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Example Microscopy Metadata JSON files produced using Micro-Meta App to document example microscopy experiments performed at individual core facilities
<p>Example <strong>Microscopy Metadata </strong>(Microscope.JSON and Settings.JSON)<strong> files </strong>produced using<strong> <a href="https://wu-bimac.github.io/MicroMetaApp.github.io/">Micro-Meta App</a> </strong>to document the <strong>Hardware Specifications</strong> of example Microscopes and the <strong>Image Acquisition Settings</strong> utilized to acquire example images as listed in the table below.</p> <blockquote> <p>For each facility, the dataset contains two JSON files:</p> <ol> <li><strong>Microscope.JSON file</strong> (e.g., 01_marcello_uliverpool_cci_zeiss_axioobserz1_lsm710.json)</li> <li><strong>Settings.JSON file</strong> (indicated with the name of the image and with the _AS suffix)</li> </ol> </blockquote> <p><strong>Micro-Meta App was</strong> developed as part of a <strong>global community initiative</strong> including the <a href="http://www.4dnucleome.org/"><strong>4D Nucleome (4DN)</strong> </a>Imaging Working Group, <strong>BioImaging North America (BINA)</strong> <a href="https://www.bioimagingna.org/qc-dm-wg">Quality Control and Data Management Working Group</a>, and <strong>QUAlity and REProducibility for Instrument and Images in Light Microscopy</strong> (<a href="https://quarep.org/"><strong>QUAREP-LiMi</strong></a>), to extend the <strong>Open Microscopy Environment (OME)</strong> <a href="https://www.openmicroscopy.org/Schemas/Documentation/Generated/OME-2016-06/ome.html">data model</a>.</p> <blockquote> <p>The works of this <strong>global community effort</strong> resulted in multiple publications featured on a recent <strong>Nature Methods FOCUS ISSUE </strong>dedicated to <a href="https://www.nature.com/collections/djiciihhjh">Reporting and reproducibility in microscopy</a>.</p> </blockquote> <blockquote> <p><strong>Learn More!</strong> For a thorough description of <strong>Micro-Meta App</strong> consult our recent <a href="https://doi.org/10.1038/s41592-021-01315-z">Nature Methods</a> and <a href="https://doi.org/10.1101/2021.05.31.446382">BioRxiv.org</a> publications!</p> </blockquote> <p> </p> <table> <tbody> <tr> <td><strong>Nr.</strong></td> <td><strong>Manufacturer</strong></td> <td><strong>Model</strong></td> <td><strong>Tier</strong></td> <td><strong>Εxperiment Type</strong></td> <td><strong>Facility Name</strong></td> <td><strong>Department and Institution</strong></td> <td><strong>URL</strong></td> <td><strong>References</strong></td> </tr> <tr> <td>1</td> <td><strong>Carl Zeiss Microscopy</strong></td> <td><strong>Axio Observer Z1 (with LSM 710 scan head)</strong></td> <td>1</td> <td>3D visualization of superhydrophobic polymer-nanoparticles</td> <td>Centre for Cell Imaging (CCI)</td> <td>University of Liverpool</td> <td>https://cci.liv.ac.uk/equipment_710.html</td> <td>Upton et al., 2020</td> </tr> <tr> <td>2</td> <td><strong>Carl Zeiss Microscopy</strong></td> <td><strong>Axio Observer (Axiovert 200M)</strong></td> <td>2</td> <td>Μeasurement of illumination stability on Chinese Hamster Ovary cells expressing Paxillin-EGFP</td> <td>Advanced BioImaging Facility (ABIF).