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Abstract Background Autophagy activation contributes to chemotherapy resistance in several cancers, including ovarian cancer. Hydroxychloroquine (HCQ) is an autophagy inhibitor inhibiting the fusion of the autophagosome with the lysosome and has been repurposed as an anti-cancer agent. In this randomized phase II study, we used HCQ in combination with standard chemotherapy in platinum sensitive relapsed ovarian cancer (PSROC) patients. Methods Patients were randomized in a 1:1 ratio to receive standard chemotherapy (carboplatin with paclitaxel/gemcitabine) with or without HCQ. Those randomized to receive HCQ received additional HCQ 200mg orally twice daily. The primary endpoint was the overall response rate (ORR). Other endpoints included survival outcomes, changes in autophagy biomarkers, toxicity, and quality of life. Results A total of 59 patients were enrolled- chemotherapy + HCQ (N = 28), chemotherapy alone (N = 31), and 56 were evaluable ( received ≥ 3 cycles treatment). The ORR was not superior with the addition of HCQ [85% (22/26) in the experimental arm as compared to 80% (24/30) in the control arm, chi-square test, P = 0.65]. The median progression-free survival was 12 (95% CI, 9.75–14.24) months for the experimental arm and 11 (95% CI, 5.25–16.74) months for the control arm (P = 0.56) , and the median overall survival was 16 (95% CI, 8.54–23.45) months vs. 21 (95% CI, 11.70–30.59 ) months (P = 0.49) respectively. HCQ was well tolerated, with no excess adverse events [21 (75%) in the experimental arm vs. 22 (71%) in the control arm]. There were no substantial differences in the reduction of autophagy biomarker levels and QOL between the control and experimental arms. Conclusion Adding HCQ to chemotherapy failed to improve response rates or survival in patients with PSROC. Conducting biomarker-stratified clinical trials might show the potential benefit of HCQ. Trial registration number (TRN): The trial was registered in the Clinical Trial Registry of India ( www.ctri.nic.in ; CTRI/2020/06/025790) on 17th June 2020.

Abstract Understanding shared pathways and mechanisms involved in the pathogenesis of diseases like oral squamous cell carcinoma (OSCC) and COVID-19 could lead to the development of novel therapeutic strategies and diagnostic biomarkers. This study aims to predict the interactome of OSCC and COVID-19 based on salivary inflammatory proteins. Datasets for OSCC and COVID-19 were obtained from https://www.salivaryproteome.org/differential-expression and selected for differential gene expression analysis. Differential gene expression analysis was performed using log transformation and a fold change of two. Hub proteins were identified using Cytoscape and Cytohubba, and machine learning algorithms including naïve Bayes, neural networks, gradient boosting, and random forest were used to predict hub genes. Top hub genes identified included ALDH1A1, MT-CO2, SERPINC1, FGB, and TF. The random forest model achieved the highest accuracy (93%) and class accuracy (84%). The naive Bayes model had lower accuracy (63%) and class accuracy (66%), while the neural network model showed 55% accuracy and class accuracy, possibly due to data pre-processing issues. The gradient boosting model outperformed all models with an accuracy of 95% and class accuracy of 95%. Salivary proteomic interactome analysis revealed novel hub proteins as potential common biomarkers.

Introduction and Objectives: Oral diseases, including gingivitis and periodontitis, are linked to the Wnt signaling pathway, vital for bone metabolism, cementum homeostasis, and mesenchymal stem cell differentiation. Advances in generative AI techniques, such as variational autoencoders (VAEs) and quantum variational classifiers (QVCs), offer promising tools for predicting gene associations between drugs and diseases. This study aims to compare the predictive performance of VAEs and QVCs in modeling drug-disease gene networks within the Wnt signaling pathway in periodontal inflammation. Methods: Genes associated with Wnt-related periodontal inflammation were identified through comprehensive literature reviews and genomic databases. Their roles in various biological processes were evaluated using gene set enrichment analysis, employing tools like Enrichr, which integrates diverse gene sets from sources such as DSigDB, DisGeNET, and Lincs_l1000.drug. The study then applied VAEs and QVCs to predict gene-disease associations related to the Wnt signaling pathway. Results: The analysis revealed an extensive network comprising 1738 nodes and 1498 edges, averaging 1.992 neighbors per node. The network exhibited a diameter of 2, a radius of 1, and a characteristic path length of 1.992, indicating limited interconnectivity. The VQA model demonstrated a high accuracy rate of 97.5%, although it only detected 50% of anomalies. The VQC model achieved a precision of 78%, with Class 1 samples showing improved recall and a balanced F1 score. Conclusion: VQC and VAE models exhibit strong potential for discovering FDA-approved drugs by predicting gene-drug associations in periodontitis based on the Wnt signaling pathway. Clinical Relevance: This study highlights the potential of VAEs and QVCs in predicting gene-drug associations for periodontal inflammation. This could lead to more targeted therapies for oral diseases like periodontitis, improving patient outcomes and advancing personalized treatment strategies in clinical practice.

Abstract The NLRP3 inflammasome, regulated by TLR4, plays a pivotal role in periodontitis by mediating inflammatory cytokine release and bone loss induced by Porphyromonas gingivalis. Periodontal disease creates a hypoxic environment, favoring anaerobic bacteria survival and exacerbating inflammation. The NLRP3 inflammasome triggers pyroptosis, a programmed cell death that amplifies inflammation and tissue damage. This study evaluates the efficacy of Variational Graph Autoencoders (VGAEs) in reconstructing gene data related to NLRP3-mediated pyroptosis in periodontitis. The NCBI GEO dataset GSE262663, containing three samples with and without hypoxia exposure, was analyzed using unsupervised K-means clustering. This method identifies natural groupings within biological data without prior labels. VGAE, a deep learning model, captures complex graph relationships for tasks like link prediction and edge detection. The VGAE model demonstrated exceptional performance with an accuracy of 99.42% and perfect precision. While it identified 5,820 false negatives, indicating a conservative approach, it accurately predicted 4,080 out of 9,900 positive samples. The model’s latent space distribution differed significantly from the original data, suggesting a tightly clustered representation of the gene expression patterns. K-means clustering and VGAE show promise in gene expression analysis and graph structure reconstruction for periodontitis research.

