BUSCADOR RECOLECTA

There are twenty zip files each one corresponding to a participant. The acronym PT stands for patients (from 01 to 10) and HC stands for healthy controls (from 01 to 10). Once unzipped, structural and functional data of each patient and healthy control are located in the folder indicated by the specific acronym and number of the participant (i.e. PT01). Thus, each folder contains the original functional data of the resting state sequence (fmri.nii.gz), the preprocessed functional data (fmri_res.nii.gz), the original structural T1-weighted image (T1.nii.gz) and the structural T1-weighted image after applying the brain extraction with the Brain Extraction Tool of fsl (T1_brain.nii.gz) and used to perform the co-registration with the functional data. All images are in NIfTI (Neuroimaging Computer Technology Initiative) format, as a gzip compressed file, normally used by different software as the software library FMRIB (FSL). We also provide the NIfTI file of the AAL Atlas used to parcellate the brain during the analysis (AAL_Contract_90_3MM.nii) and the corresponding text file indicating the list of regions composing the atlas (AAL_LabelID_90.txt)., Podeu consultar el document publicat a: http://hdl.handle.net/2445/161359, Dades primàries associades a un article publicat a la revista PLoS One, 2020, vol. 15, num. 1, p. e0226816 [https://doi.org/10.1371/journal.pone.0226816], We tested 10 hemianopic patients and 10 healthy participants. They were scanned in a 1.5 Tesla Philips scanner at the Borgo Roma Hospital in Verona (Italy). We collected a whole brain high-resolution (1x1x1 mm3) 3D T1-weighted image with magnetization-prepared rapid acquisition gradient echo (MPRAGE) and one hundred sixty resting state volumes with TR=2500ms, Echo Time=50ms; 30 slices with slice thickness of 4mm, Field of View = 224x224mm, time duration = 6.47m and echo train length = 39. The entire sample was were scanned during the period of time going from February 2017 until July 2018.

Dades de l'article publicat a la revista Food Chemistry, Volume 307, 1 March 2020, 125556. El podeu consultar a http://hdl.handle.net/2445/143358, Data base containing SPME-GC-MS raw analytical data obtained and used by Quintanilla-Casas et al. (Food Chemistry, 2020, 125556). Data correspond to 82 authentic and traceable olive oil samples, declared as EVOO by the suppliers obtained in the framework of OLEUM project (EC H2020 Programme 2014–2020) from seven different EU and non-EU countries: Croatia (n=11); Slovenia (SVN) (n=8); Spain (ESP) (n=17); Italy (ITA) (n=15); Greece (GRC) (n=6); Morocco (MAR) (n=15) and Turkey (TUR) (n=10). With the aim of reflecting the real production scenario, EVOO samples in this prospective study were obtained under usual production practices for commercial purposes, and thus consisted of both monovarietal oils as well as market blends of olive cultivars typical of each geographical origin. Briefly, data correspond to SPME-GC-MS scan intensities of the specific sesquiterpene hydrocarbon (SH) ions (m/z 93, 107, 119, 135, 157, 159, 161, 189 and 204) obtained from the Total Ion Current (TIC) between the 18th to the 30th minute. Thus, 2467 scans were obtained for each m/z ion implying 22203 variables per sample., SPME-GC-MS data have been obtained by researchers in the OLEUM project This work was developed in the context of the project OLEUM “Advanced solutions for assuring authenticity and quality of olive oil at global scale”, funded by the European Commission within the Horizon 2020 Program (2014–2020, grant agreement no. 635690). The information and views set out in this article are those of the author(s) and do not necessarily reflect the official opinion of the European Union. Neither the European Union institutions and bodies nor any person acting on their behalf may be held responsible for the use which may be made of the information contained therein. The study was also supported by the Ministerio de Ciencia, Innovación y Universidades (MICINN) from Spain through the Juan de la Cierva and Ramon y Cajal programs (JCI-2012_13412 and RYC-2017-23601), and by the Ministerio de Educación, Cultura y Deporte (MECD) from Spain through the FPU pre-doctoral program (FPU16/01744).

Dades primàries de l'article publicat a la revista Food Science and Technology 121: 108936, Dataset containing SPME-GC-MS raw analytical data (total ion chromatograms, not aligned) obtained and used by Quintanilla-Casas et al. (LWT - Food Science and Technology 121: 108936). Data correspond to the volatile fingerprint of 174 authentic and traceable virgin olive oil samples previously graded by six official sensory panels (data from 2 outlier samples are not included) in the framework of OLEUM project (EC H2020 Programme 2014–2020). Briefly, data correspond to SPME-GC-MS scan intensities of the total ion chromatogram at each retention time from 5.5 to 61.96 min. These data were aligned and used under a fingerprinting approach by Quintanilla-Casas et al. to develop a classification model (PLS-DA approach) to verify the sensory quality of virgin olive oils, and it was suggested as an instrumental method to support sensory panels., SPME-GC-MS data have been obtained by researchers in the OLEUM project This work was developed in the context of the project OLEUM “Advanced solutions for assuring authenticity and quality of olive oil at global scale”, funded by the European Commission within the Horizon 2020 Program (2014–2020, grant agreement no. 635690). The information and views set out in this article are those of the author(s) and do not necessarily reflect the official opinion of the European Union. Neither the European Union institutions and bodies nor any person acting on their behalf may be held responsible for the use which may be made of the information contained therein. The study was also supported by the Ministerio de Ciencia, Innovación y Universidades (MICINN) from Spain through the Juan de la Cierva and Ramon y Cajal programs (JCI-2012_13412 and RYC-2017-23601), and by the Ministerio de Educación, Cultura y Deporte (MECD) from Spain through the FPU pre-doctoral program (FPU16/01744).