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BACKGROUND AND OBJECTIVE: In recent years, the complex interplay between systemic health and oral well-being has emerged as a focal point for researchers and healthcare practitioners. Among the several important connections, the convergence of Type 2 Diabetes Mellitus (T2DM), dyslipidemia, chronic periodontitis, and peripheral blood mononuclear cells (PBMCs) is a remarkable example. These components collectively contribute to a network of interactions that extends beyond their domains, underscoring the intricate nature of human health. In the current study, bioinformatics analysis was utilized to predict the interactomic hub genes involved in type 2 diabetes mellitus (T2DM), dyslipidemia, and periodontitis and their relationships to peripheral blood mononuclear cells (PBMC) by machine learning algorithms. MATERIALS AND METHODS: Gene Expression Omnibus datasets were utilized to identify the genes linked to type 2 diabetes mellitus(T2DM), dyslipidemia, and Periodontitis (GSE156993).Gene Ontology (G.O.) Enrichr, Genemania, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were used for analysis for identification and functionalities of hub genes. The expression of hub D.E.G.s was confirmed, and an orange machine learning tool was used to predict the hub genes. RESULT: The decision tree, AdaBoost, and Random Forest had an A.U.C. of 0.982, 1.000, and 0.991 in the R.O.C. curve. The AdaBoost model showed an accuracy of (1.000). The findings imply that the AdaBoost model showed a good predictive value and may support the clinical evaluation and assist in accurately detecting periodontitis associated with T2DM and dyslipidemia. Moreover, the genes with p-value < 0.05 and A.U.C.>0.90, which showed excellent predictive value, were thus considered hub genes. CONCLUSION: The hub genes and the D.E.G.s identified in the present study contribute immensely to the fundamentals of the molecular mechanisms occurring in the PBMC associated with the progression of periodontitis in the presence of T2DM and dyslipidemia. They may be considered potential biomarkers and offer novel therapeutic strategies for chronic inflammatory diseases.
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Periodontite Crônica , Diabetes Mellitus Tipo 2 , Dislipidemias , Humanos , Leucócitos Mononucleares , Algoritmos , Biologia Computacional , Perfilação da Expressão GênicaRESUMO
Introduction Oral cancer is a significant global health issue that is mainly caused by factors, such as smoking, alcohol consumption, poor oral hygiene, age, and the human papillomavirus. Unfortunately, delayed diagnosis contributes to high rates of illness and mortality. However, saliva shows promise as a potential source for early detection, prognosis, and treatment. By analyzing the proteins and their interactions in saliva, we can gain insights that can assist in early detection and prediction. In this study, we aim to identify and predict the key genes, known as hub genes, in the salivary transcriptomics data of oral cancer patients and healthy individuals. Methods The data used for the analysis were obtained from salivaryproteome.org (https://salivaryproteome.org/) . The retrieved data consisted of individuals with oral cancer who were assigned unique identification numbers (IDs) 1025, 1030, 1027, and 1029, while the healthy individuals were assigned IDs 4256, 4257, 4255, and 4258, respectively. Differential gene expression analysis was used to identify genes that showed significant differences between the two groups. Uniformity and clustering were assessed through heatmaps and principal component analysis. Protein-protein interactions were investigated using the STRING database and Cytoscape. In addition, machine learning algorithms were employed to identify key genes involved in the interatomic interactions by analyzing transcriptomics data generated from the differential gene expression analysis. Results The accuracy and class accuracy of the extra tree classifier showed 98% and 97% in predicting interactomic hub genes, and HSPB1 was identified as a hub gene using Cytohubba from Cytoscape. Conclusion The predictive extra tree classifier, with its high accuracy in analysing interactomic hub genes in oral cancer, can potentially improve diagnosis and treatment strategies.
