cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.15238075
title: Coarse-Grained Molecular Dynamics Simulations of SARS-CoV-2 E Protein embedded in homogeneous saturated model membranes

description: Coarse-grained MD simulations of the SARS-CoV-2 E protein (PDB ID: 5X29) embedded in homogeneous mono-unsaturated model membranes of varying equilibrium thickness. Lipids with 2, 3, 4, 5, or 6 beads per acyl chain were used (Martini lipids DTPC, DLPC, DPPC, DBPC, and DXPC).

All simulations were performed using GROMACS 2016 and the Martini 2.2 force field. The Berendsen thermostat was set to 313 K and a semi-isotropic Berendsen barostat was set to 1 bar in both directions. The compressibility modulus in both dimensions was 3 × 10−5 bar−1 with time constant 3 ps. Electrostatics and van der Waals (vdW) were shifted with a cutoff r-value of 1.2 nm. All systems underwent 100,000 steps of steepest-descent energy minimization prior to MD simulation with a timestep of 0.025 ps.

Protein backbone beads were restrained with an elastic network which bonded all backbone bead pairs within 1.4 nm of one another with force constants of 5,000 kJ mol−1 nm−1. Five replicas of each system were simulated in the NPT ensemble for 10 μs. We discarded the first half of each trajectory prior to analysis. To determine the bulk leaflet thickness t0, we performed separate 2 μs NPT simulations of membranes composed of each lipid species listed above, but without a protein embedded. We discarded the first half of each trajectory prior to analysis.

Analysis performed using nougat. Figures and figure generation script included.
DOI: 10.5281/zenodo.15453083
title: MD Simulation of DD-Transpeptidase (PBP) protein of P. aeruginosa (with mutations recorded in 1999) and Penicillin (PEN) ligand molecule

description: A mutated sequence of DD-transpeptidase/PBP2 protein (recorded in 1999) associated with P. aeruginosa is modeled and docked with a molecule of Penicillin. The data from subsequent Molecular Dynamics simulation is presented.

 

The data from the Molecular Modelling and Docking Simulations can be found here:

Roy, A. (2025). Docking of several proteins associated with strains of Pseudomonas aeruginosa with various antibiotic molecules [Data set]. Zenodo. https://doi.org/10.5281/zenodo.15383904
DOI: 10.5281/zenodo.17595765
title: Gut microbiota mediates the anti-ulcerative colitis effects of camel milk and fermented camel milk in mice
DOI: 10.5281/zenodo.17483073
title: Supplementary data and codes for "Universally self-injection locked lasers"

description: Data and codes used in the manuscript "Universally self-injection locked lasers" (DOI to be updated).
DOI: 10.5281/zenodo.15085807
title: IL-10 Induction by Extracellular Vesicles from Glycolytic Mesenchymal Stromal Cells: An Innovative Biotherapy for Rheumatoid Arthritis

description: Mesenchymal stromal cells (MSCs) are multipotent cells with broad immunoregulatory capabilities, positioning them as promising candidates for the treatment of autoimmune diseases. MSC immunoregulatory properties are primarily mediated by the release of paracrine factors including extracellular vesicles (EVs). We have previously demonstrated that the metabolic reprogramming of human umbilical cord MSCs (UC-MSCs) to glycolysis enhances their ability to inhibit proinflammatory T cell proliferation, to reduce the secretion of pro-inflammatory cytokines by T cells and to promote the generation of T regulatory cells (Tregs). In this study, we evaluated and compared the immunoregulatory properties of EVs derived from control and glycolytic UC-MSCs in vitro and in vivo.

EVs were isolated from control and glycolytic UC-MSCs by ultracentrifugation, characterized using nanoparticle tracking analysis (NTA) and flow cytometry (FACS), and assessed for their effects on PBMCs and memory T-CD4 cells isolated from healthy donors. EV internalization was measured on memory T-CD4+ cells by FACS, confocal microscopy and qPCR. In vivo, we investigated their effects in the DTH and the CIA models. 

