Occupational Injuries on Thoroughbred Horse Farms: A Description of Latino and Non-Latino Workers\u27 Experiences

Animal production is a dangerous industry and increasingly reliant on a Latino workforce. Within animal production, little is known about the risks or the occupational hazards of working on farms involved in various aspects of thoroughbred horse breeding. Extant research suggests that horse workers are at risk of musculoskeletal and respiratory symptoms, kicks, and other injuries. However, limited known research has examined the experiences of the industry\u27s workers, including immigrant workers, despite their prominence and increased vulnerability. Using data collected from thoroughbred farm representatives via a phone-administered survey, a 2-hour face-to-face semi-structured interview, and farm injury logs, this article identifies and describes types of injuries experienced by workers (N = 284) and their surrounding circumstances. Results indicate that general injuries and musculoskeletal strains, sprains, and tears account for a majority of injuries among workers on thoroughbred farms. Upper limbs and extremities are most frequently injured, while direct contact with the horse accounted for over half of all injuries. No differences in the diagnoses or distribution of injury were found by ethnicity; however, Latinos were more often struck by or trampled by a horse while non-Latinos were more often injured by an insect or plant. Implications and opportunities for future research are discussed

Density-dependence and environmental variability have stage-specific influences on European grayling growth.

Fish somatic growth is indeterminate and can be influenced by a range of abiotic and biotic variables. With climate change forecast to increase the frequency of warming and unusual discharge events, it is thus important to understand how these variables currently influence somatic growth and how that might differ for specific age-classes and/ or life stages. Here, we used a 17-year dataset from a chalk stream in southern England to identify the abiotic and biotic influences on the growth of juvenile, sub-adult and adult life stages of European grayling (Thymallus thymallus), a cold-water riverine salmonid. The results revealed that interannual variations in grayling growth were well described by annual- and site-specific abiotic and biotic explanatory variables. We found divergent responses between life stages to increased temperature and unusual discharge during the main growth period with, for example, elevated temperatures related to increased juvenile growth but reduced sub-adult growth, and high discharge events related to increased sub-adult growth yet reduced juvenile growth. Conversely, stage-specific grayling abundance negatively influenced growth at each life stage, though only juvenile growth was impacted by the abundance of a competitor species, brown trout (Salmo trutta). These results emphasise the merits of testing a wide range of environmental and biological explanatory variables on fish growth, and across life stages. They also reveal the importance of maintaining high habitat heterogeneity in rivers to ensure all life stages can reduce their competitive interactions and have access to adequate flow and thermal refugia during periods of elevated environmental stress

Metabolomics of sorghum roots during nitrogen stress reveals compromised metabolic capacity for salicylic acid biosynthesis

Sorghum (Sorghum bicolor [L.] Moench) is the fifth most productive cereal crop worldwide with some hybrids having high biomass yield traits making it promising for sustainable, economical biofuel production. To maximize biofuel feedstock yields, a more complete understanding of metabolic responses to low nitrogen (N) will be useful for incorporation in crop improvement efforts. In this study, 10 diverse sorghum entries (including inbreds and hybrids) were field-grown under low and full N conditions and roots were sampled at two time points for metabolomics and 16S amplicon sequencing. Roots of plants grown under low N showed altered metabolic profiles at both sampling dates including metabolites important in N storage and synthesis of aromatic amino acids. Complementary investigation of the rhizosphere microbiome revealed dominance by a single operational taxonomic unit (OTU) in an early sampling that was taxonomically assigned to the genus Pseudomonas. Abundance of this Pseudomonas OTU was significantly greater under low N in July and was decreased dramatically in September. Correlation of Pseudomonas abundance with root metabolites revealed a strong negative association with the defense hormone salicylic acid (SA) under full N but not under low N, suggesting reduced defense response. Roots from plants with N stress also contained reduced phenylalanine, a precursor for SA, providing further evidence for compromised metabolic capacity for defense response under low N conditions. Our findings suggest that interactions between biotic and abiotic stresses may affect metabolic capacity for plant defense and need to be concurrently prioritized as breeding programs become established for biofuels production on marginal soils

The effects of partial sleep restriction and altered sleep timing on appetite and food reward.

