Find research datasets worth reusing

Dataset: Core excitations and ionizations of uranyl in Cs2UO2Cl4 from relativistic embedded damped response time-dependent density functional theory and equation of motion coupled cluster calculations

This dataset collects the unprocessed (= outputs from calculations) results discussed in the paper titled "Core excitations and ionizations of uranyl in  Cs2UO2Cl4  from relativistic embedded damped response time-dependent density functional theory and equation of motion coupled cluster calculations", by Wilken Aldair Misael and Andre Severo Pereira Gomes. It also contains the figures used in the manuscript.

Experimental heatwaves and warming induce distinctive community responses through their interactions with a novel species

This repository provides the data for the manuscript "experimental heatwaves and warming induce distinctive community responses through their interactions with a novel species" As the climate warms, species shift their distributions at different rates, re-organising ecological communities. The resulting novel interactions will shape the local community’s response to ongoing climate change. The distinction between extreme events and a rising mean temperature in driving range expansion of the neighbouring species has not been examined empirically, nor has the resulting ecological impact propagating through multi-trophic networks been addressed. In this study, we recreated a high-elevation host-parasitoid community comprising Drosophila species and their associated parasitoid species from the Australian Wet Tropics, and subjected them to either heatwaves or warming in combination with the introduction of a low-elevation-specific Drosophila species. This dataset contains three groups of measurements: 1. Single-generation reproductive success of each species at various sampling times (about every 3 weeks) throughout the initiation and maintenance of the community. 2. Population size of each species before the community was terminated. 3. One-day reproductive success of each species before, during, and after the last heatwave event.

opencc-by-4.0Sep 2023View details →

An Exploratory Study on the Effect of Virtual Environments on Cognitive Performances and Psychophysiological Responses

This is the dataset of the following study:  Frigione, I., Massetti, G., Girondini, M., Etzi, R., Scurati, G. W., Ferrise, F., Chirico, A., Gaggioli, A., & Gallace, A. (2022). An Exploratory Study on the Effect of Virtual Environments on Cognitive Performances and Psychophysiological Responses. Cyberpsychology, behavior and social networking, 25(10), 666–671. https://doi.org/10.1089/cyber.2021.0162 Abstract: Research shows that reduced exposure to natural contexts is associated with an increase in psychophysical disorders. Recent evidence suggests that even a brief experience in natural scenarios can positively affect people's health and well-being. However, natural contexts are not always easily accessible. This study investigates the effects of natural and indoor virtual environments (VREs) on psychophysiological and cognitive responses. Following a within-subject design, 34 healthy participants were exposed to two VREs (i.e., a forest and a living room) in a counterbalanced order through a head-mounted display (Oculus Rift). Participants were asked to explore the scenarios and execute a modified version of the Paced Auditory Serial Addition Test. Physiological parameters (heart rate, skin conductance level [SCL], and respiration rate) were recorded during the whole session. After the exposure to VREs, participants filled a set of visual analog scales to rate their subjective experience of presence, relaxation, and stress. Participants reported a higher perceived sense of relaxation in the virtual forest. Moreover, their SCLs were significantly higher in this environment, showing that the forest elicited higher physiological arousal than the living room. Furthermore, their SCLs were significantly higher during the attentional task in the virtual living room. The results suggest that a natural virtual environment can make people feel more relaxed and physiologically engaged than an indoor scenario. The latter instead can be linked to a performing venue, as reported for real contexts. However, these changes were not related to modulations of attentional performance.

Dataset related to the responses of eggplant plants to Bemisia Tabaci whitefly in presence of one of its natural enemies, the Macrolophus pygmaeus plant bug

This dataset assesses the response of eggplant plants to 3 conditions: noninfested control plants, plants infested by Bemisia tabaci whitefly, and plants infested by Bemisia tabaci where Macrolophus pygmaeus plant bug was also released. The data of the various parameters relating to the responses of the different eggplant plants to the three tested conditions were analyzed using a one-way ANOVA. Where significant differences were detected, the means were separated by Tukey’s HSD test (p < 0.05). Statistical analysis was carried out using the program Statistica (StatSoft, TIBCO Software Inc., Tulsa, OK, USA). The provided dataset was used in the investigation of whether the Macrolophus pygmaeus (Hemiptera: Miridae) plant bug can mitigate the damage caused to plants by the Bemisia tabaci whitefly (Hemiptera: Aleyrodidae). A discussion and interpretation of the data, as well as subsequent results, is provided in the scientific publication <a href="https://zenodo.org/record/7660447#.Y_Soh3aZObg">"Can Macrolophus pygmaeus (Hemiptera: Miridae) Mitigate the Damage Caused to Plants by Bemisia tabaci (Hemiptera: Aleyrodidae)?"</a>, published in the <a href="https://www.mdpi.com/2075-4450/14/2/164">Insects</a> journal.  This research was conducted within the VIRTIGATION project, which is part of the EU Open Research Data pilot. This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 101000570.

