Comparative Evaluation of the Corneal Sensitivity Thresholds between the Novel Non-Contact and Cochet-Bonnet Esthesiometers.

Purpose: Primarily, to evaluate the repeatability and reproducibility of the new noncontact esthesiometer (NCE) in healthy subjects. Secondarily, the corneal sensitivity threshold measurements of the NCE were compared with those of the Cochet-Bonnet esthesiometer (CBE).

Design: Assessment reliability study.

Blood matters: the hematological signatures of Coronavirus infection.

Recent developments have broadened our perception of SARS-CoV-2, indicating its capability to affect the body systemically beyond its initial recognition as a mere respiratory pathogen. However, the pathways of its widespread are not well understood. Employing a dual-modality approach, we integrated findings from a Murine Hepatitis Virus (MHV) infection model with corroborative clinical data to investigate the pervasive reach of Coronaviruses.

(CAG) Microsatellite and c.444T>G (p.Asp148Glu) Polymorphisms as Independent Prognostic Biomarkers in Prostate Cancer: Insights from an Argentinian Cohort.

Background/objectives: Prostate cancer (PCa) is the leading malignancy and the third most common cause of cancer-related death in Argentinian men. Predicting outcomes in localized PCa remains difficult due to tumor heterogeneity. In this study, we assessed the impact of (CAG) and c.

Unmasking Neuroendocrine Prostate Cancer with a Machine Learning-Driven Seven-Gene Stemness Signature That Predicts Progression.

Prostate cancer (PCa) poses a significant global health challenge, particularly due to its progression into aggressive forms like neuroendocrine prostate cancer (NEPC). This study developed and validated a stemness-associated gene signature using advanced machine learning techniques, including Random Forest and Lasso regression, applied to large-scale transcriptomic datasets. The resulting seven-gene signature (, , , , , , and ) was validated across independent cohorts and patient-derived xenograft (PDX) models.