Fluoride Induces Toxic Effects on the A549 Pulmonary Cell Line at Non-cytotoxic Concentrations.

Fluoride is emitted into the air not only through gas emissions but also from volcanic ash, leading to contact via inhalation. Therefore, the objective of the present study was to evaluate the cellular and biochemical responses in the A549 cell line after exposure to NaF (sodium fluoride) concentrations lower than those previously used in other studies to determine the impact on the lung epithelium. A549 cells were exposed to different concentrations (0.

Correlation of Two-Minute and Six-Minute Walk Tests With Spirometric Indices in Patients With Severe Chronic Obstructive Pulmonary Disease at a Selected Tertiary Care Hospital in Puducherry.

Background Chronic obstructive pulmonary disease (COPD) is a progressive respiratory condition characterised by airflow limitation and reduced exercise capacity. The Six-Minute Walk Test (6MWT) and Two-Minute Walk Test (2MWT) are commonly used to assess functional exercise capacity in COPD patients. This study aims to evaluate the correlation between the distance covered in the 2MWT and 6MWT with spirometric indices (such as Forced Expiratory Volume in 1 second (FEV₁), Forced Vital Capacity (FVC), and FEV₁/FVC) in COPD patients.

Correction: SRY gene isolation from teeth for forensic gender identification-An observational study.

[This corrects the article DOI: 10.1371/journal.pone.

SRY gene isolation from teeth for forensic gender identification-An observational study.

Personal identification in forensics is possible with gender determination using DNA (deoxyribonucleic acid) analysis. DNA isolation from teeth samples subjected to extreme temperatures has been shown to predict the gender of the deceased. However, the literature lacks studies on DNA extracted from tooth samples exposed to freezing temperatures.

Machine Learning in the Detection of Oral Lesions With Clinical Intraoral Images.

Introduction: Artificial intelligence in oncology has gained a lot of interest in recent years. Early detection of Oral squamous cell carcinoma (OSCC) is crucial for early management to attain a better prognosis and overall survival. Machine learning (ML) has also been used in oral cancer studies to explore the discrimination between clinically normal and oral cancer.