cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.8039939
title: Supplementary Material for: Normal Growth despite Combined Pituitary Hormone Deficiency

description: <b><i>Background:</i></b> The paradox of normal growth despite a lack of growth hormone (GH) is an unexplained phenomenon described in some pathological (sellar, suprasellar, and hypothalamic disorders) and overgrowth syndromes. It has been suggested that the paradoxical growth is due to other GH variants, GH-like moieties, prolactin, insulin, insulin-like growth factors (IGFs), and unidentified serum factors or growth mechanisms. The objective of this study was to determine the mechanism underlying this normal growth without GH. <b><i>Case Description:</i></b> We describe here growth, hormonal, and genetic analyses for an adolescent boy with panhypopituitarism who achieved an adult height above his genetic potential. <b><i>Results:</i></b> Normal growth was observed despite low serum GH, IGF-I, IGF-II, IGF binding protein 3 (IGFBP-3) and acid labile subunit (ALS) concentrations, but the IGF-II/IGFBP-3 molar ratio was slightly high. Panhypopituitarism was associated with a heterozygous missense mutation of <i>HESX1</i>, with variable penetrance in heterozygous relatives. Exome analysis detected heterozygous missense mutations of various genes involved in intracellular signaling pathways. The growth-promoting activity of the patient’s serum was unable to induce AKT phosphorylation in the MCF-7 cell line. <b><i>Conclusion:</i></b> The high IGF-II/IGFBP-3 molar ratio was not the cause of the sustained high growth velocity, due to the low affinity of IGF-II for IGF type 1 receptor. The key finding was the <i>HESX1</i> mutation, as similar cases have been described before, suggesting a common mechanism for growth without GH. However, the variable penetrance of this variant in heterozygous relatives suggests that modifier genes or mechanisms involving combinations with mutations of other genes involved in intracellular signaling pathways might be responsible.
DOI: 10.6084/m9.figshare.8039942
title: Article PLoS One data files PONE-D-19-02116

description: Epinions dataset, MovieLens-100K dataset, MovieLens-1M dataset, CiaoDVD dataset, MovieTweetings dataset, and source code
DOI: 10.6084/m9.figshare.8039915
title: Raw Data.zip

description: To understand the essential feature of gut microbiome and better preserve Père David’s deer, stool samples from captive and wild deer were used to identify healthy core microbiome in the gut of this species and investigate how dietary factor influence the gut microbiome. 16S rRNA high-throughput sequencing and comparative analysis were adopted in the present study. The results showed that the core gut microbiome in healthy deer was consisted of the Firmicutes and Bacteroidetes. The core microbiome was stable that might not change drastically with dietary factor. The difference in diet between captive and wild deer might influence on the success of reintroduction into the wild, but the influence might be very little. These results could be informative for future applications of population management in Père David’s deer conservation.<b> </b>
DOI: 10.6084/m9.figshare.8039927
title: Isolation, Identification and Antioxidant Activity of Metabolites from Endophytic Fungus Coniochaeta sp.F-8

description: Two compounds were isolated from the endophytic fungus of <i>Ageratina adenophora </i>for the first time. And the both of those compounds showed moderate antioxidant activities and some cytotoxicity on Mouse embryo fibroblasts cell line Balb/c3T3.<br>
DOI: 10.6084/m9.figshare.8039927.v1
title: Isolation, Identification and Antioxidant Activity of Metabolites from Endophytic Fungus Coniochaeta sp.F-8

description: Two compounds were isolated from the endophytic fungus of <i>Ageratina adenophora </i>for the first time. And the both of those compounds showed moderate antioxidant activities and some cytotoxicity on Mouse embryo fibroblasts cell line Balb/c3T3.<br>
DOI: 10.6084/m9.figshare.8039942.v2
title: Article PLoS One data files PONE-D-19-02116

description: Epinions dataset, MovieLens-100K dataset, MovieLens-1M dataset, CiaoDVD dataset, MovieTweetings dataset, and source code
DOI: 10.6084/m9.figshare.8039942.v1
title: Article PLoS One data files PONE-D-19-02116

description: Epinions, MovieLens-100K, MovieLens-1M, and CiaoDVD daasets and code
DOI: 10.6084/m9.figshare.8039669
title: Additional file 5: of Chemotherapy-induced oral mucositis is associated with detrimental bacterial dysbiosis

description: Table S9. Summary of upregulated gene ontology (GO) term categories. (XLSX 13 kb)
DOI: 10.6084/m9.figshare.8039669.v1
title: Additional file 5: of Chemotherapy-induced oral mucositis is associated with detrimental bacterial dysbiosis

description: Table S9. Summary of upregulated gene ontology (GO) term categories. (XLSX 13 kb)
DOI: 10.6084/m9.figshare.8039657
title: Additional file 3: of Chemotherapy-induced oral mucositis is associated with detrimental bacterial dysbiosis