We examined the effects of partial sleep restriction (PSR) with an advanced wake-time or delayed bedtime on measures of appetite, food reward and subsequent energy intake (EI). Twelve men and 6 women (age: 23 ± 4 years, body fat: 18.8 ± 10.1%) participated in 3 randomized crossover sessions: control (habitual bed- and wake-time), 50% PSR with an advanced wake-time and 50% PSR with a delayed bedtime. Outcome variables included sleep architecture (polysomnography), ad libitum EI (validated food menu), appetite sensations (visual analogue scales), the satiety quotient (SQ; mm/100 kcal) and food reward (Leeds Food Preference Questionnaire and the relative-reinforcing value (RRV) of preferred food task). Increased fasting and post-standard breakfast appetite ratings were noted following PSR with an advanced wake-time compared to the control and PSR with a delayed bedtime sessions (Fasting hunger ratings: 77 ± 16 vs. 65 ± 18 and 64 ± 16; P = 0.01; Post-meal hunger AUC: 5982 ± 1781 vs. 4508 ± 2136 and 5198 ± 2201; P = 0.03). Increased explicit wanting and liking for high-relative to low-fat foods were also noted during the advanced wake-time vs. control session (Explicit wanting: -3.5 ± 12.5 vs. -9.3 ± 8.9, P = 0.01; Explicit liking: -1.6 ± 8.5 vs. -7.8 ± 9.6, P = 0.002). No differences in the RRV of preferred food, the SQ and ad libitum lunch intake were noted between sessions. These findings suggest that appetite sensations and food reward are increased following PSR with an advanced wake-time, rather than delayed bedtime, vs. CONTROL: However, this did not translate into increased EI during a test meal. Given the increasing prevalence of shift workers and incidences of sleep disorders, additional studies are needed to evaluate the prolonged effects of voluntary sleep restriction with altered sleep timing on appetite and EI measurements

A meta-analytic review of stand-alone interventions to improve body image

Objective Numerous stand-alone interventions to improve body image have been developed. The present review used meta-analysis to estimate the effectiveness of such interventions, and to identify the specific change techniques that lead to improvement in body image. Methods The inclusion criteria were that (a) the intervention was stand-alone (i.e., solely focused on improving body image), (b) a control group was used, (c) participants were randomly assigned to conditions, and (d) at least one pretest and one posttest measure of body image was taken. Effect sizes were meta-analysed and moderator analyses were conducted. A taxonomy of 48 change techniques used in interventions targeted at body image was developed; all interventions were coded using this taxonomy. Results The literature search identified 62 tests of interventions (N = 3,846). Interventions produced a small-to-medium improvement in body image (d+ = 0.38), a small-to-medium reduction in beauty ideal internalisation (d+ = -0.37), and a large reduction in social comparison tendencies (d+ = -0.72). However, the effect size for body image was inflated by bias both within and across studies, and was reliable but of small magnitude once corrections for bias were applied. Effect sizes for the other outcomes were no longer reliable once corrections for bias were applied. Several features of the sample, intervention, and methodology moderated intervention effects. Twelve change techniques were associated with improvements in body image, and three techniques were contra-indicated. Conclusions The findings show that interventions engender only small improvements in body image, and underline the need for large-scale, high-quality trials in this area. The review identifies effective techniques that could be deployed in future interventions

Citizen science reveals widespread negative effects of roads on amphibian distributions

Landscape structure is important for shaping the abundance and distribution of amphibians, but prior studies of landscape effects have been species or ecosystem-specific. Using a large-scale, citizen science-generated database, we examined the effects of habitat composition, road disturbance, and habitat split (i.e. the isolation of wetland from forest by intervening land use) on the distribution and richness of frogs and toads in the eastern and central United States. Undergraduates from nine biology and environmental science courses collated occupancy data and characterized landscape structure at 1617 sampling locations from the North American Amphibian Monitoring Program. Our analysis revealed that anuran species richness and individual species distributions were consistently constrained by both road density and traffic volume. In contrast, developed land around wetlands had small, or even positive effects on anuran species richness and distributions after controlling for road effects. Effects of upland habitat composition varied among species, and habitat split had only weak effects on species richness or individual species distributions. Mechanisms underlying road effects on amphibians involve direct mortality, behavioral barriers to movement, and reduction in the quality of roadside habitats. Our results suggest that the negative effects of roads on amphibians occur across broad geographic regions, affecting even common species, and they underscore the importance of developing effective strategies to mitigate the impacts of roads on amphibian populations

Spectrum of KV2.1 Dysfunction in KCNB1‐Associated Neurodevelopmental Disorders

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/152486/1/ana25607.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/152486/2/ana25607_am.pd