BackgroundThe styloid process (SP), a bony projection from the temporal bone which can become elongated, resulting in cervical pain, throat discomfort, and headaches. Associated with Eagle syndrome, this elongation can compress nearby nerves and blood vessels, leading to potentially severe complications. Traditional imaging-based methods for classifying various types of elongated styloid processes (ESP) are challenging due to variations in image quality, patient positioning, and anatomical differences, which limit diagnostic accuracy. Recent advancements in artificial intelligence, particularly deep learning, provide more efficient classification of elongated styloid processes.ObjectiveThis study aims to develop an automated classification system for elongated styloid processes using deep learning models and to evaluate the performance of two distinct architectures, EfficientNetB5 and InceptionV3, in classifying elongated styloid processes.MethodsThis retrospective analysis classified elongated styloid processes using Ortho Pantomograms (OPG) sourced from our oral radiology archives. Styloid process lengths were measured using ImageJ software. A dataset of 330 elongated and 120 normal styloid images was curated for deep learning model training and testing. Pre-processing included median filtering and resizing, with data augmentation applied to improve generalization. EfficientNetB5 and InceptionV3 models, utilized as feature extractors, captured unique styloid characteristics. Model performance was evaluated based on accuracy, precision, recall, and F1-score, with a comparative analysis conducted to identify the most effective model and support advancements in patient care.ResultsThe EfficientNetB5 model achieved an accuracy of 97.49%, a precision of 98.00%, a recall of 97.00%, and an F1-score of 97.00%, demonstrating strong overall performance. Additionally, the model achieved an AUC of 0.9825. By comparison, the InceptionV3 model achieved an accuracy of 84.11%, a precision of 85.00%, a recall of 84.00%, and an F1-score of 84.00%, with an AUC of 0.8943. This comparison indicates that EfficientNetB5 outperformed InceptionV3 across all key metrics.ConclusionIn conclusion, our study presents a deep learning-based approach utilizing EfficientNetB5 and InceptionV3 to accurately categorize elongated styloid processes into distinct types based on their morphological characteristics from digital panoramic radiographs. Our results indicate that these models, particularly EfficientNetB5, can enhance diagnostic accuracy and streamline clinical workflows, contributing to improved patient care.

Oral cancer remains a significant public health concern globally, with smoking identified as a primary risk factor. This abstract reviews the role of smoking in the etiology of oral cancer, emphasizing its contribution to carcinogenesis through the induction of genetic mutations, oxidative stress, and inflammation. Tobacco smoke contains carcinogenic compounds such as polycyclic aromatic hydrocarbons, nitrosamines, and heavy metals, which are implicated in the transformation of oral mucosal cells. Epidemiological studies consistently demonstrate a dose–response relationship between smoking intensity and oral cancer risk. Despite advances in prevention and treatment, smoking cessation remains a critical component in reducing oral cancer incidence. This review underscores the importance of public health initiatives and targeted interventions aimed at mitigating smoking-related oral cancer risk.

Oral cancer remains a significant public health concern globally, with smoking being a primary risk factor. Smoking cessation has been identified as a crucial intervention in reducing the incidence of oral cancer. This abstract reviews the impact of smoking cessation on oral cancer prevention, emphasizing the benefits of quitting smoking in decreasing the risk of developing oral malignancies. Evidence suggests that smoking cessation not only reduces the immediate risk of oral cancer but also contributes to long-term health improvements. The mechanisms through which smoking cessation exerts its protective effects, including the reduction of carcinogenic exposure and enhancement of oral mucosal health, are discussed. Public health strategies and interventions aimed at promoting smoking cessation are also highlighted as essential components in oral cancer prevention efforts.

Background: Periodontitis is a slow progressing infection and has profound systemic implications. The influence of various therapeutic drugs to inhibit inflammation and promote bone regeneration has been studied. Introduction of newer congeners of older drugs necessitates testing the efficacy of newer drugs for the said use. Aim: The aim was to determine the effectiveness of newer nitroimidazoles and fluoroquinolones for controlling and eliminating periodontal pathology by binding to the targets. Methods and Material: A total of 12 drugs were selected, and the chemical structure drugs used were retrieved form PubChem and development of 2d and 3d structures was done using chem draw software. Targets used were Gingipain K, FimA, Interleukin-1β, and Estrogen Receptor β. AutoDock version 4 software was used for in silico docking simulations. The binding free energy, inhibition constant, electrostatic energy, intermolecular energy, and total interaction surface are all provided by the docking tool. In this paper, the optimal docking pose for each target is chosen and presented. Results: From the results of the study, it can be observed that gatifloxacin and ciprofloxacin have more affinity and interactions with all four targets were analyzed. Conclusions: This study has effectively tested nitroimidazoles and fluoroquinolones comparatively and proposed that fluoroquinolones are more effective for blocking periodontitis.

Background: Oral cancer is the sixth most common cancer occurring anywhere in the globe. Cancers of the mouth are caused by tobacco and alcohol overuse, and also between pre-malignancy and full-fledged malignancy. In order to avoid the onset of illness, proper cleanliness of the mouth is important. Objective: In this study we aimed to identify the potential inhibitor for Aurora kinase B as a potential therapeutic target for oral cancer from the phytocompounds from Ocimum sanctum. Methodology: Compounds from Ocimum sanctum were screened against Aurora kinase B using a structure-based virtual screening approach using Pyrx software. Based on the scoring parameters best compounds were chosen to analysis the interaction by using Discovery studio visualizer. Results: Four compounds—pedunculin, nevadensin, chrysoeriol, and genistein were selected as the most promising leads based on the scoring parameter. Conclusion: These chemicals could be potential therapeutic candidates that need to be investigated further in the laboratory.