</td> <td>McGill University</td> <td>https://www.mcgill.ca/abif/equipment/axiovert-1</td> <td>Kiepas et al., 2020</td> </tr> <tr> <td>3</td> <td><strong>Carl Zeiss Microscopy</strong></td> <td><strong>Axio Observer Z1 (with Spinning Disk)</strong></td> <td>2</td> <td>Immunofluorescence imaging of cryosection of Mouse kidney</td> <td>Imagerie Cellulaire; Quality Control managed by Miacellavie (https://miacellavie.com/)</td> <td>Centre de recherche du Centre Hospitalier Université de Montréal (CR CHUM), University of Montreal</td> <td>https://www.chumontreal.qc.ca/crchum/plateformes-et-services (the web site is for all core facilities, not specifically for the core facility hosting this microscope)</td> <td>Pilliod et al., 2020</td> </tr> <tr> <td>4</td> <td><strong>Carl Zeiss Microscopy</strong></td> <td><strong>Axio Imager Z2 (with Apotome)</strong></td> <td>2</td> <td>Immunofluorescence imaging of mitotic division in Hela cells using </td> <td>Bioimaging Unit</td> <td>Newcastle University</td> <td>https://www.ncl.ac.uk/bioimaging/</td> <td>Watson et al., 2020</td> </tr> <tr> <td>5</td> <td><strong>Carl Zeiss Microscopy</strong></td> <td><strong>Axio Observer Z1</strong></td> <td>2</td> <td>Fluorescence microscopy of human skin fibroblasts from Glycogen Storage Disease patients.</td> <td>Life Imaging Center (LIC)</td> <td>Centre for Integrative Signalling Analysis (CISA), University of Freiburg</td> <td>https://miap.eu/equipments/sd-i-abl/</td> <td>Hannibal et al., 2020</td> </tr> <tr> <td>6</td> <td><strong>Leica Microsystems</strong></td> <td><strong>DMI6000B</strong></td> <td>2</td> <td>3D immunofluorescence imaging rhinovirus infected macrophages </td> <td>IMAG'IC Confocal Microscopy Facility</td> <td>Institut Cochin, CNRS, INSERM, Université de Paris</td> <td>https://www.institutcochin.fr/core_facilities/confocal-microscopy/cochin-imaging-photonic-microscopy/organigram_team/10054/view</td> <td>Jubrail et al., 2020</td> </tr> <tr> <td>7</td> <td><strong>Leica Microsystems</strong></td> <td><strong>DM5500B</strong></td> <td>2</td> <td>Immunofluorescence analysis of the colocalization of PML bodies with DNA double-strand breaks</td> <td>Bioimaging Unit</td> <td>Edwardson Building on the Campus for Ageing and Vitality, Newcastle University</td> <td>https://www.ncl.ac.uk/bioimaging/equipment/leica-dm5500/#overview</td> <td>da Silva et al., 2019; Nelson et al., 2012<br> </td> </tr> <tr> <td>8</td> <td><strong>Leica Microsystems</strong></td> <td><strong>DMI8-CS (with TCS SP8 STED 3X)</strong></td> <td>2</td> <td>Live-cell imaging of N. benthamiana leaves cells-derived protoplasts</td> <td>Center for Advanced Imaging (CAi)</td> <td>School of Mathematics/Natural Sciences, Heinrich-Heine-Universität Düsseldorf</td> <td>https://www.cai.hhu.de/en/equipment/super-resolution-microscopy/leica-tcs-sp8-sted-3x</td> <td>Singer et al., 2017; Hänsch et al., 2020</td> </tr> <tr> <td>9</td> <td><strong>Nikon Instruments</strong></td> <td><strong>Eclipse Ti</strong></td> <td>2</td> <td>Immunofluorescence analysis of the cytoskeleton structure in COS cells</td> <td>Advanced Imaging Center (AIC)</td> <td>Janelia Research Campus, Howard Hughes Medical Institute</td> <td>https://www.janelia.org/support-team/light-microscopy/equipment</td> <td>Abdelfattah et al., 2019; Qian et al., 2019; Grimm et al., 2020</td> </tr> <tr> <td>10</td> <td><strong>Nikon Instruments</strong></td> <td><strong>Eclipse Ti-E (HCA)</strong></td> <td>2</td> <td>Τime-lapse analysis of the bursting behavior of amine-functionalized vesicular assemblies</td> <td>Light Microscopy Facility (IALS-LIF)</td> <td>Institute for Applied Life Sciences, University of Massachusetts at Amherst</td> <td>https://www.umass.edu/ials/light-microscopy</td> <td>Fernandez et al., 2020</td> </tr> <tr> <td>11</td> <td><strong>Nikon Instruments/Coleman laboratory (customized)</strong></td> <td><strong>TIRF HILO Epifluorescence light Microscope (THEM)/ Eclipse Ti</strong></td> <td>2</td> <td>Single-particle tracking of Halo-tagged PCNA in Lox cells</td> <td>Coleman laboratory</td> <td>Anatomy and Structural Biology Department, The Albert Einstein College of Medicine</td> <td>https://einsteinmed.org/faculty/12252/robert-coleman/</td> <td>Drosopoulos et al., 2020</td> </tr> <tr> <td>12</td> <td><strong>Nikon Instruments</strong></td> <td><strong>Eclipse Ti (with Andor Dragon Fly Spinning Disk)</strong></td> <td>2</td> <td>Investigation of the 3D structure of cerebral organoids</td> <td>Montpellier Resources Imagerie</td> <td>Centre de Recherche de Biologie cellulaire de Montpellier (MRI-CRBM), CNRS, Univerity of Montpellier</td> <td>https://www.mri.cnrs.fr/en/optical-imaging/our-facilities/mri-crbm.html</td> <td>Ayala-Nunez et al., 2019</td> </tr> <tr> <td>13</td> <td><strong>Nikon Instruments</strong></td> <td><strong>Eclipse Ti2</strong></td> <td>2</td> <td>Ιmmunofluorescence imaging of cryosections of mouse hearth myocardium </td> <td>Neuroscience Center Microscopy Core</td> <td>Neuroscience Center, University of North Carolina</td> <td>https://www.med.unc.edu/neuroscience/core-facilities/neuro-microscopy/</td> <td>Aghajanian et al., 2021</td> </tr> <tr> <td>14</td> <td><strong>Nikon Instruments</strong></td> <td><strong>Eclipse Ti2</strong></td> <td>2</td> <td>Live-cell imaging of bacterial cells expressing GFP-PopZ</td> <td>Microscopy Resources on the North Quad (MicRoN)</td> <td>Harvard Medical School </td> <td>https://micron.hms.harvard.edu/</td> <td>Lim and Bernhardt 2019; Lim et al., 2019</td> </tr> <tr> <td>15</td> <td><strong>Olympus/Biomedical Imaging Group (customized)</strong></td> <td><strong>TIRF Epifluorescence Structured light Microscope (TESM)/IX71</strong></td> <td>3</td> <td>3D distribution of HIV-1 in the nucleus of human cells</td> <td>Biomedical Imaging Group</td> <td>Program in Molecular Medicine, University of Massachusetts Medical School</td> <td>https://trello.com/b/BQ8zCcQC/tirf-epi-fluorescence-structured-light-microscope</td> <td>Navaroli et al., 2012</td> </tr> <tr> <td>16</td> <td><strong>Olympus/Computer Vision Laboratory (customized)</strong></td> <td><strong>3D BrightField Scanner/IX71</strong></td> <td>3</td> <td>Transmitted light brightfield visualization of swimming spermatocytes</td> <td>Laboratorio Nacional de Microscopia Avanzada (LNMA) and Computer Vision Laboratory of the Institute of Biotechnology</td> <td>Universidad Nacional Autonoma de Mexico (UNAM)</td> <td>https://lnma.unam.mx/wp/</td> <td>Pimentel et al., 2012; Silva-Villalobos et al., 2014</td> </tr> </tbody> </table> <p><strong>Getting started</strong></p> <p>Use these videos to get started with using Micro-Meta App after installation into OMERO and downloading the example data files:</p> <ol> <li><a href="https://vimeo.com/562022222">Video 1</a></li> <li><a href="https://vimeo.com/562022281">Video 2</a></li> </ol> <p><strong>More information</strong></p> <blockquote> <p>For full information on how to use Micro-Meta App please utilize the following resources:</p> <ol> <li>Micro-Meta App <a href="https://wu-bimac.github.io/MicroMetaApp.github.io/">website</a></li> <li><a href="https://micrometaapp-docs.readthedocs.io/en/latest/index.html">Full documentation</a></li> <li><a href="https://micrometaapp-docs.readthedocs.io/en/latest/docs/intro/installation.html">Installation</a> instructions</li> <li><a href="https://micrometaapp-docs.readthedocs.io/en/latest/docs/tutorials/index.html#step-by-step-instructions">Step-by-Step Instructions</a></li> <li><a