The 24-month course of manic symptoms in children

The Longitudinal Assessment of Manic Symptoms (LAMS) study was designed to investigate phenomenology and establish predictors of functional outcomes in children with elevated manic symptoms. The purpose of this series of analyses was to determine whether the participants demonstrated different trajectories of parent-reported manic and biphasic symptoms over the first 24 months of follow-up and to describe the clinical characteristics of the trajectories

Expert range maps of global mammal distributions harmonised to three taxonomic authorities

Aim: Comprehensive, global information on species' occurrences is an essential biodiversity variable and central to a range of applications in ecology, evolution, biogeography and conservation. Expert range maps often represent a species' only available distributional information and play an increasing role in conservation assessments and macroecology. We provide global range maps for the native ranges of all extant mammal species harmonised to the taxonomy of the Mammal Diversity Database (MDD) mobilised from two sources, the Handbook of the Mammals of the World (HMW) and the Illustrated Checklist of the Mammals of the World (CMW). Location: Global. Taxon: All extant mammal species. Methods: Range maps were digitally interpreted, georeferenced, error-checked and subsequently taxonomically aligned between the HMW (6253 species), the CMW (6431 species) and the MDD taxonomies (6362 species). Results: Range maps can be evaluated and visualised in an online map browser at Map of Life (mol.org) and accessed for individual or batch download for non-commercial use. Main conclusion: Expert maps of species' global distributions are limited in their spatial detail and temporal specificity, but form a useful basis for broad-scale characterizations and model-based integration with other data. We provide georeferenced range maps for the native ranges of all extant mammal species as shapefiles, with species-level metadata and source information packaged together in geodatabase format. Across the three taxonomic sources our maps entail, there are 1784 taxonomic name differences compared to the maps currently available on the IUCN Red List website. The expert maps provided here are harmonised to the MDD taxonomic authority and linked to a community of online tools that will enable transparent future updates and version control.Fil: Marsh, Charles J.. Yale University; Estados UnidosFil: Sica, Yanina. Yale University; Estados UnidosFil: Burguin, Connor. University of New Mexico; Estados UnidosFil: Dorman, Wendy A.. University of Yale; Estados UnidosFil: Anderson, Robert C.. University of Yale; Estados UnidosFil: del Toro Mijares, Isabel. University of Yale; Estados UnidosFil: Vigneron, Jessica G.. University of Yale; Estados UnidosFil: Barve, Vijay. University Of Florida. Florida Museum Of History; Estados UnidosFil: Dombrowik, Victoria L.. University of Yale; Estados UnidosFil: Duong, Michelle. University of Yale; Estados UnidosFil: Guralnick, Robert. University Of Florida. Florida Museum Of History; Estados UnidosFil: Hart, Julie A.. University of Yale; Estados UnidosFil: Maypole, J. Krish. University of Yale; Estados UnidosFil: McCall, Kira. University of Yale; Estados UnidosFil: Ranipeta, Ajay. University of Yale; Estados UnidosFil: Schuerkmann, Anna. University of Yale; Estados UnidosFil: Torselli, Michael A.. University of Yale; Estados UnidosFil: Lacher, Thomas. Texas A&M University; Estados UnidosFil: Wilson, Don E.. National Museum of Natural History; Estados UnidosFil: Abba, Agustin Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Estudios Parasitológicos y de Vectores. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. Centro de Estudios Parasitológicos y de Vectores; ArgentinaFil: Aguirre, Luis F.. Universidad Mayor de San Simón; BoliviaFil: Arroyo Cabrales, Joaquín. Instituto Nacional de Antropología E Historia, Mexico; MéxicoFil: Astúa, Diego. Universidade Federal de Pernambuco; BrasilFil: Baker, Andrew M.. Queensland University of Technology; Australia. Queensland Museum; AustraliaFil: Braulik, Gill. University of St. Andrews; Reino UnidoFil: Braun, Janet K.. Oklahoma State University; Estados UnidosFil: Brito, Jorge. Instituto Nacional de Biodiversidad; EcuadorFil: Busher, Peter E.. Boston University; Estados UnidosFil: Burneo, Santiago F.. Pontificia Universidad Católica del Ecuador; EcuadorFil: Camacho, M. Alejandra. Pontificia Universidad Católica del Ecuador; EcuadorFil: de Almeida Chiquito, Elisandra. Universidade Federal do Espírito Santo; BrasilFil: Cook, Joseph A.. University of New Mexico; Estados UnidosFil: Cuéllar Soto, Erika. Sultan Qaboos University; OmánFil: Davenport, Tim R. B.. Wildlife Conservation Society; TanzaniaFil: Denys, Christiane. Muséum National d'Histoire Naturelle; FranciaFil: Dickman, Christopher R.. The University Of Sydney; AustraliaFil: Eldridge, Mark D. B.. Australian Museum; AustraliaFil: Fernandez Duque, Eduardo. University of Yale; Estados UnidosFil: Francis, Charles M.. Environment And Climate Change Canada; CanadáFil: Frankham, Greta. Australian Museum; AustraliaFil: Freitas, Thales. Universidade Federal do Rio Grande do Sul; BrasilFil: Friend, J. Anthony. Conservation And Attractions; AustraliaFil: Giannini, Norberto Pedro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - Tucumán. Unidad Ejecutora Lillo; ArgentinaFil: Gursky-Doyen, Sharon. Texas A&M University; Estados UnidosFil: Hackländer, Klaus. Universitat Fur Bodenkultur Wien; AustriaFil: Hawkins, Melissa. National Museum of Natural History; Estados UnidosFil: Helgen, Kristofer M.. Australian Museum; AustraliaFil: Heritage, Steven. University of Duke; Estados UnidosFil: Hinckley, Arlo. Consejo Superior de Investigaciones Científicas. Estación Biológica de Doñana; EspañaFil: Holden, Mary. American Museum of Natural History; Estados UnidosFil: Holekamp, Kay E.. Michigan State University; Estados UnidosFil: Humle, Tatyana. University Of Kent; Reino UnidoFil: Ibáñez Ulargui, Carlos. Consejo Superior de Investigaciones Científicas. Estación Biológica de Doñana; EspañaFil: Jackson, Stephen M.. Australian Museum; AustraliaFil: Janecka, Mary. University of Pittsburgh at Johnstown; Estados Unidos. University of Pittsburgh; Estados UnidosFil: Jenkins, Paula. Natural History Museum; Reino UnidoFil: Juste, Javier. Consejo Superior de Investigaciones Científicas. Estación Biológica de Doñana; EspañaFil: Leite, Yuri L. R.. Universidade Federal do Espírito Santo; BrasilFil: Novaes, Roberto Leonan M.. Universidade Federal do Rio de Janeiro; BrasilFil: Lim, Burton K.. Royal Ontario Museum; CanadáFil: Maisels, Fiona G.. Wildlife Conservation Society; Estados UnidosFil: Mares, Michael A.. Oklahoma State University; Estados UnidosFil: Marsh, Helene. James Cook University; AustraliaFil: Mattioli, Stefano. Università degli Studi di Siena; ItaliaFil: Morton, F. Blake. University of Hull; Reino UnidoFil: Ojeda, Agustina Alejandra. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Investigaciones de las Zonas Áridas. Provincia de Mendoza. Instituto Argentino de Investigaciones de las Zonas Áridas. Universidad Nacional de Cuyo. Instituto Argentino de Investigaciones de las Zonas Áridas; ArgentinaFil: Ordóñez Garza, Nicté. Instituto Nacional de Biodiversidad; EcuadorFil: Pardiñas, Ulises Francisco J.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto de Diversidad y Evolución Austral; ArgentinaFil: Pavan, Mariana. Universidade de Sao Paulo; BrasilFil: Riley, Erin P.. San Diego State University; Estados UnidosFil: Rubenstein, Daniel I.. University of Princeton; Estados UnidosFil: Ruelas, Dennisse. Museo de Historia Natural, Lima; PerúFil: Schai-Braun, Stéphanie. Universitat Fur Bodenkultur Wien; AustriaFil: Schank, Cody J.. University of Texas at Austin; Estados UnidosFil: Shenbrot, Georgy. Ben Gurion University of the Negev; IsraelFil: Solari, Sergio. Universidad de Antioquia; ColombiaFil: Superina, Mariella. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Medicina y Biología Experimental de Cuyo; ArgentinaFil: Tsang, Susan. American Museum of Natural History; Estados UnidosFil: Van Cakenberghe, Victor. Universiteit Antwerp; BélgicaFil: Veron, Geraldine. Université Pierre et Marie Curie; FranciaFil: Wallis, Janette. Kasokwa-kityedo Forest Project; UgandaFil: Whittaker, Danielle. Michigan State University; Estados UnidosFil: Wells, Rod. Flinders University.; AustraliaFil: Wittemyer, George. State University of Colorado - Fort Collins; Estados UnidosFil: Woinarski, John. Charles Darwin University; AustraliaFil: Upham, Nathan S.. University of Yale; Estados UnidosFil: Jetz, Walter. University of Yale; Estados Unido