cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.11686596.v1
title: MOESM4 of A systematic review of factors influencing NHS health check uptake: invitation methods, patient characteristics, and the impact of interventions

description: Additional file 4. List of Full Text Exclusions.
DOI: 10.6084/m9.figshare.11686548
title: MOESM2 of Shotgun metagenomic analysis of microbial communities from the Loxahatchee nature preserve in the Florida Everglades

description: Additional file 2: Tables S6-S9. Containing biomarker gene counts, taxonomic data for methanogens, sulfate reducers, and nitrogen fixers.
DOI: 10.6084/m9.figshare.11686548.v1
title: MOESM2 of Shotgun metagenomic analysis of microbial communities from the Loxahatchee nature preserve in the Florida Everglades

description: Additional file 2: Tables S6-S9. Containing biomarker gene counts, taxonomic data for methanogens, sulfate reducers, and nitrogen fixers.
DOI: 10.6084/m9.figshare.11686431
title: MOESM4 of Can supernatant from immortalized adipose tissue MSC replace cell therapy? An in vitro study in chronic wounds model

description: Additional file 4. Migration activity of native HATMSC supernatants. MSU-1.1 cell migration activity was investigated at 37 °C in an incubation chamber (PeCon GmbH, Erbach, Germany) with 1%O2, 5%CO2 mounted on an Axio Observer inverted microscope equipped with a dry 5x objective (Zeiss, Gottingen, Germany). The movement of the cells was time-lapse recorded for 44 h at intervals of 2 h using Zen 2.6 Blue Edition Software (Zeiss, Gottingen, Germany) as 6 separate movies (one for each supernatant and control).
DOI: 10.6084/m9.figshare.11686431.v1
title: MOESM4 of Can supernatant from immortalized adipose tissue MSC replace cell therapy? An in vitro study in chronic wounds model

description: Additional file 4. Migration activity of native HATMSC supernatants. MSU-1.1 cell migration activity was investigated at 37 °C in an incubation chamber (PeCon GmbH, Erbach, Germany) with 1%O2, 5%CO2 mounted on an Axio Observer inverted microscope equipped with a dry 5x objective (Zeiss, Gottingen, Germany). The movement of the cells was time-lapse recorded for 44 h at intervals of 2 h using Zen 2.6 Blue Edition Software (Zeiss, Gottingen, Germany) as 6 separate movies (one for each supernatant and control).
DOI: 10.6084/m9.figshare.11686398
title: MOESM1 of Management of UK priority invasive alien plants: a systematic review protocol

description: Additional file 1. Completed ROSES form.
DOI: 10.6084/m9.figshare.11686398.v1
title: MOESM1 of Management of UK priority invasive alien plants: a systematic review protocol

description: Additional file 1. Completed ROSES form.
DOI: 10.6084/m9.figshare.11686386
title: MOESM1 of A pharmacological chaperone improves memory by reducing Aβ and tau neuropathology in a mouse model with plaques and tangles

description: Additional file 1: Figure S1. A. Effect of TPT on behavioral tests in male mice. (A) Number of total arm entries for wild-type mice (WT) and 3xTg mice (3xTg) treated with TPT or control (Ctrl). (B) Percentage of alternations for WT and 3xTg mice treated with TPT or control (Ctrl). (C) Contexual fear memory response in WT and 3xTg mice treated with TPT or control (Ctrl). (D) Cued fear memory response in WT and 3xTg mice treated with TPT or control (Ctrl). (E) Morris water maze, probe trial for the same four groups of mice, number of entries to the platform area; (F) Morris water maze, probe trial for the same four groups of mice, latency to first entry to the platform area. Values represent mean ± standard error of the mean. (#p
DOI: 10.6084/m9.figshare.11686386.v1
title: MOESM1 of A pharmacological chaperone improves memory by reducing Aβ and tau neuropathology in a mouse model with plaques and tangles

description: Additional file 1: Figure S1. A. Effect of TPT on behavioral tests in male mice. (A) Number of total arm entries for wild-type mice (WT) and 3xTg mice (3xTg) treated with TPT or control (Ctrl). (B) Percentage of alternations for WT and 3xTg mice treated with TPT or control (Ctrl). (C) Contexual fear memory response in WT and 3xTg mice treated with TPT or control (Ctrl). (D) Cued fear memory response in WT and 3xTg mice treated with TPT or control (Ctrl). (E) Morris water maze, probe trial for the same four groups of mice, number of entries to the platform area; (F) Morris water maze, probe trial for the same four groups of mice, latency to first entry to the platform area. Values represent mean ± standard error of the mean. (#p
DOI: 10.6084/m9.figshare.11683959
title: Supplementary Table 4-18 and R script for WGCNA

