Meeting Report: Aging Research and Drug Discovery

An Introductory Guide to Using Bloomington Drosophila Stock Center and FlyBase for Aging Research

Studies on numerous species have demonstrated strikingly conserved mechanisms that determine the aging process, from yeasts to worms, flies, zebrafish, mice, and humans. The fruit fly Drosophila melanogaster is an excellent model organism for studying the biological basis of normal aging and etiology of age-related diseases. Since its inception in 1967, the Bloomington Drosophila Stock Center (BDSC) has grown into the largest collection of documented D. melanogaster strains (currently > 91,000). This paper aims to briefly review conserved mechanisms of aging and provides a guide to help users understand the organization of stock listings on the BDSC website and familiarize themselves with the search functions on BDSC and FlyBase, with an emphasis on using genes in conserved pathways as examples to find stocks for aging studies.

Microbiome and One Health: Potential of Novel Metabolites from the Gut Microbiome of Unique Species for Human Health

For thousands of years, the notion that human health and performance are concomitant with the health and diversity of the microbiome has been deliberated upon [...].

Artificial Intelligence Confirming Treatment Success: The Role of Gender- and Age-Specific Scales in Performance Evaluation

In plastic surgery and cosmetic dermatology, photographic data are an invaluable element of research and clinical practice. Additionally, the use of before and after images is a standard documentation method for procedures, and these images are particularly useful in consultations for effective communication with the patient. An artificial intelligence (AI)-based approach has been proven to have significant results in medical dermatology, plastic surgery, and antiaging procedures in recent years, with applications ranging from skin cancer screening to 3D face reconstructions, the prediction of biological age and perceived age. The increasing use of AI and computer vision methods is due to their noninvasive nature and their potential to provide remote diagnostics. This is especially helpful in instances where traveling to a physical office is complicated, as we have experienced in recent years with the global coronavirus pandemic. However, one question remains: how should the results of AI-based analysis be presented to enable personalization? In this paper, the author investigates the benefit of using gender- and age-specific scales to present skin parameter scores calculated using AI-based systems when analyzing image data.