cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4184784
title: Dataset related to the article "The microRNA-34a-induced senescence-associated secretory phenotype (SASP) favors Vascular Smooth Muscle Cells calcification"

description: This record containsraw data related to the article"The microRNA-34a-induced senescence-associated secretory phenotype (SASP) favors Vascular Smooth Muscle Cells calcification" The senescence of vascular smooth muscle cells (VSMCs), characterized by the acquisition of senescence-associated secretory phenotype (SASP), is relevant for VSMCs osteoblastic differentiation and vascular calcification (VC). MicroRNA-34a (miR-34a) is a driver of such phenomena and could play a role in vascular inflammaging. Herein, we analyzed the relationship between miR-34a and the prototypical SASP component IL6 in <em>in vitro</em> and <em>in vivo</em> models. miR-34a and IL6 levels increased and positively correlated in aortas of 21 months-old male C57BL/6J mice and in human aortic smooth muscle cells (HASMCs) isolated from donors of different age and undergone senescence. Lentiviral overexpression of miR-34a in HASMCs enhanced IL6 secretion. HASMCs senescence and calcification accelerated after exposure to conditioned medium of miR-34a-overexpressing cells. Analysis of miR-34a-induced secretome revealed enhancement of several pro-inflammatory cytokines and chemokines, including IL6, pro-senescent growth factors and matrix-degrading molecules. Moreover, induction of aortas medial calcification and concomitant IL6 expression, with an overdose of vitamin D, were reduced in male C57BL/6J <em>Mir34a<sup>-/-</sup></em> mice. Finally, a positive correlation was observed between circulating miR-34a and IL6 in healthy subjects of 20-90 years. Hence, the vascular age-associated miR-34a promotes VSMCs SASP activation and contributes to arterial inflammation and dysfunctions such as VC.
description: This research was supported by Fondazione Cariplo (Research on Ageing diseases 2015) and Centro Cardiologico Monzino (Ricerca Corrente) to A.R.. E.Z., I.B. and F.S.E.Z. were supported by Fondazione Veronesi Fellowship (2017-202019).
DOI: 10.5281/zenodo.4121665
title: Dataset related to the article "Predictive Value of Pre‐Operative 2D and 3D Transthoracic Echocardiography in Patients Undergoing Mitral Valve Repair: Long Term Follow Up of Mitral Valve Regurgitation Recurrence and Heart Chamber Remodeling"

description: This record contains raw data related to the article "Predictive Value of Pre‐Operative 2D and 3D Transthoracic Echocardiography in Patients Undergoing Mitral Valve Repair: Long Term Follow Up of Mitral Valve Regurgitation Recurrence and Heart Chamber Remodeling" <strong>Abstract</strong>: The “ideal” management of asymptomatic severe mitral regurgitation (MR) in valve<br> prolapse (MVP) is still debated. The aims of this study were to identify pre‐operatory parameters<br> predictive of residual MR and of early and long‐term favorable remodeling after MVP repair. We<br> included 295 patients who underwent MV repair for MVP with pre‐operatory two‐ and threedimensional<br> transthoracic echocardiography (2DTTE and 3DTTE) and 6‐months (6M) and 3‐years<br> (3Y) follow‐up 2DTTE. MVP was classified by 3DTTE as simple or complex and surgical procedures<br> as simple or complex. Pre‐operative echo parameters were compared to post‐operative values at 6M<br> and 3Y. Patients were divided into Group 1 (6M‐MR &lt; 2) and Group 2 (6M‐MR ≥ 2), and predictors<br> of MR  2 were investigated. MVP was simple in 178/295 pts, and 94% underwent simple<br> procedures, while in only 42/117 (36%) of complex MVP a simple procedure was performed. A<br> significant relation among prolapse anatomy, surgical procedures and residual MR was found. Postoperative<br> MR ≥ 2 was present in 9.8%: complex MVP undergoing complex procedures had twice the<br> percentage of MR ≥ 2 vs. simple MVP and simple procedures. MVP complexity resulted<br> independent predictor of 6M‐MR ≥ 2. Favorable cardiac remodeling, initially found in all cases, was<br> maintained only in MR &lt; 2 at 3Y. Pre‐operative 3DTTE MVP morphology identifies pts undergoing<br> simple or complex procedures predicting MR recurrence and favorable cardiac remodeling.
DOI: 10.5281/zenodo.4121664
title: Dataset related to the article "Predictive Value of Pre‐Operative 2D and 3D Transthoracic Echocardiography in Patients Undergoing Mitral Valve Repair: Long Term Follow Up of Mitral Valve Regurgitation Recurrence and Heart Chamber Remodeling"

