Find research datasets worth reusing

BATS With in Combination With Low Dose IL-1 and GM-CSF for Advanced Pancreatic Cancer

ClinicalTrials.gov study NCT02620865. IPD Sharing: Not stated. Countries: 1. Publications: 1.

Trastuzumab, Cyclophosphamide, and an Allogeneic GM-CSF-secreting Breast Tumor Vaccine for the Treatment of HER-2/Neu-Overexpressing Metastatic Breast Cancer

ClinicalTrials.gov study NCT00399529. IPD Sharing: Not stated. Countries: 1. Publications: 1.

closedIPD-NOFeb 2026View details →

Study of TJ003234 (Anti-GM-CSF Monoclonal Antibody) in Subjects With Severe Coronavirus Disease 2019 (COVID-19)

ClinicalTrials.gov study NCT04341116. IPD Sharing: NO. Countries: 1. Publications: 1.

Autologous Vaccination With Lethally Irradiated, Autologous Breast Cancer Cells Engineered to Secrete GM-CSF in Women With Operable Breast Cancer

ClinicalTrials.gov study NCT00880464. IPD Sharing: Not stated. Countries: 1. Publications: 1.

A Randomized Trial of GM-CSF in Patients With ALI/ARDS

ClinicalTrials.gov study NCT00201409. IPD Sharing: Not stated. Countries: 1. Publications: 7.

Efficacy and Safety Study of Talimogene Laherparepvec Compared to Granulocyte Macrophage Colony Stimulating Factor (GM-CSF) in Melanoma

ClinicalTrials.gov study NCT00769704. IPD Sharing: Not stated. Countries: 4. Publications: 3.

G-CSF Versus G-CSF Plus GM-CSF for Stem Cell Mobilization in NHL Patients

ClinicalTrials.gov study NCT00499343. IPD Sharing: Not stated. Countries: 1. Publications: 1.

Phase II Study of Fludarabine and Mitoxantrone, Followed by GM-CSF(Granulocyte-macrophage Colony-stimulating Factor) and Rituximab

ClinicalTrials.gov study NCT00208975. IPD Sharing: Not stated. Countries: 1. Publications: 1.

Efficacy Study of Granulocyte-macrophage Colony Stimulating Factor (GM-CSF) for Use in Human IVF

ClinicalTrials.gov study NCT00565747. IPD Sharing: Not stated. Countries: 2. Publications: 2.

closedIPD-NOFeb 2026View details →

Treadmill Exercise and GM-CSF Study to Improving Functioning in Peripheral Artery Disease (PAD)

ClinicalTrials.gov study NCT01408901. IPD Sharing: NO. Countries: 1. Publications: 12.

GM-CSF for Maintenance of Prostate Cancer for Patients Responding to Taxotere

ClinicalTrials.gov study NCT00274287. IPD Sharing: Not stated. Countries: 1. Publications: 1.

publicJul 2022View details →

dryad36/100

Data from: IFN-γ-independent control of M. tuberculosis requires CD4 T cell-derived GM-CSF and activation of HIF-1α

Open the record for dataset details and reuse information.

dryad32/100

Data from: Genetic diversity of oilseed rape fields and feral populations in the context of coexistence with GM crops

Despite growing concern about transgenes escaping from fields, few studies have analysed the genetic diversity of crops in an agroecosystem over several years. Accurate information about the dynamics and relationship of the genetic diversity of crops in an agroecosystem is essential for risk assessment and policies concerning the containment of genetically modified crops and their coexistence with crops grown by conventional practices. Here, we analysed the genetic diversity of oilseed rape plants from fields and feral populations over 4 years in an agricultural landscape of 41 km2. We used exact compatibility and maximum likelihood assignment methods to assign these plants to cultivars. Even pure lines and hybrid cultivar seed lots contained several genotypes. The cultivar diversity in fields reflected the conventional view of agroecosystems quite well: that is, there was a succession of cultivars, some grown for longer than others because of their good performance, some used for one year and then abandoned, and others gradually adopted. Three types of field emerged: fields sown with a single cultivar, fields sown with two cultivars, and unassigned fields (too many cultivars or unassigned plants to reliably assign the field). Field plant diversity was higher than expected, indicating the persistence of cultivars that were grown for only one year. The cultivar composition of feral populations was similar to that of field plants, with an increasing number of cultivars each year. By using genetic tools, we found a link between the cultivars of field plants in a particular year and the cultivars of feral population plants in the following year. Feral populations on road verges were more diverse than those on path verges. All of these findings are discussed in terms of their consequences in the context of coexistence with genetically modified crops.