In vitro, we showed that EVs derived from glycolytic MSC induced the generation of Tregs. In vivo, in the DTH model we found that EVs derived from glycolytic MSC decreased proinflammatory T cell infiltration, DTH inflammation compared to EVs derived from control MSC. In the CIA model, EVs derived from glycolytic MSC reduced prevent the development and the progression to a higher rate than EVs isolated from control MSC. This was associated with significantly higher Treg/Th1 and Treg/Th17 ratios in the LN and spleen, respectively, of arthritic mice treated with EVs derived from glycolytic MSCs compared with arthritic mice or mice treated with EVs isolated from control MSCs.

Overall, our findings indicate that EV derived from glycolytic MSC effectively suppress the pro-inflammatory T cell response while promoting the generation of regulatory T cells, highlighting their enhanced therapeutic potential in inflammatory and autoimmune diseases like arthritis.
DOI: 10.5281/zenodo.16889270
title: Supporting dataset for Triggering Larger Earthquakes on Moderately Unstable Faults under Long-Term Injection: Insights from The Geysers, California

description: This dataset contains the processed earthquake features used for the machine learning analysis in Wang et al. (2025), submitted to Journal of Geophysical Research: Solid Earth.

The dataset (features_for_ml.csv) includes the following columns:





ID: event identifier




Mw: earthquake magnitude




Inst I: instability index




V_weighted: distance-weighted injection volume (million m³)




Dist_to_9: distance to well Prati 9 (m)




Dist_to_29ab: distance to wells Prati 29a/29b midpoint (m)



This dataset allows reproducibility of the feature importance, SHAP analysis, and magnitude prediction presented in the manuscript.
description: This dataset was derived from the publicly available EPISODES platform and processed for machine learning experiments.
DOI: 10.5281/zenodo.14023031
title: MD source and data of Zebhb-PHZ

description: Python Codes, shell scripts and GROMACS data files of molecular dynamics simulations of Zebrafish Hemoglobin protein (Zebhb) and Phenylhydrazine (PHZ) Ligand
DOI: 10.5281/zenodo.15114138
title: GeoEcoMar Macrozoobenthos BRIDGE-BS July 2024

description: The dataset contains macrozoobenthos data collected in July 2024, from 6 stations located in the South of the Romanian Black Sea area. The sampling was performed within H2020 BRIDGE-BS Project with the aim of monitoring and data collection, in line with the project objectives, bringing together the expertise and competences required for implementing planned activities. The sediment samples were taken with a Box corer (the sampling size - 0.1 m2) and Van-Veen grab (the sampling size - 0.125 m2). The sediment was preserved in buffered formalin 4% , then sieved through a 1 mm and 0.5 mm mesh sieve and subsequently stored in 70% ethanol. The database comprises taxonomic and quantitative data (density and wet weight biomass per square meter) for 56 macrobenthic species and 2 supraspecific groups.
DOI: 10.5281/zenodo.15690187
title: Assessing the Usefulness of Digital Contact Tracing Using Real-World Contact Data

description: File organisation




File Name
Contents
#Rows
Size each
Format inside




par000000_contact_h3_10.zip … par000003_contact_h3_10.zip
H3-10 contact dataset
215 124 846
≈ 425 MB
part-*.csv, header row


par000000_contact_h3_9.zip … par000017_contact_h3_9.zip
H3-9 contact dataset
820 508 676
≈ 562 MB
part-*.csv, header row


covid_infected_date_anonymized_h3_10.zip
infection events at H3-10 resolution
7 415
87 kB
single CSV (header)


covid_infected_date_anonymized_h3_9.zip
infection events at H3-9 resolution
8 026
94 kB
single CSV (header)




Schema

Contact datasets (H3-9 & H3-10)




Column
Type
Description




o_s
timestamp
Start time of the contact episode (UTC)


contact_duration_sec
long
Contact duration in seconds


src_device_id
int
Hashed identifier of the source device


dst_device_id
int
Hashed identifier of the destination device




Infection look-up tables




Column
Type
Description




anonymous_id
int
Hashed identifier of an individual reported as infected


date
string
Reported infection date (yyyy-MM-dd)




All identifiers are irreversibly hashed; no personally identifiable information is present.


