Publications by authors named "A T C J van Eck"

Objectives: This work highlights the methods used to develop a multi-pulse 1726 nm laser system combined with bulk air-cooling for selective sebaceous gland (SG) photothermolysis using thermal imaging and software algorithms. This approach enables treating to a desired tissue temperature and depth to provide a safe, effective, reproducible, and durable treatment of acne.

Methods: We designed and built a 1726 nm laser system with a 40 W maximum power output, a highly controlled air-cooling device, and a thermal camera in the handpiece, which permits real-time temperature monitoring of the epidermis.

View Article and Find Full Text PDF

Background: Early-term complications may not predict long-term success after adult cervical deformity (ACD) correction.

Objective: Evaluate whether optimal realignment results in similar rates of perioperative complications but achieves longer-term cost-utility.

Study Design: Retrospective cohort study.

View Article and Find Full Text PDF

Hub regions in the brain, recognized for their roles in ensuring efficient information transfer, are vulnerable to pathological alterations in neurodegenerative conditions, including Alzheimer's disease (AD). Computational simulations and animal experiments have hinted at the theory of activity-dependent degeneration as the cause of this hub vulnerability. However, two critical issues remain unresolved.

View Article and Find Full Text PDF

Objective: To evaluate outcome in 60 dogs with cystine urolithiasis treated with surgical removal with and without castration and postoperative therapeutic diet to determine frequency of recurrence and urolith-free duration.

Methods: Patient records were reviewed for dogs with documented cystine urolithiasis from September 2010 to December 2020. Medical records, client interviews, and referring veterinarians were contacted to document the absence of clinical signs associated with subsequent urolith formation and to evaluate risk factors for urolith reoccurrence.

View Article and Find Full Text PDF

Machine learning algorithms are increasingly being utilized to identify brain connectivity biomarkers linked to behavioral and clinical outcomes. However, research often prioritizes prediction accuracy at the expense of biological interpretability, and inconsistent implementation of ML methods may hinder model accuracy. To address this, our paper introduces a network-level enrichment approach, which integrates brain system organization in the context of connectome-wide statistical analysis to reveal network-level links between brain connectivity and behavior.

View Article and Find Full Text PDF