Introduction: Different factors affect the quality and viability of cord blood stem cells, and therefore the efficacy of umbilical cord stem cell transplantation. Fetal distress is one factor affecting the quantity of CD34+ cells in cord blood. This study was designed to compare the viability and yield of the umbilical cord blood stem cells of women who have undergone emergency lower segment caesarean section for fetal distress or for other causes. Materials and methods: This cross-sectional analytical study was performed at a tertiary care hospital facility with a total sample size of 68: 34 participants had undergone emergency C-section for fetal distress, and 34 had undergone emergency C-section for other causes. Umbilical cord blood was collected ex-utero in a 350 mL bag with citrate-phosphate-dextrose solution with adenine. Three milliliter of blood were transferred to an ethylenediaminetetraacetic acid (EDTA) tube for cell counts and flow cytometry testing for CD34+. The chi-square test was used to compare the total mononuclear cell, CD34+, and viability between the groups. Results: The CD34+ count [mean 4.9 versus 1.1 (× 106 cells/unit)] and total nucleated cell count [mean 14.2 versus 7.5 (× 108/unit)] were significantly higher in cord blood units collected from women who delivered by C-section for fetal distress (p-value 0.05). Conclusion: The current study shows that umbilical cord blood collected during fetal distress has a significantly higher content of stem cells and total nucleated cells than the non-fetal distress group

IntroductionPeri-implantitis, a destructive inflammatory condition affecting the tissues surrounding dental implants, shares pathological similarities with periodontitis, a chronic inflammatory disease that impacts the supporting structures of natural teeth. This study utilizes a network-based approach to classify interactome hub genes associated with peri-implantitis and periodontitis, aiming to improve understanding of disease mechanisms and identify potential therapeutic targets.MethodsWe employed gradient boosting and Weighted Gene Co-expression Network Analysis (WGCNA) to predict and classify these interactome hub genes. Gene expression data related to these diseases were sourced from the NCBI GEO dataset GSE223924, and differential gene expression analysis was conducted using the NCBI GEO R tool. Through WGCNA, we constructed a co-expression network to identify key hub genes, while gradient boosting was used to predict these hub genes.ResultsOur analysis revealed a co-expression network comprising 216 genes, including prominent hub genes such as IL17RC, CCN2, BMP7, TPM1, and TIMP1, which are implicated in periodontal disease. The gradient boosting model achieved an 88.2% accuracy in classifying interactome hub genes in samples related to peri-implantitis and periodontitis.DiscussionThese identified genes play roles in inflammation, osteoclast genesis, angiogenesis, and immune response regulation. This study highlights essential hub genes and molecular pathways associated with peri-implantitis and periodontitis, suggesting potential therapeutic targets for developing innovative treatment strategies.

Nanoparticles are attractive therapeutic tools due to their distinctive characteristics, including more accurate drug delivery, improved bioavailability, and enhanced targeted therapy. This review offers a comprehensive analysis of the therapeutic potentials of cutting-edge nanoparticles as demonstrated in human clinical trials, based on empirical evidence. Through systematic searches of major scientific databases, relevant studies published up to March 2024 were included, focusing on clinical trials utilizing advanced nanoparticles for therapeutic purposes. The review discusses the diverse applications of nanoparticles in oncology, infectious diseases, neurology, and other medical fields. Additionally, it scrutinizes the safety profiles, efficacy outcomes, and challenges associated with nanoparticle-based therapies. The findings underscore significant progress in translating nanoparticle research into clinical practice and highlight the potential of these innovative platforms to revolutionize medical treatments. This review contributes valuable insights into the growing field of nanoparticle-based therapeutics, fostering a deeper understanding of their clinical applications and implications in medical practice.

The P2X7 receptor, a member of the P2X receptor family, plays a crucial role in various physiological processes, particularly pain perception. Its expression across immune, neuronal, and glial cells facilitates the release of pro-inflammatory molecules, thereby influencing pain development and maintenance, as evidenced by its association with pulpitis in rats. Notably, P2X receptors such as P2X3 and P2X7 are pivotal in dental pain pathways, making them promising targets for novel analgesic interventions. Leveraging graph neural networks (GNNs) presents an innovative approach to model graph data, aiding in the identification of drug targets and prediction of their efficacy, complementing advancements in genomics and proteomics for therapeutic development. In this study, 921 drug-gene interactions involving P2X receptors were accessed through https://www.probes-drugs.org/. These interactions underwent meticulous annotation, preprocessing, and subsequent utilization to train and assess GNNs. Furthermore, leveraging Cytoscape, the CytoHubba plugin, and other bioinformatics tools, gene expression networks were constructed to pinpoint hub genes within these interactions. Through analysis, SLC6A3, SLC6A2, FGF1, GRK2, and PLA2G2A were identified as central hub genes within the context of P2X receptor-mediated drug-gene interactions. Despite achieving a 65 percent accuracy rate, the GNN model demonstrated suboptimal predictive power for gene-drug interactions associated with oral pain. Hence, further refinements and enhancements are imperative to unlock its full potential in elucidating and targeting pathways underlying oral pain mechanisms.

Introduction: Oral cancer’s aggressive nature poses a significant health risk, demanding timely diagnosis and effective treatment. Despite progress in conventional therapies like chemotherapy and surgery, their limitations drive the exploration of alternative strategies. This study assessed Solanum trilobatum-derived silver nanoparticles (AgNPs) in impacting cancer cell cycles, inducing apoptosis, and modulating key pathways, including the phosphoinositide 3-kinase (PI3K)/Protein kinase B (AKT)/mammalian target of rapamycin (mTOR) pathway, leveraging phytotherapy and nanotechnology—a promising frontier in cancer treatment. Methods: AgNPs were synthesized through the reduction of ions and stabilized using aqueous leaf extracts of S. trilobatum. After the characterization of AgNPs, the mRNA Gene Expression and mitochondrial membrane potentials (MMPs) were assessed. DNA fragmentation was done and DNA pattern by gel documentation system was observed. The study also assessed the modulation of the PI3K/Akt/mTOR cascade, impacting tumor growth and proliferation. Results: Biosynthesized AgNPs were characterized using UV-visible spectrophotometry (UVvis), energy-dispersive X-ray spectroscopy (EDX), scanning electron microscopy (SEM), and Fourier-transform infrared (FTIR) spectroscopy. DNA fragmentation exhibited a typical ladder pattern. Dose-dependent changes in MMP were observed in the treated oral cancer cells. The effect of S. trilobatum-derived AgNPs in targeting the cell signaling pathway correlated significantly with their anticancer potency (P

