Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
1,742
datasets available to search
ShareScore release 0.9.0
Dataset results
1,742 results for “Activity data”
Data from: Evaluating active learning methods for annotating semantic predications
Objectives: This study evaluated and compared a variety of active learning strategies, including a novel strategy we proposed, as applied to the task of filtering incorrect SemRep semantic predications. Materials and Methods: We evaluated three types of active learning strategies – uncertainty, representative, and combined– on two datasets of semantic predications from SemMedDB covering the domains of substance interactions and clinical medicine, respectively. We also designed a novel combined strategy with dynamic β without hand-tuned hyperparameters. Each strategy was assessed by the Area under the Learning Curve (ALC) and the number of training examples required to achieve a target Area Under the ROC curve (AUC). We also visualized and compared the query patterns of the query strategies. Results: Combined strategies outperformed all other methods in terms of ALC, outperforming the baseline by over 0.05 ALC for both datasets and reducing 58% annotation efforts in the best case. While representative strategies performed well, their performance was matched or outperformed by the combined methods. All the uncertainty sampling methods beat the baseline but they were the worst performing methods overall. Our proposed AL method with dynamic β shows promising ability to achieve near-optimal performance across two datasets. Discussion: Our visual analysis of query patterns indicates that strategies which efficiently obtain a representative subsample perform better on this task. Conclusion: Active learning is shown to be effective at reducing annotation costs for filtering incorrect semantic predications from SemRep. Our proposed AL method demonstrated promising performance.
Data from: Short-term activity cycles impede information transmission in ant colonies
Rhythmical activity patterns are ubiquitous in nature. We study an oscillatory biological system: collective activity cycles in ant colonies. Ant colonies have become model systems for research on biological networks because the interactions between the component parts are visible to the naked eye, and because the time-ordered contact network formed by these interactions serves as the substrate for the distribution of information and other resources throughout the colony. To understand how the collective activity cycles influence the contact network transport properties, we used an automated tracking system to record the movement of all the individuals within nine different ant colonies. From these trajectories we extracted over two million ant-to-ant interactions. Time-series analysis of the temporal fluctuations of the overall colony interaction and movement rates revealed that both the period and amplitude of the activity cycles exhibit a diurnal cycle, in which daytime cycles are faster and of greater amplitude than night cycles. Using epidemiology-derived models of transmission over networks, we compared the transmission properties of the observed periodic contact networks with those of synthetic aperiodic networks. These simulations revealed that contrary to some predictions, regularly-oscillating contact networks should impede information transmission. Further, we provide a mechanistic explanation for this effect, and present evidence in support of it.
Data from: Effect of mild thyrotoxicosis on performance and brain activations in a working memory task
Aims: Disturbed levels of thyroid hormones are associated with neuropsychiatric disorders, including memory impairments. The aim of this study was to evaluate effects of mild induced thyrotoxicosis on working memory and its neural correlates. Methods: Twenty-nine healthy, male subjects with normal thyroid state participated in the study. Functional MRI was acquired during a working memory task (n-back task) before and after ingesting 250 μg L-thyroxin per day for a period of eight weeks. In addition, neuropsychological tests were performed. Results: In the hyperthyroid condition the subjects showed slower reaction times, but a higher accuracy in the 0-back version of the memory tasks. Fewer differences between euthyroid and hyperthyroid state were seen for the more difficult conditions of the n-back task. FMRI revealed effects of difficulty in the parahippocampal gyrus, supplementary motor area, prefrontal cortex, anterior cingulate cortex, posterior cerebellum, rolandic operculum and insula (p<0.05, FWE corrected). When comparing euthyroid and hyperthyroid condition in relation to task-induced activation, differences of activation were found in the right prefrontal cortex as well as in the right parahippocampal area. In the psychological assessment, the alerting effect in the Attention Network Task (ANT) and four out of five parameters of the auditory verbal learning test (AVLT) showed an increase from euthyroid to hyperthyroid state. Conclusions: It can be concluded that even a short-term intake of thyroid hormones leads to an activation of brain areas associated with working memory and to an improvement of accuracy of working memory tasks.
