of Inflammatory Inducing Protein Coding mRNA in P. gingivalis Released Outer Membrane Vesicles.

Aim: The Insilco study uses deep learning algorithms to predict the protein-coding pg m RNA sequences.

Material And Methods: The NCBI GEO DATA SET GSE218606's GEO R tool discovered P.G's outer membrane vesicles' most differentially expressed mRNA.

Variational Autoencoders for Generative Drug-Gene Interactions in Periodontal Bone Resorption.

Introduction Periodontal bone resorption is a significant dental problem causing tooth loss and impaired oral function. It is influenced by factors such as bacterial plaque, genetic predisposition, smoking, systemic diseases, medications, hormonal changes, and poor oral hygiene. This condition disrupts bone remodeling, favoring resorptive processes.

Advanced machine learning for estimating vascular occlusion percentage in patients with ischemic heart disease and periodontitis.

Objective: The study aimed to assess the efficacy of advanced machine learning algorithms in estimating the percentage of vascular occlusion in ischemic heart disease (IHD) cases with periodontitis.

Methods: This study involved 300 IHD patients aged 45 to 65 with stage III periodontitis undergoing coronary angiograms. Dental and periodontal examinations assessed various factors.

AI-based 3D-QSAR model of FDA-approved repurposed drugs for inhibiting sclerostin.

Background: Wnt activation promotes bone formation and prevents bone loss. The Wnt pathway antagonist sclerostin and additional anti-sclerostin antibodies were discovered as a result of the development of the monoclonal antibody romosozumab. These monoclonal antibodies greatly increase the risk of cardiac arrest.

Machine learning in the detection of dental cyst, tumor, and abscess lesions.

Background And Objective: Dental panoramic radiographs are utilized in computer-aided image analysis, which detects abnormal tissue masses by analyzing the produced image capacity to recognize patterns of intensity fluctuations. This is done to reduce the need for invasive biopsies for arriving to a diagnosis. The aim of the current study was to examine and compare the accuracy of several texture analysis techniques, such as Grey Level Run Length Matrix (GLRLM), Grey Level Co-occurrence Matrix (GLCM), and wavelet analysis in recognizing dental cyst, tumor, and abscess lesions.

Implant practitioners' knowledge, awareness and attitudes regarding soft and hard tissue considerations at a single implant site: A questionnaire study.

Background: The success of implant therapy depends on the proper evaluation of soft and hard tissues around implants, and the careful selection of biomaterials to manage the associated defects. To attain healthy peri-implant tissues, knowledge about evaluating and managing soft and hard tissues around dental implants is essential.

Objectives: The aim of the present study was to assess the knowledge, awareness and attitudes regarding soft and hard tissue considerations for single implant sites among the registered dental implant practitioners.

CRISPR-Cas-Based Adaptive Immunity Mediates Phage Resistance in Periodontal Red Complex Pathogens.

Periodontal diseases are polymicrobial immune-inflammatory diseases that can severely destroy tooth-supporting structures. The critical bacteria responsible for this destruction include red complex bacteria such as , and . These organisms have developed adaptive immune mechanisms against bacteriophages/viruses, plasmids and transposons through clustered regularly interspaced short palindromic repeats (CRISPR) and their associated proteins (Cas).

Indigenous Oral and Gut Phages Defeat the Deadly NDM-1 Superbug.

Aim: Antibiotics treat various diseases by targeting microorganisms by killing them or reducing their multiplication rate. New Delhi Metallo-beta-lactamase-1 (NDM-1) is produced by bacteria possessing the resistance gene blaNDM-1, the enzyme that makes bacteria resistant to beta-lactams. Bacteriophages, especially Lactococcus, have shown their ability to break down lactams.

Assessment of myocardial strain in hypertensive patients with periodontitis.

Background: Left ventricular (LV) relaxation is affected by hypertension. The inflammatory mediators produced in response to systemic inflammation, such as in periodontal disease, may also alter ventricular mechanics and the existing ventricular dysfunction. Thus, the systemic inflammatory burden which occurs in response to chronic periodontitis may alter myocardial activity.

Designing Novel Multi-Epitope Vaccine Construct against -Interpain A: An Immunoinformatics Approach.

: Periodontitis is a chronic multifactorial inflammatory infectious disease marked by continuous degradation of teeth and surrounding parts. One of the most important periodontal pathogens is , and with its interpain A proteinase, it leads to an increase in lethal infection. : The current study was designed to create a multi-epitope vaccine using an immunoinformatics method that targets the interpain A of .

Clinical efficacy of subepithelial connective tissue graft and A-PRF in the treatment of gingival recession.

Objective: The current study was designed to clinically compare and evaluate subepithelial connective tissue graft (SCTG) and advanced platelet-rich fibrin (A-PRF) membrane-based root coverage in the treatment of gingival recession type 1 (RT1).

Method And Materials: The current study involved 17 patients with bilateral gingival recession (RT1). Thirty-four sites were randomly allocated to test (A-PRF) and control (SCTG) sites and all the procedures were performed by a single operator.

Gingival biotype as an indicator for the buccal bone thickness - a systematic review of the literature.

Introduction A relationship between thin gingiva and thin buccal bone has been proposed but concrete evidence for this is lacking. This study was undertaken to assess the reliability of measuring gingival thickness in estimating the buccal bone thickness.Objectives To answer the following PICO question: do periodontally healthy individuals exhibit any correlation between gingival biotype and buccal/labial/facial bone thickness?Data sources and selection An electronic search was performed in PubMed and Embase databases.

Autologous platelet-rich fibrin as an adjunct to non-surgical periodontal therapy-A follow up clinical pilot study.

The aim was to evaluate the effectiveness of autologous platelet-rich fibrin (PRF) as an adjunct to scaling and root planing (SRP) in moderate periodontal pockets. The split-mouth study involved 32 sites from 16 patients. Baseline parameters were recorded followed by complete full-mouth SRP.