Data for 'Thermal regimes of groundwater- and lake-fed headwater streams differ in their response to climate variability'

This dataset contains seasonal and annual mean spot stream temperatures for the six groundwater-fed and seven lake-fed streams at the Turkey Lakes Watershed. We have also included seasonal and annual scale hydroclimatic variables (air temperature, solar radiation, discharge, precipitation, ice on/off dates, and April 1st SWE). The Turkey Lakes Watershed is approximately 65 km northwest of Sault Ste. Marie, Ontario, Canada.  Manual spot stream temperature measurements were made by field technicians visiting the catchment outlets as part of a routine water quality monitoring program at the TLW. The stream temperature data record extends from 1983 through 2018. The stream temperature record for stream 013 is 1986-2018. Hydroclimatic data is also 1983-2018, with the exception of lake ice data which ended in 2015. See the methods section of the associated publication for more details.

Modelling the response of mangroves and saltmarshes to sea-level rise: model development and validation

Data used to parameterise and calibrate a model (IWEM0D) of the response of coastal wetlands to sea-level rise. Model parameterisation with core data from Westernport Bay, Victoria, Australia. IWEM0D (Intertidal Wetland Evolution Model - 0D) simulates how mangrove forests and saltmarsh wetlands respond to sea-level rise. The model framework, as detailed in Rogers et al. (in review), treats surface elevation change over time as a function of: <ul> <li>Present elevation <code>E</code></li> <li>Inorganic/mineral matter accumulation rate <code>MAR</code></li> <li>Organic matter addition rate <code>OAR</code> for mangroves and saltmarsh</li> <li>Autocompaction <code>AC</code></li> </ul> Specifically, incremental change in surface elevation <code>E</code> over time <code>t</code> is modelled as: <code>E[t+1] = E[t] + MAR[t] + OAR[t] - AC[t]</code>

opencc-by-4.0Sep 2022View details →

Gut microbiota inter-species interactions shape the response of Clostridioides difficile to clinically relevant antibiotics

In the human gut, the growth of Clostridioides difficile is impacted by a complex web of inter-species interactions with members of human gut microbiota. We investigate the contribution of inter-species interactions on the antibiotic response of C. difficile to clinically relevant antibiotics using bottom-up assembly of human gut communities. We discover two classes of microbial interactions that alter C. difficile’s antibiotic susceptibility: interactions resulting in increased C. diffiicle tolerance at high antibiotic concentrations (rare) and interactions resulting in C. difficile growth enhancement at low antibiotic concentrations (common). Based on genome-wide transcriptional profiling data, we demonstrate that metal sequestration due to hydrogen sulfide production by the prevalent gut species Desulfovibrio piger increases metronidazole tolerance of C. difficile. Competition with species that display higher sensitivity to the antibiotic than C. difficile leads to enhanced growth of C. difficile at low antibiotic concentrations. A dynamic computational model identifies the ecological design principles driving this effect. Our results provide a deeper understanding of ecological and molecular principles shaping C. difficile’s response to antibiotics, which could inform therapeutic interventions.In the human gut, the growth of Clostridioides difficile is impacted by a complex web of inter-species interactions with members of human gut microbiota. We investigate the contribution of inter-species interactions on the antibiotic response of C. difficile to clinically relevant antibiotics using bottom-up assembly of human gut communities. We discover two classes of microbial interactions that alter C. difficile’s antibiotic susceptibility: interactions resulting in increased C. diffiicle tolerance at high antibiotic concentrations (rare) and interactions resulting in C. difficile growth enhancement at low antibiotic concentrations (common). Based on genome-wide transcriptional profiling data, we demonstrate that metal sequestration due to hydrogen sulfide production by the prevalent gut species Desulfovibrio piger increases metronidazole tolerance of C. difficile. Competition with species that display higher sensitivity to the antibiotic than C. difficile leads to enhanced growth of C. difficile at low antibiotic concentrations. A dynamic computational model identifies the ecological design principles driving this effect. Our results provide a deeper understanding of ecological and molecular principles shaping C. difficile’s response to antibiotics, which could inform therapeutic interventions.

opencc-by-4.0Jan 2023View details →

Underlying data of Impact of shipping temperature on cell viability and T cell responses to bacterial antigens

