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.

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. 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. 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. 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. 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.

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.

Copper-based biomaterials are increasingly investigated for bone tissue engineering due to their osteogenic and angiogenic properties. Green synthesis using plant extracts offers an eco-friendly route for producing biocompatible nanoparticles. This study aimed to synthesize copper oxide nanoparticles (CuO NPs) using Alpinia calcarata leaf extract and evaluate their cytocompatibility and osteogenic potential in vitro. CuO NPs were synthesized by reacting copper nitrate trihydrate with A. calcarata leaf extract under alkaline conditions, followed by calcination. The nanoparticles were characterized using SEM, TEM, XRD, and FTIR to confirm morphology, crystallinity, and functional group interactions. C3H10T1/2 murine mesenchymal stem cells were used to assess cytocompatibility (MTT assay, FDA staining), osteogenic differentiation (Alizarin Red S staining and quantification), and gene expression (qRT-PCR for Runx2, Col-I, and ALP). SEM and TEM revealed aggregated, spherical nanoparticles of <100 nm, while XRD confirmed crystalline monoclinic CuO and FTIR indicated phytochemical capping. MTT and FDA assays showed CuO NPs were cytocompatible up to 50 μg/mL, with dose-dependent cytotoxicity observed at higher concentrations. Under osteogenic conditions, cells treated with 50 μg/mL CuO NPs displayed significantly enhanced mineral deposition compared to controls. Gene expression analysis demonstrated upregulation of Runx2, Col-I, and ALP, confirming promotion of osteogenic differentiation. Biogenically synthesized CuO NPs using A. calcarata extract are structurally pure, biocompatible at defined concentrations, and capable of enhancing osteoblast differentiation by stimulating matrix mineralization and osteogenic gene expression. These findings position A. calcarata–mediated CuO NPs as sustainable, multifunctional nanomaterials with promising applications in bone tissue engineering.

Periodontal disease is a chronic inflammatory condition marked by the destruction of the supporting apparatus of the tooth. The pathogenesis is largely determined by an imbalance between the pro-inflammatory and anti-inflammatory mediators. IL-23, being pro-inflammatory in nature, contributes to tissue inflammation and deregulation through the production of IL-17. On the other hand, IL-27 exerts an anti-inflammatory effect by regulating the immune response by inhibiting IL-17. The current study aimed to assess IL-23 and IL-27 levels in gingival crevicular fluid (GCF) and saliva in periodontal health and disease. Forty systemically healthy subjects were allocated into three groups: healthy (Group A, n=10), gingivitis (Group B, n=15), and periodontitis (Group C, n=15). Clinical parameters including probing depth (PD) and clinical attachment loss (CAL) were recorded. GCF and saliva samples were collected to quantify IL-23 and IL-27 levels which were analyzed using a multiplex ELISA (ProcartaPlex™ Human Th9/Th17/Th22 Cytokine Panel). The results were statistically analysed using SPSS software (version 21.0, IBM, USA). IL-23 levels in both GCF and saliva significantly increased from healthy to gingivitis to periodontitis (p < 0.05). Conversely, IL-27 levels decreased progressively across the same groups (p < 0.05). IL-23 levels showed a strong positive correlation with PD and CAL, while IL-27 levels were negatively correlated with these parameters, particularly in the periodontitis group. Elevated IL-23 levels are associated with greater disease severity, whereas IL-27 appears to exert a protective, anti-inflammatory effect. The study highlights the potential of both cytokines as biomarkers for diagnosing and monitoring periodontal conditions. However, to confirm their clinical relevance, further longitudinal studies with larger cohorts are recommended.