href="https://micrometaapp-docs.readthedocs.io/en/latest/docs/tutorials/VideoTutorials.html#micro-meta-app-video-tutorials">Tutorial Videos</a></li> </ol> </blockquote> <p><strong>Background</strong></p> <p>If you want to learn more about the importance of <strong>metadata and quality contro</strong>l to ensure full <strong>reproducibility, quality and scientific value</strong> in light microscopy, please take a look at our recent publications describing the development of community-driven light <strong>4DN-BINA-OME Microscopy Metadata</strong> specifications <a href="https://doi.org/10.1038/s41592-021-01327-9">Nature Methods</a> and <a href="https://doi.org/10.1101/2021.04.25.441198">BioRxiv.org</a> and our <a href="https://arxiv.org/abs/1910.11370">overview manuscript</a> entitled <strong>A perspective on Microscopy Metadata: data provenance and quality control</strong>.</p> <p> </p> <p> </p>
Potential Metabolic Activity, Catalase Activity, Performance traits and Morphological variables of 94 individuals belonging to Podarcis muralis species used in the analysis
<p>Potential Metabolic Activity (ETS26_P, ETS31_P, ETS36_P), Catalase Activity (CAT_P), Performance traits (BITE, SPRINT,CLIMB, MANO) and Morphological variables (snout-vent length (SVL), trunk length (TRL), pileus length (PL), head length (HL), head width (HW), head height (HH), fore limb length (FLL) and hind limb length (HLL) of 94 individuals belonging to <em>Podarcis muralis</em> species. The data was used in the analysis of the paper entitled: Is It Function or Fashion? An Integrative Analysis of Morphology, Performance, and Metabolism in a Colour Polymorphic Lizard, by authors Verónica Gomes, Anamarija Žagar, Guillem Pérez i de Lanuza, Tatjana Simčič and Miguel A. Carretero, published in the journal Diversity 2022, 14, 116. <a href="https://doi.org/10.3390/d14020116">https://doi.org/10.3390/d14020116</a></p>
Data from: Evaluating the foraging performance of individual honey bees in different environments with automated field RFID systems
<p>Measuring the individual foraging performances of pollinators is crucial to guide environmental policies that aim at enhancing pollinator health and pollination services. Automated systems have been developed to track the activity of individual honey bees, but their deployment is extremely challenging. This has limited the assessment of individual foraging performances in full-strength bee colonies in the field. Most studies available to date have been constrained to use downsized bee colonies located in urban and suburban areas. Environmental policy-making, on the other hand, needs a more comprehensive assessment of honey bee performances in a broader range of environments, including in remote agricultural and wild areas. Here we detail a new autonomous field method to record high quality data on the flight ontogeny and foraging performance of honey bees, using Radio-Frequency Identification (RFID). We separate bee traffic into returning and exiting tunnels to improve data quality, solving many previous limitations of RFID systems caused by traffic jams and the parasitic coupling of RFID antennae. With this method, we assembled a large RFID dataset made of control bee colonies from experiments conducted in different locations and seasons. We hope our results will be a starting point to understand how ontogenetic and environmental factors affect the individual performances of honey bees, and that our method will enable the large-scale replication of individual pollinator performance studies.</p>
Raw videos of the experiments performed with small groups of sheep (N=2,3 and 4 individuals).
