Controlling Thermogenesis: Understanding the Role of PRDM16 in the Development and Function of Brown Fat

The alarming rise in the incidence of obesity found throughout the world has precipitated a need to look for novel methods to increase energy expenditure to counter weight gain. Recently it was discovered that adult humans possess a substantial mass of brown adipose tissue (BAT), a tissue that consumes stored lipid to produce heat. Although the primary physiologic role for BAT is to protect mammals from the cold, it is currently thought that enhancing BAT mass or activating BAT in humans is a novel way to decrease adiposity. However, before BAT can be effectively utilized for therapeutic purposes a better understanding of the transcriptional regulation underlying BAT function is required. Here, we investigated the role of the transcription factor PRDM16 in BAT. We found that PRDM16 is not required for BAT development, however it is required to maintain BAT identity in adult mice. The loss of PRDM16 in adult mice led to a loss of BAT functionality and an inability to produce heat. We found that PRDM16s ability to drive a thermogenic program is due to its recruitment of Med1/the Mediator Complex to BAT-selective genes. Without PRDM16 in BAT a loss of higher order chromatin structure and a corresponding loss of transcription takes place at genes required for BAT identity and function

Symphony No. 1 Movement 1

Matthew Harms conducting his Symphony No. 1 Movement 1 - performed by the IMSA Orchestra.https://digitalcommons.imsa.edu/art_sw/1001/thumbnail.jp

Comparison of three collection techniques for capture of Coleoptera, with an emphasis on saproxylic species, in Great Smoky Mountains National Park, USA

Collection methods and/or habitats sampled influence how many and which species are captured during entomological surveys. Here we compare Coleoptera catches among three survey activities, each using a single collection method, at the same study sites in Great Smoky Mountains National Park, USA. Activities included: short-term flight intercept trapping (FITs); sifting/Berlese funneling of leaf litter and extremely decayed downed coarse woody debris; and using emergence chambers containing coarse woody debris of various decay classes. In total, 2472 adult beetle specimens, representing 217 lowest identifiable taxa within 164 genera and 42 families, were collected during the FIT survey. Each survey activity yielded more than 2000 specimens, and a combined total of 413 species was collected. A combination of all surveys yielded the highest species richness when normalized for number of specimens indicating that variation of habitat and/or collection method significantly increases species richness. Of single surveys the FIT survey had the highest absolute species richness (217) and the highest richness when normalized for number of specimens. Species overlap among survey activities was low (Sorensen’s quotient of similarity was 0.20–0.27), which showed that each was about equally dissimilar from all others. Overlap of catch between FITs and emergence chambers was too low to justify substitution of emergence surveys with the FIT survey protocol used when attempting to collect saproxylic Coleoptera

Assessing User Experiences with ZORQ: A Gamification Framework for Computer Science Education

ZORQ is a gamification software framework designed to increase student engagement within undergraduate Computer Science (CS) education. ZORQ is an attractive learning method that (1) utilizes numerous gamification elements, (2) provides a collaborative, game-development based learning approach, (3) offers an opportunity for students to explore a complex, real-world software development implementation, and (4) provides students with a high level of engagement with the system and a high level of social engagement in its collaborative customization. The usage of ZORQ was assessed using quantitative, qualitative and sentiment analyses in a Data Structures and Algorithms course over five years. The overwhelmingly positive results show that students were satisfied with their user experience and ZORQ was beneficial to their educational experience. By triangulating results from multiple analyses, this study adds to a deeper understanding of how gamification can improve learning and retention and provides a novel, robust, holistic methodology for evaluating user experiences

Genetics of Amyotrophic Lateral Sclerosis

Peer reviewedPublisher PD

QuNex-An integrative platform for reproducible neuroimaging analytics

INTRODUCTION: Neuroimaging technology has experienced explosive growth and transformed the study of neural mechanisms across health and disease. However, given the diversity of sophisticated tools for handling neuroimaging data, the field faces challenges in method integration, particularly across multiple modalities and species. Specifically, researchers often have to rely on siloed approaches which limit reproducibility, with idiosyncratic data organization and limited software interoperability. METHODS: To address these challenges, we have developed Quantitative Neuroimaging Environment & Toolbox (QuNex), a platform for consistent end-to-end processing and analytics. QuNex provides several novel functionalities for neuroimaging analyses, including a turnkey command for the reproducible deployment of custom workflows, from onboarding raw data to generating analytic features. RESULTS: The platform enables interoperable integration of multi-modal, community-developed neuroimaging software through an extension framework with a software development kit (SDK) for seamless integration of community tools. Critically, it supports high-throughput, parallel processing in high-performance compute environments, either locally or in the cloud. Notably, QuNex has successfully processed over 10,000 scans across neuroimaging consortia, including multiple clinical datasets. Moreover, QuNex enables integration of human and non-human workflows DISCUSSION: Collectively, this effort stands to significantly impact neuroimaging method integration across acquisition approaches, pipelines, datasets, computational environments, and species. Building on this platform will enable more rapid, scalable, and reproducible impact of neuroimaging technology across health and disease