Intended use

Combine the infection look-up tables with the large contact graphs to:





trace probable exposure chains,




measure secondary attack rates, or




validate SEIR-type simulation outputs against empirical spreading patterns.
DOI: 10.5281/zenodo.14773545
title: PCSK9 missense mutations
DOI: 10.5281/zenodo.17047273
title: Sea currents data from Southern Black Sea, December 2022.

description: The dataset contains sea currents data collected in Southern Black Sea withing the Turkish EEZ in December 2022 in framework of the R/V Bilim-2 cruise supported by EU-funded BRIDGE-BS project.

The data on sea currents velocities were acquired aboard the research vessel R/V Bilim-2 with ADCP OS150. Raw data were processed with CODAS software, imported to ODV collection and, upon finalizing quality control, exported to output file.
DOI: 10.5281/zenodo.14284222
title: Optimizing Class Integration Testing with Criticality-Driven Test Order Generation

description: The generation of class integration test orders (CITOs) is a pivotal element in integration testing, which focuses on determining the optimal order for integrating classes while testing an object-oriented system. Due to a high number of dependencies and their possible error proneness, some classes are more critical than others in a program. Existing methods for handling these classes only assess risk in terms of their dependencies; they do not consider historical bug information as an additional indicator and mainly work on small programs. 

To overcome these limitations, this paper introduces Criticality-Driven CITO (CD-CITO) generation, an innovative approach to optimize CITOs by focusing on class criticality. CD-CITO assesses both the importance of a class in terms of its dependencies and the likelihood of defects, based on historical bug data, to determine a criticality score. Then, it reformulates the CITO generation problem as a reinforcement learning task and uses the Advantage Actor-Critic (A2C) algorithm to address it. We propose a novel reward calculation strategy to guide the learning agent, balancing stubbing costs with the criticality values of classes to optimize the test order. To extract fault proneness information and access the approach, the paper uses Defects4j, a data set that contains real bugs and patches of Java programs. The results obtained show that CD-CITO effectively identifies and prioritizes highly critical classes and also minimizes stubbing costs while generating CITOs, which makes it a valuable tool for integration testing.
DOI: 10.5281/zenodo.15395687
title: Multiomics Reveals Compartmentalized Immune Responses and Tissue-Vascular Signatures in Lyme Disease

description: This Zenodo record contains the datasets supporting our Lyme disease manuscript.

 
description: Lyme disease (LD) is growing in incidence, with nearly 500,000 cases diagnosed annually in the United States. Despite treatment, some patients experience persistent symptoms. The immune mechanisms underlying LD remain poorly understood. We conducted a multiomic longitudinal analysis of 49 LD patients and matched controls, integrating plasma proteomics, metabolomics, PBMC immunophenotyping, and a meta-analysis of skin lesions. We identified compartmentalized immune responses in acute LD, with coordinated alterations in circulating plasma proteins and metabolites linked to endothelial barrier stability, metabolic reprogramming, and symptom severity, predominantly traced to tissue and vascular immune processes at the site of infection. In contrast, PBMCs remained largely quiescent, revealing a disconnect between localized tissue responses and systemic immunity. These findings provide novel insights into LD pathophysiology and highlight the potential for diagnostics leveraging tissue and vascular immune markers detectable in blood. They also provide a resource for biomarker discovery and predictive modeling to improve LD management.
DOI: 10.5281/zenodo.15448122
title: Molecular Dynamics Simulations of Aminonucleotidyltransferase protein from Pseudomonas aeruginosa with various antibiotic molecules

description: 3 sequences of Aminonucleotidyltransferase, associated with various strains of P. aeruginosa were been obtained from the Uniprot database, modelled and docked with ligands, streptomycin (with the 2012 and 2016 strains) and tobramycin (with the 2016 strain only).