Abstract Background: Interferon-γ (IFN-γ) secretion by T cells is a key correlate of immune protection against many pathogens including tuberculosis and the neglected tropical disease melioidosis. Clinical studies in tropical regions of immune responses to pathogens and vaccine monitoring studies require the collection of samples in resource-limited rural areas and subsequent shipment to central laboratories for downstream assays and long-term storage. Here, we studied the impact of two different shipping temperatures on the viability, composition and function of peripheral blood mononuclear cells (PBMC) using multi-colour flow cytometry and IFN-g enzyme-linked immunospot assay (IFN-g ELISpot), in order to provide guidance on sample shipment conditions for future clinical studies. Methods: Paired peripheral blood mononuclear cell (PBMC) samples from recovered melioidosis patients were stored in liquid nitrogen (-196°C) and then shipped from Bangkok, Thailand to Oxford, UK at either -80°C (dry ice) or -196°C (dry shipper).  After thawing, cell viability and composition were assessed by flow cytometry and antigen specific responses to Burkholderia pseudomallei (BP) were measured using IFN-g ELISpot. Results: We observed modest lowering of viability in the majority of samples and a reduction in IFN-g responses to BP which correlated to a decrease of monocytes and NK cells in samples shipped at -80°C compared to -196°C. Despite being lower in magnitude antigen-specific responses remained detectable in the majority of samples. Conclusions:Here we demonstrate that shipment of cryopreserved PBMC at -196°C has a benefit on cell viability, recovery and T cell responses to bacterial antigens, although useful information can still be obtained from samples shipped at -80°C, thus providing important guidance for sample management in future clinical trials.

opencc-zeroMar 2023View details →

The practice and promise of temporal genomics for measuring evolutionary responses to global change

Understanding the evolutionary consequences of anthropogenic change is imperative for estimating long-term species resilience. While contemporary genomic data can provide us with important insights into recent demographicic histories, investigating past change using present genomic data alone has limitations. In comparison, temporal genomics studies, defined herein as those that incorporate time series genomic data, leverage museum collections and repeated field sampling to directly examine evolutionary change. As temporal genomics is applied to more systems, species, and questions, best practices can be helpful guides to make the most efficient use of limited resources. Here, we conduct a systematic literature review to synthesize the effects of temporal genomics methodology on our ability to detect evolutionary changes. We focus on studies investigating recent change within the past 200 years, highlighting evolutionary processes that have occurred during the past two centuries of accelerated anthropogenic pressure. We first identify the most frequently studied taxa, systems, questions, and drivers, before highlighting overlooked areas where further temporal genomics studies may be particularly enlightening. Then, we provide guidelines for future study and sample designs while identifying key considerations that may influence statistical and analytical power. Our aim is to provide recommendations to a broad array of researchers interested in using temporal genomics in their work.

opencc-by-4.0Sep 2022View details →

EEG Dataset for 'Decoding of selective attention to continuous speech from the human auditory brainstem response' and 'Neural Speech Tracking in the Theta and in the Delta Frequency Band Differentially Encode Clarity and Comprehension of Speech in Noise'.

The repository contains the unprocessed EEG data recorded for the publications [1, 2]. For convenience, the onsets of the EEG data provided here are time-aligned with the onsets of the audio books in the 'audiobooks' folder, and the EEG data are provided in HDF5 format. Please refer to the original version of this dataset for more details. More details, as well as the original data files, are available at the original repository <a href="https://doi.org/10.5281/zenodo.7086209">here</a>. Examples of using these data (preprocessing, fitting linear models) can be found <a href="https://github.com/Mike-boop/trf-examples">here</a>. The English conditions (clean, lb, mb, hb, fM, fW) comprised a single recording session. The Dutch conditions (cleanDutch, lbDutch, mbDutch, hbDutch) comprised a separate recording session. You see which participants took part in each session in session_info.json. Please note some details about the stimulus presentation for the various listening conditions: <ul> <li>English speech-in-babble-noise (lb, mb, hb): babble noise was played by itself for one second before the audiobook track began. The babble noise was also played for one second after the audiobook track ended. Therefore, you should discard the first second and the last second from these trial during your analysis.</li> <li>Dutch speech-in-babble-noise (lbDutch, mbDutch, hbDutch): the story (narrated in Dutch) was played by itself for one second before the babble noise track began. Then, the babble noise was increased linearly in amplitude for one second. Therefore, you should discard the first two seconds from these trials during your analysis.</li> <li>Dutch in quiet, and Dutch-in-babble-noise (cleanDutch, lbDutch, mbDutch, hbDutch): some English sentences were embedded in the Dutch narratives in order to encourage attention. You should crop these from your analysis. The onsets and offsets of the English sentences (in samples, at 44100Hz) are provided in the audiobooks/*Dutch/english_onsets_info.json files.</li> <li>Competing-speakers conditions (fM, fW): sometimes the attended track is longer than the unattended track, or vice-versa. The onsets of both tracks are aligned. You should crop the trial to the length of the shortest track for your analysis.</li> </ul> If you use this data, please cite the original publications, as well as this repository [1,2,3]. [1] Etard O, Kegler M, Braiman C, Forte A E and Reichenbach T. “Decoding of selective attention to continuous speech from the human auditory brainstem response” 2019. NeuroImage 200 1–11 [2] Etard O and Reichenbach T. “Neural speech tracking in the theta and in the delta frequency band differentially encode clarity and comprehension of speech in noise” 2019. J. Neurosci. 39 5750–9 [3] Etard O and Reichenbach T. "EEG Dataset for 'Decoding of selective attention to continuous speech from the human auditory brainstem response' and 'Neural Speech Tracking in the Theta and in the Delta Frequency Band Differentially Encode Clarity and Comprehension of Speech in Noise". Doi: 10.5281/zenodo.7086208