<p>Here we upload the videos used to study the spontaneous and intermittent collective motion observed in small groups of sheep. We used groups of size N=2, 3 and 4 individuals. Details on the analysis can be found in DOI: 10.1038/s41567-022-01769-8 (published in Nature Physics).</p>
Group-level trait and individual performance: the impact of in-nest activity on food recruitment in ants
<p>Dataset, R and Python scripts corresponding to the results displayed in the article "Group-level trait and individual performance: the impact of in-nest activity on food recruitment in ants".</p> <p>R script works in pair with all three .csv files.</p> <p>.txt files are example of output generated by the Python script that analyses a worker's path inside the nest.</p> <p>3 videos from the experiment are also available. They allow visualization of the setup as well as testing of Python scripts.</p>
Data set for "Measuring synchronization and anticipation between individual investors from their daily performance"
<p>The data stored here is used as a support of the paper "Measuring<br> synchronization and anticipation between individual investors from their<br> daily performance" where a measure based on Mutual Information and<br> Transfer of Entropy is used in order to map investors' behaviour and which<br> ones are following same behavioural patterns.</p> <p>The study linked to this data is published on pre-print Arxiv.org<br> with the following citation:</p> <p><br> Mario Gutiérrez-Roig, Javier Borge-Holthoeffer, Alex Arenas and<br> Josep Perelló. Measuring synchronization and anticipation between<br> individual investors from their daily performance (2018)</p>
Individualized mental fatigue does not impact neuromuscular function and exercise performance
<p>Previous work has shown that mental fatigue may have negative consequences on cognitive or physical performance, although recent reports question this previous empirical evidence. Here, we investigate the critical role of inter-individual differences in susceptibility to develop mental fatigue by measuring neurophysiological and physical responses to an individualized mental fatigue task. We expected mental load to alter both subjective, i.e., increased subjective perception of fatigue, and objective markers of fatigue, i.e., impaired knee extensor neuromuscular function, impaired corticospinal excitability and reduced cerebral oxygenation. Even though all participants performed a similar mental effort, their performance in a subsequent exercise did not differ. Furthermore, even if there was an elevated subjective feeling of mental fatigue, none of the neurophysiological parameters were affected. The study provides new insights into an issue that has grown in popularity in recent years without questioning individual differences and which has taken for granted the detrimental effect of acute mental fatigue on performance.</p>
Data from: A high-performance brain-computer interface for finger decoding and quadcopter game control in an individual with paralysis
Open the record for dataset details and reuse information.
Data from: Evaluating the foraging performance of individual honey bees in different environments with automated field RFID systems
Open the record for dataset details and reuse information.