 

The data from the Molecular Modelling and Docking Simulations can be found here:

Roy, A. (2025). Docking of several proteins associated with strains of Pseudomonas aeruginosa with various antibiotic molecules [Data set]. Zenodo. https://doi.org/10.5281/zenodo.15383904
DOI: 10.5281/zenodo.17037483
title: CTD data from South-Western Black Sea, July 2024

description: The dataset contains hydrophysical data collected in South-Western Black Sea withing the Turkish EEZ in September 2024 in framework of the R/V Bilim-2 cruise supported by EU-funded BRIDGE-BS project. Automated in-situ measurements of physical, chemical and optical parameters were performed with SBE 9-11 plus CTD profiler equipped with the following sensors: SBE-43 dissolved oxygen sensor, SBE 27 pH and O.R.P. sensor, WetLabs ECO FLNTU chlorophyll fluorescence and turbidity sensor, and LI-COR Biospherical PAR sensor. The raw data from total 19 casts were processed with SBE Seasoft V2 package, imported to ODV collection and, upon performing quality control, exported to output file. The output file contains following parameters: Pressure, Temperature, Salinity, Oxygen (SBE 43), PAR, Fluorescence, Turbidity, pH, ORP.
DOI: 10.5281/zenodo.12686434
title: L19-IL2 inhibits pancreatic cancer growth in combination with chemotherapy (Transcriptomic Data)

description: Transcriptomics Analyses data files:

1)  Aggregated RNA counts ( counts.csv) 

2) Stereo-seq OMNI .gef file ( TMA-filtered.gef)
DOI: 10.5281/zenodo.11048438
title: Biodegradable mulching film degradation in soil in Italy

description: The biodegradable mulching samples underwent a visible degradation process in the soil at the experimental field of the University of Bari (Italy). The surface area of each sample clearly presented gaps that increased in size over time. After 42 days of burial the surface loss was 1.30%, reaching 56.70% on the last sampling.
DOI: 10.5281/zenodo.15348298
title: Time-resolved pump-probe ellipsometry of the photoinduced insulator-metal transition in VO2 nanocrystals

description: Data available

Pseudo dielectric function measured with a time-resolved pump-probe ellipsometry on metamaterial consisting on VO2 NCs embedded in a SiO2 matrix. This metamaterial and its static properties are described in J. John, Y. Gutierrez, Z. Zhang, H. Karl, S. Ramanathan, R. Orobtchouk, F. Moreno, and S. Cueff, "Multipolar Resonances with Designer Tunability Using VO2 Phase-Change Materials," Phys. Rev. Appl. 13, 044053 (2020).

The data of the  pseudo dielectric function are provided for four different pump fluences.



\lambda_{pump} = 500 nm - F_{pump} = 0.6 mJ/cm2

\lambda_{pump} = 500 nm - F_{pump} = 1.7 mJ/cm2

\lambda_{pump} = 500 nm - F_{pump} = 2.5 mJ/cm2

\lambda_{pump} = 500 nm - F_{pump} = 3.0 mJ/cm2


Naming of the files

In the .zip file that can be downloaded here, there are several folders.

Each are named as lambda_pump_500_nm_fluence_YYY_mJcm-2  YYY is the fluence of the pump.

In each folder are two files.



pseudoepsilon1.txt- spectral values of the real part of the pseudo dielectric function for the different time delays.

pseudoepsilon2.txt- spectral values of the imaginary part of the  pseudo dielectric function for the different time delays.


Structure of the files

Each file has the same structure:

The first row an array time delays in picosecond for which measurements have been performed.

In the rest of rows, the first element of the array are the photon energy, while the rest of the elements are the values of the dielectric function at each of the elements in the time delay array.