Data from: Escherichia coli populations in unpredictably fluctuating environments evolve to face novel stresses through enhanced efflux activity
There is considerable understanding about how laboratory populations respond to predictable (constant or deteriorating environment) selection for single environmental variables such as temperature or pH. However, such insights may not apply when selection environments comprise multiple variables that fluctuate unpredictably, as is common in nature. To address this issue, we grew replicate laboratory populations of Escherichia coli in nutrient broth whose pH and concentrations of salt (NaCl) and hydrogen peroxide (H2O2) were randomly changed daily. After ~170 generations, the fitness of the selected populations had not increased in any of the three selection environments. However, these selected populations had significantly greater fitness in four novel environments which have no known fitness-correlation with tolerance to pH, NaCl or H2O2. Interestingly, contrary to expectations, hypermutators did not evolve. Instead, the selected populations evolved an increased ability for energy-dependent efflux activity that might enable them to throw out toxins, including antibiotics, from the cell at a faster rate. This provides an alternate mechanism for how evolvability can evolve in bacteria and potentially lead to broad-spectrum antibiotic resistance, even in the absence of prior antibiotic exposure. Given that environmental variability is increasing in nature, this might have serious consequences for public health.
Data from: Down-regulation of Rad51 activity during meiosis in yeast prevents competition with Dmc1 for repair of double-strand breaks
Interhomolog recombination plays a critical role in promoting proper meiotic chromosome segregation but a mechanistic understanding of this process is far from complete. In vegetative cells, Rad51 is a highly conserved recombinase that exhibits a preference for repairing double strand breaks (DSBs) using sister chromatids, in contrast to the conserved, meiosis-specific recombinase, Dmc1, which preferentially repairs programmed DSBs using homologs. Despite the different preferences for repair templates, both Rad51 and Dmc1 are required for interhomolog recombination during meiosis. This paradox has recently been explained by the finding that Rad51 protein, but not its strand exchange activity, promotes Dmc1 function in budding yeast. Rad51 activity is inhibited in dmc1Δ mutants, where the failure to repair meiotic DSBs triggers the meiotic recombination checkpoint, resulting in prophase arrest. The question remains whether inhibition of Rad51 activity is important during wild-type meiosis, or whether inactivation of Rad51 occurs only as a result of the absence of DMC1 or checkpoint activation. This work shows that strains in which mechanisms that down-regulate Rad51 activity are removed exhibit reduced numbers of interhomolog crossovers and noncrossovers. A hypomorphic mutant, dmc1-T159A, makes less stable presynaptic filaments but is still able to mediate strand exchange and interact with accessory factors. Combining dmc1-T159A with up-regulated Rad51 activity reduces interhomolog recombination and spore viability, while increasing intersister joint molecule formation. These results support the idea that down-regulation of Rad51 activity is important during meiosis to prevent Rad51 from competing with Dmc1 for repair of meiotic DSBs.
Data from: Intestinal Serum Amyloid A suppresses systemic neutrophil activation and bactericidal activity in response to microbiota colonization
The intestinal microbiota influences the development and function of myeloid lineages such as neutrophils, but the underlying molecular mechanisms are unresolved. Using gnotobiotic zebrafish, we identified the immune effector Serum amyloid A (Saa) as one of the most highly induced transcripts in digestive tissues following microbiota colonization. Saa is a conserved secreted protein produced in the intestine and liver with described effects on neutrophils in vitro, however its in vivo functions remain poorly defined. We engineered saa mutant zebrafish to test requirements for Saa on innate immunity in vivo. Zebrafish mutant for saa displayed impaired neutrophil responses to wounding but augmented clearance of pathogenic bacteria. At baseline, saa mutants exhibited moderate neutrophilia and altered neutrophil tissue distribution. Molecular and functional analyses of isolated neutrophils revealed that Saa suppresses expression of pro-inflammatory markers and bactericidal activity. Saa's effects on neutrophils depend on microbiota colonization, suggesting this protein mediates the microbiota's effects on host innate immunity. To test tissue-specific roles of Saa on neutrophil function, we over-expressed saa in the intestine or liver and found that sufficient to partially complement neutrophil phenotypes observed in saa mutants. These results indicate Saa produced by the intestine in response to microbiota serves as a systemic signal to neutrophils to restrict aberrant activation, decreasing inflammatory tone and bacterial killing potential while simultaneously enhancing their ability to migrate to wounds.