Introduction: This research explores the capability of silver nanoparticles (AgNPs) produced via friendly methods by using Solanum trilobatum leaf extract. The choice of S. trilobatum was supported by its diverse phytochemical makeup, which comprises recognized bioactive elements known for their anti-inflammatory and anti-cancer attributes. This research explores the effect of AgNPs derived from this plant as a promising eco-friendly strategy in oral cancer treatment. Methods: The synthesis of AgNPs involved employing S. trilobatum leaf extract, with observable color changes and spectral analyses confirming the unique characteristics of the nanoparticles. Fourier transform infrared spectroscopy detected distinct functional groups, whereas scanning electron microscopy (SEM) confirmed the presence of biocapped nanoparticles exhibiting various shapes and sizes spanning from 100 to 300 nm. Results: Cytotoxicity assessments via the 3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide (MTT) assay revealed a half-minimal inhibitory concentration (IC50) value of 3.715 ± 0.242 μg/mL against the oral cancer (KB) cell line, indicating a significant inhibition. Acridine orange/ethidium bromide (AO/EtBr) and reactive oxygen species (ROS) assays further supported the AgNPs’ anti-cancer potential, affirming their promise for oral cancer therapy. Conclusion: AgNPs synthesized from S. trilobatum leaf extract showed substantial potential as a therapeutic agent for oral cancer. This research adds to the increasing evidence endorsing the use of environmentally friendly synthesized nanoparticles in medical treatments.

Introduction: Malocclusion is multifactorial in origin, caused by the interaction of various general and local factors. The consequences of malocclusion include dental caries, periodontitis, impaction of teeth, and compromised chewing abilities. Thus, if left untreated, malocclusion can not only lead to oral health problems like periodontal problems and dental caries but also psychological problems, causing a loss of self-esteem and confidence in the individual. Aim: To assess the potential relationship between malocclusion with orthodontic treatment needs and dental caries, periodontal diseases, dental traumatic injuries, oral hygiene, and Oral Health-related Quality of Life (OHRQoL). Materials and Methods: A cross-sectional study was conducted among 1800 school-going and college students at their respective Institutions in Chennai, Tamil Nadu, India from December 2021 to June 2022 with and without orthodontic treatment needs, to identify malocclusion and various oral conditions/diseases associated with it, in addition to the effect of malocclusion on OHRQoL. Oral health status was assessed using the World Health Organisation (WHO) Basic Oral Health Survey (2013); malocclusion was assessed using the Index of Orthodontic Treatment Needs (IOTN) index, and OHRQoL was measured using OHIP-14. Data were analysed using Statistical Packages for Social Sciences (SPSS) version 23.0 software, and statistical significance was assessed using Pearson’s Chi-square test and Mann-Whitney U Test. Results: The study was conducted among 1800 subjects aged between 14 and 21 years (mean 17.47±1.58 years) from various schools and colleges in Chennai. Among the study subjects, 1066 (59.2%) were males, and 734 (40.8%) were females. About 46.7% of the study subjects had malocclusion. The binomial logistic regression analysis suggested that study subjects with orthodontic treatment needs had greater odds of experiencing dental caries, gingival bleeding, and traumatic dental injuries compared to study subjects without orthodontic treatment needs. Conclusion: There is a definite relationship between malocclusion, orthodontic treatment needs, dental caries, periodontal diseases, dental traumatic injuries, oral hygiene, and OHRQoL.

IntroductionUntreated periodontitis significantly increases the risk of tooth loss, often delaying treatment due to asymptomatic phases. Recent studies have increasingly associated poor dental health with conditions such as rheumatoid arthritis, diabetes, obesity, pneumonia, cardiovascular disease, and renal illness. Despite these connections, limited research has investigated the relationship between appendicitis and periodontal disease. This study aims to predict appendicitis in patients with periodontal disease using biochemical and clinical parameters through the application of a light gradient boost tree classifier.MethodsData from 125 patient records at Saveetha Institute of Dental College and Medical College were pre-processed and analyzed. We utilized data preprocessing techniques, feature selection methods, and model development approaches to estimate the risk of appendicitis in patients with periodontitis. Both Random Forest and Light Gradient Boosting algorithms were evaluated for accuracy using confusion matrices to assess their predictive performance.ResultsThe Random Forest model achieved an accuracy of 94%, demonstrating robust predictive capability in this context. In contrast, the Light Gradient Boost algorithms achieved a significantly higher accuracy of 98%, underscoring their superior predictive efficiency. This substantial difference highlights the importance of algorithm selection and optimization in developing reliable predictive models. The higher accuracy of Light Gradient Boost algorithms suggests effective minimization of prediction errors and improved differentiation between appendicitis with periodontitis and healthy states. Our study identifies age, white blood cell count, and symptom duration as pivotal predictors for detecting concurrent periodontitis in acute appendicitis cases.ConclusionsThe newly developed prediction model introduces a novel and promising approach, providing valuable insights into distinguishing between periodontitis and acute appendicitis. These findings highlight the potential to improve diagnostic accuracy and support informed clinical decision-making in patients presenting with both conditions, offering new avenues for optimizing patient care strategies.

This descriptive research has attempted to assess customers' satisfaction with services offered by car servicing firms in India. The researcher administered a structured questionnaire to 300 company customers, selected using the Systematic Random Sampling technique. Data collected were analyzed using SPSS, applying the analytical tools of Frequency, Percentage, Mean, factor analysis, cluster analysis, Chi-square and Correspondence Analysis. Results of the study have revealed that the caring nature of servicing staff, the quality of services and service personnel, and the convenience and comfort offered to customers have been identified as the most important factors affecting customer satisfaction.