description: This record contains raw data related to the article "Predictive Value of Pre‐Operative 2D and 3D Transthoracic Echocardiography in Patients Undergoing Mitral Valve Repair: Long Term Follow Up of Mitral Valve Regurgitation Recurrence and Heart Chamber Remodeling" <strong>Abstract</strong>: The “ideal” management of asymptomatic severe mitral regurgitation (MR) in valve<br> prolapse (MVP) is still debated. The aims of this study were to identify pre‐operatory parameters<br> predictive of residual MR and of early and long‐term favorable remodeling after MVP repair. We<br> included 295 patients who underwent MV repair for MVP with pre‐operatory two‐ and threedimensional<br> transthoracic echocardiography (2DTTE and 3DTTE) and 6‐months (6M) and 3‐years<br> (3Y) follow‐up 2DTTE. MVP was classified by 3DTTE as simple or complex and surgical procedures<br> as simple or complex. Pre‐operative echo parameters were compared to post‐operative values at 6M<br> and 3Y. Patients were divided into Group 1 (6M‐MR &lt; 2) and Group 2 (6M‐MR ≥ 2), and predictors<br> of MR  2 were investigated. MVP was simple in 178/295 pts, and 94% underwent simple<br> procedures, while in only 42/117 (36%) of complex MVP a simple procedure was performed. A<br> significant relation among prolapse anatomy, surgical procedures and residual MR was found. Postoperative<br> MR ≥ 2 was present in 9.8%: complex MVP undergoing complex procedures had twice the<br> percentage of MR ≥ 2 vs. simple MVP and simple procedures. MVP complexity resulted<br> independent predictor of 6M‐MR ≥ 2. Favorable cardiac remodeling, initially found in all cases, was<br> maintained only in MR &lt; 2 at 3Y. Pre‐operative 3DTTE MVP morphology identifies pts undergoing<br> simple or complex procedures predicting MR recurrence and favorable cardiac remodeling.
DOI: 10.5281/zenodo.3957755
title: CADA Training Dataset, image and geometry data

description: Training data for the CADA challenge(s) for tasks 1, 2 and 3. The rupture information for task 3 is available via a separate dataset (check https://cada-rre.grand-challenge.org/) See https://cada.grand-challenge.org/Copyright/ for license info on the data. If you have already downloaded an earlier version, you only need to download <strong>CADA-AS-Training_SeedPoints.zip </strong>and update <strong>CADA-Training_MaskImages-NIFTI.zip </strong>and <strong>delete all PA3* files </strong>(dataset was found unsuitable). See README.md for detailed info.
DOI: 10.5281/zenodo.3747759
title: CADA Training Dataset, image and geometry data

description: Training data for the CADA challenge(s) for tasks 1, 2 and 3. The rupture information for task 3 is available via a separate dataset (check https://cada-rre.grand-challenge.org/) See https://cada.grand-challenge.org/Copyright/ for license info on the data. If you have already downloaded an earlier version, you only need to download <strong>CADA-AS-Training_SeedPoints.zip </strong>and update <strong>CADA-Training_MaskImages-NIFTI.zip </strong>and <strong>delete all PA3* files </strong>(dataset was found unsuitable). See README.md for detailed info.
DOI: 10.5281/zenodo.4002043
title: CADA Training Dataset, Part 2 (Add-On for Task 3)

description: Second part of the training data for the CADA challenge 2020 required only for task 3. Download and use restricted registered participants of the CADA Challenge 2020. See https://cada.grand-challenge.org/Copyright/ for license info on the data. See _README.md for detailed info.
DOI: 10.5281/zenodo.3753170
title: CADA Training Dataset, Part 2 (Add-On for Task 3)

description: Second part of the training data for the CADA challenge 2020 required only for task 3. Download and use restricted registered participants of the CADA Challenge 2020. See https://cada.grand-challenge.org/Copyright/ for license info on the data. See _README.md for detailed info.
DOI: 10.5281/zenodo.3971914
title: CADA Test Dataset, original image data

description: Test data for the CADA challenge(s). This dataset contains only the original image data, which is sufficient to submit results for the detection task (Task 1). For the segmentation and rupture risk estimation tasks, additional test data is necessary and will be provided according to schedule as separate datasets. See https://cada.grand-challenge.org/Copyright/ for license info on the data. See README.md for detailed info.
DOI: 10.5281/zenodo.3971911
title: CADA Test Dataset, original image data

