Updates on Psoriasis in Special Areas.

Special areas of involvement in psoriasis include the scalp region, the palms and soles, genital areas, as well as intertriginous sites. The involvement of these topographical regions is associated with important physical and emotional implications, resulting in reduced quality of life, social isolation, and work disability. Palms and soles can be affected as part of the generalized form of psoriasis or can be exclusively affected as palmo-plantar psoriasis.

Mobile health technologies in an interventional hybrid study on actinic keratosis: Results from an early phase randomized controlled trial investigating the safety and efficacy of a cytosolic phospholipase A2 inhibitor gel in photodamaged skin.

Hybrid trials are a new trend in dermatological research that leverage mobile health technologies to decentralize a subset of clinical trial elements and thereby reduce the number of in-clinic visits. In a Phase I/IIa randomized controlled hybrid trial, the safety and efficacy of an anti-proliferative and anti-inflammatory drug inhibiting cytosolic phospholipase A2 (AVX001) was tested using 1%, 3% or vehicle gel in 60 patients with actinic keratosis (AK) and assessed in-clinic as well as remotely. Over the course of 12 weeks, patients were assessed in-clinic at baseline, end of treatment (EOT) and end of study (EOS), as well as 9 times remotely on a weekly to biweekly basis.

Accelerating patient recruitment using social media: Early adopter experience from a good clinical practice-monitored randomized controlled phase I/IIa clinical trial on actinic keratosis.

Background: Patient recruitment is a major cause of delays in randomized controlled trials (RCT). Online recruitment is evolving into an alternative to conventional in-clinic recruitment for RCT. The objective of this study was to test the effectiveness of online patient recruitment for an RCT on actinic keratosis (AK).

Predicting Fatigue-Associated Aberrant Driving Behaviors Using a Dynamic Weighted Moving Average Model With a Long Short-Term Memory Network Based on Heart Rate Variability.

Objective: This study proposed a moving average (MA) approach to dynamically process heart rate variability (HRV) and developed aberrant driving behavior (ADB) prediction models by using long short-term memory (LSTM) networks.

Background: Fatigue-associated ADBs have traffic safety implications. Numerous models to predict such acts based on physiological responses have been developed but are still in embryonic stages.