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As every life form is composed of cells, elements of consciousness, namely memory and sentience, must be grounded in mechanisms that are integral to unicellular organisms. Earlier studies indicated that cellular cytoskeletal structures consisting of excitable, flexible, and oscillating polymers such as microtubules, along with quantum events, are potentially responsible for information processing and thus consciousness. This work attempts to solve the unknown, that is, how, at the spark of life, the phenomenon of cellular information processing first appears. This study posits that the spatially distributed wave energy of the molecules of an incepting cell interacts with space and generates a rotating bioinformation field, forming a vortex. This vortex, the local energy maximum, whose inbound and outbound energy fluxes represent signal reception and dispersal, is a critical step in the spark of life responsible for information storage, and with incremental wave superpositions, exhibits information processing. The vorticity of the rotating field is computed, and the obtained field characteristics indicated the emergence of a prebiotic complex to initiate information processing. Furthermore, the developed system model explains how perturbations from the environment are converted into response signals for the emanation of sense, locomotion, nutrition, and asexual reproduction, the fundamental evolutionary building blocks of prokaryotes. Further research directions include explaining how the energy potential available in the bio-information field and the vortex leads to the first formation of genetic material, emergence of cytoskeleton, and extension of bio-information field to multi-cellular organisms.
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Dental implantology has been considered the mainstay in the rehabilitation of partial or complete edentulism. Nevertheless, complications and failures are occasionally encountered, and the most significant is the neurosensory disturbance. It not only causes persistent discomfort to the patient but frequently degrades the patient's oral health-related quality of life, even leading to a negative psychological impact. This paper presents a case report of a 65-year-old male patient who underwent the replacement of his missing tooth in the right mandibular region (46) with an implant-supported prosthesis two years ago. Since then, he has been experiencing numbness in the right side of the lip and occasional drooling of saliva from the right corner of the mouth. Clinical examination revealed the presence of a prosthetic crown supported by an implant in relation to 46 with inflamed and enlarged gingiva in the region with paresthesia of the right lower lip region. Radiological examination with orthopantomogram (OPG) and cone beam computed tomography (CBCT) revealed that the implant apex rested on the inferior alveolar nerve canal. Careful surgical retrieval of the well-osseointegrated implant was performed under local anesthesia in about seven days. The patient gradually experienced neurosensory improvement, and the paraesthesia was completely resolved in a six-week period. After complete recovery, as evaluated with an objective and subjective assessment, the edentulous site was successfully restored with a provisional fixed partial denture.
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Introduction The Wnt signaling pathway is crucial for tooth development, odontoblast differentiation, and dentin formation. It interacts with epithelial cadherin (E-cadherin) and beta-catenin in tooth development and periodontal ligament (PDL) formation. Dysregulation of Wnt signaling is linked to periodontal diseases, requiring an understanding of therapeutic interventions. Weighted gene co-expression network analysis (WGCNA) can identify co-expressed gene modules. Our study aims to identify hub genes in WGCNA analysis of Wnt signaling-based PDL formation. Methods The study used a microarray dataset GSE201313 from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus to analyze the impact of DMP1 expression on XLH dental pulp cell differentiation and PDL formation. The standardized dataset was used for WGCNA analysis, which generated a co-expression network by calculating pairwise correlations between genes and constructing an adjacency matrix. The topological overlap matrix (TOM) was transformed into a hierarchical clustering tree and then cut into modules or clusters of highly interconnected genes. The module eigengene (ME) was calculated for each module, and the genes within this module were identified as hub genes. Gene ontology (GO) and KEGG pathway enrichment analysis were performed to gain insights into the biological functions of the hub genes. The integrated Differential Expression and Pathway analysis (iDEP) tool (http://bioinformatics.sdstate.edu/idep/; South Dakota State University, Brookings, USA) was used for WGCNA analysis. Results The study used the WGCNA package to analyze 1,000 differentially expressed genes, constructing a gene co-expression network and generating a hierarchical clustering tree and TOM. The analysis reveals a scale-free topology fitting index R2 and mean connectivity for various soft threshold powers, with an R2 value of 5. COL6A1, MMP3, BGN, COL1A2, and FBN2 are hub genes implicated in PDL development. Conclusion The study identified key hub genes, including COL6A1, MMP3, BGN, and FBN2, crucial for PDL formation, tissue remodeling, and cell-matrix interactions, guiding future therapeutic strategies.