Chronic periodontitis is a ubiquitous inflammatory disease in dental healthcare that is challenging to treat due to its impact on bone and tooth loss. Conventional mechanical debridement has been challenging in eliminating complex subgingival biofilms. Hence, adjunctive approaches like low-level laser antimicrobial photodynamic therapy (A-PDT) utilising methylene blue (MB) have been emerging approaches in recent times. This review evaluates the latest research on the use of MB-mediated A-PDT to decrease microbial count and enhance clinical results in chronic periodontitis. Studies have shown the interaction between laser light and MB generates a phototoxic effect thereby, eliminating pathogenic bacteria within periodontal pockets. Moreover, numerous clinical trials have shown that A-PDT using MB can reduce probing depths, improve clinical attachment levels, and decrease bleeding during probing in comparison to traditional treatment approaches. Notably, A-PDT shows superior antibiotic resistance compared to conventional antibiotic treatments. In conclusion, the A-PDT using MB shows promise as an adjunctive treatment for chronic periodontitis. Additional research is required to standardize treatment protocols and assess long-term outcomes of A-PDT with MB in the treatment of periodontitis.

BackgroundCooling towers are specialized heat exchanger devices in which air and water interact closely to cool the water's temperature. However, the cooling water contains organic nutrients that can cause microbial corrosion (MC) on the metal surfaces of the tower. This research explores the combined wastewater treatment approach using electrochemical-oxidation (EO), photo-oxidation (PO), and photoelectrochemical oxidation (PEO) to contain pollutants and prevent MC.MethodsThe study employed electro-oxidation, a process involving direct current (DC) power supply, to degrade wastewater. MC studies were conducted using weight loss assessments, scanning electron microscopy (SEM), and x-ray diffraction (XRD).ResultsAfter wastewater is subjected to electro-oxidation for 4 h, a notable decrease in pollutants was observed, with degradation efficiencies of 71, 75, and 96%, respectively. In the wastewater treated by PEO, microbial growth is restricted as the chemical oxygen demand decreases.DiscussionA metagenomics study revealed that bacteria present in the cooling tower water consists of 12% of Nitrospira genus and 22% of Fusobacterium genus. Conclusively, PEO serves as an effective method for treating wastewater, inhibiting microbial growth, degrading pollutants, and protecting metal from biocorrosion.

Oral malignancy, notably oral squamous cell carcinoma (OSCC), stands as a formidable global health issue, characterized by disparate prevalence among demographics and geographic regions. Traditional diagnostic modalities, reliant on biopsy and histopathological methods, they all often exhibit constraints in expeditiousness and subjectivity, thus an alternative methodologies are needed for fostering early detection and personalized therapeutic strategies. Artificial intelligence (AI) emerges as a forefront avenue in oral cancer (OC) therapeutics, engaged in providing solutions for diagnostic augmentation, treatment optimization, and prognostic delineation. Machine learning paradigms, encompassing supervised and unsupervised learning, afford meticulous classification and pattern identification from multifarious clinical and histopathological datasets. Deep learning architectures, exemplified by convolutional neural networks (CNNs), automatize lesion detection, and characterization from medical imagery, thereby expediting diagnostic efficacy. Predictive analytics methodologies combine multifaceted patient data to access risk and prognosticate disease trajectory, thereby facilitating bespoke treatment schema. Expert systems harness medical knowledge and patient-centric intelligence to furnish decision support for clinicians in treatment modality selection and disease monitoring. Robotic and automated systems contribute to surgical precision and procedural streamlining, ultimately fostering enhanced patient outcomes. Despite these advancements, challenges remain persists necessitating continued interdisciplinary collaboration and research efforts. This review explores about burgeoning role of AI in OC therapeutics, elucidating extant applications, challenges, and future trajectories for research and clinical adoption in oral oncology.

Summary: Genome-wide association studies (GWASs) have identified numerous variants associated with polygenic traits and diseases. However, with few exceptions, a mechanistic understanding of which variants affect which genes in which tissues to modulate trait variation is lacking. Here, we present genomic analyses to explain trait heritability of blood pressure (BP) through the genetics of transcriptional regulation using GWASs, multiomics data from different tissues, and machine learning approaches. Approximately 500,000 predicted regulatory variants across four tissues explain 33.4% of variant heritability: 2.5%, 5.3%, 7.7%, and 11.8% for kidney-, adrenal-, heart-, and artery-specific variants, respectively. Variation in the enhancers involved shows greater tissue specificity than in the genes they regulate, suggesting that gene regulatory networks perturbed by enhancer variants in a tissue relevant to a phenotype are the major source of interindividual variation in BP. Thus, our study provides an approach to scan human tissue and cell types for their physiological contribution to any trait.

The fabrication of zinc oxide-based nanomaterials (including natural and synthetic polymers like sulfated polysaccharide, chitosan, and polymethyl methacrylate) has potential to improve oral cancer treatment strategies. This comprehensive review explores the diverse synthesis methods employed to fabricate zinc oxide nanomaterials tailored for oral cancer applications. Several synthesis processes, particularly sol–gel, hydrothermal, and chemical vapor deposition approaches, are thoroughly studied, highlighting their advantages and limitations. The review also examines how synthesis parameters, such as precursor selection, the reaction temperature, and growth conditions, influence both the physicochemical attributes and biological efficacy of the resulting nanomaterials. Furthermore, recent advancements in surface functionalization and modification strategies targeted at improving the targeting specificity and pharmaceutical effectiveness of zinc oxide-based nanomaterials in oral cancer therapy are elucidated. Additionally, the review provides insights into the existing issues and prospective views in the field, emphasizing the need for further research to optimize synthesis methodologies and elucidate the mechanisms underlying the efficacy of zinc oxide-based nanoparticles in oral cancer therapy.