opencc-zeroMar 2023View details →

Data from: Changes in movement characteristics in response to private and social information acquisition of socially foraging fish

To overcome the cost of competition resulting from foraging socially, individuals may balance their use of private (i.e. acquired from personal sampling) and social (i.e. acquired by watching other individuals) information to adjust their foraging strategy accordingly. Reliability of private information about environmental characteristics, such as the spatial distribution of prey, is thus likely to affect individual movement and social interactions. We aimed to investigate how movement characteristics of foraging individuals changed as they acquired reliable information about the spatial occurrence of prey in a foraging context. We allowed guppies (Poecilia reticulata) to develop the reliability of their private knowledge about prey spatial occurrence by repeatedly testing shoals in a foraging task under three experimental distributions of prey: 1) aggregated prey forming three patches located in fixed locations, 2) scattered distribution of prey with random locations, or 3) no prey (used as control). Using individual time series of spatial coordinates, we computed a suite of movement variables reflecting search effort, social proximity and locomotion characteristics during foraging, to examine changes occurring over repeated trials. Over time, individuals foraging on either scattered or aggregated prey travelled greater distances, showed an increasing distance to their closest neighbour and became more stochastic in their acceleration profile, compared to control individuals. We found that behaviour changed as private information increased over time, with a behavioural shift and an increase of collective foraging efficiency occurring on the third testing day. Social proximity was the major predictor of foraging success in the absence of prior foraging information, while search effort became the most important predictors of foraging success as information increased. In conclusion, we show that individual movement patterns changed as they acquired private information. Contrary to our predictions, the spatial distribution of prey did not affect any of the movement variables of interest.

opencc-by-4.0Mar 2023View details →

Data accompanying Using Neural Networks to Learn the Forced Response of the Jet-Stream to Tropospheric Temperature Tendencies

Data used to train and evaluate a CNN. Details about data and the preprocessing can be found in the citation given below Charlotte Connolly, Elizabeth A. Barnes, Pedram Hassanzadeh, and Mike Pritchard: Using Neural Networks to Learn the Jet Stream Forced Response from Natural Variability, accepted to Artificial Intelligence for the Earth Systems 03/2023. Preprint available at <a href="https://arxiv.org/abs/2301.00496">https://arxiv.org/abs/2301.00496</a>. Code found at https://doi.org/10.5281/zenodo.7796266.