description: Supplementary Table 4. List of annotated probes that were significantly (p &lt;0.05) upregulated with ≥2-fold changes in any B cell subset of pSS compared with those of HCs.Supplementary Table 5. List of probes that were significantly (p &lt;0.05) upregulated with ≥2-fold changes in all B cell subpopulations compared with those of HCs.Supplementary Tables 6 and 7. List of probes in gene co-expression modules of pSS (Table 6) and HCs (Table 7). To quantify associations of individual genes with the disease activity score (EULAR Sjögren's Syndrome Disease Activity Index, ESSDAI), we defined Gene Significance (GS) as the absolute value of the correlation between each gene and ESSDAI. P.GS represents the p-value of GS. For each module, we defined a quantitative measure of module membership (MM) as the correlation between the module eigengene and the gene expression profile. P.MM means the p value of MM. This allowed us to quantify the similarities among all genes of every module.Supplementary Table 8. List of canonical pathways associated with gene co-expression modules of pSS.Supplementary Table 9. List of upstream regulators associated with gene co-expression modules of pSS.Supplementary Table 10. List of disease and functions associated with gene co-expression modules of pSS.Supplementary Table 11. List of canonical pathways associated with the identified gene co-expression modules of HCs.Supplementary Table 12. List of upstream regulators associated with gene co-expression modules of HCs.Supplementary Table 13. List of disease and functions associated with gene co-expression modules of HCs.Supplementary Table 14. List of canonical pathways specific to pSS.Supplementary Table 15. List of upstream regulators specific to pSS.Supplementary Table 16. List of disease and functions specific to pSS.Supplementary Table 17. The distribution of ESSDAI of patients with pSS.Supplementary Table 18. The detailed clinical information of patients with pSS.
DOI: 10.6084/m9.figshare.11683959.v1
title: Supplementary Table 4-14

description: Supplementary files of our article.
DOI: 10.6084/m9.figshare.11683959.v2
title: Supplementary Table 4-14

description: Supplementary files of our article.
DOI: 10.6084/m9.figshare.11683959.v3
title: Supplementary Table 4-14 and R script for WGCNA

description: Supplementary files of our article.Supplementary Table 4. List of annotated probes that were significantly (p &lt;0.05) upregulated with ≥2-fold changes in any B cell subset of pSS compared with those of HCs.Supplementary Table 5. List of probes that were significantly (p &lt;0.05) upregulated with ≥2-fold changes in all B cell subpopulations compared with those of HCs.Supplementary Tables 6 and 7. List of probes in gene co-expression modules of pSS (Table 6) and HCs (Table 7). To quantify associations of individual genes with the disease activity score (EULAR Sjögren's Syndrome Disease Activity Index, ESSDAI), we defined Gene Significance (GS) as the absolute value of the correlation between each gene and ESSDAI. P.GS represents the p-value of GS. For each module, we defined a quantitative measure of module membership (MM) as the correlation between the module eigengene and the gene expression profile. P.MM means the p value of MM. This allowed us to quantify the similarities among all genes of every module.Supplementary Table 8. List of canonical pathways associated with gene co-expression modules of pSS.Supplementary Table 9. List of upstream regulators associated with gene co-expression modules of pSS.Supplementary Table 10. List of disease and functions associated with gene co-expression modules of pSS.Supplementary Table 11. List of canonical pathways associated with the identified gene co-expression modules of HCs.Supplementary Table 12. List of upstream regulators associated with gene co-expression modules of HCs.Supplementary Table 13. List of disease and functions associated with gene co-expression modules of HCs.Supplementary Table 14. List of canonical pathways, upstream regulators and disease and functions specific to pSS.
DOI: 10.6084/m9.figshare.11683959.v4
title: Supplementary Table 4-14 and R script for WGCNA

