An animal's maneuverability will determine the outcome of many of its most important interactions. A common approach to studying maneuverability is to force the animal to perform a specific maneuver or to try to elicit maximal performance. Recently, the availability of wider-field tracking technology has allowed for high-throughput measurements of voluntary behavior, an approach that produces large volumes of data. Here, we show how these data allow for measures of inter-individual variation that are necessary to evaluate how performance depends on other traits, both within and among species. We use simulated data to illustrate best practices when sampling a large number of voluntary maneuvers. Our results show how the sample average can be the best measure of inter-individual variation, whereas the sample maximum is neither repeatable nor a useful metric of the true variation among individuals. Our studies with flying hummingbirds reveal that their maneuvers fall into three major categories: simple translations, simple rotations and complex turns. Simple maneuvers are largely governed by distinct morphological and/or physiological traits. Complex turns involve both translations and rotations, and are more subject to inter-individual differences that are not explained by morphology. This three-part framework suggests that different wingbeat kinematics can be used to maximize specific aspects of maneuverability. Thus, a broad explanatory framework has emerged for interpreting hummingbird maneuverability. This framework is general enough to be applied to other types of locomotion, and informative enough to explain mechanisms of maneuverability that could be applied to both animals and bio-inspired robots.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1242/jeb.161828 | DOI Listing |
Introduction: Previous studies identified genetic links between the TCF7L2 C/T variant rs7903146, type 2 diabetes (T2D), and obesity. We wished to deepen our understanding of how specific diets interact with this variant to affect blood metabolites, an aspect not previously investigated. Hence, we conducted a controlled study where individuals with different genotypes followed a Mediterranean (Med) or low-fat (LF) diet for one week.
View Article and Find Full Text PDFExpert Opin Drug Discov
January 2025
Centro de Investigación en Reproducción Animal, Universidad Autónoma de Tlaxcala - CINVESTAV Tlaxcala, Tlaxcala, México.
Introduction: Existing pharmacotherapies for schizophrenia have not progressed beyond targeting dopamine and serotonin neurotransmission. Rodent models of schizophrenia are a necessary tool for elucidating neuropathological processes and testing potential pharmacotherapies, but positive preclinical results in rodent models often do not translate to positive results in the clinic.
Areas Covered: The authors reviewed PubMed for studies that applied rodent behavioral models of schizophrenia to assess the antipsychotic potential of several novel pharmacotherapies currently under investigation.
Evolution
January 2025
Department of Environmental Science, Policy & Management, University of California Berkeley, Berkeley, CA, 94720, United States.
Selection on animal signal form often changes significantly with the environment, yet signal form may itself be environment dependent. Little is known about how variation in individual responses to changing environments affects the relationship between selection and the subsequent evolution of signal traits. To address this question, we assess the effects of variation in temperature on individual signaling and mating behavior responses across temperatures in the wolf spider Schizocosa floridana.
View Article and Find Full Text PDFNat Commun
January 2025
MRC Laboratory of Medical Sciences, London, UK.
Gene enhancers often form long-range contacts with promoters, but it remains unclear if the activity of enhancers and their chromosomal contacts are mediated by the same DNA sequences and recruited factors. Here, we study the effects of expression quantitative trait loci (eQTLs) on enhancer activity and promoter contacts in primary monocytes isolated from 34 male individuals. Using eQTL-Capture Hi-C and a Bayesian approach considering both intra- and inter-individual variation, we initially detect 19 eQTLs associated with enhancer-eGene promoter contacts, most of which also associate with enhancer accessibility and activity.
View Article and Find Full Text PDFGlob Epidemiol
June 2025
Business Analytics (BANA) Program, Business School, University of Colorado, 1475 Lawrence St. Denver, CO 80217-3364, USA.
AI-assisted data analysis can help risk analysts better understand exposure-response relationships by making it relatively easy to apply advanced statistical and machine learning methods, check their assumptions, and interpret their results. This paper demonstrates the potential of large language models (LLMs), such as ChatGPT, to facilitate statistical analyses, including survival data analyses, for health risk assessments. Through AI-guided analyses using relatively recent and advanced methods such as Individual Conditional Expectation (ICE) plots using Random Survival Forests and Heterogeneous Treatment Effects (HTEs) estimated using Causal Survival Forests, population-level exposure-response functions can be disaggregated into individual-level exposure-response functions.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!