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4,215 results for “high risk”
Data from: Evolution of male age-specific reproduction under differential risks and causes of death: males pay the cost of high female fitness
Classic theories of ageing evolution predict that increased extrinsic mortality due to an environmental hazard selects for increased early reproduction, rapid ageing and short intrinsic lifespan. Conversely, emerging theory maintains that when ageing increases susceptibility to an environmental hazard, increased mortality due to this hazard can select against ageing in physiological condition and prolong intrinsic lifespan. However, evolution of slow ageing under high-condition-dependent mortality is expected to result from reallocation of resources to different traits and such reallocation may be hampered by sex-specific trade-offs. Because same life-history trait values often have different fitness consequences in males and females, sexually antagonistic selection can preserve genetic variance for lifespan and ageing. We previously showed that increased condition-dependent mortality caused by heat shock leads to evolution of long-life, decelerated late-life mortality in both sexes and increased female fecundity in the nematode, Caenorhabditis remanei. Here, we used these cryopreserved lines to show that males evolving under heat shock suffered from reduced early-life and net reproduction, while mortality rate had no effect. Our results suggest that heat-shock resistance and associated long-life trade-off with male, but not female, reproduction and therefore sexually antagonistic selection contributes to maintenance of genetic variation for lifespan and fitness in this population.
Data from: Social learning in a high-risk environment: incomplete disregard for the 'minnow that cried pike' results in culturally transmitted neophobia
Many prey species rely on conspecifics to gather information about unknown predation threats, but little is known about the role of varying environmental conditions on the efficacy of social learning. We examined predator-naive minnows that had the opportunity to learn about predators from experienced models that were raised in either a low- or high-risk environment. There were striking differences in behaviour among models; high-risk models showed a weaker response to the predator cue and became neophobic in response to the control cue (a novel odour, NO). Observers that were previously paired with low-risk models acquired a strong antipredator response only to the predator cue. However, observers that interacted with high-risk models, displayed a much weaker response to the predator odour and a weak neophobic response to the NO. This is the first study reporting such different outcomes of social learning under different environmental conditions, and suggests high-risk environments promote the cultural transmission of neophobia more so than social learning. If such a transfer can be considered similar to secondary traumatization in humans, culturally transmitted neophobia in minnows may provide a good model system for understanding more about the social ecology of fear disorders.
Data from: Altered fronto-temporal functional connectivity in individuals at ultra-high-risk of developing psychosis
Background: The superior temporal gyrus (STG) is one of the key regions implicated in psychosis, given that abnormalities in this region are associated with an increased risk of conversion from an at-risk mental state to psychosis. However, inconsistent results regarding the functional connectivity strength of the STG have been reported, and the regional heterogeneous characteristics of the STG should be considered. Methods: To investigate the distinctive functional connection of each subregion in the STG, we parcellated the STG of each hemisphere into three regions: the planum temporale, Heschl's gyrus, and planum polare. Resting-state functional magnetic resonance imaging was obtained from 22 first-episode psychosis (FEP) patients, 41 individuals at ultra-high-risk for psychosis (UHR), and 47 demographically matched healthy controls. Results: Significant group differences (in seed-based connectivity) were demonstrated in the left planum temporale and from both the right and left Heschl's gyrus seeds. From the left planum temporale seed, the FEP and UHR groups exhibited increased connectivity to the bilateral dorsolateral prefrontal cortex. In contrast, the FEP and UHR groups demonstrated decreased connectivity from the bilateral Heschl's gyrus seeds to the dorsal anterior cingulate cortex. The enhanced connectivity between the left planum temporale and right dorsolateral prefrontal cortex was positively correlated with positive symptom severity in individuals at UHR (r = .34, p = .03). Conclusions: These findings corroborate the fronto-temporal connectivity disruption hypothesis in schizophrenia by providing evidence supporting the altered fronto-temporal intrinsic functional connection at earlier stages of psychosis. Our data indicate that subregion-specific aberrant fronto-temporal interactions exist in the STG at the early stage of psychosis, thus suggesting that these aberrancies are the neural underpinning of proneness to psychosis.