Oral cancer (OC) is among the most common malignancies in the world. Despite advances in therapy, the worst-case scenario for OC remains metastasis, with a 50% survival rate. Therefore, it is critical to comprehend the pathophysiology of the condition and to create diagnostic and treatment plans for OC. The development of high-throughput genome sequencing has revealed that over 90% of the human genome encodes non-coding transcripts, or transcripts that do not code for any proteins. This paper describes the function of these different kinds of non-coding RNAs (ncRNAs) in OC as well as their intriguing therapeutic potential. The onset and development of OC, as well as treatment resistance, are linked to dysregulated ncRNA expression. These ncRNAs’ potentially significant roles in diagnosis and prognosis have been suggested by their differing expression in blood or saliva. We have outlined every promising feature of ncRNAs in the treatment of OC in this study.

Periodontal disease is the inflammation of the periodontal supporting structures of teeth. An index is an important tool of surveillance system based on the requirements of reliability, simplicity, and validity to screen oral health disease of the population. This paper aims to discuss on various indices formulated to measure periodontal disease from past to present. This paper reviews indices and different recording systems used to measure periodontal diseases at the population level by retrieving articles, selecting, writing, and summarizing the article. The advantages and disadvantages of various indices used for measuring periodontal disease are discussed in this article. Community Periodontal Index is the most widely accepted index used in larger research studies. However, presently, clinical attachment loss is a widely accepted tool for the diagnosis of periodontal disease. Future advances in new screening methods will be able to provide new opportunities in the diagnosis of active and progressive periodontal disease, which will further help in more precise screening of periodontal disease in larger research studies.

The field of nanotechnology or nanoscience encompasses research and development in the applied sciences at the atomic or molecular levels and has a huge impact on nearly every aspect of human health and well-being, including pharmacological studies, clinical diagnosis, and supplemental immune system treatments. The numerous dental uses of nanotechnology have led to the development of the field of nanodentistry. The efficacy of dental operations and the field’s possibilities have grown greatly over the years as a result of extensive research in the fields of biomaterials and nanotechnology. Materials with nanoscale dimensions can display features not found in their larger-scale equivalents. Endodontic procedures are time-consuming and usually require multiple visits to attain the best results. The eradication of primary bacterial infection from dental root canals is still a serious concern in dentistry. Nanoparticles have been shown to be more efficient than standard materials and to have superior capabilities in terms of surface chemistry and bonding. Their antimicrobial characteristics are also promising in all medical procedures, particularly in endodontics. Because of their versatility, nanomaterials are a useful tool in dental clinics for a variety of operations including pulp regeneration, drug administration, root restoration, cleaning, obturation, and canal filling. This review provides an overview of the synthesis and characteristics of nanomaterials and their potential applications in dentistry and describes future perspectives of nanotechnology in dentistry with an updated literature review.

Early detection is crucial for the treatment and prognosis of oral cancer, a potentially lethal condition. Tumor markers are abnormal biological byproducts produced by malignant cells that may be found and analyzed in a variety of bodily fluids, including saliva. Early detection and appropriate treatment can increase cure rates to 80–90% and considerably improve quality of life by reducing the need for costly, incapacitating medicines. Salivary diagnostics has drawn the interest of many researchers and has been proven to be an effective tool for both medication monitoring and the diagnosis of several systemic diseases. Since researchers are now searching for biomarkers in saliva, an accessible bodily fluid, for noninvasive diagnosis of oral cancer, measuring tumor markers in saliva is an interesting alternative to blood testing for early identification, post-treatment monitoring, and monitoring high-risk lesions. New molecular markers for oral cancer detection, treatment, and prognosis have been found as a result of developments in the fields of molecular biology and salivary proteomics. The numerous salivary tumor biomarkers and how they relate to oral cancer and pre-cancer are covered in this article. We are optimistic that salivary protein biomarkers may one day be discovered for the clinical detection of oral cancer because of the rapid advancement of proteomic technology.

Throughout the world, oral cancer is a common and aggressive malignancy with a high risk of morbidity, mortality, and recurrence. The importance of early detection in cancer prevention and disease treatment cannot be overstated. Conventional therapeutic strategies have minor difficulties but considerable side effects and unfavourable consequences in clinical applications. Hence, there is a requirement for effective ways for early detection and treatment of oral cancer. At present, numerous forms of nanoparticles have piqued researchers’ interest as a potentially useful tool for diagnostic probes and medicinal devices. Because of their inherent physicochemical properties and customizable surface modification, they are able to circumvent some of restrictions and accomplish the intended diagnostic and therapeutic impact. Nanotechnology is a unique field that has revolutionised the industry and is paving the way for new treatments for oral cancer. It can help with a better diagnosis with less harmful substances and is setting current guidelines for treatment. The use of nanotechnology in cancer diagnosis, therapy, and care improves clinical practise dramatically. The different types of nanoparticles that have been developed for the diagnosis and therapy of oral cancers will be covered in this study. The difficulties and potential uses of nanoparticles in the treatment and diagnosis of oral cancer are then highlighted. In order to emphasise existing difficulties and potential remedies for oral cancer, a prospective view of the future is also provided.

Oral squamous cell carcinoma is characterized by the upregulation of RAC-alpha serine/threonine-protein kinase (Akt1) and RAC-beta serine/threonine-protein kinase (Akt2). In this work, Akt1 and Akt2 were inhibited using a cocktail of 20 marine algae chemicals. From the PyRx Virtual Screening Tool, dieckol, 6,6′-bieckol, siphonaxanthin and sargachromanol E were chosen as the best four compounds for Akt1 based on the scoring. Similarly, dieckol, 6,6′-bieckol, dioxinodehydroeckol and caulerpenyne were chosen as Akt2 inhibitors. Additionally, the results of the Lipinski rule of five indicated that some of the selected compounds, such as dieckol, 6,6′-bieckol and siphonaxanthin, violated some Lipinski rules, but they demonstrated excellent binding in terms of scoring. Thus, this study demonstrates that the identified lead compounds may act against Akt1 and Akt2 in oral cancer.

