cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.31324000.v2
title: Data from: Big sharks in the dark: high densities of the bluntnose sixgill shark <i>Hexanchus griseus</i> in the Gulf of Naples_Noè et al. 2026

description: Discovery of a high-density population of the bluntnose sixgill shark <i>Hexanchus griseus</i> in a newly explored and highly diverse habitat on the margins of Dohrn Canyon in the Gulf of Naples (Mediterranean Sea).
DOI: 10.6084/m9.figshare.31324000.v1
title: Data from: Big sharks in the dark: high densities of the bluntnose sixgill shark <i>Hexanchus griseus</i> in the Gulf of Naples_Noè et al. 2026

description: Discovery of a high-density population of the bluntnose sixgill shark <i>Hexanchus griseus</i> in a newly explored and highly diverse habitat on the margins of Dohrn Canyon in the Gulf of Naples (Mediterranean Sea).
DOI: 10.6084/m9.figshare.31293025
title: <b>SF1</b>: Compressed output folder created by RSeqFlow pipeline for the differential expression analysis between 'Picual' and 'Arbequina' mature pollen samples

description: Differential expression analysis between ‘Picual’ and ‘Arbequina’ MP samples as performed by <i>RSeqFlow</i> v1.1.1 pipeline. Raw reads of ‘Picual’ MP were those deposited as Bioproject PRJEB59024 and Arbequina reads were deposited as part of the Bioproject PRJEB107245.Configuration details are the following: (1) only transcripts having <code>CPM &gt; 1</code> in three replicates were considered reliable for differential expression; (2) normalization was performed using the TMM; (3) differential expression relied on the limma v3.64.3 library after correction for homoskedasticity with the limma::voom function; (4) differentially expressed genes were obtained using the the limma::treat function; (5) the minimal fold-change threshold was set to 1.25 and the adjusted p-value must be below 0.05; and (6) TMM-normalized counts were converted to CTF for further analyses. All output files are text files in tab separated values (.tsv) format and their meaning is explained in the RSeqFlow site.
DOI: 10.6084/m9.figshare.31293025.v2
title: <b>SF1</b>: Compressed output folder created by RSeqFlow pipeline for the differential expression analysis between 'Picual' and 'Arbequina' mature pollen samples

description: Differential expression analysis between ‘Picual’ and ‘Arbequina’ MP samples as performed by <i>RSeqFlow</i> v1.1.1 pipeline. Raw reads of ‘Picual’ MP were those deposited as Bioproject PRJEB59024 and Arbequina reads were deposited as part of the Bioproject PRJEB107245.Configuration details are the following: (1) only transcripts having <code>CPM &gt; 1</code> in three replicates were considered reliable for differential expression; (2) normalization was performed using the TMM; (3) differential expression relied on the limma v3.64.3 library after correction for homoskedasticity with the limma::voom function; (4) differentially expressed genes were obtained using the the limma::treat function; (5) the minimal fold-change threshold was set to 1.25 and the adjusted p-value must be below 0.05; and (6) TMM-normalized counts were converted to CTF for further analyses. All output files are text files in tab separated values (.tsv) format and their meaning is explained in the RSeqFlow site.
DOI: 10.6084/m9.figshare.31293025.v1
title: Compressed output folder created by RSeqFlow pipeline for the differential expression analysis between 'Picual' and 'Arbequina' mature pollen samples

description: Differential expression analysis between ‘Picual’ and ‘Arbequina’ MP samples as performed by <i>RSeqFlow</i> v1.1.1 pipeline. Raw reads of ‘Picual’ MP were those deposited as Bioproject PRJEB59024 and Arbequina reads were deposited as part of the Bioproject PRJEB107245.Configuration details are the following: (1) only transcripts having <code>CPM &gt; 1</code> in three replicates were considered reliable for differential expression; (2) normalization was performed using the TMM; (3) differential expression relied on the limma v3.64.3 library after correction for homoskedasticity with the limma::voom function; (4) differentially expressed genes were obtained using the the limma::treat function; (5) the minimal fold-change threshold was set to 1.25 and the adjusted p-value must be below 0.05; and (6) TMM-normalized counts were converted to CTF for further analyses. All output files are text files in tab separated values (.tsv) format and their meaning is explained in the RSeqFlow site.
DOI: 10.7298/n064-ne73
title: Data and scripts from: Mechanistic and scale-specific analyses advance the preference-performance hypothesis