opencc-by-4.0Apr 2023View details →

SARS-CoV-2 Omicron Boosting Induces De Novo B Cell Response in Humans

These are the processed BCR repertoire and transcriptomics data described in <a href="https://doi.org/10.1038/s41586-023-06025-4">Alsoussi & Malladi et al., Nature, 2023</a>. The raw sequencing data new to this study are available on SRA under BioProject <a href="https://www.ncbi.nlm.nih.gov/sra/?term=PRJNA800176">PRJNA800176</a>. This study also used BCR repertoire data from <a href="https://doi.org/10.1038/s41586-021-03738-2">Turner & O'Halloran et al., Nature, 2021</a> (<a href="https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA731610">PRJNA731610</a>), <a href="https://doi.org/10.1016/j.immuni.2021.08.013">Schmitz, Turner & Liu et al., Immunity, 2021</a> (<a href="https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA741267">PRJNA741267</a>), and <a href="https://doi.org/10.1038/s41586-022-04527-1">Kim & Zhou et al., Nature, 2022</a> (<a href="https://www.ncbi.nlm.nih.gov/bioproject/PRJNA777934/">PRJNA777934</a>).   Code Code along with Docker containers for reproducing the NGS data-based figures and analyses in the published paper can be <a href="https://github.com/julianqz/wustl_published/tree/main/nature_2023">found on GitHub</a>.   Metadata File: WU382_alsoussi_et_al_nature_2023_meta.tsv.gz Notes: <ul> <li>181 samples in total, including: <ul> <li>78 new</li> <li>90 from <a href="https://doi.org/10.1038/s41586-022-04527-1">Kim & Zhou et al., Nature, 2022</a></li> <li>8 from <a href="https://doi.org/10.1016/j.immuni.2021.08.013">Schmitz, Turner & Liu et al., Immunity, 2021</a></li> <li>5 from <a href="https://doi.org/10.1038/s41586-021-03738-2">Turner & O'Halloran et al., Nature, 2021</a></li> </ul> </li> <li>Participant IDs: 6 participants who were in previous studies and who continued in the new study were referenced by new participant IDs. Correspondence with previous participant IDs is as follows: <ul> <li>382-01 = 368-22</li> <li>382-02 = 368-20</li> <li>382-07 = 368-02a</li> <li>382-08 = 368-04</li> <li>382-13 = 368-01a</li> <li>382-15 = 368-10</li> </ul> </li> <li>Sample collection time was originally recorded in days in the `timepoint` column. Values in parentheses indicate variations in which the BCR data was coded. Timepoints were mainly referenced in weeks in the manuscript, as shown in the `timepoint_ms` column. </li> <li>Pre-3rd dose ("pre-boost") samples were coded `b0` in the `booster_num` column; post-3rd dose ("post-boost") samples were coded `b1`.</li> <li>The `booster_type` column records the 3rd dose ("booster") variant. <ul> <li>`regular` = mRNA-1273 (WA1/2020)</li> <li>`beta_delta` = mRNA-1273.213 (Beta & Delta)</li> <li>`v1.1.529` = mRNA-1273.529 (Omicron)</li> </ul> </li> <li>382-02/07/08 received mRNA-1273; 382-01/13/15 received mRNA-1273.213; 382-53/54/55 received mRNA-1273.529.</li> <li>The `seq_type` column indicates the platform from which sequences originated. <ul> <li>`bulk` = bulk BCR sequencing</li> <li>`tgx` = 10x Genomics single-cell VDJ + 5' gene expression</li> <li>`mab`, `mab_1`, `mab_2`: single-cell sorted mAb synthesis. The suffixes were purely for the convenience of distinguishing originating studies.</li> </ul> </li> </ul> Abbreviations: <ul> <li>LN = lymph node</li> <li>BM = bone marrow</li> <li>PB = plasmablast</li> <li>GC = germinal centre</li> <li>LLPC = long-lived plasma cell</li> <li>NS = no sorting</li> <li>mAb = monoclonal antibody</li> </ul>   [Beta & Delta booster] Processed BCR data - heavy chains File: WU382_alsoussi_et_al_nature_2023_betaDelta_bcr_heavy.tsv.gz Analysis was based on heavy chain-based clonal inference. Notes on columns: The columns largely follow the <a href="https://changeo.readthedocs.io/en/stable/standard.html">AIRR-C Rearrangement format</a>. The main deviation is that CDR3s were used, as opposed to IMGT-defined "junctions". Nonetheless, junction-related columns are included here as some repositories such as <a href="https://gateway.ireceptor.org/login">iReceptor</a> use these. Non-standard columns are noted below. <ul> <li>`cell_id`:  Only sequences from single-cell samples and synthesized mAbs have cell IDs. 10x sequences follow the format `[donor]_[sample]@[id]`. `NA` for bulk sequences.</li> <li>`sequence_id`: Sequence IDs follow the format `[donor]_[sample]@[id]`.</li> <li>`v_call_genotyped`: V gene annotation reassigned after individualized genotyping by <a href="https://tigger.readthedocs.io/en/stable/">TIgGER</a>.</li> <li>`germline_[vdj]_call`: Clonal consensus germline calls after corresponding clonal consensus sequences were reconstructed via <a href="https://changeo.readthedocs.io/en/stable/methods/germlines.html">`CreateGermlines.py --cloned` from Change-O</a>.</li> <li>`collapse_count`: Number of duplicate IMGT-aligned V(D)J sequences that were collapsed by <a href="https://alakazam.readthedocs.io/en/stable/topics/collapseDuplicates/">`alakazam::collapseDuplicates`</a>.</li> <li>`timepoint`: Timepoints follow the format `b[01]_d*`, where `b0` and `b1` correspond to pre-3rd dose ("pre-boost") and post-3rd dose ("post-boost") respectively, and `d*` indicates the timepoint in days. There's one exception: `b0_m6or9` for pre-3rd dose d201 or d280 (m6or9 = 6 or 9 months).