description: Supplementary files of our article.Supplementary Table 4. List of annotated probes that were significantly (p &lt;0.05) upregulated with ≥2-fold changes in any B cell subset of pSS compared with those of HCs.Supplementary Table 5. List of probes that were significantly (p &lt;0.05) upregulated with ≥2-fold changes in all B cell subpopulations compared with those of HCs.Supplementary Tables 6 and 7. List of probes in gene co-expression modules of pSS (Table 6) and HCs (Table 7). To quantify associations of individual genes with the disease activity score (EULAR Sjögren's Syndrome Disease Activity Index, ESSDAI), we defined Gene Significance (GS) as the absolute value of the correlation between each gene and ESSDAI. P.GS represents the p-value of GS. For each module, we defined a quantitative measure of module membership (MM) as the correlation between the module eigengene and the gene expression profile. P.MM means the p value of MM. This allowed us to quantify the similarities among all genes of every module.Supplementary Table 8. List of canonical pathways associated with gene co-expression modules of pSS.Supplementary Table 9. List of upstream regulators associated with gene co-expression modules of pSS.Supplementary Table 10. List of disease and functions associated with gene co-expression modules of pSS.Supplementary Table 11. List of canonical pathways associated with the identified gene co-expression modules of HCs.Supplementary Table 12. List of upstream regulators associated with gene co-expression modules of HCs.Supplementary Table 13. List of disease and functions associated with gene co-expression modules of HCs.Supplementary Table 14. List of canonical pathways, upstream regulators and disease and functions specific to pSS.Supplementary Table 15. The distribution of ESSDAI of patients with pSS.<br>
DOI: 10.6084/m9.figshare.11683959.v5
title: Supplementary Table 4-14 and R script for WGCNA

description: Supplementary Table 4. List of annotated probes that were significantly (p &lt;0.05) upregulated with ≥2-fold changes in any B cell subset of pSS compared with those of HCs.Supplementary Table 5. List of probes that were significantly (p &lt;0.05) upregulated with ≥2-fold changes in all B cell subpopulations compared with those of HCs.Supplementary Tables 6 and 7. List of probes in gene co-expression modules of pSS (Table 6) and HCs (Table 7). To quantify associations of individual genes with the disease activity score (EULAR Sjögren's Syndrome Disease Activity Index, ESSDAI), we defined Gene Significance (GS) as the absolute value of the correlation between each gene and ESSDAI. P.GS represents the p-value of GS. For each module, we defined a quantitative measure of module membership (MM) as the correlation between the module eigengene and the gene expression profile. P.MM means the p value of MM. This allowed us to quantify the similarities among all genes of every module.Supplementary Table 8. List of canonical pathways associated with gene co-expression modules of pSS.Supplementary Table 9. List of upstream regulators associated with gene co-expression modules of pSS.Supplementary Table 10. List of disease and functions associated with gene co-expression modules of pSS.Supplementary Table 11. List of canonical pathways associated with the identified gene co-expression modules of HCs.Supplementary Table 12. List of upstream regulators associated with gene co-expression modules of HCs.Supplementary Table 13. List of disease and functions associated with gene co-expression modules of HCs.Supplementary Table 14. List of canonical pathways specific to pSS.Supplementary Table 15. List of upstream regulators specific to pSS.Supplementary Table 16. List of disease and functions specific to pSS.Supplementary Table 17. The distribution of ESSDAI of patients with pSS.
DOI: 10.6084/m9.figshare.11683959.v6
title: Supplementary Table 4-17 and R script for WGCNA

description: Supplementary Table 4. List of annotated probes that were significantly (p &lt;0.05) upregulated with ≥2-fold changes in any B cell subset of pSS compared with those of HCs.Supplementary Table 5. List of probes that were significantly (p &lt;0.05) upregulated with ≥2-fold changes in all B cell subpopulations compared with those of HCs.Supplementary Tables 6 and 7. List of probes in gene co-expression modules of pSS (Table 6) and HCs (Table 7). To quantify associations of individual genes with the disease activity score (EULAR Sjögren's Syndrome Disease Activity Index, ESSDAI), we defined Gene Significance (GS) as the absolute value of the correlation between each gene and ESSDAI. P.GS represents the p-value of GS. For each module, we defined a quantitative measure of module membership (MM) as the correlation between the module eigengene and the gene expression profile. P.MM means the p value of MM. This allowed us to quantify the similarities among all genes of every module.Supplementary Table 8. List of canonical pathways associated with gene co-expression modules of pSS.Supplementary Table 9. List of upstream regulators associated with gene co-expression modules of pSS.Supplementary Table 10. List of disease and functions associated with gene co-expression modules of pSS.Supplementary Table 11. List of canonical pathways associated with the identified gene co-expression modules of HCs.Supplementary Table 12. List of upstream regulators associated with gene co-expression modules of HCs.Supplementary Table 13. List of disease and functions associated with gene co-expression modules of HCs.Supplementary Table 14. List of canonical pathways specific to pSS.Supplementary Table 15. List of upstream regulators specific to pSS.Supplementary Table 16. List of disease and functions specific to pSS.Supplementary Table 17. The distribution of ESSDAI of patients with pSS.
DOI: 10.3886/e119451v1-43680
title: National Neighborhood Data Archive (NaNDA): Socioeconomic Status and Demographic Characteristics of Census Tracts, United States, 2008-2017

