cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3337695
title: BCdatabaser - 18s.apicystis.none.2019-07-16.zip

description: Parameters: --marker-search-string 18S --taxonomic-range Apicystis --sequence-length-filter 100:2000 --sequences-per-taxon 9
description: This dataset was automatically created with data from NCBI using the BCdatabaser tool
description: {"references": ["Keller et al. (2019) BCdatabaser: on-the-fly reference database creation for (meta-)barcoding. EcoEvoRxiv (2019); https://doi.org/10.32942/osf.io/cmfu2 - https://github.com/molbiodiv/bcdatabaser", "eutils: Sayers E. E-utilities Quick Start. 2008 Dec 12 [Updated 2018 Oct 24]. In: Entrez Programming Utilities Help [Internet]. Bethesda (MD): National Center for Biotechnology Information (US); 2010-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK25500/", "NCBI::Taxonomy: F\u00f6rster et al. https://github.com/greatfireball/NCBI-Taxonomy - F\u00f6rster F. greatfireball/NCBI-Taxonomy v0.90. Zenodo. 2018 Oct 15; https://doi.org/10.5281/zenodo.1462861", "SeqFilter: Hackl et al. https://github.com/BioInf-Wuerzburg/SeqFilter", "dispr: Cofield et al. https://github.com/douglasgscofield/dispr", "Krona: Ondov BD, Bergman NH, and Phillippy AM. Interactive metagenomic visualization in a Web browser. BMC Bioinformatics. 2011 Sep 30; 12(1):385."]}
DOI: 10.5281/zenodo.3337264
title: Binary neutron-star simulation SXS:NSNS:0002

description: Simulation of a neutron-star binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.3337694
title: BCdatabaser - 18s.apicystis.none.2019-07-16.zip

description: Parameters: --marker-search-string 18S --taxonomic-range Apicystis --sequence-length-filter 100:2000 --sequences-per-taxon 9
description: This dataset was automatically created with data from NCBI using the BCdatabaser tool
description: {"references": ["Keller et al. (2019) BCdatabaser: on-the-fly reference database creation for (meta-)barcoding. EcoEvoRxiv (2019); https://doi.org/10.32942/osf.io/cmfu2 - https://github.com/molbiodiv/bcdatabaser", "eutils: Sayers E. E-utilities Quick Start. 2008 Dec 12 [Updated 2018 Oct 24]. In: Entrez Programming Utilities Help [Internet]. Bethesda (MD): National Center for Biotechnology Information (US); 2010-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK25500/", "NCBI::Taxonomy: F\u00f6rster et al. https://github.com/greatfireball/NCBI-Taxonomy - F\u00f6rster F. greatfireball/NCBI-Taxonomy v0.90. Zenodo. 2018 Oct 15; https://doi.org/10.5281/zenodo.1462861", "SeqFilter: Hackl et al. https://github.com/BioInf-Wuerzburg/SeqFilter", "dispr: Cofield et al. https://github.com/douglasgscofield/dispr", "Krona: Ondov BD, Bergman NH, and Phillippy AM. Interactive metagenomic visualization in a Web browser. BMC Bioinformatics. 2011 Sep 30; 12(1):385."]}
DOI: 10.5281/zenodo.3338394
title: Data set supporting Journal article: Siebicke, L., and Emad, A., "True eddy accumulation trace gas flux measurements: proof of concept", Atmos. Meas. Tech., 12, 1–28, 2019.

description: This data set contains carbon dioxide trace gas flux measurements obtained by the true eddy accumulation technique as described in the research article: Siebicke, L., and Emad, A., "True eddy accumulation trace gas flux measurements: proof of concept", Atmos. Meas. Tech., 12, 1–28, 2019. It contains meteorological measurements (file "meteo.csv"), turbulent energy fluxes (file "energy_fluxes.csv"), three-diomensional wind vector measurements ("file wind.csv"), and carbon dioxide trace gas fluxes obtained by true eddy accumulation (file "co2_flux_TEA.csv") and eddy covariance using data from two separate anomemoters (files "co2_flux_EC_TEA_sonic.csv" and "co2_flux_EC_EC_sonic.csv").
DOI: 10.5281/zenodo.3338395
title: Data set supporting Journal article: Siebicke, L., and Emad, A., "True eddy accumulation trace gas flux measurements: proof of concept", Atmos. Meas. Tech., 12, 1–28, 2019.