</li> <li>`gex_anno`: Cell type identity annotation based on transcriptomic profiles. Mapped from `anno_leiden_0.35` from WU382_alsoussi_et_al_nature_2023_betaDelta_gex_b_cells.h5ad.</li> <li>`compartment`: B cell compartment</li> <li>`clone_id`: B cell clonal lineage IDs follow the format `[donor]@[id]`.</li> <li>`s_pos_clone`: `TRUE` if a sequence belonged to a B cell clone that was designated as S-binding by virtue of containing one of the recombinant mAbs that tested positive via ELISA.</li> <li>`expressed_id`: mAb IDs of mAbs from <a href="https://doi.org/10.1038/s41586-021-03738-2">Turner & O'Halloran et al., Nature, 2021</a> and the current study; and of recombinant mAbs generated based on 10x BCRs from <a href="https://doi.org/10.1038/s41586-022-04527-1">Kim & Zhou et al., Nature, 2022</a>. `NA` for everything else.</li> <li>`elisa`: ELISA results for binding of recombinant mAbs to SARS-CoV-2 S. `TRUE` if positive (WA1+); `FALSE` if negaive; `NA` if not tested or test failed.</li> <li>`nuc_RS_19_312`: number of replacement and silent mutations between IMGT-numbered nucleotide positions 19-312 along IGHV sequences, calculated by <a href="https://shazam.readthedocs.io/en/stable/topics/calcObservedMutations/">`shazam::calcObservedMutations`</a>.</li> <li>`nuc_denom_19_312`: number of informative nucleotide positions for counting mutations, excluding non-A/T/G/C positions (such as "N", "-", ".").</li> <li>`nuc_RS_freq_19_312`: nucleotide-level mutation frequency (= nuc_RS_19_312 / nuc_denom_19_312).</li> </ul>   [Beta & Delta booster] Processed BCR data - light chains File: WU382_alsoussi_et_al_nature_2023_betaDelta_bcr_light.tsv.gz Light chains were not used for heavy chain-based clonal inference or analysis.   [Beta & Delta booster] Processed transcriptomics data Files:  <ul> <li>WU382_alsoussi_et_al_nature_2023_betaDelta_gex_all_cells.h5ad</li> <li>WU382_alsoussi_et_al_nature_2023_betaDelta_gex_b_cells.h5ad</li> <li>WU382_alsoussi_et_al_nature_2023_betaDelta_gex_b_cell_umap.tsv.gz</li> </ul> Notes on the `h5ad` files: <ul> <li>These files can be imported into <a href="https://scanpy.readthedocs.io/en/stable/index.html">Scanpy</a> as an <a href="https://scanpy.readthedocs.io/en/stable/usage-principles.html#anndata">AnnData object</a>.</li> <li>Each `AnnData` object has 3 `.layers`, each representing a version of the count matrix. <ul> <li>`raw_counts`: Imported from `<a href="https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/6.0/using/aggregate">cellranger aggr</a>` output by `scanpy.read_10x_mtx`.</li> <li>`log_norm`: Log-noramlized expression values outputted by `scanpy.pp.normalize_total` followed by `scanpy.pp.log1p`.</li> <li>`scaled`: The `log_norm` layer scaled to unit variance and zero mean by `scanpy.pp.scale`. </li> </ul> </li> <li>The `gene_name` and `biotype` columns in `.var` were extracted from GENCODE v32 GTF.</li> <li>Columns in `.obs` (each row corresponds to a cell) <ul> <li>`n_feature`: The `n_genes_by_counts` column produced by `scanpy.pp.calculate_qc_metrics`, renamed. The number of genes expressed. This is before subsetting the genes.</li> <li>`n_umi`: The `total_counts` column produced by `scanpy.pp.calculate_qc_metrics`, renamed. The total UMI counts in a cell.</li> <li>`pct_mt`: The `pct_counts_mt` column produced by `scanpy.pp.calculate_qc_metrics`, renamed. The percentage of counts in mitochondrial genes.</li> <li>`n_hkg`: The number of housekeeping genes for which expression was detected.</li> <li>`n_gene_expressed`: The total number of genes for which expression was detected. This is after subsetting the genes.</li> <li>`pre_qc_bcr`: `TRUE` if a cell also had paired BCR data available. Produced by cross-referencing the cellular barcodes in `cell_barcodes.json` outputted by `cellranger vdj`. At this point the BCR data had not gone through the QC process in the BCR processing pipeline (hence `pre_qc`). </li> <li>`leiden_[resolution]`: Cluster assignment by `scanpy.tl.leiden`.</li> <li>`anno_leiden_[resolution]`: Cell type identity annotations based on transcriptomic profiles. This was mapped onto the `gex_anno` column in the processed heavy chain BCR data.</li> </ul> </li> <li>UMAP coordinates can be found in `.obsm["X_umap"]`.</li> <li>`.X` has been set to `None` in order to reduce file size.</li> </ul> Note on the `tsv.gz` file: This file was derived from WU382_alsoussi_et_al_nature_2023_betaDelta_gex_b_cells.h5ad. It contains UMAP coordinates and select attributes of the cells, including their log-normalized expression values of XBP1 (`ln_XBP1`). For analysis and visualization in conjunction with BCR data. In addition, the preprocessed count matrix outputted by `<a href="https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/6.0/using/aggregate">cellranger aggr</a>` is available from <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE227562">GEO under BioProject PRJNA800176</a>.   [Omicron booster] Processed BCR data - heavy chains File: WU382_alsoussi_et_al_nature_2023_omicron_bcr_heavy.tsv.gz Notes on columns: <ul> <li>`elisa`: ELISA results for mAbs, with values being one of `WA1+`, `BA1+WA1-`, or `negative`. `NA` for bulk sequences.</li> <li>`clone_type`: If a sequence was in an S-binding B cell clone (`TRUE` for `s_pos_clone`), its `clone_type` was based on the `elisa` value of the S-binding mAb in that clone -- either `WA1+` or `BA1+WA1-`; otherwise `NA`.</li> </ul>

