Comparison of aqueous humor ascorbic acid level in smokers and non-smokers.

In this study, we studied effect of smoking on ascorbic acid level in aqueous humor. A cohort of 112 individuals undergoing cataract surgery for senile cataract (mean ± SD age-65 ± 8 years) was sub-grouped as smoker (n = 56) and non-smoker (n = 56) based on smoking habit. The aqueous humor sample was collected in beginning of the surgery and quantitative ascorbic acid estimation was done by colorimetric method (spectrophotometry at λ = 578 nm) using commercially available assay kits using the auto-analyzer assay procedure. The mean (±SD) aqueous humor ascorbic acid level was 1396 ± 629 µmol/L among non-smokers and 774 ± 436 µmol/L among smokers (p < 0.0001). The aqueous humor ascorbic acid concentration is significantly lower in smokers compared to non-smokers. The aqueous humor ascorbic acid concentration is affected by gender but not by age or morphology of cataract.

Accident severity prediction modeling for road safety using random forest algorithm: an analysis of Indian highways.

Background: Road accidents claim around 1.35 million lives annually, with countries like India facing a significant impact. In 2019, India reported 449,002 road accidents, causing 151,113 deaths and 451,361 injuries. Accident severity modeling helps understand contributing factors and develop preventive strategies. AI models, such as random forest, offer adaptability and higher predictive accuracy compared to traditional statistical models. This study aims to develop a predictive model for traffic accident severity on Indian highways using the random forest algorithm. Methods: A multi-step methodology was employed, involving data collection and preparation, feature selection, training a random forest model, tuning parameters, and evaluating the model using accuracy and F1 score. Data sources included MoRTH and NHAI. Results: The classification model had hyperparameters 'max depth':  10, 'max features': 'sqrt', and 'n estimators': 100. The model achieved an overall accuracy of 67% and a weighted average F1-score of 0.64 on the training set, with a macro average F1-score of 0.53. Using grid search, a random forest Classifier was fitted with optimal parameters, resulting in 41.47% accuracy on test data. Conclusions: The random forest classifier model predicted traffic accident severity with 67% accuracy on the training set and 41.47% on the test set, suggesting possible bias or imbalance in the dataset. No clear patterns were found between the day of the week and accident occurrence or severity. Performance can be improved by addressing dataset imbalance and refining model hyperparameters. The model often underestimated accident severity, highlighting the influence of external factors. Adopting a sophisticated data recording system in line with MoRTH and IRC guidelines and integrating machine learning techniques can enhance road safety modeling, decision-making, and accident prevention efforts.

Air embolism during percutaneous nephrolithotomy using air pyelogram during initial access: Does it really occur?

INTRODUCTION: In the present era, percutaneous nephrolithotomy (PCNL) is the standard treatment for large (>2 cm) renal or staghorn renal stones. Both air and iodinated contrast has been used to opacify the pelvicalyceal system (PCS) before the dilatation of the tract. There are rare reports of air embolism following air pyelogram on mere presumptions. MATERIALS AND METHODS: This is a prospective observational study. A total of 164 patients underwent PCNL in which air was used to opacify the PCS by placing a ureteric catheter for initial access. RESULTS: None of our patients developed any complication during the procedure or in the postoperative period, which could be attributed to air embolism. CONCLUSIONS: The present study ascertains that using air for opacification of PCS for initial puncture access is a safe and acceptable alternative to iodinated contrast.

Changing Trends in oral cancer - a global scenario.

Oral cancer is one of the highly prevalent cancers worldwide and a leading cause of mortality in certain regions like South-Central Asia. It is a major public health problem. Late diagnosis, high mortality rates and morbidity are characteristics of the disease worldwide. For control of oral cancer an idea of the coverage of the same in the various regions is necessary. The estimated incidence, mortality and 5-year survival due to lip, oral cavity cancer in world is 3, 00, 373(2.1%), 1, 45, 328(1.8%) and 7, 02, 149(2.2%) respectively according to data of GLOBOCAN 2012. A changing trend in incidence and prevalence of oral cancer has been observed with more women and youngsters being affected by oral cancer.