Data from: Using hidden Markov models to improve quantifying physical activity in accelerometer data – a simulation study
Introduction The use of accelerometers to objectively measure physical activity (PA) has become the most preferred method of choice in recent years. Traditionally, cutpoints are used to assign impulse counts recorded by the devices to sedentary and activity ranges. Here, hidden Markov models (HMM) are used to improve the cutpoint method to achieve a more accurate identification of the sequence of modes of PA. Methods:1,000 days of labeled accelerometer data have been simulated. For the simulated data the actual sedentary behavior and activity range of each count is known. The cutpoint method is compared with HMMs based on the Poisson distribution (HMM[Pois]), the generalized Poisson distribution (HMM[GenPois]) and the Gaussian distribution (HMM[Gauss]) with regard to misclassification rate (MCR), bout detection, detection of the number of activities performed during the day and runtime. Results:The cutpoint method had a misclassification rate (MCR) of 11% followed by HMM[Pois] with 8%, HMM[GenPois] with 3% and HMM[Gauss] having the best MCR with less than 2%. HMM[Gauss] detected the correct number of bouts in 12.8% of the days, HMM[GenPois] in 16.1%, HMM[Pois] and the cutpoint method in none. HMM[GenPois] identified the correct number of activities in 61.3% of the days, whereas HMM[Gauss] only in 26.8%. HMM[Pois] did not identify the correct number at all and seemed to overestimate the number of activities. Runtime varied between 0.01 seconds (cutpoint), 2.0 minutes (HMM[Gauss]) and 14.2 minutes (HMM[GenPois]). Conclusions: Using simulated data, HMM-based methods were superior in activity classification when compared to the traditional cutpoint method and seem to be appropriate to model accelerometer data. Of the HMM-based methods, HMM[Gauss] seemed to be the most appropriate choice to assess real-life accelerometer data.
Data from: Lysine-14 acetylation of histone H3 in chromatin confers resistance to the deacetylase and demethylase activities of an epigenetic silencing complex
The core CoREST complex (LHC) contains histone deacetylase HDAC1 and histone demethylase LSD1 held together by the scaffold protein CoREST. Here we analyze the purified LHC with modified peptide and reconstituted semisynthetic mononucleosome substrates. LHC demethylase activity toward methyl-Lys4 in histone H3 is strongly inhibited by H3 Lys14 acetylation, and this appears to be an intrinsic property of the LSD1 subunit. Moreover, the deacetylase selectivity of LHC unexpectedly shows a marked preference for H3 acetyl-Lys9 versus acetyl-Lys14 in nucleosome substrates but this selectivity is lost with isolated acetyl-Lys H3 protein. This diminished activity of LHC for Lys14 deacetylation in nucleosomes is not merely due to steric accessibility based on the pattern of sensitivity of the LHC enzymatic complex to hydroxamic acid-mediated inhibition. Overall, these studies have revealed how a single Lys modification can confer a composite of resistance in chromatin to a key epigenetic enzyme complex involved in gene silencing.
Data from: Response repetition biases in human perceptual decisions are explained by activity decay in competitive attractor models
Animals and humans have a tendency to repeat recent choices, a phenomenon known as choice hysteresis. The mechanism for this choice bias remains unclear. Using an established, biophysically informed model of a competitive attractor network for decision making, we found that decaying tail activity from the previous trial caused choice hysteresis, especially during difficult trials, and accurately predicted human perceptual choices. In the model, choice variability could be directionally altered through amplification or dampening of post-trial activity decay through simulated depolarizing or hyperpolarizing network stimulation. An analogous intervention using transcranial direct current stimulation (tDCS) over left dorsolateral prefrontal cortex (dlPFC) yielded a close match between model predictions and experimental results: net soma depolarizing currents increased choice hysteresis, while hyperpolarizing currents suppressed it. Residual activity in competitive attractor networks within dlPFC may thus give rise to biases in perceptual choices, which can be directionally controlled through non-invasive brain stimulation.
Data from: Akt-mTORC1 signaling regulates Acly to integrate metabolic input to control of macrophage activation
Macrophage activation/polarization to distinct functional states is critically supported by metabolic shifts. How polarizing signals coordinate metabolic and functional reprogramming, and the potential implications for control of macrophage activation, remains poorly understood. Here we show that IL-4 signaling co-opts the Akt-mTORC1 pathway to regulate Acly, a key enzyme in Ac-CoA synthesis, leading to increased histone acetylation and M2 gene induction. Only a subset of M2 genes is controlled in this way, including those regulating cellular proliferation and chemokine production. Moreover, metabolic signals impinge on the Akt-mTORC1 axis for such control of M2 activation. We propose that Akt-mTORC1 signaling calibrates metabolic state to energetically demanding aspects of M2 activation, which may define a new role for metabolism in supporting macrophage activation.