Obesity is a worldwide health issue which is displaying increasing prevalence trend. World Health Organisation (WHO) has already given it as epidemic status. Many physiological parameters such as Body Mass Index (BMI), Waist Circumference (WC), Waist to Hip Ratio (WHR) are used for measurement of obesity. This review was written with the aim to give an inclusive picture of current prevalence of obesity along with discussing the physiology and function of different adipocytes and the numerous chemical messengers released by them. The manifold impact of obesity on various body systems can be elucidated by exploring the adipocytes, adipokines, its functions and signalling mechanism. The adipokines enlist as key players in numerous systemic diseases. Obesity has a significant pathophysiological role in morbidity and mortality causing conditions globally. Obesity can potentially be the leading reason of economic burden on global healthcare, adversely impacting the comprehensive quality of life. This review is an effort to provide a better understanding of the current obesity status and emphasise further researches on its diverse aspects.

Various e-tools and interactive media have improved and enhanced the teaching and learning in higher education. For example, flipped teaching pedagogy encourages the students to engage in the various in-class activities rather than just to be a passive learner by listening to the lectures. On the other hand, newly joined students have trouble understanding the key modules since they don't know the fundamental concepts related to the modules. This paper illustrates how online quiz creators and education tools might improve the student performance in academic setup. The online quiz creator has numerous styles, including photo quizzes, team quizzes, one-page quizzes, image quizzes, memory games, and match games for dynamic, energetic, and passionate student engagement. Students may self-assess their progress using ICT-based online quizzes. This platform assists with student engagement and learning to make them active learner. Students are greatly motivated by various learning styles and technology that suits them. This also has helped the students to avoid a random online tool and join a safe environment to enhance their learning. Supporting multiple learning styles is one of the techniques that should be implemented in every module delivery. The effectiveness of using these practices in teaching is measured through student feedback. Based on their responses, it is concluded that many benefits are found by adapting these practices, such as students' increased interest in their modules, improved understanding skills, and relational abilities.

Globally, millions of people suffer from poor wound healing, which is associated with higher mortality rates and higher healthcare costs. There are several factors that can complicate the healing process of wounds, including inadequate conditions for cell migration, proliferation, and angiogenesis, microbial infections, and prolonged inflammatory responses. Current therapeutic methods have not yet been able to resolve several primary problems; therefore, their effectiveness is limited. As a result of their remarkable properties, bio-based materials have been demonstrated to have a significant impact on wound healing in recent years. In the wound microenvironment, bio-based materials can stimulate numerous cellular and molecular processes that may enhance healing by inhibiting the growth of pathogens, preventing inflammation, and stimulating angiogenesis, potentially converting a non-healing environment to an appropriately healing one. The aim of this present review article is to provide an overview of the mechanisms underlying wound healing and its pathophysiology. The development of bio-based nanomaterials for chronic diabetic wounds as well as novel methodologies for stimulating wound healing mechanisms are also discussed.

Background: The expression of major histocompatibility complex (MHC) molecule is essential for homeostasis of the immune system. The expression of MHC-II is regulated by the master regulator for transcription, the Class II transactivator (CIITA) gene. Homozygous mutations affecting the CIITA gene result in bare lymphocyte syndrome type-II, but the clinical manifestations of heterozygous mutations are not well reported. Clinical Description: Herein, we describe the roller coaster course of a 6-year-old child who had presented with recurrent infections in infancy and systemic lupus erythematosus (SLE) in toddler age, who was later found to have heterozygous mutation in the CIITA gene. Management: The child was managed with immunosuppression for SLE and monthly intravenous immunoglobulin replacement therapy and daily cotrimoxazole prophylaxis for features of immunodeficiency. Conclusion: This case report aims to provide more insight into the clinical features associated with heterozygous mutations of CIITA.

Summary: In the heart, primary microRNA-208b (pri-miR-208b) and Myheart (Mhrt) are long non-coding RNAs (lncRNAs) encoded by the cardiac myosin heavy chain genes. Although preclinical studies have shown that lncRNAs regulate gene expression and are protective for pathological hypertrophy, the mechanism underlying sex-based differences remains poorly understood. In this study, we examined DNA- and RNA-methylation-dependent regulation of pri-miR-208b and Mhrt. Expression of pri-miR-208b is elevated in the left ventricle of the female heart. Despite indistinguishable DNA methylation between sexes, the interaction of MeCP2 on chromatin is subject to RNase digestion, highlighting that affinity of the methyl-CG reader is broader than previously thought. A specialized procedure to isolate RNA from soluble cardiac chromatin emphasizes sex-based affinity of an MeCP2 co-repressor complex with Rest and Hdac2. Sex-specific Mhrt methylation chromatinizes MeCP2 at the pri-miR-208b promoter and extends the functional relevance of default transcriptional suppression in the heart. : Molecular Physiology; Molecular Genetics; Molecular Mechanism of Gene Regulation Subject Areas: Molecular Physiology, Molecular Genetics, Molecular Mechanism of Gene Regulation

Oral cancer is a serious concern to people all over the world because of its high mortality rate and metastatic spread to other areas of the body. Despite recent advancements in biomedical research, OC detection at an early stage remains a challenge and is complex and inaccurate with conventional diagnostics procedures. It is critical to study innovative approaches that can enable a faster, easier, non-invasive, and more precise diagnosis of OC in order to increase the survival rate of patients. In this paper, we conducted a review on how biosensors might be an excellent tool for detecting OC. This review covers the strategies that use different biosensors to target various types of biomarkers and focuses on biosensors that function at the molecular level viz. DNA biosensors, RNA biosensors, and protein biosensors. In addition, we reviewed non-invasive electrochemical methods, optical methods, and nano biosensors to analyze the OC biomarkers present in body fluids such as saliva and serum. As a result, this review sheds light on the development of ground-breaking biosensors for the early detection and diagnosis of OC.

