Publications by authors named "B C Jham"

To investigate the association of NANOG polymorphisms with oral leukoplakia. In this case-control study, 68 cases of oral leukoplakia, and 21 of normal oral mucosa (control) were submitted to genotyping of tagSNPs polymorphisms: rs877716 and rs10845877 in NANOG, through real-time polymerase chain reaction (PCR). Pearson's chi-squared and Fisher's exact statistical tests were used, with a significance of 5%.

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Article Synopsis
  • The study evaluated ChatGPT-4.0's ability to diagnose oral and maxillofacial lesions by analyzing 102 histopathological cases and comparing its performance to that of pathologists.
  • ChatGPT-4.0 achieved an accuracy of about 59.8%, diagnosing 61 cases correctly, with varying success depending on lesion type—being particularly poor with granulomas and inflammation, but strong with mucoceles.
  • There was a notable correlation between age and accuracy, indicating that older ages might be associated with lower diagnostic scores, although gender did not significantly affect results.
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Purpose: To investigate the association of SOX2 polymorphisms with oral leukoplakia with dysplasia (OLD) and compare it with the immunohistochemical expression of SOX-2.

Methods: The samples comprised 64 patients with oral leukoplakia and 20 with normal oral mucosa who were subjected to SOX2 polymorphism rs77677339 genotyping by real-time polymerase chain reaction and immunohistochemistry for SOX-2 (basal epithelium expression, suprabasal and total; nuclear area and intensity). Statistical tests included the Chi-square and Fisher's exact tests.

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Objectives: To investigate the effects of dietary folate and sex on histopathology of oral squamous cell carcinoma in mice.

Materials And Methods: Mice (C57Bl/6, 30/sex) were fed either a deficient folate or sufficient folate diet. Vehicle or 4-nitroquinoline1-oxide (50 μg/mL) in vehicle were administered in drinking water for 20 weeks, followed by 6 weeks of regular drinking water.

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Early diagnosis of oral potentially malignant disorders (OPMDs) may be hindered by similar clinical presentations shared between benign oral lesions and OPMDs. The goal of this retrospective pilot study was to assess the use of machine learning (ML) as an adjunctive evaluation in conjunction with conventional comprehensive oral examination of OMPDs. Digital images of 80 deidentified intraoral lesions (40 benign intraoral lesions and 40 OPMDs) were collected.

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