opencc-by-4.0Apr 2023View details →

National Open Access Monitor Survey: Defining Requirements: Responses Dataset

This dataset contains the response data from the ‘National Open Access Monitor Survey: Defining Requirements’ which was carried out between February 2-28th 2023 under the National Open Access Monitor Project: <a href="https://doi.org/10.5281/zenodo.7588787">https://doi.org/10.5281/zenodo.7588787</a> To note:  <ul> <li>Email addresses have been redacted. </li> <li>Responses have been pseudonymised to the level of stakeholder-group e.g. Contributor 1, Research Funding Organisation #, where requested by the participant in the participant consent form: <a href="https://doi.org/10.5281/zenodo.7589770">https://doi.org/10.5281/zenodo.7589770</a>. </li> <li>Detail within responses by individuals who requested pseudonymisation, which might identify the individual or the organisation has been removed and marked "[redacted]".</li> <li>Responses by individuals who did not provide a signed consent form in advance of contributing to the survey were deleted immediately on receipt, as advised in the survey text: <a href="https://doi.org/10.5281/zenodo.7588787">https://doi.org/10.5281/zenodo.7588787</a>. Such responses are not included in these files.</li> </ul> There are five files within in this dataset: - Results.NationalOpenAccessMonitorSurvey.DefiningRequirements.README - this PDF details the changes made to the raw data, as specified in the bullet points above and a description of the files within the dataset. - Results.NationalOpenAccessMonitorSurvey.DefiningRequirements.Pseudonymised.100323 - this is the original raw data, in csv format, as downloaded from the Online Surveys platform and subsequently pseudonymised and redacted. - NationalOpenAccessMonitor.DefiningRequirements.Contributor3Government1.270223 - this PDF file contains a single pseudonymised stakeholder response to the survey, obtained by the Project Manager by email and not through the Online Surveys platform. - NationalOpenAccessMonitorSurvey.MasterChangeFile.080323 - this is a change file, in csv format, which documents the changes which participants requested to be made to their submissions after they were received and the survey was closed. - Results.NationalOpenAccessMonitorSurvey.DefiningRequirements.Pseudonymised.Updated.100323 -  this is the original raw data, pseudonymised and redacted, with the requested changes implemented. This is the file on which analysis was carried out for the purposes of the <a href="http://doi.org/10.5281/zenodo.7822367">survey outcome report</a> and the resulting National Open Access Monitor tender documents.  ------------------------ The context for the survey files is detailed in the National Open Access Monitor Project Plan: <a href="https://doi.org/10.5281/zenodo.7331431">https://doi.org/10.5281/zenodo.7331431</a> This project is managed by <a href="http://www.irel.ie/">IReL </a>and has received funding from Ireland’s National Open Research Forum under the NORF Open Research Fund. <a href="https://norf.ie/funding/">https://norf.ie/funding/</a> <a href="https://norf.ie/orf-projects-announcement/">https://norf.ie/orf-projects-announcement/</a>

opencc-zeroApr 2023View details →

Herbaceous vegetation responses to experimental fire in savannas and forests depend on biome and climate

Fire-vegetation feedbacks potentially maintain global savanna and forest distributions. Accordingly, vegetation in savanna and forest ecosystems should have differential responses to fire, but fire response data for herbaceous vegetation has yet to be synthesized across biomes. Here, we examined herbaceous vegetation responses to experimental fire at 30 sites spanning four continents. Across a variety of metrics, herbaceous vegetation increased in abundance where fire was applied, with larger responses to fire in wetter and in cooler and/or less seasonal systems. Compared to forests, savannas were associated with a 4.8 (±0.4) times larger difference in burned versus unburned herbaceous vegetation abundance. In particular, grass cover decreased with fire exclusion in savannas, largely via decreases in C4 grass cover, whereas changes in fire frequency had a relatively weak effect on grass cover in forests. These differential responses underscore the importance of fire for maintaining the vegetation structure of savannas and forests.