description: Test data for the CADA challenge(s). This dataset contains only the original image data, which is sufficient to submit results for the detection task (Task 1). For the segmentation and rupture risk estimation tasks, additional test data is necessary and will be provided according to schedule as separate datasets. See https://cada.grand-challenge.org/Copyright/ for license info on the data. See README.md for detailed info.
DOI: 10.5281/zenodo.3989437
title: CADA Test Dataset Addon for Task 3: Vessel and Aneurysm Masks/Geometries

description: Test data addon for the CADA challenge task 3 (rupture risk estimation). This dataset is an addon required for providing processed results for Task 3. See challenge web site for a link to the original image data. See https://cada.grand-challenge.org/Copyright/ for license info on the data. See README.md for detailed info.
DOI: 10.5281/zenodo.3989436
title: CADA Test Dataset Addon for Task 3: Vessel and Aneurysm Masks/Geometries

description: Test data addon for the CADA challenge task 3 (rupture risk estimation). This dataset is an addon required for providing processed results for Task 3. See challenge web site for a link to the original image data. See https://cada.grand-challenge.org/Copyright/ for license info on the data. See README.md for detailed info.
DOI: 10.5519/qd.tjd5g5pl
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (7534 records)
DOI: 10.6084/m9.figshare.13181366.v1
title: Learning what is irrelevant or relevant: Expectations facilitate distractor inhibition and target facilitation through distinct neural mechanisms

description: Part of the EEG data saved at OSF
DOI: 10.5258/soton/d1616
title: Data for 'Effects of laser shock peening on mechanisms of short crack initiation and propagation'

description: Data supporting the paper Sanchez AG, You C, Leering M, Glaser D, Furfari D, Fitzpatrick ME, Wharton J, Reed PAS. "Effects of laser shock peening on mechanisms of short crack initiation and propagation" International Journal of Fatigue. Contains all data
DOI: 10.6084/m9.figshare.13180169.v1
title: R0220_20180301a_videos

description: Rat 0220, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.6084/m9.figshare.13181366
title: Learning what is irrelevant or relevant: Expectations facilitate distractor inhibition and target facilitation through distinct neural mechanisms

description: Part of the EEG data saved at OSF
DOI: 10.5258/soton/d1617
title: Dataset for Efficient Energy Conversion in Electrically Assisted Bicycles Using a Switched Reluctance Machine under Torque Control

description: This dataset supports the publication: Bahareh Zaghari, Aleksas Stuikys, Alex S. Weddell, Steve Beeby Efficient Energy Conversion in Electrically Assisted Bicycles Using a Switched Reluctance Machine under Torque Control IEEE ACCESS
DOI: 10.25345/c5mr3t
title: MassIVE MSV000086402 - Proteome analysis of cblX syndrome
title: CblX is a recently described X-linked variant of vitamin B12 (cobalamin) deficiency cblC type. While cblC is due to mutations in MMACHC, an enzyme in the cobalamin metabolic pathway, cblX is caused by mutations in the transcriptional cofactor HCFC1 and its obligate transcription factor partner RONIN. Since HCFC1 and RONIN jointly regulate MMACHC transcription, cblX patients suffer from low levels of MMACHC during development and thus develop a disease highly similar to cblC. Beyond this finding, there is little else known about the other genes de-regulated in cblX and the resulting pathophysiology. Therefore, we have generated a Ronin point mutation mouse model, which carries the same missense mutation observed in a cblX patient. We have found that our cblX mice exhibit several defects typically observed in cblC patients. To further discover the proteomic changes in cblX mice, we collected mouse embryonic fibroblasts (MEFs) and performed mass spectrometry experiments.
DOI: 10.6084/m9.figshare.13172246.v1
title: 2020 01 03 VID00028 Analysis and Results

description: Slide presentation with frame-by-frame, context, and discussion with unambiguous detection and identification of at least two anomalous large non-human primates.<br>For transparency, includes the Java program used for custom frame-by-frame image stabilization, the anchor point data file, and a close up of the anchor point.<br><br>NOTE: The unrelated final GoPro segment from 3 January 2020 is also stored in this folder. See 2020 01 03 Field Notes for the first four segments. Then see 2020 01 09 Field Notes for GoPro video of the next hike starting from a location near to where this video drops off. The full set of GoPro videos provide a wide angle view of the areas surveyed along the primary route taken repeatedly in gathering data on the animals' behavioral patterns.
DOI: 10.5519/qd.kptw8j9p
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (11 records)
DOI: 10.15131/shef.data.13176131
title: Data for the paper: "Optimization of the failure criterion in micro-Finite Element models of the mouse tibia for the non-invasive prediction of its failure load in preclinical applications"