description: These files contain data and script supporting all results reported in "Mechanistic and scale-specific analyses advance the preference-performance hypothesis". In Slimon et al. we used the specialist seed predator moth Schinia florida and the common evening primrose Oenothera biennis, to investigate the mechanistic drivers of preference and performance and how these dynamics shift across scales, between- versus within-plants. We measured a suite of 126 plant traits, most of which were plant specialized metabolites captured by ultra-high performance liquid chromatography and mass spectrometry, and applied a novel machine learning approach to identify traits that predict both preference and performance. Between-plants, we found no relationship between preference and performance. However, nine overlapping plant traits predicted both preference and performance, with all traits positively correlated with preference showing a negative association with performance. This negative trait-based preference-performance link may result from trade-offs of moths using plant defenses as host finding cues. Overall, weak correlations between the nine predictive traits appear to limit a link between preference and performance between plants. Within plants, moths disproportionally oviposited on flower buds over fruits and concordantly showed higher relative performance on buds. At this scale, only two overlapping traits predicted both preference and performance, and both showed positive associations with preference and performance. Thus, our results show that 1) a specialist herbivore faces trait-based trade-offs between host-selection among plants and larval performance, while making more adaptive decisions at finer scales within plants, and 2) mechanistic and cross-scale approaches offer insight into when adult preference predicts larval performance.
DOI: 10.5281/zenodo.18624098
title: CBio3 Laboratory Solubility Database: SolCbio3Database

description: SolCbio3Database : an open database that compiles experimentally determined intrinsic solubility (logS, in mol/L), melting point (mp, in °C), and neutral octanol-water partition coefficient (logPN) values for organic molecules, as reported in literature, to calculate their intrinsic solubility using the General Solubility Equation (GSE, in logS units). This database also includes the absolute error between the calculated and experimental solubility value (diff_logS).

 

Each experimental value reports its source (Ref_logS, Ref_mp, and Ref_logP). These are the Articles of the explored external databases:

 

AqSolDB:  Sorkun, M. C.; Khetan, A.; Er, S. AqSolDB, a Curated Reference Set of Aqueous Solubility and 2D Descriptors for a Diverse Set of Compounds. Sci Data 2019, 6 (1), 143. https://doi.org/10.1038/s41597-019-0151-1.

 

BigSolDB2.0: Krasnov, L.; Malikov, D.; Kiseleva, M.; Tatarin, S.; Sosnin, S.;Bezzubov, S. BigSolDB 2.0, Dataset of Solubility Values for Organic Compounds in Different Solvents at Various Temperatures. Sci Data 2025, 12 (1), 1236. https://doi.org/10.1038/s41597-025-05559-8.
DOI: 10.5281/zenodo.18624099
title: CBio3 Laboratory Solubility Database: SolCbio3Database

description: SolCbio3Database : an open database that compiles experimentally determined intrinsic solubility (logS, in mol/L), melting point (mp, in °C), and neutral octanol-water partition coefficient (logPN) values for organic molecules, as reported in literature, to calculate their intrinsic solubility using the General Solubility Equation (GSE, in logS units). This database also includes the absolute error between the calculated and experimental solubility value (diff_logS).

 

Each experimental value reports its source (Ref_logS, Ref_mp, and Ref_logP). These are the Articles of the explored external databases:

 

AqSolDB:  Sorkun, M. C.; Khetan, A.; Er, S. AqSolDB, a Curated Reference Set of Aqueous Solubility and 2D Descriptors for a Diverse Set of Compounds. Sci Data 2019, 6 (1), 143. https://doi.org/10.1038/s41597-019-0151-1.

 

BigSolDB2.0: Krasnov, L.; Malikov, D.; Kiseleva, M.; Tatarin, S.; Sosnin, S.;Bezzubov, S. BigSolDB 2.0, Dataset of Solubility Values for Organic Compounds in Different Solvents at Various Temperatures. Sci Data 2025, 12 (1), 1236. https://doi.org/10.1038/s41597-025-05559-8.
DOI: 10.5281/zenodo.18623839
title: Reduced NIRSpec/IFU G235H data-cube used in "When relics were made: vigorous stellar rotation and low dark matter content in the massive ultra-compact galaxy GS-9209 at z=4.66" (Pascalau+2026a)

description: This is the reduced NIRSpec/IFU data-cube (with the G235H / F170LP grating, filter combination) that was used in the analysis of the spatially resolved stellar kinematics and dynamical modelling of the galaxy GS-9209 at z=4.66 (Pascalau et al. 2026a, accepted for publication in MNRAS, 28 January 2026; https://doi.org/10.1093/mnras/stag210 ; https://ui.adsabs.harvard.edu/abs/2026MNRAS.tmp..202P/exportcitation).