Data from: Lack of activity of recombinant HIF prolyl hydroxylases (PHDs) on reported non-HIF substrates
Human and other animal cells deploy three closely related dioxygenases (PHD 1, 2 and 3) to signal oxygen levels by catalysing oxygen regulated prolyl hydroxylation of the transcription factor HIF. The discovery of the HIF prolyl-hydroxylase (PHD) enzymes as oxygen sensors raises a key question as to the existence and nature of non-HIF substrates, potentially transducing other biological responses to hypoxia. Over 20 such substrates are reported. We therefore sought to characterise their reactivity with recombinant PHD enzymes. Unexpectedly, we did not detect prolyl-hydroxylase activity on any reported non-HIF protein or peptide, using conditions supporting robust HIF-α hydroxylation. We cannot exclude PHD-catalysed prolyl hydroxylation occurring under conditions other than those we have examined. However, our findings using recombinant enzymes provide no support for the wide range of non-HIF PHD substrates that have been reported.
Data files from: Host plant association, calling activity and sexual dimorphism in an Indian weta
<p>Both sexes of Indian weta <i>Gryllacropsis</i> sp. communicate acoustically. Females lack an external ovipositor making it difficult to differentiate between the sexes in the field. There is limited ecological information on the species as it is found high up on the trunks of evergreen trees, well camouflaged and active only at night. The present study was conducted to gain ecological information on this little known yet intriguing species. We tested the hypotheses that 1) calling activity of Indian weta is uniformly distributed throughout the year and 2) there is no difference in morphometric measurements between the sexes. The study was conducted in Bhagwan Mahavir Wildlife Sanctuary and Mollem National Park, Goa, India. Visual scanning of tree trunks followed by vegetation sampling, psychoacoustic sampling and morphometric analyses were carried out. Resource selection function values, obtained for a total of 52 tree species from 1984 individuals, were less than 0.1 for all plant species indicating no preference by the wetas. Peak calling activity was observed in the month of November <span>(Rayleigh's Test, Z = 7.90, p< 0.01)</span>. Discriminant Function Analysis on morphometric characters of males and females (Wilk's lambda= 0.32 approx. F (4, 21) =11.24 p< .0001, classification accuracy= 96.15 %) provided clear distinction between males and females. Contribution of body weight was significant (Standardized canonical discriminant function coefficients = +1) and could be used for identification of sexes in the field. These polyphagous insects provide insights on understanding ecological specialization due to host plant association, signal evolution and mating behavior.</p>
Data from: Grazing and nitrogen addition restructure the spatial heterogeneity of soil microbial community structure and enzymatic activities
<p>1. In grassland ecosystems, large herbivorous animal grazing activity and increasing nitrogen deposition strongly alters microbial community structure and function. Understanding the effects of grazing and nitrogen addition on the spatial heterogeneity in soil microbial community structure, enzymatic activities and the underlying mechanisms are crucial for making better predictions of soil organic matter dynamics and nutrient cycling. </p> <p>2. We examined the spatial heterogeneity of soil microbial community structure and enzymatic activity associated with changes in soil microclimate, soil characteristics, plant biomass and soil nutrient responses to grazing and nitrogen addition using a manipulative experiment with control (CK), grazing (G), nitrogen addition (N) and grazing plus nitrogen addition (NG) treatments in a <i>Leymus chinensis </i>meadow steppe, in northeastern China. </p> <p>3. The results demonstrated that soil microbial community structure and enzymatic activities showed a high level of spatial dependence [C/(C + C0)≥0.9] in the CK plot. G, N and NG treatments not only reduced the spatial variability ofsoil microbial community structure and enzymatic activities, but also reshaped the spatial links between enzymes activities and microbial community structure. Litter biomass, soil temperature and soil nutrients (soil dissolved inorganic nitrogen or soil dissolved organic carbon) explained 21-27% of the spatial variability of soil microbial community structure in the CK treatment and pH was the strongest driver for the spatial variability of soil enzymatic activities. Meanwhile, the homogenization in soil water content induced by the N addition treatment was a determinant of the reduction in spatial heterogeneity of the microbial community structure. The combination of soil physicochemical properties (bulk density, soil pH and soil dissolved inorganic nitrogen), soil temperature and root biomass explained 32-43% of the spatial variability of the microbial community structure in the G treatment, and N and G treatments had additive effects on the spatial heterogeneity of total PLFAs by homogenizing root biomass. Plant biomass and microbial community structure were the major drivers for the spatial heterogeneity of enzymatic activities under G, N and NG. In NG, the change in spatial variability of enzymatic activities was dominated by N addition. Regardless of grazing, N addition facilitated the spatial correlation between microbial community structure and enzyme activities. </p> <p>4. Overall, our results revealed the drivers of soil microbial community structure and enzymatic activities spatial pattern shift due to grazing and N addition, highlighting the role that spatial variability in soil microbial community structure and enzymatic activities has on the <i>L. chinensis</i> meadow steppe.</p>
