Development and validation of betel-year: a clinical tool for quantifying exposure to betel quid chewing, utilizing nuclear morphometric analysis and validated by cytomorphological analysis.

BACKGROUND: Betel quid chewing, prevalent in Southeast Asia and South Asia, involves components such as betel leaf, areca nut, slaked lime, and sometimes tobacco. This study aims to assess buccal mucosa changes in betel quid chewers, develop a clinical tool for assessing exposure, and investigate its usability in predicting dysplasia. METHODS: After obtaining ethical approval and informed consent, patients were recruited from the Out-Patient Department of Government Medical College, Omandurar, Government Estate, India. A target sample size of 200 was calculated. The data included the history of betel quid chewing, buccal mucosa cells obtained by oral cytology, and the severity of dysplasia of the slides assessed by pathologists. We utilized principal component analysis (PCA) and confirmatory factor analysis (CFA) to validate a new outcome variable reflecting nuclear morphometric parameters (NMPs). Multiplicative regression models were developed for betel years based on betel exposure and additives. Spearman correlation and Kruskal-Wallis test was used to check the association between betel years and dysplasia. RESULTS: Significant differences in NMPs were observed among different betel chewing groups. We derived multiplicative regression models for betel years. In the logarithmic transformation approach, betel year = 0.05×betel-exposure×0.09×slaked-lime use×0.11×tobacco-use. In the original variable approach, betel year = 5.05×betel-exposure^0.00048×slaked-lime-use^0.18133×tobacco-use^1.47513. Spearman correlation and Kruskal-Wallis tests confirmed associations with dysplasia. CONCLUSION: Betel year is a pioneering tool for assessing lifetime betel quid exposure, similar to pack years for smoking. It could aid in risk stratification, targeted interventions and shaping public health policies. Despite limitations, betel year holds promise for revolutionizing oral health risk assessment, and future research can expand its scope globally, considering diverse betel quid compositions.

Exploring mean platelet volume and neutrophil-to-albumin ratio as surrogate markers for monitoring tuberculosis treatment: a prospective longitudinal study.

BACKGROUND: Tuberculosis (TB) remains a global health challenge, with India bearing a significant burden. Despite advancements in TB diagnosis and treatment, monitoring TB treatment is challenging, particularly in resource-limited settings. This study aimed to explore the mean platelet volume (MPV) as a potential surrogate marker for monitoring TB treatment and assessing if the neutrophil-to-albumin ratio (NAR) enhances treatment monitoring. METHODS: Patients diagnosed with TB following NTEP guidelines were recruited. Participants underwent routine blood tests during the six-month Anti-Tubercular therapy course at the start, end of the intensive phase, and end of the continuous phase. Statistical analyses included Spearman correlation, Friedman test, linear mixed effects (LME) models, and multiple linear regression. RESULTS: 150 individuals were included for analysis. Deviations from normality were noted. Significant associations were found between CRP and sputum grade. MPV mediated between CRP and sputum grade. Significant differences were observed across the three-time points. LME models showed changes in MPV and CRP levels over time. Including NAR enhanced predictive capability. CONCLUSIONS: MPV may serve as a promising surrogate marker for monitoring ATT. Personalized approaches are crucial in TB treatment monitoring. LME models revealed MPV and CRP level trends. Future research should explore MPV's treatment response mechanisms and cost-effectiveness.

Assessing the use of the triglyceride-glycemic index (TyG), neutrophil-lymphocyte Ratio (NLR), and platelet-lymphocyte Ratio (PLR) in distinguishing benign and malignant tumors among patients with complaints of breast mass.