description: This data set contains carbon dioxide trace gas flux measurements obtained by the true eddy accumulation technique as described in the research article: Siebicke, L., and Emad, A., "True eddy accumulation trace gas flux measurements: proof of concept", Atmos. Meas. Tech., 12, 1–28, 2019. It contains meteorological measurements (file "meteo.csv"), turbulent energy fluxes (file "energy_fluxes.csv"), three-diomensional wind vector measurements ("file wind.csv"), and carbon dioxide trace gas fluxes obtained by true eddy accumulation (file "co2_flux_TEA.csv") and eddy covariance using data from two separate anomemoters (files "co2_flux_EC_TEA_sonic.csv" and "co2_flux_EC_EC_sonic.csv").
DOI: 10.25919/5d2e58a84bc93
title: Parkes observations for project P958 semester 2019APRS_48

description: Fast radio bursts (FRBs) continue to raise more questions than they answer. Until a few months ago, only one burst – the only one known to repeat - had been localized to a bright radio nebula (either a young supernova remnant or pulsar wind nebulae) in a distant dwarf galaxy. Over the last year searches with the Australian Square Kilometre Array Pathfinder (ASKAP) have detected 28 bursts, two of which have been localised to host galaxies at redshifts &gt; 0.3. These bursts and their hosts are very unlike the repeater, suggesting there may be a dichotomy in the population. Over the next six months we expect to detect another 12 FRBs, which will also have sub-arcsecond localisations. Here we propose to search this population for repeats. Our comprehensive sample and a dense monitoring campaign of well localised bursts, at a fluence limit more than 60 times lower than that of their detections, will either confirm the presence of additional repeating FRBs or the uniqueness of FRB 121102 amongst the population.
DOI: 10.6073/pasta/50e635a1ac210481b1ef9a5df3a3df60
title: Annual snow survey, Green Lakes Valley, Niwot Ridge, Colorado, 2013-ongoing

description: Yearly snow surveys were conducted in the Green Lakes Valley in the City of Boulder Watershed at the estimated peak of snowpack in late spring. Over a period of several days, surveying teams (1 to several people) traversed valley slopes measuring snow depth with avalanche probes. Locations of each depth measurement were recorded as waypoints in Garmin hand-held GPS units (eTrex Legend and eTrex Legend H models). Snow depths were recorded on standardized field sheets along with dates, recorder names, waypoint numbers, and comments. GPS locations were downloaded as text files from Garmin units using Topo! software, specifying NAD83 for surveys conducted after 2009. Download files contained waypoint number, latitude, longitude, date, and elevation. Each file was imported into a Microsoft Excel spreadsheet and snow depths corresponding to waypoints were entered manually from field sheets. Shapefiles were constructed in ArcInfo/ArcGIS from dbf files generated either directly from Excel spreadsheets (before 2008) or after importing into Microsoft Access and then exporting as dbfs. All shapefiles are provided in a UTM zone 13 projection and NAD83 horizontal datum.
DOI: 10.25345/c5hs9h
title: MassIVE MSV000084097 - NPC1 lipidomics by LC-MS and FAMEs by GC-MS
title: Untargeted lipidomic analysis via QTOF and FAME analysis by GC-EI-MS in Niemann-pick type C1
DOI: 10.25810/fj1y-8c74.6
title: International Wire Services Coverage of Climate Change or Global Warming, 2004-2019 - June 2019

description: The Media and Climate Change Observatory Data monitors 79 sources (across newspapers, radio and TV) in 38 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://sciencepolicy.colorado.edu/icecaps/research/media_coverage/index.html. These data include Excel (.xlsx), CSV (.csv), and plain-text README files (.txt).
DOI: 10.25810/fx6e-r462.3
title: European Newspaper Coverage of Climate Change or Global Warming, 2004-2019 - June 2019