description: Data used in the paper: "Optimization of the failure criterion in micro-Finite Element models of the mouse tibia for the non-invasive prediction of its failure load in preclinical applications"Oliviero, Owen, Reilly, Bellantuono, Dall'Ara<br>published in JMBBM<br><br>We share here an example of ex vivo microCT image used for the assessment, and the results obtained from the different analyses.<br>Short description of the files included:<br>Densitometric_and_morphometric_parameters.xlsx includes:-Densitometric parameters, and correlations with experimental mechanical data, calculated for each specimen and each region of interestTotal = total volume of interest (80% of tibia length)10 Longitudinal sections: section 1 corresponds to proximal tibia, section 10 corresponds to distal tibiaSectors: anterior (A), posterior (P), medial (M) and lateral (L)<br>-Morphometric parameters calculated for each specimen, and correlations with experimental mechanical data. -microFE_results.xlsx includes:Stiffness estimated for each specimen with microFE models, and correlations with experimental data.Failure load estimated with microFE models, and correlations with experimental data, for each failure criterion:Pistoia methodCompression: tibia fails when a portion of the nodes (failure volume) reaches a critical compressive (third principal) strain levelTension: tibia fails when a portion of the nodes reaches a critical tensile (first principal) strain levelCompression&Tension: tibia fails when a portion of the nodes reaches a critical strain, either in tension or in compressionSections: tibia fails when the median first principal strain or third principal strain in one section (tibia divided into ten portions) or in one sector (tibia divided into ten sections and each section divided into anterior and posterior partitions; 20 portions in total) reaches a critical strain level -microCT data:Example of a segmented microCT image used as input for the microFE model (Specimen1, C57BL/6J, wild type, 16 weeks of age, right tibia).<br><br>In case the reader is interested in the whole database they should contact Dr Enrico Dall'Ara (e.dallara@sheffield.ac.uk).
DOI: 10.15131/shef.data.13176131.v1
title: Data for the paper: "Optimization of the failure criterion in micro-Finite Element models of the mouse tibia for the non-invasive prediction of its failure load in preclinical applications"

description: Data used in the paper: "Optimization of the failure criterion in micro-Finite Element models of the mouse tibia for the non-invasive prediction of its failure load in preclinical applications"Oliviero, Owen, Reilly, Bellantuono, Dall'Ara<br>published in JMBBM<br><br>We share here an example of ex vivo microCT image used for the assessment, and the results obtained from the different analyses.<br>Short description of the files included:<br>Densitometric_and_morphometric_parameters.xlsx includes:-Densitometric parameters, and correlations with experimental mechanical data, calculated for each specimen and each region of interestTotal = total volume of interest (80% of tibia length)10 Longitudinal sections: section 1 corresponds to proximal tibia, section 10 corresponds to distal tibiaSectors: anterior (A), posterior (P), medial (M) and lateral (L)<br>-Morphometric parameters calculated for each specimen, and correlations with experimental mechanical data. -microFE_results.xlsx includes:Stiffness estimated for each specimen with microFE models, and correlations with experimental data.Failure load estimated with microFE models, and correlations with experimental data, for each failure criterion:Pistoia methodCompression: tibia fails when a portion of the nodes (failure volume) reaches a critical compressive (third principal) strain levelTension: tibia fails when a portion of the nodes reaches a critical tensile (first principal) strain levelCompression&Tension: tibia fails when a portion of the nodes reaches a critical strain, either in tension or in compressionSections: tibia fails when the median first principal strain or third principal strain in one section (tibia divided into ten portions) or in one sector (tibia divided into ten sections and each section divided into anterior and posterior partitions; 20 portions in total) reaches a critical strain level -microCT data:Example of a segmented microCT image used as input for the microFE model (Specimen1, C57BL/6J, wild type, 16 weeks of age, right tibia).<br><br>In case the reader is interested in the whole database they should contact Dr Enrico Dall'Ara (e.dallara@sheffield.ac.uk).
DOI: 10.25392/leicester.data.13139363
title: Radar Blackouts at Mars

description: This data set contains the time when the radars Mars Advanced Radar for Subsurface and Ionosphere Sounding (MARSIS) on board Mars Express and the Shallow Radar (SHARAD) on board Mars Reconnaissance Orbiter suffered total or partial blackouts when sounding the surface of Mars. This data set accompanies the following paper, which should be cited if the dataset is used: M. Lester, B. Sanchez-Cano, D. Potts, R. Lillis, M. Cartacci, F. Bernardini, R. Orosei, M. Perry, N. Putzig, B. Campbell, P.-L. Blelly, S. Milan, H. Opgenoorth, O.Witasse, Eleven Years of Radar Blackouts at Mars: Mars Express, Mars Reconnaissance Orbiter and MAVEN Observations, under review at Journal of Geophysical Research Space Physics (awaiting DOI).
DOI: 10.25392/leicester.data.13139363.v1
title: Radar Blackouts at Mars

