Background. Microscopes are omnipresent throughout the field of biological research. With microscopes one can see in detail what is going on at the cellular level in tissues. Though it is a ubiquitous tool, the limitation is that with high magnification there is a small field of view. It is often advantageous to see an entire sample at high magnification. Over the years technological advancements in optics have helped to provide solutions to this limitation of microscopes by creating the so-called dedicated “slide scanners” which can provide a “whole slide digital image.” These scanners can provide seamless, large-field-of-view, high resolution image of entire tissue section. The only disadvantage of such complete slide imaging system is its outrageous cost, thereby hindering their practical use by most laboratories, especially in developing and low resource countries.Methods. In a quest for their substitute, we tried commonly used image editing software Adobe Photoshop along with a basic image capturing device attached to a trinocular microscope to create a digital pathology slide.Results. The seamless image created using Adobe Photoshop maintained its diagnostic quality.Conclusion. With time and effort photomicrographs obtained from a basic camera-microscope set up can be combined and merged in Adobe Photoshop to create a whole slide digital image of practically usable quality at a negligible cost.

Aim. To present a case of Cowden's syndrome and emphasize the importance of continued cancer surveillance in these patients. Cowden syndrome is an inherited autosomal dominant trait with incomplete penetrance and a range of expressivity. It is characterized by multiple hamartomas and neoplasms. Mucocutaneous features include trichilemmomas, oral mucosal papillomatosis, acral keratosis, and palmoplantar keratosis. Here, we report a case of Cowdens syndrome of a 30-year-old female patient who came with a complaint of multiple growths in the oral cavity of a three-month duration. On examination, multiple skin-colored, flat-topped papules over her forehead and right malar bone and multiple papillomatous papules involving all the mucosal surfaces intraorally were observed. This syndrome is associated with the development of several types of malignancies, especially breast carcinoma and thyroid carcinoma, which is why early recognition and regular and vigilant surveillance of individuals with the syndrome are important.

Objectives: This study evaluated the number and quality of working length (WL) and master cone (MC) radiographs taken during root canal treatment by dental undergraduates, and their associations with the technical quality of root canal fillings (TQRCF) and endodontic outcomes (EO).Methods: A retrospective evaluation of radiographs from 303 root canal-treated teeth in 231 patients was conducted, with 72 patients attending recall visits to assess EO. The chi-square and one-way analysis of variance tests were performed.Results: A total of 505 WL and 557 MC radiographs were reviewed, with 72.9% and 75% deemed satisfactory, respectively. Satisfactory TQRCF was achieved in 60.4% of cases. Significant associations were found between the extension of the file in WL and gutta-percha in MC radiographs and TQRCF (p = 0.000). Misinterpretation of these radiographs resulted in poor TQRCF. Furthermore, 64.2% of teeth had satisfactory EO. A significant relationship was noted between the quality of MC radiographs and both TQRCF (p = 0.043) and EO (p = 0.003).Conclusions: Unsatisfactory MC radiographs were linked to poor TQRCF and unfavorable EO. Regular radiographic training is recommended to enhance EO.

Objectives: Oral potentially malignant disorders (OPMDs) carry a variable risk of malignant transformation, making early detection important. Deep learning relies on specialized imaging, which is often inaccessible in routine practice, and detection from standard clinical photographs remains poorly characterized. We assessed the feasibility of automated OPMD detection from white-light intraoral photographs, compared two convolutional neural network paradigms (global classification with DenseNet-121 versus one-stage instance segmentation with YOLOv8), and identified the main barriers to clinical translation. Methods: A dataset of 1500 photographs (750 OPMD and 750 non-OPMD) from institutional archives and publicly accessible sources was split in an 80:20 ratio for training and testing. Lesion boundaries were annotated by three trainees using Cytomine and validated by three specialists. The DenseNet-121 and YOLOv8-large-segmentation models were evaluated for accuracy, sensitivity, specificity, precision, F1 score, and Wilson 95% CI. Results: DenseNet-121 required extensive manual lesion cropping to converge, negating the automation rationale. YOLOv8-large-segmentation reached 62.2% accuracy (95% CI 56.4 to 67.6), 75% sensitivity (95% CI 67.3 to 81.4), 59.7% precision (95% CI 52.4 to 66.5), 49.3% specificity (95% CI 41.3 to 57.4), and an F1 score of 66.5%, detecting lesions in 96% of the test set. High sensitivity was obtained at a low confidence threshold of 0.1, with correspondingly reduced specificity, and the model produced interpretable color-coded segmentation masks. Conclusions: One-stage instance segmentation is the more viable direction and yields spatially interpretable output, but performance at this dataset scale is not yet clinically sufficient. Dataset scale, threshold calibration, low specificity, and absent patient metadata are the key barriers to address.