description: The Media and Climate Change Observatory Data monitors 74 sources (across newspapers, radio and TV) in 38 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://sciencepolicy.colorado.edu/icecaps/research/media_coverage/index.html. These data include Excel (.xlsx), CSV (.csv), and plain-text README files (.txt).
DOI: 10.5281/zenodo.3338691
title: DWD European Weather 2

description: opendata.dwd.de - OpenData by Deutscher Wetter Dienst Conditions: https://www.dwd.de/EN/service/copyright/copyright_node.html dates and times are UTC.
DOI: 10.21227/63es-sq40
title: Heritage Interpretation Simulation Dataset

description: This dataset details the raw data obtained from simulation experiments of heritage tourism. It details several parameter sweeps and experiments done to characterise an agent-based model created for the purpose of exploring the role of communication strategies and topology in determining the transformation of cultural systems. It characterises systems in terms of the stantardised entropy (HRel) of "local prototypes" (LP) - here understood as vectors of probabilities of interpretation of certain categories - as well as the convergence of these LP to the "Global Prototypes" (GP), using a simple ratio of the two Hrel (CL).
DOI: 10.21227/ghpx-pw02
title: Heritage Interpretation Simulation Dataset

description: This dataset details the raw data obtained from simulation experiments of heritage tourism. It details several parameter sweeps and experiments done to characterise an agent-based model created for the purpose of exploring the role of communication strategies and topology in determining the transformation of cultural systems. It characterises systems in terms of the stantardised entropy (HRel) of "local prototypes" (LP) - here understood as vectors of probabilities of interpretation of certain categories - as well as the convergence of these LP to the "Global Prototypes" (GP), using a simple ratio of the two Hrel (CL).
DOI: 10.25810/5dxz-xm93.15
title: Latin American Newspaper Coverage of Climate Change or Global Warming, 2004-2019 - June 2019

description: The Media and Climate Change Observatory Data monitors 74 sources (across newspapers, radio and TV) in 38 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://sciencepolicy.colorado.edu/icecaps/research/media_coverage/index.html. These data include Excel (.xlsx), CSV (.csv), and plain-text README files (.txt).
DOI: 10.25810/8196-e820.15
title: United Kingdom Newspaper Coverage of Climate Change or Global Warming, 2004-2019 - June 2019

description: The Media and Climate Change Observatory Data monitors 74 sources (across newspapers, radio and TV) in 38 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://sciencepolicy.colorado.edu/icecaps/research/media_coverage/index.html. These data include Excel (.xlsx), CSV (.csv), and plain-text README files (.txt).
DOI: 10.25810/c862-0e81.15
title: US Television Coverage of Climate Change or Global Warming, 2004-2019 - June 2019

description: The Media and Climate Change Observatory Data monitors 74 sources (across newspapers, radio and TV) in 38 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://sciencepolicy.colorado.edu/icecaps/research/media_coverage/index.html. These data include Excel (.xlsx), CSV (.csv), and plain-text README files (.txt).
DOI: 10.25810/jck1-hf50.15
title: United States Newspaper Coverage of Climate Change or Global Warming, 2004-2019 - June 2019

description: The Media and Climate Change Observatory Data monitors 74 sources (across newspapers, radio and TV) in 38 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://sciencepolicy.colorado.edu/icecaps/research/media_coverage/index.html. These data include Excel (.xlsx), CSV (.csv), and plain-text README files (.txt).
DOI: 10.25810/k55w-7a04.15
title: World Radio Coverage of Climate Change or Global Warming, 2004-2019 - June 2019

description: The Media and Climate Change Observatory Data monitors 74 sources (across newspapers, radio and TV) in 38 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://sciencepolicy.colorado.edu/icecaps/research/media_coverage/index.html. These data include Excel (.xlsx), CSV (.csv), and plain-text README files (.txt).
DOI: 10.25810/qt7k-6r09.2
title: Swedish Newspaper Coverage of Climate Change or Global Warming, 2004-2019 - June 2019