opencc-by-4.0Apr 2023View details →

Dataset article "Demand-Response Control of Electric Storage Water Heaters Based on Dynamic Electricity Pricing and Comfort Optimization"

"README-SupplementaryMaterial.txt" explains the information gathered in each csv files, and including the DHW consumption profiles generated, the hourly electricity pricing for 2022 (Spain), and the experimental data utilized for the validation of the model.

opencc-zeroDec 2022View details →

Whole blood RNA-seq demonstrates an increased host immune response in individuals with cystic fibrosis who develop nontuberculous mycobacterial pulmonary disease

Background Individuals with cystic fibrosis have an elevated lifetime risk of colonization, infection, and disease caused by nontuberculous mycobacteria. A prior study involving non-cystic fibrosis individuals reported a gene expression signature associated with susceptibility to nontuberculous mycobacteria pulmonary disease (NTM-PD). In this study, we determined whether people living with cystic fibrosis who progress to NTM-PD have a gene expression pattern similar to the one seen in the non-cystic fibrosis population. Methods We evaluated whole blood transcriptomics using bulk RNA-seq in a cohort of cystic fibrosis patients with samples collected closest in timing to the first isolation of nontuberculous mycobacteria. The study population included patients who did (n = 12) and did not (n = 30) develop NTM-PD following the first mycobacterial growth. Progression to NTM-PD was defined by a consensus of two expert clinicians based on reviewing clinical, microbiological, and radiological information. Differential gene expression was determined by DESeq2. Results No differences in demographics or composition of white blood cell populations between groups were identified at baseline. Out of 213 genes associated with NTM-PD in the non-CF population, only two were significantly different in our cystic fibrosis NTM-PD cohort. Gene set enrichment analysis of the differential expression results showed that CF individuals who developed NTM-PD had higher expression levels of genes involved in the interferon (α and γ), tumor necrosis factor, and IL6-STAT3-JAK pathways. Conclusion In contrast to the non-cystic fibrosis population, the gene expression signature of patients with cystic fibrosis who develop NTM-PD is characterized by increased innate immune responses.

opencc-zeroApr 2023View details →

Data for: Simulated climate change causes asymmetric responses in insect life history timing potentially disrupting a classic ecological speciation system

Climate change may alter phenology within populations with cascading consequences for community interactions and ongoing evolutionary processes. Here, we measured the response to climate change in two sympatric, recently diverged (~170 years) populations of Rhagoletis pomonella flies specialized on different host fruits (hawthorn and apple) and their parasitoid wasp communities. We tested whether warmer temperatures affect dormancy regulation and its consequences for synchrony across trophic levels and temporal isolation between divergent populations. Under warmer temperatures, both fly populations developed earlier. However, warming significantly increased the proportion of maladaptive pre-winter development in apple, but not hawthorn, flies. Parasitoid phenology was less affected, potentially generating ecological asynchrony. Observed shifts in fly phenology under warming may decrease temporal isolation, potentially limiting ongoing divergence. Our findings of complex sensitivity of life-history timing to changing temperatures predict that coming decades may see multifaceted ecological and evolutionary changes in temporal specialist communities.

opencc-zeroMay 2023View details →

Induction of Sis1 promotes fitness but not feedback in the heat shock response

<div class="page"> <div class="layoutArea"> <div class="column"> The heat shock response (HSR) controls expression of molecular chaperones to maintain protein homeostasis. Previously, we proposed a feedback loop model of the HSR in which heat-denatured proteins sequester the chaperone Hsp70 to activate the HSR, and subsequent induction of Hsp70 deactivates the HSR. However, recent work has implicated newly synthesized proteins (NSPs) – rather than unfolded mature proteins – and the Hsp70 co-chaperone Sis1 in HSR regulation, yet their contributions to HSR dynamics have not been determined. Here we generate a new mathematical model that incorporates NSPs and Sis1 into the HSR activation mechanism, and we perform genetic decoupling and pulse-labeling experiments to demonstrate that Sis1 induction is dispensable for HSR deactivation. Rather than providing negative feedback to the HSR, transcriptional regulation of Sis1 by Hsf1 promotes fitness by coordinating stress granules and carbon metabolism. These results support an overall model in which NSPs signal the HSR by sequestering Sis1 and Hsp70, while induction of Hsp70 – but not Sis1 – attenuates the response. </div> </div> </div>