The effects of fasting and dehydration on pupillary light reflex as detected by pupillometry.

The pupillary light reflex could serve as a valuable method for measuring dynamic responses in the autonomic nervous system (ANS). However, it remains unclear whether physiological conditions such as fasting and dehydration affect pupillary reflexes. In this study, we investigated the effects of fasting and dehydration on pupillary responses using pupillometry.

Performance and durability of additively and subtractively manufactured resin-based onlay restorations after thermomechanical aging.

Purpose: To evaluate the effect of material type on dimensional stability, occlusal surface wear, fracture resistance, and failure behavior of resin-based onlay restorations.

Material And Methods: A mandibular right first molar typodont was prepared and digitized using an intraoral scanner to virtually design an onlay restoration with the minimum occlusal thickness of 1.5 mm.

Corneal innervation changes ın Alzheimer's: implications for sensory dysfunction.

Purpose: To compare, between Alzheimer's disease (AD) patients and healthy individuals, corneal subbasal nerve plexus (CSNP) parameters and corneal sensitivities.

Methods: Twenty-two patients who were followed up with Alzheimer's disease (Alzheimer's group) and 18 age- and gender-matched healthy individuals (control group) were included in this cross-sectional study. CSNP parameters, including nerve fiber length (NFL), nerve fiber density (NFD), and nerve branch density (NBD), were evaluated using in vivo confocal microscopy.

Triglyceride Glucose Index: A Potential Indicator in the Evaluation of Graves Ophthalmopathy.

Purpose: To determine the relationship between Graves ophthalmopathy (GO) and triglyceride glucose index (TGI) and to evaluate the predictive importance of this index in terms of GO activity.

Methods: This retrospective study included 20 inactive GO patients, 20 active GO patients, and 20 healthy controls. TGI was calculated using fasting plasma triglyceride and fasting plasma glucose levels and values were compared between the groups.

Automated LVO detection and collateral scoring on CTA using a 3D self-configuring object detection network: a multi-center study.

The use of deep learning (DL) techniques for automated diagnosis of large vessel occlusion (LVO) and collateral scoring on computed tomography angiography (CTA) is gaining attention. In this study, a state-of-the-art self-configuring object detection network called nnDetection was used to detect LVO and assess collateralization on CTA scans using a multi-task 3D object detection approach. The model was trained on single-phase CTA scans of 2425 patients at five centers, and its performance was evaluated on an external test set of 345 patients from another center.