The data were obtained as part of the JWST Cycle 2 Program ID 3659 (PI: Francesco D'Eugenio). The data were reduced using the JWST data reduction pipeline v1.12.5, with calibration files from the context file 1193. This standard pipeline was then complemented by customised methods for snowball flagging, pink noise correction and outliers removal that were described in Perna et al. (2023) (A&A 679, A89). The provided data-cube is not background subtracted, but Pascalau et al. (2026a) used a custom background subtraction algorithm developped by Francesco D'Eugenio and which is described in the paper.

If you have any questions, please feel free to email Robert Pascalau (rgp34@cam.ac.uk). We would greatly appreciate getting in touch if you plan to use the data.
DOI: 10.5281/zenodo.18623840
title: Reduced NIRSpec/IFU G235H data-cube used in "When relics were made: vigorous stellar rotation and low dark matter content in the massive ultra-compact galaxy GS-9209 at z=4.66" (Pascalau+2026a)

description: This is the reduced NIRSpec/IFU data-cube (with the G235H / F170LP grating, filter combination) that was used in the analysis of the spatially resolved stellar kinematics and dynamical modelling of the galaxy GS-9209 at z=4.66 (Pascalau et al. 2026a, accepted for publication in MNRAS, 28 January 2026; https://doi.org/10.1093/mnras/stag210 ; https://ui.adsabs.harvard.edu/abs/2026MNRAS.tmp..202P/exportcitation).

The data were obtained as part of the JWST Cycle 2 Program ID 3659 (PI: Francesco D'Eugenio). The data were reduced using the JWST data reduction pipeline v1.12.5, with calibration files from the context file 1193. This standard pipeline was then complemented by customised methods for snowball flagging, pink noise correction and outliers removal that were described in Perna et al. (2023) (A&A 679, A89). The provided data-cube is not background subtracted, but Pascalau et al. (2026a) used a custom background subtraction algorithm developped by Francesco D'Eugenio and which is described in the paper.

If you have any questions, please feel free to email Robert Pascalau (rgp34@cam.ac.uk). We would greatly appreciate getting in touch if you plan to use the data.
DOI: 10.6084/m9.figshare.31306783
title: <b>SF4</b>: Pollen transcriptomes of the four olive cultivars analysed and the resulting pan-transcriptome

description: The compressed file <b>PollenTranscriptomes.zip</b> contains the transcripts four olive cultivars. Each text file in tab separated values (.tsv) format containsa first column with the 'Picual' ID;the other one or tree columns contain the transcript counts in the corresponding replicate sample.File <b>PollenTR_ARB.tsv</b> corresponds to 'Arbequina', <b>PollenTR_MAN.tsv</b> to 'Manzanilla', <b>PollenTR_MES.tsv</b> to 'Meski', and <b>PollenTR_PIC.tsv</b> to 'Picual'. The compressed file also contains the table <b>PantranscriptomeIntersect.tsv</b> distributing the complete pollen pan-transcriptome between the different intersections of the four cultivars in a Venn diagram.<br>
DOI: 10.6084/m9.figshare.31306783.v2
title: <b>SF4</b>: Pollen transcriptomes of the four olive cultivars analysed and the resulting pan-transcriptome

description: The compressed file <b>PollenTranscriptomes.zip</b> contains the transcripts four olive cultivars. Each text file in tab separated values (.tsv) format containsa first column with the 'Picual' ID;the other one or tree columns contain the transcript counts in the corresponding replicate sample.File <b>PollenTR_ARB.tsv</b> corresponds to 'Arbequina', <b>PollenTR_MAN.tsv</b> to 'Manzanilla', <b>PollenTR_MES.tsv</b> to 'Meski', and <b>PollenTR_PIC.tsv</b> to 'Picual'. The compressed file also contains the table <b>PantranscriptomeIntersect.tsv</b> distributing the complete pollen pan-transcriptome between the different intersections of the four cultivars in a Venn diagram.<br>
DOI: 10.6084/m9.figshare.31306783.v1
title: <b>SF4</b>: Pollen transcriptomes of the four olive cultivars analysed in the paper

description: The compressed file <b>PollenTranscriptomes.zip</b> contains the transcripts four olive cultivars. Each text file in tab separated values (.tsv) format contains a first column with the 'Picual' ID; the other one or tree columns contain the transcript counts in the corresponding replicate sample. File <b>PollenTR_ARB.tsv</b> corresponds to 'Arbequina', <b>PollenTR_MAN.tsv</b> to 'Manzanilla', <b>PollenTR_MES.tsv</b> to 'Meski', and <b>PollenTR_PIC.tsv</b> to 'Picual'.
DOI: 10.6084/m9.figshare.31325743
title: Similar, but not in functioning: investigating diatom traits in high-elevation ponds