One of the most frequent head and neck cancers is oral cancer, with less than half of those diagnosed surviving five years. Despite breakthroughs in the treatment of many other cancers, the prognosis for people with OSCC remains dismal. The conventional methods of detection include a thorough clinical examination, biochemical investigations, and invasive biopsies. Early identification and treatment are important for a better chance of extending a patient’s life. Early diagnosis may be possible by identifying biomarkers in biological fluids. Currently, the primary method for diagnosing oral lesions is a visual oral examination; however, such a technique has certain drawbacks, as individuals are recognized after their cancer has advanced to a severe degree. The first section of this review discusses several diagnostic techniques for cancer detection, while the second section discusses the present state of knowledge about known existing predictive markers for the timely identification of malignant lesions, as well as disease activity tracking. The aim of the paper is to conduct a critical review of existing oral cancer diagnostic processes and to consider the possible application of innovative technology for early detection. This might broaden our diagnostic choices and enhance our capacity to identify and treat oral malignant tumors more effectively.

Background: Fixed orthodontic treatment is time-consuming procedure. Pain is usually associated with orthodontic treatment. The aim of the present study was to evaluate the role of low-level laser therapy (LLLT) on orthodontic tooth movement (OTM) duration and pain perception. Materials and Methods: This randomized double-blind splint-mouth controlled clinical study includes 20 (8 males and 12 females) orthodontic patients requiring bilateral canine retraction. Time taken for canine retraction with LLLT (Group A) over control (Group B) quadrant on the same patient was assessed along with pain experience using facial pain scale. The data were tabulated and statistically evaluated using SPSS 20 for windows (Microsoft, Chicago, IL, USA) and t-test with P < 0.05. The difference in pain was evaluated with Wilcoxon signed-rank test. Results: There was no difference in values for age and sex of patient for tooth movement and pain (P > 0.05). There was statistically significant decrease in rate of canine retraction in Group A compared to Group B. There was statistically significant difference for maxillary and mandibular arches in Group A whereas it was not significant in Group B. Pain experience was statistically significant till 2nd day, and after 3rd day, it was not significant between the groups. Conclusion: LLLT can reduce the fixed OTM timing and pain experience.

A 55-year-old male, with a 2-month history of urinary incontinence, a suspected case of pyelonephritis was initially treated by a nephrologist, but with no relief in spite of medication. On further evaluation, he was found to have a history of back pain, progressive bilateral weakness of lower extremities, and difficulty walking. He was thus referred to us for further management. Magnetic resonance imaging (MRI) of the spine was done, which revealed the presence of multiple bilateral dumbbell-shaped lesions at multiple spinal levels, associated with widening of the neural foramina of the cervical, dorsal, and lumbar regions. Surgical excision of all lesions was done in a single sitting. The patient had postoperative weakness and urinary incontinence, which slowly recovered and weakness gradually improved by physiotherapy. On follow-up, the patient was able to walk without any weakness. Surgical excision is the treatment of choice for spinal neurofibromatosis. Diagnosis of the condition may be difficult due to the lack of symptoms in majority of the cases or presentation with rare symptoms. However, it is recommended that a routine MRI of the spine be performed in patients with a history of urinary incontinence associated with weakness of limbs.

Transesophageal echocardiography has been shown to provide unique information about cardiac anatomy, function, hemodynamics and blood flow and is relatively easy to perform with a low risk of complications. Echocardiographic evaluation of the tricuspid and pulmonary valves can be achieved with two-dimensional and Doppler imaging. Transesophageal echocardiography of these valves is more challenging because of their complex structure and their relative distance from the esophagus. Two-dimensional echocardiography allows an accurate visualization of the cardiac chambers and valves and their motion during the cardiac cycle. Doppler echocardiography is the most commonly used diagnostic technique for detecting and evaluating valvular regurgitation. The lack of good quality evidence makes it difficult to recommend a validated quantitative approach but expert consensus recommends a clinically useful qualitative approach. This review ennumerates probe placement, recommended cross-sectional views, flow patterns, quantitative equations including the clinical approach to the noninvasive quantification of both stenotic and regurgitant lesions.

An 18-month-old boy presented with recurrent episodes of irritability and documented fast heart rate suggestive of supraventricular tachycardia. Cardiovascular examination revealed significant cardiomegaly, normal heart sounds and no murmurs. The differential diagnosis of marked right atrial dilatation and management principles of idiopathic dilatation of the right atrium are described., Competing Interests: Declarations. Human rights statements and informed consent: All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1964 and later revisions. Informed consent was obtained from the patient for being included in the study. No patient identity particulars have been disclosed., (© 2024. Japanese Society of Echocardiography.)

Background: Cardiac autonomic neuropathy (CAN) is an underdiagnosed complication of type 2 diabetes mellitus (T2DM) and is associated with cardiovascular morbidity and mortality. Cardiac autonomic reflex tests (CARTs) are the gold standard; they are non-invasive and clinically feasible for screening CAN. The objective of the present meta-analysis was to examine exercise's effect on cardiac autonomic function using CARTs in T2DM., Methods: The Preferred Reporting Items for Systematic Review and Meta-Analysis Checklist (PRISMA) was used. Electronic databases were systematically used to retrieve relevant studies after title and abstract screening. Studies utilizing exercise training with cardiac autonomic function (CARTs) outcomes in individuals with type 2 diabetes mellitus were included. The meta-analysis was conducted using RevMan 5.4.1, using the random effects model, and appropriate tests for heterogeneity. The Cohrane ROB-2 tool was used for randomized controlled trials (RCTs) and the ROBINS-I tool for non-RCT for risk of bias assessment were used., Results: Three studies were included (two for meta-analysis), considering the outcome of the E:I ratio, 30:15 ratio, and Valsalva ratio. The studies did not show any influence on the E:I and 30:15 ratio in the pooled analysis with a low risk of ineffectiveness for the exercise intervention. Exercise training significantly affected the Valsalva ratio. A different type of exercise intervention was utilized in all three studies. There was a low to moderate certainty for the evidence., Conclusion: The results indicate that further robust and high-quality randomized controlled trials utilizing cardiac autonomic reflex tests (which have clinical and physiological relevance) in type 2 diabetes mellitus are required for drawing conclusions., Systematic Review Registration: PROSPERO CRD42023445561., Competing Interests: Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)