description: This data set contains the time when the radars Mars Advanced Radar for Subsurface and Ionosphere Sounding (MARSIS) on board Mars Express and the Shallow Radar (SHARAD) on board Mars Reconnaissance Orbiter suffered total or partial blackouts when sounding the surface of Mars. This data set accompanies the following paper, which should be cited if the dataset is used: M. Lester, B. Sanchez-Cano, D. Potts, R. Lillis, M. Cartacci, F. Bernardini, R. Orosei, M. Perry, N. Putzig, B. Campbell, P.-L. Blelly, S. Milan, H. Opgenoorth, O.Witasse, Eleven Years of Radar Blackouts at Mars: Mars Express, Mars Reconnaissance Orbiter and MAVEN Observations, under review at Journal of Geophysical Research Space Physics (awaiting DOI).
DOI: 10.25392/leicester.data.13148036
title: Appendices to PhD thesis entitled: To identity and beyond: exploring the limits of the archaeological study of identity

description: Appendices to PhD thesis entitled: To identity and beyond: exploring the limits of the archaeological study of identity<br>Includes:Appendix A: Original description of the criteria for application of category labelsAppendix B: Discussion of the utility of Ontological Data Modelling for FST in archaeologyAppendix C: Digital image of Figure B.3Appendix D: Graph Markup Language file of Figure B.3Appendix E: Populated Ontological Data Model of data from Rottweil's Kappelenösch cemetery and Nikolausfeld excavations.Appendix F: Excel document with embedded VBA subroutines for automatically generating dates for closed contextsAppendix G: VBA code for automated max-min matrix composition<br>
DOI: 10.25392/leicester.data.13148036.v1
title: Appendices to PhD thesis entitled: To identity and beyond: exploring the limits of the archaeological study of identity

description: Appendices to PhD thesis entitled: To identity and beyond: exploring the limits of the archaeological study of identity<br>Includes:Appendix A: Original description of the criteria for application of category labelsAppendix B: Discussion of the utility of Ontological Data Modelling for FST in archaeologyAppendix C: Digital image of Figure B.3Appendix D: Graph Markup Language file of Figure B.3Appendix E: Populated Ontological Data Model of data from Rottweil's Kappelenösch cemetery and Nikolausfeld excavations.Appendix F: Excel document with embedded VBA subroutines for automatically generating dates for closed contextsAppendix G: VBA code for automated max-min matrix composition<br>
DOI: 10.5517/ccdc.csd.cc26b9nj
title: CCDC 2035697: Experimental Crystal Structure Determination

description: Related Article: Peter G. Jones, Daniel Zaremba, Hans-Hermann Johannes, Wolfgang Kowalski|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26b9pk
title: CCDC 2035698: Experimental Crystal Structure Determination

description: Related Article: Peter G. Jones, Daniel Zaremba, Hans-Hermann Johannes, Wolfgang Kowalski|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26b9ql
title: CCDC 2035699: Experimental Crystal Structure Determination

description: Related Article: Peter G. Jones, Daniel Zaremba, Hans-Hermann Johannes, Wolfgang Kowalski|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26bd76
title: CCDC 2035777: Experimental Crystal Structure Determination

description: Related Article: Nerissa A. Lewis, Luigi G. Marzilli, Frank R. Fronczek|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26bd87
title: CCDC 2035778: Experimental Crystal Structure Determination

description: Related Article: Nerissa A. Lewis, Luigi G. Marzilli, Frank R. Fronczek|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26bkhm
title: CCDC 2035940: Experimental Crystal Structure Determination

description: Related Article: Nerissa A. Lewis, Luigi G. Marzilli, Frank R. Fronczek|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26bscq
title: CCDC 2036153: Experimental Crystal Structure Determination

description: Related Article: Nerissa A. Lewis, Luigi G. Marzilli, Frank R. Fronczek|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26c2b0
title: CCDC 2036431: Experimental Crystal Structure Determination

description: Related Article: Peter G. Jones, Daniel Zaremba, Hans-Hermann Johannes, Wolfgang Kowalski|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26c2ym
title: CCDC 2036450: Experimental Crystal Structure Determination

description: Related Article: Arnold L. Rheingold and David S. Glueck|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc26c30q
title: CCDC 2036452: Experimental Crystal Structure Determination

description: Related Article: Arnold L. Rheingold and David S. Glueck|2020|CSD Communication|||