Example:

time delay       t1                         t2                           t3                   ...                    tn

E1(eV)      eps1(E1, t1)        eps1(E1, t2)          eps1(E1, t3)            ...             eps1(E1, tn)

E2(eV)      eps1(E2, t1)       eps1(E2, t2)         eps1(E2, t3)            ...             eps1(E2, tn)

E3(eV)      eps1(E3, t1)       eps1(E3, t2)        eps1(E3, t3)             ...             eps1(E3, tn)

...                      ...                          ...                        ...                      ...                 ...

En(eV)      eps1(En, t1)       eps1(En, t2)        eps1(En, t3)             ...             eps1(En, tn)
DOI: 10.5281/zenodo.17238003
title: MUSE observation of 1RXS J052832.5+283824 bow shock

description: MUSE datacube of bow shock associated with 1RXS J052832.5+283824
DOI: 10.5281/zenodo.16752091
title: Granulometry in the Romanian shelf waters - September 2020 (PN 19 20 01 02 - National Project)

description: Dataset contains granulometry data collected in the Romanian shelf during a cruise conducted in September 2020, onboard R/V Mare Nigrum, within the national project "Multidisciplinary research to improve knowledge of the climate change and human pressure interaction and its effects on the Black Sea ecosystem" – PN 19 20 01 02. Thirty stations were performed for grain size investigations by the GeoEcoMar team. Sediment samples were collected using Van Veen grab sampler and Multicorer MARK II-400 and analyzed for grain size composition and textural parameters with Mastersizer 2000E Ver. 5.20 (MALVERN) equipment in the GeoEcoMar lab.
DOI: 10.5281/zenodo.16753790
title: CTD data from South-Western Black Sea, September 2021

description: The dataset contains hydrophysical data collected in South-Western Black Sea withing the Turkish EEZ in September 2021 in framework of the R/V Bilim-2 cruise supported by EU-funded BRIDGE-BS project. Automated in-situ measurements of physical, chemical and optical parameters were performed with SBE 9-11 plus CTD profiler equipped with the following sensors: SBE-43 dissolved oxygen sensor, SBE 27 pH and O.R.P. sensor, WetLabs ECO FLNTU chlorophyll fluorescence and turbidity sensor, and LI-COR Biospherical PAR sensor. The raw data from total 27 casts were processed with SBE Seasoft V2 package, imported to ODV collection and, upon performing quality control, exported to output file. The output file contains following parameters: Pressure, Temperature, Salinity, Oxygen (SBE 43), PAR, Fluorescence, Turbidity, pH, ORP.
DOI: 10.5281/zenodo.14144945
title: Key Audit Matters UK 2013-2018
title: KAMS
title: Cuestiones claves de auditoría

description:  The initial sample comprises all companies listed on the London Stock Exchange in 2013, as the UK was the first country in Europe to implement the disclosure requirements for key audit matters (KAMs) in ISA 701. As the UK regulations on extended audit reports only apply to company audit reports, we focused on companies with a premium listing classification whose auditors were required to file extended audit reports as of fiscal year-end 30 September 2013 or later. Due to the costs and effort involved in manual data collection, we focused our sample on companies with a premium rating in the 2013 fiscal year and manually collected KAMs for these companies from their first extended audit report (2013 or 2014, depending on their fiscal year-end date) until 2018. If we find an insolvent or merged company during our sampling period, we only include data for such companies up to the extended audit report of the latest available fiscal year.After excluding the firm-year observation without all the data needed for our analysis, our final sample includes 1925 firm-year observations pertaining to 381 unique firms.
DOI: 10.5281/zenodo.15478360
title: MD Simulation of DD-Transpeptidase (PBP) protein of P. aeruginosa (with mutations recorded in 2018) and Mezlocillin (MEZ) ligand molecule

description: A mutated sequence of DD-transpeptidase/PBP2 protein (recorded in 2018) associated with P. aeruginosa is modeled and docked with a molecule of Mezlocillin. The data from subsequent Molecular Dynamics simulation is presented.