description: This dataset contains measures of socioeconomic and demographic characteristics by US census tract for the years 2008-2017. Example measures include population density; population distribution by race, ethnicity, age, and income; and proportion of population living below the poverty level, receiving public assistance, and female-headed families. The dataset also contains a set of index variables to represent neighborhood disadvantage and affluence.
description: This dataset complements a similar version (National Neighborhood Data Archive [NaNDA]: Neighborhood Socioeconomic and Demographic Characteristics of Census Tracts, United States, 2000-2010, https://www.openicpsr.org/openicpsr/project/111107/) which is based on the same theoretical findings and covers the period 2000-2010. Users wanting to combine this dataset with measures from 2000-2010 should be aware of key differences between how measures are calculated across the two datasets. For more information, see the "Usage Note" section of the documentation.
description: All census tracts in the United States, including Puerto Rico. Smallest Geographic Unit: census tract
DOI: 10.3886/e111107v1-43681
title: National Neighborhood Data Archive (NaNDA): Neighborhood Socioeconomic and Demographic Characteristics of Census Tracts, United States, 2000-2010

description: This dataset contains measures of socioeconomic and demographic characteristics by US census tract for the years 2000-2010. Example measures include population density; population distribution by race, ethnicity, age, and income; and proportion of population living below the poverty level, receiving public assistance, and female-headed families. The dataset also contains a set of index variables to represent neighborhood disadvantage and affluence.
description: This dataset is complemented by a similar version (National Neighborhood Data Archive (NaNDA): Socioeconomic Status and Demographic Characteristics of Census Tracts, United States, 2008-2017, https://www.openicpsr.org/openicpsr/project/119451) which is based on the same theoretical findings and covers the period 2008-2017. Users wanting to combine this dataset with measures from 2008-2017 should be aware of key differences between how measures are calculated across the two datasets. For more information, see the "Usage Note" section of the documentation.
description: All census tracts in the United States, including Puerto Rico. Smallest Geographic Unit: Census tract
DOI: 10.6084/m9.figshare.11679090
title: File description

description: Raw images used for a paper https://www.ncbi.nlm.nih.gov/pubmed/31383032.
DOI: 10.6084/m9.figshare.11679090.v1
title: File description

description: Raw images used for a paper https://www.ncbi.nlm.nih.gov/pubmed/31383032.
DOI: 10.3886/e119451v1-43682
title: National Neighborhood Data Archive (NaNDA): Socioeconomic Status and Demographic Characteristics of Census Tracts, United States, 2008-2017

description: This dataset contains measures of socioeconomic and demographic characteristics by US census tract for the years 2008-2017. Example measures include population density; population distribution by race, ethnicity, age, and income; and proportion of population living below the poverty level, receiving public assistance, and female-headed families. The dataset also contains a set of index variables to represent neighborhood disadvantage and affluence.
description: This dataset complements a similar version (National Neighborhood Data Archive [NaNDA]: Neighborhood Socioeconomic and Demographic Characteristics of Census Tracts, United States, 2000-2010, https://www.openicpsr.org/openicpsr/project/111107/) which is based on the same theoretical findings and covers the period 2000-2010. Users wanting to combine this dataset with measures from 2000-2010 should be aware of key differences between how measures are calculated across the two datasets. For more information, see the "Usage Note" section of the documentation.
description: All census tracts in the United States, including Puerto Rico. Smallest Geographic Unit: census tract
DOI: 10.6084/m9.figshare.11678700
title: Action of citronella (Cymbopogon nardus L) essential oil on the pathogen Lasiodiplodia theobromae in bunches of grapevine cv. ‘Itália’