Data from: Along with intraspecific functional trait variation, individual performance is key to resolving community assembly processes
<ol> <li>Species contributing high proportions to community biomass strongly influence ecosystem processes within the community. Studies have shown that dominant species may serve as nurse plants, helping to ensure biomass stability of the subordinate species under stress conditions. The question is widely debated as to whether either niche differentiation or neutral processes drive the net outcome of plant interactions within a subordinate plant community. To answer this question, requires precise estimates of individual variation in functional traits and performance.</li> <li>In a five-year mesocosm experiment, the functional responses of a subordinate plant community to the removal of the dominant species were evaluated across two drought-stress scenarios. Small scale (i.e., large pots) wetland communities were constructed comprising one dominant species (Carex elata) and three subordinate species. Removal of the dominant species allowed evaluation of the net effects of drought and interspecific interactions. We estimated the functional divergences for three traits (specific leaf area, leaf dry matter content and height growth allocation) and compared these with performance differences quantified individually. This enabled distinctions to be made between deterministic (i.e., niche differentiation) and neutral processes driving the drought response of the subordinate community.</li> <li>We showed that the dominant species decreased relative performance differences within the subordinate plant community under conditions of permanent drought stress. These changes were associated with the convergence of traits related to resource acquisition and growth. The dominant species equalised species performance differences by supressing relatively drought-tolerant species with low competitive ability and by supporting the less drought-tolerant species with relatively high competitive ability. Meanwhile, under conditions of interannual drought, the subordinate species likely coexisted due to differentiation in resource-use strategies and the interaction with the dominant species.</li> <li>Inclusion of individual variation in performance with a functional trait approach provides valuable insights into the processes structuring plant communities. Ours is the first study to provide evidence that subordinate species exposed to drought may coexist via neutral processes arising from their interactions with the dominant species, leading to functional convergence of traits associated with the trade-off between stress tolerance and competitive ability.</li> </ol>
Colorful traits in avian females, individual condition, reproductive performance, and male mate preferences: A meta-analytic approach
<p>Colorful ornaments in females are suggested to have evolved and be maintained by sexual selection. Although several studies have evaluated this idea evidence is still equivocal. Results from empirical studies have been compilated in reviews, but quantitative analyses have seldom been performed. Here, using a meta-analytic approach, we show that evidence from empirical studies conducted in birds, supports the ideas that colorful female ornaments are positively associated with individual condition, reproductive performance, and male-mate preferences. Hence, females' colorful traits, in birds, likely evolved and are maintained by sexual selection.</p>
Data from: Luck in food-finding affects individual performance and population trajectories
Energy harvesting by animals is important because it provides the power needed for all metabolic processes. Beyond this, efficient food-finding enhances individual fitness [1] and population viability [2], although rates of energy accumulation are affected by the environment and food distribution. Typically, differences between individuals in the rate of food acquisition are attributed to varying competencies [3] even though food encounter rates are known to be probabilistic [4]. We used animal-attached technology to quantify food intake in four disparate free-living vertebrates (condors, cheetahs, penguins and sheep) and found that inter-individual variability depended critically on the probability of food encounter. We modelled this to reveal that animals taking rarer food, such as apex predators and scavengers, are particularly susceptible to breeding failure because this variability results in larger proportions of the population failing to accrue the necessary resources for their young before they starve, and because even small changes in food abundance can affect this variability disproportionately. A test of our model on wild animals indicated why Magellanic penguins have a stable population while the congeneric African penguin population has declined for decades. We suggest that such models predicting probabilistic ruin can help predict the fortunes of species operating under globally changing conditions.
Data for: Genetic and context-specific effects on individual inhibitory control performance in the guppy (Poecilia reticulata)