opencc-zeroDec 2015View details →

opencc-by-nc-sa-4.0Aug 2015View details →

GM EEG data zip 1 of 2

This is the EEG dataset part 1 of 2 as well as the trial-by-trial behavioural data for the paper "Reduction of Pavlovian bias in schizophrenia" under submission at PLoS One. EEG data contains the cleaned, ICA eye-blink corrected data in EEGLAB format. Also included is an ICA decomposition using the AMICA algorithm. Triggers: Triggers are also included in the behavioural R data file "BehaviouralData&M6Fits.RData" as a data.table (will need the 'data.table' package in R) named "dftr". Model fits are in the R data file, also as a data.table, labelled dfM3. Stimulus onset codes are: 1 & 101 = Go-to-Avoid; 2 & 202 = Go-to-Win; 3 & 303 = NoGo-to-Avoid; 4 & 104 = NoGo-to-Win. (with 100s as invalid stimuli, or requiring the opposite response based on the contingency) Feedback onset codes are as follows: 21, 121, 41, 141 = win (thumbs up); 29, 129, 9, 109 = lose (thumbs down); 20, 120, 40, 140, 30, 130, 10, 110 = no change (horizontal thumb). Response onset codes are: 301, 302, 303, 304 for a response to a 'valid' stimulus (not necessarily correct - refers to contingency); 401, 402, 403, 404 for a response to an invalid stimulus. Hope you enjoy!

Single-cell RNA sequencing of CNS-infiltrating HSC-derived phagocytes of Ms4a3Ai14, BM chimeric mice (CD45.2 Csf2rb-/-: CD45.1 Csf2rb+/+ and CD45.2 Ifngr1-/-: CD45.1 Ifngr1+/+) using 10X Genomics platform. IFN-γ and GM-CSF control complementary differentiation programs in the monocyte to phagocyte transition during neuroinflammation.

Single-cell RNA sequencing of CNS-infiltrating HSC-derived phagocytes of Ms4a3Ai14 at onset and peak EAE,  BM chimeric mice (CD45.2 Csf2rb-/-: CD45.1 Csf2rb+/+ and CD45.2 Ifngr1-/-: CD45.1 Ifngr1+/+) using 10X Genomics platform. The sorted cells were loaded into 10x Genomics Chromium in parallel. Libraries were prepared as per the manufacturer's protocol (Chromium Next GEM Single Cell 3ʹ Reagent Kits v3.1 protocol) and sequenced on an Illumina NovaSeq sequencer according to 10X Genomics recommendations (paired-end reads, R1=28, i7=8, R2=91) to a depth of around 50,000 reads per cell. Initial processing was done using Cell Ranger (v3.1.0) mkfastq and count (reads were aligned to GENCODE reference build GRCm38.p6 Release M23 with added tdTomato sequence for the dataset from Ms4a3Ai14 mouse and collapse UMIs). Starting from the filtered gene-cell count matrix produced by CellRranger's in-built cell calling algorithms, we proceeded with Seurat v4 workflow.

Single-cell RNA sequencing of Lymph node-infiltrating HSC-derived phagocytes of Ms4a3Ai14 using 10X Genomics platform. IFN-γ and GM-CSF control complementary differentiation programs in the monocyte to phagocyte transition during neuroinflammation.