description: Table S4. Identity and proportionsÂ of taxaÂ with significantly different relative abundance at any study visit compared to baseline. (XLSX 15 kb)
DOI: 10.6084/m9.figshare.8039663
title: Additional file 4: of Chemotherapy-induced oral mucositis is associated with detrimental bacterial dysbiosis

description: Table S8. SAM analysis of differential gene expressionÂ between baseline and V3 in 14 subjects, showingÂ 158 upregulated and 2 downregulated genes at V3 (&gt;â 1.5-fold). (XLSX 24 kb)
DOI: 10.6084/m9.figshare.8039663.v1
title: Additional file 4: of Chemotherapy-induced oral mucositis is associated with detrimental bacterial dysbiosis

description: Table S8. SAM analysis of differential gene expressionÂ between baseline and V3 in 14 subjects, showingÂ 158 upregulated and 2 downregulated genes at V3 (&gt;â 1.5-fold). (XLSX 24 kb)
DOI: 10.6084/m9.figshare.8039657.v1
title: Additional file 3: of Chemotherapy-induced oral mucositis is associated with detrimental bacterial dysbiosis

description: Table S4. Identity and proportionsÂ of taxaÂ with significantly different relative abundance at any study visit compared to baseline. (XLSX 15 kb)
DOI: 10.6084/m9.figshare.8039615
title: Additional file 4 of An empirical comparison of Bayesian modelling strategies for missing binary outcome data in network meta-analysis

description: Analysed dataset of 29 network meta-analyses and selected empirical prior distributions for between-trial variance. (TXT 39 kb)
DOI: 10.6084/m9.figshare.8039615.v1
title: Additional file 4 of An empirical comparison of Bayesian modelling strategies for missing binary outcome data in network meta-analysis

description: Analysed dataset of 29 network meta-analyses and selected empirical prior distributions for between-trial variance. (TXT 39 kb)
DOI: 10.6084/m9.figshare.8039576
title: MOESM5 of Integrating field-based heat tents and cyber-physical system technology to phenotype high night-time temperature impact on winter wheat

description: Additional file 5. Parts list and cost per tent.
DOI: 10.6084/m9.figshare.8039576.v1
title: MOESM5 of Integrating field-based heat tents and cyber-physical system technology to phenotype high night-time temperature impact on winter wheat

description: Additional file 5. Parts list and cost per tent.
DOI: 10.6084/m9.figshare.8039558
title: MOESM3 of Integrating field-based heat tents and cyber-physical system technology to phenotype high night-time temperature impact on winter wheat

description: Additional file 3. Thermostat Controller Python Script.
DOI: 10.6084/m9.figshare.8039555
title: MOESM2 of Origination and selection of ABCDE and AGL6 subfamily MADS-box genes in gymnosperms and angiosperms

description: Additional file 2. Txt files of 27 species and 381 sequences.
DOI: 10.6084/m9.figshare.8039558.v1
title: MOESM3 of Integrating field-based heat tents and cyber-physical system technology to phenotype high night-time temperature impact on winter wheat

description: Additional file 3. Thermostat Controller Python Script.
DOI: 10.6084/m9.figshare.8039555.v1
title: MOESM2 of Origination and selection of ABCDE and AGL6 subfamily MADS-box genes in gymnosperms and angiosperms

description: Additional file 2. Txt files of 27 species and 381 sequences.
DOI: 10.6084/m9.figshare.8039534
title: MOESM9 of Quantitative assay of targeted proteome in tomato trichome glandular cells using a large-scale selected reaction monitoring strategy

description: Additional file 9: Table S5. QconCAT information. Sequence: amino acid sequence of designed QconCAT; Molecular Weight: theoretical molecular weight of QconCAT; Synthesized Gene Sequence: nucleic acid sequence of artificial synthetic gene encoding QconCAT; Accession: accession ID of protein to be quantified by QconCAT; Peptide: peptide sequence used for QconCAT design; KEGG Information: information on enzymatic function from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (sly01110 Biosynthesis of secondary metabolites - Solanum lycopersicum).
DOI: 10.6084/m9.figshare.8039519
title: MOESM6 of Quantitative assay of targeted proteome in tomato trichome glandular cells using a large-scale selected reaction monitoring strategy

description: Additional file 6: Table S4. Differential expression of trichome glandular cell (TGC) proteins between tomato organs. Fold Change: fold change for differential protein expression; p value: statistical significance; Accession: accession IDs of proteins with differential expression between different organs; Protein: targeted protein name; Peptide: peptide sequence used for selected reaction monitoring (SRM) quantitative analysis; GO - Molecular function: gene ontology annotation for molecular function; GO - Biological process: gene ontology annotation for biological process.
DOI: 10.6084/m9.figshare.8039534.v1
title: MOESM9 of Quantitative assay of targeted proteome in tomato trichome glandular cells using a large-scale selected reaction monitoring strategy