Data from: Overall dynamic body acceleration measures activity differently on large vs small aquatic animals
<p>Acceleration-based proxies for activity and energy expenditure are widely used in bio-logging studies of animal movement and locomotion to explore biomechanical strategies, energetic costs of behaviour, habitat use and the impact of anthropogenic disturbance. The foremost such proxy is Overall Dynamic Body Acceleration (ODBA) along with variants VeDBA and PDBA. This technique, which involves summing the magnitude of high-pass-filtered acceleration signals (the so-called dynamic acceleration) over a reference interval, has been applied to animals as diverse as shags, lobsters, humans and whales. The relationship between ODBA and energy use has been tested empirically on animals small enough to house in laboratory facilities and arguments have been offered for why the method should be generally applicable, however validations on larger animals are scant.</p> <p><span>Here, we examine how body size impacts ODBA and its variants under steady locomotion in large aquatic animals, using cetaceans as model species. To do this, we first develop a simplified mathematical model for the acceleration signals that would be measured by a tag on a swimming animal. We then test this model with empirical data gathered using bio-logging tags on whale species covering nearly an order of magnitude difference in body length from 1.3 m harbour porpoises to 12 m sperm whales.</span></p> <p><span>We show that the motions measured by ODBA can be fundamentally different in small compared to large aquatic animals. Whereas dynamic acceleration in small animals is predominantly due to specific acceleration (i.e., actual accelerative motions generated by muscle action), in larger aquatic animals body rotations (i.e., changes in orientation that accompany swimming and manoeuvring) can dominate the measured acceleration. </span></p> <p><span>As body rotations do not necessarily increase in magnitude as swimming speed increases, ODBA may under-estimate the relative cost of behaviours or responses to disturbance in large aquatic animals. This does not lessen the value of ODBA for small animals, but it raises a caution against uncritical use on larger animals. For large aquatic animals, activity proxies that specifically remove body rotations using gyroscopes or magnetometers may provide more consistent estimates of energy use although these methods are yet to be validated.</span></p>
Data from: Post-fledging behavioral ecology of migratory songbirds: How do fledgling activity rates vary across species?
<p>This datsaset contains data for a comparison of fledgling activity rates from 9 songbird species in east-central Illinois, USA, described in the paper: "Jones, TM, and MP Ward. 2021. Post-fledging behavioral ecology of migratory songbirds: how do fledgling activity rates vary across species?"; published in <em>Behavioral Ecology</em>. The dataset contains estimates of fledgling activity rates during the daytime, nighttime, and across the post-fledging period, which were compared to estimates of fledgling morphologies (e.g. mass, tarsus, wing development) and post-fledging survival. Analyses, which can be reproduced with this data, showed that overall rates of post-fledging activity differed by species, but species showed similarities in the development of activity rates across the period. All species exhibited a stead increase in activity rates with age and general patterns mirrored rates of post-fledging mortality, including the presence and absence of post-fledging bottlenecks within each species. Additionally, our findings suggest that fledgling wing development and brood size at fledging contribute to variatio in activity rates within and across species.</p>
Data set IDA tests for activity A 3.3.1 MeDDII
<p>Data set IDA tests for activity A 3.3.1 MeDDII</p>
Data from: Biotic and abiotic factors shaping bat activity in Maryland soybean fields
<p>Data and code for <em>Ecosphere</em> publication, "Biotic and abiotic factors shaping bat activity in Maryland soybean fields." @susanrw</p> <p> </p> <p><a href="https://doi.org/10.1002/ecs2.4575">https://doi.org/10.1002/ecs2.4575</a></p>
raw data INa ipsc (activation & inactivation) at 37C
<p>Raw data INa ipsc (activation & inactivation) at 37C</p>
Data supplement for "Stationary broken parity states in active matter models''
<p>Data sets and python codes that produce all figures in "Stationary broken parity states in active matter models''. Additionally it contains example Matlab codes that perform the numerical path continuation with pde2path.</p>
Key data used in "Western North Pacific tropical cyclone activity modulated by phytoplankton feedback under global warming" submitted to Nature Climate Change
<p>Key data</p>
ScienceDex guides
Understand access before you commit
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.