Single-cell RNA sequencing of Lymph node-infiltrating HSC-derived phagocytes of Ms4a3Ai14 at onset and peak EAE using 10X Genomics platform. The sorted cells were loaded into 10x Genomics Chromium in parallel. Libraries were prepared as per the manufacturer's protocol (Chromium Next GEM Single Cell 3ʹ Reagent Kits v3.1 protocol) and sequenced on an Illumina NovaSeq sequencer according to 10X Genomics recommendations (paired-end reads, R1=28, i7=8, R2=91) to a depth of around 50,000 reads per cell. Initial processing was done using Cell Ranger (v3.1.0) mkfastq and count (reads were aligned to GENCODE reference build GRCm38.p6 Release M23 with added tdTomato sequence for the dataset from Ms4a3Ai14 mouse and collapse UMIs). Starting from the filtered gene-cell count matrix produced by CellRranger's in-built cell calling algorithms, we proceeded with Seurat v4 workflow.

Single-cell RNA sequencing of Bone Marrow-infiltrating HSC-derived phagocytes of Ms4a3Ai14 using 10X Genomics platform. IFN-γ and GM-CSF control complementary differentiation programs in the monocyte to phagocyte transition during neuroinflammation.

Single-cell RNA sequencing of Bone Marrow-infiltrating HSC-derived phagocytes of Ms4a3Ai14 at onset and peak EAE using 10X Genomics platform. The sorted cells were loaded into 10x Genomics Chromium in parallel. Libraries were prepared as per the manufacturer's protocol (Chromium Next GEM Single Cell 3ʹ Reagent Kits v3.1 protocol) and sequenced on an Illumina NovaSeq sequencer according to 10X Genomics recommendations (paired-end reads, R1=28, i7=8, R2=91) to a depth of around 50,000 reads per cell. Initial processing was done using Cell Ranger (v3.1.0) mkfastq and count (reads were aligned to GENCODE reference build GRCm38.p6 Release M23 with added tdTomato sequence for the dataset from Ms4a3Ai14 mouse and collapse UMIs). Starting from the filtered gene-cell count matrix produced by CellRranger's in-built cell calling algorithms, we proceeded with Seurat v4 workflow.

Single-cell RNA sequencing of Blood-infiltrating HSC-derived phagocytes of Ms4a3Ai14 using 10X Genomics platform. IFN-γ and GM-CSF control complementary differentiation programs in the monocyte to phagocyte transition during neuroinflammation.

Single-cell RNA sequencing of Blood-infiltrating HSC-derived phagocytes of Ms4a3Ai14 at onset and peak EAE using 10X Genomics platform. The sorted cells were loaded into 10x Genomics Chromium in parallel. Libraries were prepared as per the manufacturer's protocol (Chromium Next GEM Single Cell 3ʹ Reagent Kits v3.1 protocol) and sequenced on an Illumina NovaSeq sequencer according to 10X Genomics recommendations (paired-end reads, R1=28, i7=8, R2=91) to a depth of around 50,000 reads per cell. Initial processing was done using Cell Ranger (v3.1.0) mkfastq and count (reads were aligned to GENCODE reference build GRCm38.p6 Release M23 with added tdTomato sequence for the dataset from Ms4a3Ai14 mouse and collapse UMIs). Starting from the filtered gene-cell count matrix produced by CellRranger's in-built cell calling algorithms, we proceeded with Seurat v4 workflow.

opencc-by-4.0Aug 2017View details →

Supplementary material 2 from: Redolfi De Zan L, Bardiani M, Antonini G, Campanaro A, Chiari S, Mancini E, Maura M, Sabatelli S, Solano E, Zauli A, Sabbatini Peverieri G, Roversi PF (2017) Guidelines for the monitoring of Cerambyx cerdo. In: Carpaneto GM, Audisio P, Bologna MA, Roversi PF, Mason F (Eds) Guidelines for the Monitoring of the Saproxylic Beetles protected in Europe. Nature Conservation 20: 129-164. https://doi.org/10.3897/natureconservation.20.12703

Field sheet 2 : Explanation note: Field sheet to be compiled during each survey (three a week for five weeks, 15 on the whole). For each trap checked, the operator must write the number of individuals captured, divided by sex and for trap height.