 

The data from the Molecular Modelling and Docking Simulations can be found here:

Roy, A. (2025). Docking of several proteins associated with strains of Pseudomonas aeruginosa with various antibiotic molecules [Data set]. Zenodo. https://doi.org/10.5281/zenodo.15383904
DOI: 10.5281/zenodo.17207532
title: some data

description: data
DOI: 10.5281/zenodo.17553151
title: Data for: Neural Synchrony Links Sensorimotor Cortices in a Network for Facial Motor Control

description: README

Dataset for: Neural Synchrony Links Sensorimotor Cortices in a Network for Facial Motor Control

Authors: Yuriria Vázquez, Geena R. Ianni, Elie Rassi, Adam G. Rouse, Marc H. Schieber, Faraz Yazdani, Yifat Prut, Winrich A. Freiwald

Contact:  Yuriria Vázquez (yuvazuster@gmail.com /yvazquez@rockefeller.edu)

Code: Available at https://github.com/yuvazu/facial-motor-synchrony-code
DOI: 10.60888/epos-gnss-vdgo00esp
title: GNSS data of VDGO00ESP, Villadiego, Spain

description: Permanent GNSS station dataset as RINEX files
DOI: 10.5281/zenodo.15101288
title: Water column chemistry in the southern Romanian EEZ 2023-2024 (H2020 BRIDGE-BS project)

description: Dataset contains hydrochemistry data collected along the Mangalia - East transect, in the Romanian southern EEZ (bottom depths between 15 and 1160 m), within the period February 2023 - July 2024. Data were collected during three BRIDGE -BS cruises carried out onboard R/V Mare Nigrum in February 2023 (cruise MN238), June 2023 (cruise MN242), and July 2024 (cruise MN260). In situ measurements of physical-chemical seawater parameters were done at each sampling station using SBE 25 CTD. Seawater samples were collected with 5L Niskin bottles from different depths, according to the CTD vertical profiles, and further analyzed in the GeoEcoMar lab for nutrients (by spectrometry), chlorophylls (by spectrometry), total mercury, and PAHs (by UPLC), the latter two only for July 2024 cruise. OCPs (by GC-ECD), PCBs (GC-ECD), and PAHs (by GC-MS) were analyzed in the NIMRD lab for the 2023 cruises. In addition, size-fractioned chlorophyll was analyzed by spectrometry for the June 2023 cruise in the NIMRD lab.
DOI: 10.5281/zenodo.15515343
title: MD Simulation of DNA topoisomerase IV subunit C (parC) protein of P. aeruginosa, with mutations recorded in 1999 and 2018, each in complex with Nalidixic Acid (NDX) ligand molecule

description: Mutated sequences of DNA topoisomerase IV (subunit C) protein (mutations recorded in 1999 and 2018) associated with P. aeruginosa are modeled and individually docked with a molecule of Nalidixic Acid. The data from subsequent Molecular Dynamics simulation is presented.

 

The data from the Molecular Modelling and Docking Simulations can be found here:

Roy, A. (2025). Docking of several proteins associated with strains of Pseudomonas aeruginosa with various antibiotic molecules [Data set]. Zenodo. https://doi.org/10.5281/zenodo.15383904
DOI: 10.5281/zenodo.15494005
title: MD Simulation of DNA gyrase (subunit A) and topoisomerase IV (subunit C) proteins of P. aeruginosa (with mutations recorded in 2018), each in complex with Levofloxacin (LEV) ligand molecule

description: Mutated sequences of DNA gyrase (subunit A) and topoisomerase IV (subunit C) proteins (recorded in 2018) associated with P. aeruginosa are modeled and individually docked with a molecule of Levofloxacin. The data from subsequent Molecular Dynamics simulation is presented.

 

The data from the Molecular Modelling and Docking Simulations can be found here:

Roy, A. (2025). Docking of several proteins associated with strains of Pseudomonas aeruginosa with various antibiotic molecules [Data set]. Zenodo. https://doi.org/10.5281/zenodo.15383904