description: 1. On a planet constantly under siege from climate change, temporary ponds represent sentinels for the analysis of landscape and climatic changes at both local and regional scales. In this research, we investigated which local and regional factors shape diatom functional diversity in alpine temporary ponds.2. We investigated twelve alpine temporary ponds located within the Gran Sasso e Monti della Laga National Park (Italy), sampled in July 2024 together with physicochemical, geographical (elevation), and spatial (kernel isolation) variables. We quantified functional α-diversity using five indices and assessed functional β-diversity from a presence–absence matrix using the Sørensen dissimilarity index.3. Elevation emerged as a key predictor for functional richness and functional dispersion, temperature was associated with patterns in functional evenness, while, conversely, spatial isolation showed negative effect on functional evenness. A Mantel test revealed that community dissimilarity and elevational distance were correlated. Physicochemical factors and isolation were not.4. Community similarity decreased as elevation difference between sites increased. Differently, community similarity did not vary with increasing isolation among sites.
DOI: 10.6084/m9.figshare.31325743.v1
title: Similar, but not in functioning: investigating diatom traits in high-elevation ponds

description: 1. On a planet constantly under siege from climate change, temporary ponds represent sentinels for the analysis of landscape and climatic changes at both local and regional scales. In this research, we investigated which local and regional factors shape diatom functional diversity in alpine temporary ponds.2. We investigated twelve alpine temporary ponds located within the Gran Sasso e Monti della Laga National Park (Italy), sampled in July 2024 together with physicochemical, geographical (elevation), and spatial (kernel isolation) variables. We quantified functional α-diversity using five indices and assessed functional β-diversity from a presence–absence matrix using the Sørensen dissimilarity index.3. Elevation emerged as a key predictor for functional richness and functional dispersion, temperature was associated with patterns in functional evenness, while, conversely, spatial isolation showed negative effect on functional evenness. A Mantel test revealed that community dissimilarity and elevational distance were correlated. Physicochemical factors and isolation were not.4. Community similarity decreased as elevation difference between sites increased. Differently, community similarity did not vary with increasing isolation among sites.
DOI: 10.15139/s3/bqa98q
title: Data Management and Sharing Plan for: Characterizing Injury-Related Fear in Patients after Anterior Cruciate Ligament Reconstruction

description: The Data Management and Sharing Plan describes the scientific data to be generated and/or used in the research and outlines a strategy for managing and sharing project data.
description: Data Management and Sharing Plan
DOI: 10.25824/redu/fidrhu
title: Dados de pesquisa multicêntrica de imagens de ressonância magnética T1w cerebral

description: Este conjunto de dados reúne imagens de ressonância magnética (MRI) da medula espinhal e estruturas associadas, coletadas no contexto de três consórcios internacionais de pesquisa: ENIGMA–Ataxia, TRACK-FA e READISCA. Os dados foram adquiridos em múltiplos centros, utilizando diferentes protocolos de aquisição, com o objetivo de investigar alterações estruturais da medula espinhal em populações clínicas e controles saudáveis. O dataset inclui imagens T1-weighted, segmentações automatizadas, além de derivados gerados por pipelines baseados em aprendizado profundo para rotulagem vertebral e segmentação da medula espinhal. A finalidade principal deste conjunto de dados é apoiar o desenvolvimento, validação externa e avaliação de métodos automatizados para análise quantitativa da medula espinhal, bem como possibilitar estudos reprodutíveis em neuroimagem.
DOI: 10.5281/zenodo.18468770
title: Dataset for Molecular Dynamics Simulation of TLR4/MD-2 Complex with β-Sesquiphellandrene

description: Dataset Overview

This dataset contains the input and processed molecular dynamics (MD) simulation data supporting the computational findings of our study. The simulations modeled the interaction between the TLR4/MD-2 receptor complex and the lead bioactive ligand β-sesquiphellandrene from Aframomum Melegueta over a 100-nanosecond trajectory.

---

Associated Project: "Integrated In Vivo and In Silico Analysis Reveals Aframomum Melegueta Neuroprotection Against LPS-Induced Memory Impairment Through TLR4/MD-2 Modulation"

License: Creative Commons Attribution 4.0 International (CC-BY 4.0)

---

File Inventory & Description



Simulation Inputs (Topology & Structure)* complex_solvated.gro`: The final solvated system coordinates (Protein + Ligand + Water + Ions).* topol.top: GROMACS system topology file.* ligand.itp: Ligand topology parameters generated via CGenFF.* index.ndx: Index file defining groups (System, Protein, Ligand, Solvent).* md_input files: .edr, .nvt, .npt, .cpt, .gro files, etc.