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BACKGROUND: Type 2 diabetes mellitus (DM) is a known systemic risk factor for periodontitis. An increased expression of CD44 has been suggested in type 2 diabetics and periodontitis patients. OBJECTIVES: The present study aimed to assess the expression of CD44 antigen in patients with chronic periodontitis (CP) and type 2 DM in a South Indian urban population. Additionally, the relationships between the expression of CD44 antigen in gingival tissues, periodontal clinical parameters, and the random blood sugar (RBS) and glycated hemoglobin (HbA1c) levels were assessed. MATERIAL AND METHODS: A total of 63 subjects were divided into 3 groups: systemically and periodontally healthy controls (group H); CP patients, otherwise healthy (group CP); and CP patients with type 2 DM (group CP+DM). Periodontal parameters were recorded for all groups, and additionally the RBS and HbA1c levels for group CP+DM. Gingival tissue samples were obtained and subjected to immunohistochemical analysis for CD44. RESULTS: The expression of CD44 was significantly higher in the diseased groups. Epithelial CD44 expression was significantly stronger in group CP+DM as compared to groups CP and H (p < 0.001), whereas connective tissue CD44 expression was similar in groups CP and CP+DM (p = 0.657). Furthermore, an inverse relationship was observed between blood glucose parameters and CD44 expression in the epithelium and connective tissue. CONCLUSIONS: The expression of CD44 increased with the severity of periodontal disease. Additionally, glycemic control in patients with CP and type 2 DM had an impact on CD44 expression. Our findings indicate a possible destructive role of CD44 in the pathogenesis of periodontal diseases in individuals with type 2 DM.
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Periodontite Crônica , Diabetes Mellitus Tipo 2 , Gengiva , Hemoglobinas Glicadas , Receptores de Hialuronatos , Humanos , Receptores de Hialuronatos/metabolismo , Diabetes Mellitus Tipo 2/metabolismo , Diabetes Mellitus Tipo 2/complicações , Masculino , Feminino , Periodontite Crônica/metabolismo , Adulto , Hemoglobinas Glicadas/metabolismo , Pessoa de Meia-Idade , Gengiva/metabolismo , Imuno-Histoquímica , Glicemia/metabolismo , Índice Periodontal , Estudos de Casos e Controles , ÍndiaRESUMO
OBJECTIVE: The focus of research has recently shifted toward developing herbal-based medicines due to the emerging bacterial resistance and side effects of antibiotics. Solanum xanthocarpum (Sx) is a medicinal plant with potent pharmacological properties. This study aimed to evaluate the antibacterial activity of its crude extracts on bacteria isolated from dental plaque in patients with gingivitis. MATERIALS AND METHODS: Aqueous, ethyl acetate, hexane, chloroform, and ethanolic extracts were prepared from Sx. Dental plaque samples were collected from patients with plaque-induced gingivitis. Disk diffusion assay was performed to determine the antibacterial activity of the extracts at concentrations of 25 mg/ml, 50 mg/ml, and 75 mg/ml with ampicillin 200 mg/ml as a positive control. The minimum inhibitory concentration (MIC) of the aqueous extract was also evaluated by broth dilution test against bacteria isolated from dental plaque biofilm. RESULTS: The antibacterial activity was estimated by measuring the zones of inhibition through the disc diffusion method. The Kruskal Wallis with Dunn post hoc test performed for intergroup comparison between the various extracts showed a statistically significant difference in inhibition of bacterial growth between 25 mg/ml and 75 mg/ml concentrations. There was no significant difference between the 75 mg/ml Sx concentration and the positive control. In addition, the MIC was elucidated to be 0.625 g/ml, at which there was maximum inhibition of bacterial growth. CONCLUSION: The Sx extract exhibited antibacterial activity against periodontal pathogens. Thus, it can be concluded that optimum concentrations of Sx could be used in therapeutic strategies to prevent and manage periodontal diseases.
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Miller's Class III gingival recessions (GRs) have always posed a challenge to the clinicians in terms of achieving complete root coverage (CRC). In the present case, a cell-based therapy with autologous fibroblasts seeded onto a Type 1 collagen membrane, through an in-vitro culturing method was utilized. The fibroblasts-seeded membrane was surgically placed under a laterally repositioned flap. The patient presented with a CRC, which was stable even at the postoperative period of 45 months. In addition, a 3-mm substantial gain in the width of keratinized tissue was achieved and maintained throughout the postoperative period. Hence, the results of the cell-seeded therapy emphasize that it can serve as an effective alternative method for the management of Miller's Class III GRs.