Background: Variants of uncertain significance (VUSs) in TP53 and CDKN2A are reported often in oral squamous cell carcinoma (OSCC), yet variant-level evidence tends to lag behind established gene-level associations. Candidate variant lists compiled by automated literature synthesis, registry mining, or AI-assisted extraction carry a risk of gene-level or transcript-level mis-annotation that is not widely recognized. Methods: Ten candidate VUSs (one TP53 and nine CDKN2A), drawn from a candidate list generated by an AI-assisted literature and registry search (SciSpace, PubMed, Google Scholar, and ClinicalTrials.gov), were curated using ClinVar, dbSNP/NCBI Gene, gnomAD (via VarSome), and UCSC phyloP conservation tracks. To address regional population representation, two Indian genomic resources (dbGENVOC and TMC-SNPdb 2.0) and one OSCC-specific catalogue (dbGVOSCC) were also queried. Gene and transcript assignment was verified independently for every variant before evaluation against American College of Medical Genetics and Genomics and Association for Molecular Pathology (ACMG/AMP) criteria. Results: The candidate TP53 variant (rs2543751607) is a coding variant of the adjacent gene WRAP53 and is non-coding relative to TP53; it was excluded. All CDKN2A variants mapped only to the p14(ARF) transcript (NM_058195.4) and not to the p16(INK4a) transcript (NM_000077.5) that underlies the CDK4/6-inhibitor predictive-biomarker role of CDKN2A. One rsID (rs2489327173) resolved to two distinct missense variants, giving ten evaluated CDKN2A variants: two Likely Pathogenic (provisional, isoform-qualified), seven Uncertain Significance, and one Uncertain Significance and leaning benign. None of the ten was recorded in dbGENVOC, TMC-SNPdb 2.0, or dbGVOSCC. In dbGENVOC the only CDKN2A coding variants in Indian OSCC patients fell in the shared exon 2, and in dbGVOSCC the curated OSCC CDKN2A events were mainly deletions and p16 methylation. Curation also corrected an allele-matching error at a multiallelic position and resolved two conservation-score discordances by independent phyloP querying. Conclusions: Public-database curation of a small candidate VUS set exposed structural annotation problems, namely gene misassignment and isoform misassignment, that change the clinical interpretation of the source synthesis. Variant lists derived automatically or from the literature warrant independent gene-level and transcript-level verification, and CDKN2A isoform specificity should be stated explicitly whenever it is discussed as a biomarker in OSCC or HNSCC.

Purpose: Graphical abstracts have become a routine tool for disseminating research through social media and scholarly repositories. However, evidence regarding their effectiveness remains inconsistent. A key question is whether increased engagement translates into substantive readership or, ultimately, citation.Methods: We conducted a systematic review that synthesized 22 studies, including 8 randomized controlled trials and 14 observational or survey-based studies. Outcomes were grouped into four domains: social media engagement, article access, citation and altmetric impact, and reader perception. Certainty ratings were assigned using the GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) approach.Results: Eighteen studies (81.8%) measured engagement, and all but one reported higher impressions, retweets/reposts, likes, or overall engagement for graphical abstracts than for text-only posts. Among seven studies that measured access, three reported significantly higher click-throughs or article access. Citation outcomes were more heterogeneous. Only one study demonstrated a sustained citation advantage, whereas most found no difference or a slight disadvantage. Certainty ratings indicated moderate confidence for engagement and low to very low confidence for access and citation.Conclusion: Evidence drawn predominantly from Twitter/X indicates that graphical abstracts reliably increase early engagement, but whether this engagement extends to article access or citation remains inconsistent and uncertain.