description: ABSTRACT Presence of Lasiodiplodia theobromae (dry rot) in vines established in irrigated areas of the Brazilian semiarid region has shown to be highly aggressive when infecting several parts of the plants. Essential oils have shown efficiency in controlling diseases, both by the fungitoxic action, inhibiting mycelial growth and spore germination, and by the presence of eliciting compounds. Thus, the objective of this study was to obtain control of L. theobromae by using citronella oil (Cymbopogon nardus L) at different levels. Mycelial growth of L. theobromae was analyzed in Petri dishes containing potato-dextrose-agar medium supplemented with essential oil at the following concentrations: 0; 0.25; 0.5; 1.0; 1.5 and 2.0%. To evaluate the direct effect of the essential oil on the development of the disease, grape bunches were inoculated with the pathogen and, after 4 h, sprayed with solutions containing the same concentrations described above; subsequently, in order to evaluate the potential of the essential oil in the preventive treatment, the same treatments were applied in grape bunches 4 hours before inoculation. Citronella oil at all tested concentrations was capable of inhibiting the mycelial growth of L. theobromae by 100%. For the healing treatment, considering incidence, 0.25% citronella reduced by 38% the infection in berries of grape bunches inoculated with L. theobromae and was capable of reducing the disease severity by 56%. As regards the preventive treatment, 0.25% citronella oil reduced by 52% the infection in berries of grape bunches cv. ‘Itália’, reducing the disease severity by 66.3%. These results lead to the conclusion that 0.25% was the best concentration tested for disease control with citronella essential oil.
DOI: 10.6084/m9.figshare.11678700.v1
title: Action of citronella (Cymbopogon nardus L) essential oil on the pathogen Lasiodiplodia theobromae in bunches of grapevine cv. ‘Itália’

description: ABSTRACT Presence of Lasiodiplodia theobromae (dry rot) in vines established in irrigated areas of the Brazilian semiarid region has shown to be highly aggressive when infecting several parts of the plants. Essential oils have shown efficiency in controlling diseases, both by the fungitoxic action, inhibiting mycelial growth and spore germination, and by the presence of eliciting compounds. Thus, the objective of this study was to obtain control of L. theobromae by using citronella oil (Cymbopogon nardus L) at different levels. Mycelial growth of L. theobromae was analyzed in Petri dishes containing potato-dextrose-agar medium supplemented with essential oil at the following concentrations: 0; 0.25; 0.5; 1.0; 1.5 and 2.0%. To evaluate the direct effect of the essential oil on the development of the disease, grape bunches were inoculated with the pathogen and, after 4 h, sprayed with solutions containing the same concentrations described above; subsequently, in order to evaluate the potential of the essential oil in the preventive treatment, the same treatments were applied in grape bunches 4 hours before inoculation. Citronella oil at all tested concentrations was capable of inhibiting the mycelial growth of L. theobromae by 100%. For the healing treatment, considering incidence, 0.25% citronella reduced by 38% the infection in berries of grape bunches inoculated with L. theobromae and was capable of reducing the disease severity by 56%. As regards the preventive treatment, 0.25% citronella oil reduced by 52% the infection in berries of grape bunches cv. ‘Itália’, reducing the disease severity by 66.3%. These results lead to the conclusion that 0.25% was the best concentration tested for disease control with citronella essential oil.
DOI: 10.6084/m9.figshare.11678694
title: Effect on Merlot red wine of fining agents mixture: application of the simplex centroid design

description: Abstract In the elaboration of young red wine, it is necessary to obtain a clear product with stable color. The clarity and stability can be obtained using fining agents. The objective of this study was to evaluate the combined effect of fining with pea protein isolate (PPI), bentonite, and polyvinylpyrrolidone (PVPP) on a red wine, using the experimental design of mixtures. Merlot wine was used to evaluate the changes on monomeric flavan-3-ol, turbidity and anthocyanin levels promoted by the fining compounds. For all the parameters, the adjusted models showed influence of the combination of the three fining agents. Together, bentonite and PVPP have synergistic effect on the reduction in monomeric flavanol levels. Such synergistic effect was also observed with PPI and PVPP combination for the reduction in turbidity. However, for this same characteristic (turbidity), the combination of PPI and bentonite has antagonistic effect. To achieve broader wine fining objectives, the simultaneous optimization of the three response variables demonstrated the importance of the presence of the three refining agents in the following proportions: 25% PPI, 43% PVPP and 32% Bentonite. The isolated use of these additives would not result in the same effect on the three studied variables.