Anticoagulant and anti-inflammatory effects of fondaparinux sodium in anterior cruciate ligament reconstruction in patients at high risk of VTE: A Randomized Controlled Trial
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Underlying data for (Hepatitis G Viremia as a Predictor of Liver Disease Prognosis in High-Risk Populations and chronic liver patients)
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Reproducibility data for tables in "A machine learning approach to portfolio pricing and risk management for high dimensional problems"
<p>This dataset contains all the information necessary for reproducing the tables in the paper "A machine learning approach to portfolio pricing and risk management for high dimensional problems".</p> <p>The raw benchmark data can be found in the Zenodo dataset "Benchmark and training data for replicating financial and insurance examples" (https://zenodo.org/record/3837381). To the extend necessary, only summary data from that dataset is used in this dataset.</p> <p>The dataset includes a jupyter notebook file that explains what the different files contain, and provides sample code to analyze the information and reproduce the tables.</p>
Supplementary material 3 from: Bernardo-Madrid R, González-Moreno P, Gallardo B, Bacher S, Vilà M (2022) Consistency in impact assessments of invasive species is generally high and depends on protocols and impact types. In: Giannetto D, Piria M, Tarkan AS, Zięba G (Eds) Recent advancements in the risk screening of freshwater and terrestrial non-native species. NeoBiota 76: 163-190. https://doi.org/10.3897/neobiota.76.83028
Figure S1
Supplementary material 2 from: Bernardo-Madrid R, González-Moreno P, Gallardo B, Bacher S, Vilà M (2022) Consistency in impact assessments of invasive species is generally high and depends on protocols and impact types. In: Giannetto D, Piria M, Tarkan AS, Zięba G (Eds) Recent advancements in the risk screening of freshwater and terrestrial non-native species. NeoBiota 76: 163-190. https://doi.org/10.3897/neobiota.76.83028
Impact assessments and function to calculate G coefficient
Supplementary material 1 from: Bernardo-Madrid R, González-Moreno P, Gallardo B, Bacher S, Vilà M (2022) Consistency in impact assessments of invasive species is generally high and depends on protocols and impact types. In: Giannetto D, Piria M, Tarkan AS, Zięba G (Eds) Recent advancements in the risk screening of freshwater and terrestrial non-native species. NeoBiota 76: 163-190. https://doi.org/10.3897/neobiota.76.83028
Tables S1–S13
Proteomics and Transcriptomics of the Hippocampus and Cortex in SUDEP and High-Risk SUDEP Patients
<p class="AbstractSummary">To identify the molecular signaling pathways underlying sudden unexpected death in epilepsy (SUDEP) and high-risk SUDEP compared to control patients with epilepsy. For proteomics analyses, we evaluated the hippocampus and frontal cortex from microdissected postmortem brain tissue of 12 patients with SUDEP and 14 with non-SUDEP epilepsy. For transcriptomics analyses, we evaluated hippocampus and temporal cortex surgical brain tissue from patients with mesial temporal lobe epilepsy: 6 low-risk and 8 high-risk SUDEP as determined by a short (<50 seconds) or prolonged (=50 seconds) postictal generalized EEG suppression (PGES) that may indicate severely depressed brain activity impairing respiration, arousal, and protective reflexes. In autopsy hippocampus and cortex, we observed no proteomic differences between patients with SUDEP and those with non-SUDEP epilepsy, contrasting with our previously reported robust differences between epilepsy and controls without epilepsy. Transcriptomics in hippocampus and cortex from patients with surgical epilepsy segregated by PGES identified 55 differentially expressed genes (37 protein-coding, 15 long noncoding RNAs, 3 pending) in hippocampus. The SUDEP proteome and high-risk SUDEP transcriptome were similar to those in other patients with epilepsy in hippocampus and cortex, consistent with diverse epilepsy syndromes and comorbid conditions associated with SUDEP. Studies with larger cohorts and different epilepsy syndromes, as well as additional anatomic regions, may identify molecular mechanisms of SUDEP.</p>
FIGURES 97–100 in Facial affect recognition in individuals at clinical high risk for psychosis
FIGURES 97–100. Geographical distributions of Parasthetops species.
FIGURES 115–116 in Facial affect recognition in individuals at clinical high risk for psychosis
FIGURES 115–116. Geographical distributions of Mesoceration species.
FIGURE 77 in Facial affect recognition in individuals at clinical high risk for psychosis
FIGURE 77. Mesoceration littlekarroo, dorsal and lateral habitus of holotype.
FIGURE 62 in Facial affect recognition in individuals at clinical high risk for psychosis
FIGURE 62. Mesoceration bicurvum, dorsal and lateral habitus of holotype.
FIGURE 59 in Facial affect recognition in individuals at clinical high risk for psychosis
FIGURE 59. Mesoceration integer, dorsal and lateral habitus of holotype.
FIGURE 53 in Facial affect recognition in individuals at clinical high risk for psychosis
FIGURE 53. Mesoceration semicarinulum, dorsal and lateral habitus of holotype.
FIGURE 52 in Facial affect recognition in individuals at clinical high risk for psychosis
FIGURE 52. Mesoceration incarinum, dorsal and lateral habitus of holotype.
FIGURE 45 in Facial affect recognition in individuals at clinical high risk for psychosis
FIGURE 45. Mesoceration periscopum, dorsal and lateral habitus of holotype.
FIGURE 44 in Facial affect recognition in individuals at clinical high risk for psychosis
FIGURE 44. Mesoceration rapidensis, dorsal and lateral habitus of holotype.
FIGURE 76 in Facial affect recognition in individuals at clinical high risk for psychosis
FIGURE 76. Mesoceration tabulare, dorsal and lateral habitus of holotype.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.