<p>Among-individual variation in cognitive traits, widely assumed to have evolved under adaptive processes, is increasingly being demonstrated across animal taxa. As variation among individuals is required for natural selection, characterising individual differences and their heritability is important to understand how cognitive traits evolve. Here we use a quantitative genetic study of wild-type guppies repeatedly exposed to a 'detour task' to test for genetic variance in the cognitive trait of inhibitory control. We also test for genotype-by-environment interactions (GxE) by testing related fish under alternative experimental treatments (transparent vs. semi-transparent barrier in the detour-task). We find among-individual variation in detour task performance, consistent with differences in inhibitory control. However, analysis of GxE reveals that heritable factors only contribute to performance variation in one treatment. This suggests that the adaptive evolutionary potential of inhibitory control (and/or other latent variables contributing to task performance) may be highly sensitive to environmental conditions. The presence of GxE also implies that the plastic response of detour task performance to treatment environment is genetically variable. Our results are consistent with a scenario where variation in individual inhibitory control stems from complex interactions between heritable and plastic components.</p>
Behavioral flexibility in solitary foraging ants: how experience, colony size and food distribution shape individual and collective performance
<p>To deal with the unpredictability of available food resources, animals must adjust their behavior to optimize foraging efficiency. Various mechanisms can influence an individual’s food acquisition behaviour, and thus our knowledge of their combined impact on foraging efficiency remains limited. In this study, we conducted laboratory experiments with seven colonies of the solitary foraging ant Dinoponera quadriceps. Foragers were individually observed in semi-controlled experiments where food was offered in aggregated or dispersed distributions. During the experiments, individual participation was voluntary (i.e. ants were free to enter or not the experimental arena), giving us an opportunity to assess internal processes such as motivation. Besides, behavioral traits such as foraging activity, exploration of food patches, and performance were recorded across repeated trials. We found that solitary foragers of D. quadriceps were highly efficient (retrieving food in 77.38% of the trips), especially when exploiting aggregated and abundant food resources. However, individual foraging success declined when more conspecific foragers were present and with longer foraging experience. Foragers increased their exploration levels in environments with larger numbers of dispersed prey items. Individual foraging activity was higher with more experience and in smaller colonies with fewer foragers. Furthermore, foragers and colonies exhibited low but consistent differences in levels of activity, exploration, and success rates. These findings provide a comprehensive view of how different factors combine to give rise to complex behaviors such as foraging. Additionally, they emphasize the importance of individual traits for effective task performance within social groups, an understudied topic.</p>
Linking Problem Landscape Features with the Performance of Individual CMA-ES Modules - Data
<p>This repository contains the performance data used in the paper "Linking Problem Landscape Features with the Performance of Individual CMA-ES Modules".</p> <p>The configurations run are in 'dt_run_confs.csv', and each other csv-file corresponds the the AUC values of one of these configurations.</p> <p>The script used to generate the full performance data is included in 'generate.py', and the processing using IOHanalyzer is shown in 'script.R' </p>
Linking individual and species-level leaf traits with ontogenetic development stage to explain tree performance under competition and environmental contexts
<p><span>To verify how species traits and individual traits link ontogenetic size, external biotic and abiotic factors to influence tree performance. In a temperate natural forest in northeastern China, we measured dynamic performance, size, as well as competition, topography, and soil variables as biotic and abiotic variables for all 1320 trees of 17 species in 62 monitoring plots from 2010-2020. For each individual tree, we also measured five typical functional traits representing leaf size and elemental content: leaf area, specific leaf area, leaf dry matter content, leaf nitrogen content, and leaf carbon : nitrogen ratios. These traits are not only strongly associated with performance, but trade-offs between traits have previously been shown to express plant acquisitive-conservative strategy characteristics. Reconceptualized based on previous understanding of trait-based approach (Fig. 1). We first tested the direct explanatory effects of species traits and individual traits on performance in multifactorial contexts.</span> <span>We first tested the direct explanatory effects of species traits and individual traits on performance in multifactorial contexts. Subsequently, we analyzed the moderating and mediating effects of these two levels of traits in explaining ontogenetic size, external competition, and environmental influences on performance. The following three questions were posed in response to the results:</span></p> <p><em><span>QI: Do species and individual traits differ in directly explaining performance in a multifactor context that includes ontogenetic size, external biotic and abiotic factors?</span></em></p> <p><em><span>QII: How species and individual traits explain the effect of ontogenetic size on performance</span> </em><em><span>by moderating and mediating effects.</span></em></p> <p><em><span>QIII: Can traits at the species and individual level influence competition- and environment-performance relationships</span> </em><em><span>through trait-based approaches? Does ontogenetic size work jointly with traits at different levels in this process?</span></em></p>