description: The Media and Climate Change Observatory Data monitors 74 sources (across newspapers, radio and TV) in 38 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://sciencepolicy.colorado.edu/icecaps/research/media_coverage/index.html. These data include Excel (.xlsx), CSV (.csv), and plain-text README files (.txt).
DOI: 10.5281/zenodo.3337768
title: BCdatabaser - 18s.crustacea.none.2019-07-16.zip

description: Parameters: --marker-search-string 18S --taxonomic-range Crustacea --sequence-length-filter 100:2000 --sequences-per-taxon 9
description: This dataset was automatically created with data from NCBI using the BCdatabaser tool
description: {"references": ["Keller et al. (2019) BCdatabaser: on-the-fly reference database creation for (meta-)barcoding. EcoEvoRxiv (2019); https://doi.org/10.32942/osf.io/cmfu2 - https://github.com/molbiodiv/bcdatabaser", "eutils: Sayers E. E-utilities Quick Start. 2008 Dec 12 [Updated 2018 Oct 24]. In: Entrez Programming Utilities Help [Internet]. Bethesda (MD): National Center for Biotechnology Information (US); 2010-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK25500/", "NCBI::Taxonomy: F\u00f6rster et al. https://github.com/greatfireball/NCBI-Taxonomy - F\u00f6rster F. greatfireball/NCBI-Taxonomy v0.90. Zenodo. 2018 Oct 15; https://doi.org/10.5281/zenodo.1462861", "SeqFilter: Hackl et al. https://github.com/BioInf-Wuerzburg/SeqFilter", "dispr: Cofield et al. https://github.com/douglasgscofield/dispr", "Krona: Ondov BD, Bergman NH, and Phillippy AM. Interactive metagenomic visualization in a Web browser. BMC Bioinformatics. 2011 Sep 30; 12(1):385."]}
DOI: 10.5281/zenodo.3337769
title: BCdatabaser - 18s.crustacea.none.2019-07-16.zip

description: Parameters: --marker-search-string 18S --taxonomic-range Crustacea --sequence-length-filter 100:2000 --sequences-per-taxon 9
description: This dataset was automatically created with data from NCBI using the BCdatabaser tool
description: {"references": ["Keller et al. (2019) BCdatabaser: on-the-fly reference database creation for (meta-)barcoding. EcoEvoRxiv (2019); https://doi.org/10.32942/osf.io/cmfu2 - https://github.com/molbiodiv/bcdatabaser", "eutils: Sayers E. E-utilities Quick Start. 2008 Dec 12 [Updated 2018 Oct 24]. In: Entrez Programming Utilities Help [Internet]. Bethesda (MD): National Center for Biotechnology Information (US); 2010-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK25500/", "NCBI::Taxonomy: F\u00f6rster et al. https://github.com/greatfireball/NCBI-Taxonomy - F\u00f6rster F. greatfireball/NCBI-Taxonomy v0.90. Zenodo. 2018 Oct 15; https://doi.org/10.5281/zenodo.1462861", "SeqFilter: Hackl et al. https://github.com/BioInf-Wuerzburg/SeqFilter", "dispr: Cofield et al. https://github.com/douglasgscofield/dispr", "Krona: Ondov BD, Bergman NH, and Phillippy AM. Interactive metagenomic visualization in a Web browser. BMC Bioinformatics. 2011 Sep 30; 12(1):385."]}
DOI: 10.5281/zenodo.3337770
title: BCdatabaser - 18s.sphaeromatidae.none.2019-07-16.zip