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BACKGROUND: Mucormycosis is an infection caused by fungi belonging to the order Mucorales. Rhizopus oryzae is one of the most prevalent organisms identified in mucormycosis patients. Because it spreads quickly through the blood vessels, this opportunistic illness has an exceptionally high fatality rate, even when vigorous treatment is administered. Nonetheless, it has a high tolerance to antifungal medicines, limiting treatment options. As a result, improved methods for preventing and treating mucormycosis are desperately needed. Hence, this study was aimed at assessing the effect of lupeol, quercetin, and solasodine against mucormycosis based on computational approaches. METHODS: The Rhizopus oryzae RNA-dependent RNA polymerase (RdRp) was the target for the design of drugs against the deadly mucormycosis. The three-dimensional structure of the RdRp was modelled with a Swiss model and validated using PROCHECK, VERIFY 3D, and QMEAN. Using the Schrodinger maestro module, a molecular docking study was performed between RdRp and the antimicrobial phytochemicals lupeol, quercetin, and solasodine. A molecular dynamics (MD) simulation study was used to assess the stability and interaction of the RdRp with these phytochemicals. RESULTS: The RdRp protein binds strongly to lupeol (-7.2 kcal/mol), quercetin (-9.1 kcal/mol), and solasodine (-9.6 kcal/mol), according to molecular docking assessment based on the lowest binding energy, confirmation, and bond interaction. Simulations suggest that lupeol, quercetin, and solasodine complexes with RdRp and showed stable confirmation with minimal fluctuation throughout the 200 nanoseconds based on the RMSD and RMSF trajectory assessments. CONCLUSION: The molecular docking and MD simulation investigation improved our understanding of phytochemical-RdRp interactions. Due to its high affinity for RdRp, solasodine may be a better treatment option for mucormycosis.
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Mucormicose , Humanos , Mucormicose/tratamento farmacológico , Rhizopus/genética , Rhizopus oryzae , Simulação de Acoplamento Molecular , Quercetina/farmacologia , Quercetina/uso terapêutico , RNA Polimerase Dependente de RNARESUMO
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 Porphoromonas gingivalis, Tanerella forsythia and Treponema denticola. 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). The CRISPR-Cas system contributes to adaptive immunity, and this acquired genetic immune system of bacteria may contribute to moderating the microbiome of chronic periodontitis. The current research examined the role of the CRISPR-Cas system of red complex bacteria in the dysbiosis of oral bacteriophages in periodontitis. Whole-genome sequences of red complex bacteria were obtained and investigated for CRISPR using the CRISPR identification tool. Repeated spacer sequences were analyzed for homologous sequences in the bacteriophage genome and viromes using BLAST algorithms. The results of the BLAST spacer analysis for T. denticola spacers had a 100% score (e value with a bacillus phage), and the results for T. forsthyia and P. gingivalis had a 56% score with a pectophage and cellulophage (e value: 0.21), respectively. The machine learning model of the identified red complex CRISPR sequences predicts with area an under the curve (AUC) accuracy of 100 percent, indicating phage inhibition. These results infer that red complex bacteria could significantly inhibit viruses and phages with CRISPR immune sequences. Therefore, the role of viruses and bacteriophages in modulating sub-gingival bacterial growth in periodontitis is limited or questionable.
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COVID-19 mainly spreads through cough or sneeze droplets produced by an infected person. The viral particles are mostly present in the oral cavity. The risk of contracting COVID-19 is high in the dental profession due to the nature of procedures involved that produce aerosols. Along with other measures to limit the risk of infection, pre-procedural mouth rinses are beneficial in reducing the viral particles in the oral cavity. In this study, the antiviral efficacy of essential oil components has been determined specifically against SARS-CoV-2 by molecular docking and conceptual DFT approach. Based on the binding affinities of the components against the receptor binding domain of the S1 glycoprotein, cuminal, carvacrol, myrtanol, and pinocarveol were found to be highly active. The molecular descriptor values obtained through conceptual DFT also indicated the above-mentioned components to be active based on the correlation between the structure and the activity of the compounds. Therefore, pre-procedural mouth rinses with these components included may be specifically suitable for dental procedures during the COVID-19 period.