Introduction: Breast cancer is a prevalent global health concern characterized by uncontrolled cell growth in breast tissue. In 2020, approximately 2.3 million cases were reported worldwide, with 162,468 new cases and 87,090 fatalities documented in India in 2018. Early diagnosis is crucial for reducing mortality. Our study focused on the use of markers such as the triglyceride-glycemic index and hematological markers to distinguish between benign and malignant breast masses. Methods: A prospective cross-sectional study included female patients with breast mass complaints. The target sample size was 200. Data collection included medical history, clinical breast examination, mammography, cytological assessment via fine-needle aspiration cytology (FNAC), and blood sample collection. The analyzed parameters included neutrophil-to-lymphocyte Ratio (NLR), platelet-to-lymphocyte Ratio (PLR), and triglyceride-glycemic index (TyG). Histopathological examination confirmed the FNAC results. Statistical analysis including propensity score matching, Kolmogorov-Smirnov tests, Mann-Whitney U tests, receiver's operator curve (ROC) analysis, and logistic regression models was conducted using SPSS and R Software. Additional validation was performed on 25 participants. Results: This study included 200 participants. 109 had benign tumors and 91 had malignant tumors. Propensity score matching balanced covariates. NLR did not significantly differ between the groups, while PLR and TyG index differed significantly. NLR correlated strongly with the breast cancer stage, but not with the BI-RADS score. PLR and TyG index showed moderate positive correlations with the BI-RADS score. ROC analysis was used to determine the optimal cutoff values for PLR and TyG index. Logistic regression models combining PLR and TyG index significantly improved malignancy prediction. Conclusions: TyG index and PLR show potential as adjunctive markers for distinguishing breast masses. NLR correlated with cancer stage but not lesion type. Combining TyG and PLR improves prediction, aiding clinical decisions, but large-scale multicenter trials and long-term validation are required for clinical implementation.

Childhood Cerebral Adrenoleukodystrophy: Case Report and Literature Review Advocating for Newborn Screening.

Background: X-linked adrenoleukodystrophy (ALD) is a rare genetic disorder caused by a pathogenic variant of the ABCD1 gene, leading to impaired peroxisomal function and the accumulation of very long-chain fatty acids (VLCFAs). ALD presents a wide range of neurological and adrenal symptoms, ranging from childhood cerebral adrenoleukodystrophy to adrenomyeloneuropathy and adrenal insufficiency. Newborn screening (NBS) for ALD is available in some regions but remains lacking in others, such as India. Case Presentation: We present a case of a 10-year-old boy with ALD who presented with seizures, progressive weakness, visual impairment, and adrenal insufficiency. Despite symptomatic management and dietary adjustments, the disease progressed rapidly, leading to respiratory failure and eventual demise. The diagnosis was confirmed through molecular analysis and elevated VLCFA levels. Neuroimaging revealed characteristic white matter changes consistent with ALD. Conclusion: ALD is a devastating disease with no cure, emphasizing the importance of early detection through newborn screening and genetic testing. Management strategies include adrenal hormone therapy, gene therapy, and allogenic stem cell transplantation, as well as investigational treatments such as VLCFA normalization. Our case advocates the need for worldwide NBS and pediatric neurologic follow-up to enable early intervention and improve patient outcomes. Additionally, the association between ALD, recurrent febrile seizures, and unexplained developmental delay warrants further investigation to better understand disease progression and potential therapeutic targets.

Evaluation of nuclear morphometry in exfoliative cytology of buccal mucosa in patients with high risk of oral cancer.

BACKGROUND: Oral cancer poses a significant global health burden, with India having the highest prevalence. Effective detection is crucial in effective prevention. This study aimed to evaluate nuclear morphometric parameters (NMPs) in buccal mucosa cells of smokers, correlate NMPs with dysplasia, establish cut off values for grading dysplasia, and investigate the relationship between NMPs and smoking. METHODS: After obtaining ethical approval and informed consent, patients were recruited from the outpatient department of our institution. A target sample size of 250 was calculated. The data included smoking exposure quantified in pack-years, nuclear morphometric analysis (NMA) of buccal mucosa cells obtained through oral cytology using Image J, and the severity of dysplasia of the slides assessed by pathologists. Statistical analysis assessed the impact of dysplasia and the association between nuclear characteristics and smoking exposure. Receiver operating characteristic (ROC) plots determined the potential of these parameters to distinguish dysplasia levels. RESULTS: Significant differences in NMPs were observed among different smoking groups. Dysplasia severity had a significant correlation with NMPs, and strong correlations were found between NMPs and lifetime smoking exposure. ROC analysis established cut off values for NMPs with good sensitivity and specificity for classifying dysplasia severity. CONCLUSIONS: This study highlights the potential of NMA as a tool for oral cancer screening. NMPs can distinguish dysplasia severity and correlate with tobacco (smoking). The efficiency of NMA in a non-invasive oral cytology offers promise for patient-centered screening Additionally, the findings suggest future applications in telepathology and the potential for AI integration in automated screening after conducting multicentric large-scale studies.