description: Parameters: --marker-search-string 18S --taxonomic-range Sphaeromatidae --sequence-length-filter 100:2000 --sequences-per-taxon 9
description: This dataset was automatically created with data from NCBI using the BCdatabaser tool
description: {"references": ["Keller et al. (2019) BCdatabaser: on-the-fly reference database creation for (meta-)barcoding. EcoEvoRxiv (2019); https://doi.org/10.32942/osf.io/cmfu2 - https://github.com/molbiodiv/bcdatabaser", "eutils: Sayers E. E-utilities Quick Start. 2008 Dec 12 [Updated 2018 Oct 24]. In: Entrez Programming Utilities Help [Internet]. Bethesda (MD): National Center for Biotechnology Information (US); 2010-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK25500/", "NCBI::Taxonomy: F\u00f6rster et al. https://github.com/greatfireball/NCBI-Taxonomy - F\u00f6rster F. greatfireball/NCBI-Taxonomy v0.90. Zenodo. 2018 Oct 15; https://doi.org/10.5281/zenodo.1462861", "SeqFilter: Hackl et al. https://github.com/BioInf-Wuerzburg/SeqFilter", "dispr: Cofield et al. https://github.com/douglasgscofield/dispr", "Krona: Ondov BD, Bergman NH, and Phillippy AM. Interactive metagenomic visualization in a Web browser. BMC Bioinformatics. 2011 Sep 30; 12(1):385."]}
DOI: 10.5281/zenodo.3337771
title: BCdatabaser - 18s.sphaeromatidae.none.2019-07-16.zip

description: Parameters: --marker-search-string 18S --taxonomic-range Sphaeromatidae --sequence-length-filter 100:2000 --sequences-per-taxon 9
description: This dataset was automatically created with data from NCBI using the BCdatabaser tool
description: {"references": ["Keller et al. (2019) BCdatabaser: on-the-fly reference database creation for (meta-)barcoding. EcoEvoRxiv (2019); https://doi.org/10.32942/osf.io/cmfu2 - https://github.com/molbiodiv/bcdatabaser", "eutils: Sayers E. E-utilities Quick Start. 2008 Dec 12 [Updated 2018 Oct 24]. In: Entrez Programming Utilities Help [Internet]. Bethesda (MD): National Center for Biotechnology Information (US); 2010-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK25500/", "NCBI::Taxonomy: F\u00f6rster et al. https://github.com/greatfireball/NCBI-Taxonomy - F\u00f6rster F. greatfireball/NCBI-Taxonomy v0.90. Zenodo. 2018 Oct 15; https://doi.org/10.5281/zenodo.1462861", "SeqFilter: Hackl et al. https://github.com/BioInf-Wuerzburg/SeqFilter", "dispr: Cofield et al. https://github.com/douglasgscofield/dispr", "Krona: Ondov BD, Bergman NH, and Phillippy AM. Interactive metagenomic visualization in a Web browser. BMC Bioinformatics. 2011 Sep 30; 12(1):385."]}
DOI: 10.17632/93m27cgfnw.1
title: Code for: Optimizing treatment combination for lymphoma using artificial intelligence

description: Source code (C++) to replicate the simulations and graphs of "Optimizing treatment combination for lymphoma using an optimization heuristic" by N. Houy and F. Le Grand
DOI: 10.25829/idiv.1771-48-2459
title: FragSAD: A database of diversity and species abundance distributions from habitat fragments (Version:1.0)

description: 117 studies that compared species assemblages among habitat fragments that varies in area
DOI: 10.5061/dryad.2ct6558/1
title: Dryad Item 10.5061/DRYAD.2CT6558/1

description: (:tba)
DOI: 10.5061/dryad.2ct6558/2
title: Dryad Item 10.5061/DRYAD.2CT6558/2

description: (:tba)
DOI: 10.5061/dryad.2ct6558/3
title: Dryad Item 10.5061/DRYAD.2CT6558/3

description: (:tba)
DOI: 10.5061/dryad.2ct6558/4
title: Dryad Item 10.5061/DRYAD.2CT6558/4

description: (:tba)
DOI: 10.5061/dryad.2ct6558/5
title: Dryad Item 10.5061/DRYAD.2CT6558/5

description: (:tba)
DOI: 10.5061/dryad.2ct6558/6
title: Dryad Item 10.5061/DRYAD.2CT6558/6

description: (:tba)
DOI: 10.17632/5z38hczndv.2
title: Data for: ADVENTURES IN PYROLYSIS II, Modeling Pyrolysis Peaks of Petroleum Source Rocks

description: Results for modeling of programmed pyrolysis yields.
DOI: 10.5061/dryad.2ct6558/10
title: Dryad Item 10.5061/DRYAD.2CT6558/10

description: (:tba)
DOI: 10.5061/dryad.2ct6558/11
title: Dryad Item 10.5061/DRYAD.2CT6558/11