Production Outputs* md_01 xtc file: Compressed trajectory file (100 ns simulation, frames saved every 10 ps).* md_01 tpr file: The run input file used to generate the trajectory.* md_01 log file: GROMACS log file containing energy and performance data.

Analysis Outputs (Processed Data)* rmsd.xvg, rmsf.xvg, potential.xvg, 


---

Methodology Summary

Software: GROMACS (Version 2025.2)Force Field: CHARMM36m (Protein) / CGenFF (Ligand)Water Model: TIP3PEnsemble: NPT (Isothermal-Isobaric)Temperature: 300 K (V-rescale thermostat)Pressure: 1 bar (Parrinello-Rahman barostat)Duration: 100 nsTime Step: 2 fs

---

Citation

If you use this dataset, please cite both the dataset DOI and the associated publication:

Dataset: Oladele, T. S., Iteire, K. A., Ogunmiluyi, O. E., Adebisi, K. A., Siyanbade, A. J., Sulaiman, K. A., Leko, B. J., & Ijomone, O. M. (2026). Dataset for Molecular Dynamics Simulation of TLR4/MD-2 Complex with β-Sesquiphellandrene (v1.0.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.18468770
DOI: 10.5281/zenodo.18468769
title: Dataset for Molecular Dynamics Simulation of TLR4/MD-2 Complex with β-Sesquiphellandrene

description: Dataset Overview

This dataset contains the input and processed molecular dynamics (MD) simulation data supporting the computational findings of our study. The simulations modeled the interaction between the TLR4/MD-2 receptor complex and the lead bioactive ligand β-sesquiphellandrene from Aframomum Melegueta over a 100-nanosecond trajectory.

---

Associated Project: "Integrated In Vivo and In Silico Analysis Reveals Aframomum Melegueta Neuroprotection Against LPS-Induced Memory Impairment Through TLR4/MD-2 Modulation"

License: Creative Commons Attribution 4.0 International (CC-BY 4.0)

---

File Inventory & Description



Simulation Inputs (Topology & Structure)* complex_solvated.gro`: The final solvated system coordinates (Protein + Ligand + Water + Ions).* topol.top: GROMACS system topology file.* ligand.itp: Ligand topology parameters generated via CGenFF.* index.ndx: Index file defining groups (System, Protein, Ligand, Solvent).* md_input files: .edr, .nvt, .npt, .cpt, .gro files, etc.

Production Outputs* md_01 xtc file: Compressed trajectory file (100 ns simulation, frames saved every 10 ps).* md_01 tpr file: The run input file used to generate the trajectory.* md_01 log file: GROMACS log file containing energy and performance data.

Analysis Outputs (Processed Data)* rmsd.xvg, rmsf.xvg, potential.xvg, 


---

Methodology Summary

Software: GROMACS (Version 2025.2)Force Field: CHARMM36m (Protein) / CGenFF (Ligand)Water Model: TIP3PEnsemble: NPT (Isothermal-Isobaric)Temperature: 300 K (V-rescale thermostat)Pressure: 1 bar (Parrinello-Rahman barostat)Duration: 100 nsTime Step: 2 fs

---

Citation

If you use this dataset, please cite both the dataset DOI and the associated publication:

Dataset: Oladele, T. S., Iteire, K. A., Ogunmiluyi, O. E., Adebisi, K. A., Siyanbade, A. J., Sulaiman, K. A., Leko, B. J., & Ijomone, O. M. (2026). Dataset for Molecular Dynamics Simulation of TLR4/MD-2 Complex with β-Sesquiphellandrene (v1.0.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.18468770
DOI: 10.15468/adnwtk
title: National Peatland Action Programme Water Vole and Otter Surveys

description: The data shows evidence of water vole and otter activity in surveys taken to inform the approaches to peatland restoration.
DOI: 10.5281/zenodo.18624201
title: Comparative Process Efficiency Dataset: Global vs Local Automotive Supply Chains (2019–2024)

description: This dataset contains the consolidated KPI panel used in a comparative analysis of process efficiency and resilience-related performance in two major automotive OEMs over the period 2019–2024.

The dataset includes publicly extracted annual delivery volumes, cost of sales (COGS), and inventory values, as well as computed KPI proxies including Days Inventory Outstanding (DIO), COGS per unit, and year-on-year delivery change.

All variables are standardized for comparability across firms and years. The dataset is provided to ensure transparency, reproducibility, and independent verification of the reported empirical results.

The archive includes the frozen dataset used for analysis and documentation of variable definitions and calculation logic.