Assemblies of two Greenland wolf individuals and one Flying lemur performed by LJA,
<p>These assemblies were generated as a part of analysis performed in paper Zhu et al (2024) titled "Assessing Assembly Errors in Immunoglobulin Loci: A Comprehensive Evaluation of Long-read Genome Assemblies Across Vertebrates"</p>
Brain signal variability within individually defined alpha frequency range as a marker of cognitive performance
<p><strong>General description</strong></p> <p>Eight subjects with severe acquired brain injury and fourteen healthy participants took part in the study. EEG was recorded at 19 international standard 10-20 system locations with a sampling frequency of 256 Hz, using an ear-linked reference and the <em>Fpz</em> location as ground.</p> <p>For all participants three-minute baseline recordings were obtained, one with eyes open and one with eyes closed. Both groups participated in the same sustained attention task while EEG data was being collected. Healthy participants underwent 10 blocks of 225 trials while ABI patients were given 7 blocks of 225 trials.</p> <p> </p> <p><strong>Content of the zip files uploaded here</strong></p> <p>Each zip file contains matlab files with raw EEG data plus a channel that contains information of the triggers used in the sustained attention task. In addition, log files contain the latency of the experimental events and responses.</p> <p> </p> <p><strong>Description of the task</strong></p> <p>The Continuous Temporal Expectancy Task (CTET), developed by O’Connell <em>et al.</em> (2009), is a computerized task that measures sustained attention. Participants are required to notice and respond with a click of the mouse when an alternating pattern (Fig. 1) is randomly displayed for a longer interval than the regular interval (800ms). Participants practiced the experiment initially to ensure they obtained 100% accuracy at the end of the training trials. Longer target duration should be easily detected during the training block, but challenging when performed over an extended period of time. The healthy group detected the target difference at 1120ms (duration 40% longer than the standard), whereas the ABI group detected a difference at 1200ms latency (duration 50% longer than the standard). The hand that responded to the longer stimulus with a mouse-click was counterbalanced in each block.</p>
Colorful traits in female birds relate to individual condition, reproductive performance, and male mate preferences: A meta-analytic approach dataset
<p>Colorful traits in females are suggested to have evolved and be maintained by sexual selection. Although several studies have evaluated this idea, support is still equivocal. <span><span>Evidence has been compiled in reviews, and a handful of quantitative synthesis have explored evidence of the link between condition and specific color traits in males and females. However, understanding the potential function of females' colorful traits in sexual communication has not been the primary focus of any of those previous studies</span></span><span>. </span>Here, using a meta-analytic approach, we find that evidence from empirical studies in birds supports the idea that colorful female ornaments are positively associated with residual mass and immune response, clutch size, and male-mate preferences. Hence, colorful traits in female birds likely evolved and are maintained by sexual selection.</p>
Individual variation in feeding performance and kinematics in the canary
<ol> <li><span>In granivorous songbirds, feeding is a complex process as seeds need to be dehusked before they can be consumed, making the feeding act a biomechanically challenging endeavour. However, most previous research has focused on how beak morphology affects feeding performance, while the influences of beak kinematics remain largely unknown. </span></li> <li><span>In this study, we hence investigated at the individual level how feeding performance (i.e. seed processing time and success rate) relates to both beak kinematics (i.e. beak tip speed, acceleration, frequency) and skill (i.e. seed handling tactics and cracking techniques) in the Canary (<em>Serinus</em> <em>canaria</em>). To do so, high-speed videos during feeding were recorded and subjected to automated tracking of beak tip movements.</span></li> <li><span>Better skills, i.e. accurate positioning of the seed for being split in half, reduced total seed handling time compared to more random positioning and crushing the husk into multiple, scattering fragments. Surprisingly, individual variation in beak speed, acceleration, or frequency generally did not relate to differences in performance. </span></li> <li><span>Thus, our data suggests that seed positioning precision, and hence the control of coordinated beak and tongue movement, is critical to minimize feeding durations in songbirds. Further studies are needed to explore whether this develops via a positive feedback between behaviour, learning and increased efficiency or if it relates to intrinsic differences.</span></li> </ol>
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.