description: (:tba)
DOI: 10.5061/dryad.2ct6558/12
title: Dryad Item 10.5061/DRYAD.2CT6558/12

description: (:tba)
DOI: 10.5061/dryad.2ct6558/13
title: Dryad Item 10.5061/DRYAD.2CT6558/13

description: (:tba)
DOI: 10.5061/dryad.2ct6558/14
title: Dryad Item 10.5061/DRYAD.2CT6558/14

description: (:tba)
DOI: 10.5061/dryad.2ct6558/15
title: Dryad Item 10.5061/DRYAD.2CT6558/15

description: (:tba)
DOI: 10.5061/dryad.2ct6558/7
title: Dryad Item 10.5061/DRYAD.2CT6558/7

description: (:tba)
DOI: 10.5061/dryad.2ct6558/8
title: Dryad Item 10.5061/DRYAD.2CT6558/8

description: (:tba)
DOI: 10.5061/dryad.2ct6558/9
title: Dryad Item 10.5061/DRYAD.2CT6558/9

description: (:tba)
DOI: 10.17632/3yw64k54wg.1
title: Data for: Visual Acuity Outcomes and Anti-Vascular Endothelial Growth Factor Therapy Intensity in Neovascular AMD Patients: A “Real World” Analysis in 49,485 Eyes
DOI: 10.5061/dryad.2ct6558/16
title: Dryad Item 10.5061/DRYAD.2CT6558/16

description: (:tba)
DOI: 10.25345/c5d36j
title: MassIVE MSV000084098 - NPC1 lipidomics by LC-MS and FAMEs by GC-MS
title: Lipidomics in the liver of late-stage NPC1 with a focus on fatty acid metabolism.
DOI: 10.21227/qghv-2c47
title: HANDMADE GINGER PILLS FOR DIABETES MELLITUS MANAGEMENT , A PHASE 2 TRIAL IN YAOUNDE CAMEROON

description: ackgroundEffects of plants on glucose metabolism have been highlighted and are of particular interest in Type 2 Diabetes (T2DM). Zingiber Officinale (ZO)for instance, is a plant widely used as a spice, known for its hypoglycaemic and hypolipidaemic virtues. However, few studies were conducted in humans, and none have used reference methods for assessing glucose metabolism. The study aims to evaluate the effect of ginger extracts supplementation on diabetes mellitus patients metabolic profile.AimBased on a Phase II trial model, we conducted a non-randomized single arm trial study on 10 T2DM patients. During 24 days, patients were given 2grs ginger pills. Data as Blood pressure, anthropometric data, Insulin Sensitivity, Blood Plasma Glucose, HbA1c, and Lipid.ResultsWe found asignificant improve ofinsulin sensitivity30.85% (p= 0.008). Plasma glucose Area under the curve varied from (5.1[0.77 – 13.72]) to (0.60[-5.85 – 4.87] g/l/120 min )(p = 0.139). There was a non-significant decrease after intervention of triglycerides from 1.64 [1.47-2.22] mmol/l to1.26 [0.91-1.84] mmol/l; and LDL cholesterol from 3.92 [3.07-5.07] mmol/l to 2.48 [1.45-4.03] mmol/l ,p˃0.05. There was also a non-significant increase of HDL cholesterol (from 1.26[0.81-1. 90] mmol/l to 1.96 [1.63-2. 18] mmol/l ;p˃0.05). We observed mild hypoglycemia in two patients. Hepatic and renal functions were normal before and after intervention for all patients.ConclusionGinger pills had beneficial metabolic effects on insulin sensitivity, glycemic, and lipid profiles after eight weeks of supplementation to T2DM patients. Hence, it might be useful as add-on therapy in the management of T2DM.Key words: Ginger pills, Insulin Sensitivity, Lipid Profile, Glycemic Profile.
DOI: 10.17632/fgfcvzjm98.2
title: Data for: European charophyte evolution across the Cretaceous–Paleogene boundary

description: The supplementary data uploaded help to shed light into charophyte taxonomy in the Ibero-Armorican Island during the K/Pg crisis.