description: Additional file 9: Table S5. QconCAT information. Sequence: amino acid sequence of designed QconCAT; Molecular Weight: theoretical molecular weight of QconCAT; Synthesized Gene Sequence: nucleic acid sequence of artificial synthetic gene encoding QconCAT; Accession: accession ID of protein to be quantified by QconCAT; Peptide: peptide sequence used for QconCAT design; KEGG Information: information on enzymatic function from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (sly01110 Biosynthesis of secondary metabolites - Solanum lycopersicum).
DOI: 10.6084/m9.figshare.8039513
title: MOESM5 of Quantitative assay of targeted proteome in tomato trichome glandular cells using a large-scale selected reaction monitoring strategy

description: Additional file 5: Table S3. Relative expression levels of targeted proteins in tomato trichome glandular cells (TGCs). The relative expression levels of target protein in each sample type (fruit, leaf, and calyx) was estimatedÂ based on the selected reaction monitoring (SRM) peak area of the corresponding peptide. Protein: targetedprotein name; Peptide: peptide sequence used for selected reaction monitoring (SRM) quantitative analysis.
DOI: 10.6084/m9.figshare.8039507
title: MOESM4 of Quantitative assay of targeted proteome in tomato trichome glandular cells using a large-scale selected reaction monitoring strategy

description: Additional file 4: Table S2. Established selected reaction monitoring (SRM) assays targeting tomato trichome glandular cell (TGC) proteome. The SRM assay was developed using Skyline Software. Q1: quadrupole mass filter to select a precursor ion; Q3: quadrupole mass filter to select a fragment ion; Protein: protein targeted by the assay; Sequence: monitoring peptide sequence; Charge: charge of precursor ion selected by Q1; Fragment ion: fragment ion selected by Q3; DP: declustering potential; CE: collision energy; Verified: SRM transition which was verified using tryptic digest of tomato TGC extract.
DOI: 10.6084/m9.figshare.8039513.v1
title: MOESM5 of Quantitative assay of targeted proteome in tomato trichome glandular cells using a large-scale selected reaction monitoring strategy

description: Additional file 5: Table S3. Relative expression levels of targeted proteins in tomato trichome glandular cells (TGCs). The relative expression levels of target protein in each sample type (fruit, leaf, and calyx) was estimatedÂ based on the selected reaction monitoring (SRM) peak area of the corresponding peptide. Protein: targetedprotein name; Peptide: peptide sequence used for selected reaction monitoring (SRM) quantitative analysis.
DOI: 10.6084/m9.figshare.8039519.v1
title: MOESM6 of Quantitative assay of targeted proteome in tomato trichome glandular cells using a large-scale selected reaction monitoring strategy

description: Additional file 6: Table S4. Differential expression of trichome glandular cell (TGC) proteins between tomato organs. Fold Change: fold change for differential protein expression; p value: statistical significance; Accession: accession IDs of proteins with differential expression between different organs; Protein: targeted protein name; Peptide: peptide sequence used for selected reaction monitoring (SRM) quantitative analysis; GO - Molecular function: gene ontology annotation for molecular function; GO - Biological process: gene ontology annotation for biological process.
DOI: 10.6084/m9.figshare.8039504
title: Additional file 1: of Case report: reinitiating pembrolizumab treatment after small bowel perforation

description: Supplemental Materials. Table S1 Consideration of PD-L1 and/or tumor-mutation burden in clinical trials of immune checkpoint inhibitors in non-small cell lung cancer. Figure S1. Case timeline. (ZIP 74 kb)
DOI: 10.6084/m9.figshare.8039507.v1
title: MOESM4 of Quantitative assay of targeted proteome in tomato trichome glandular cells using a large-scale selected reaction monitoring strategy

description: Additional file 4: Table S2. Established selected reaction monitoring (SRM) assays targeting tomato trichome glandular cell (TGC) proteome. The SRM assay was developed using Skyline Software. Q1: quadrupole mass filter to select a precursor ion; Q3: quadrupole mass filter to select a fragment ion; Protein: protein targeted by the assay; Sequence: monitoring peptide sequence; Charge: charge of precursor ion selected by Q1; Fragment ion: fragment ion selected by Q3; DP: declustering potential; CE: collision energy; Verified: SRM transition which was verified using tryptic digest of tomato TGC extract.
DOI: 10.6084/m9.figshare.8039495
title: MOESM2 of Quantitative assay of targeted proteome in tomato trichome glandular cells using a large-scale selected reaction monitoring strategy

description: Additional file 2: Table S1. Tomato trichome glandular cell (TGC) proteins identified by gel electrophoresis-assisted liquid chromatography-tandem mass spectrometry (GeLC–MS/MS) analysis. TGC proteins were identified using ProteinPilot (SCIEX) software with a false discovery rate (FDR) of 1%. Accession: accession ID in UniProtKB database; Protein Name: name of identified protein; Identified Peptide #: number of tryptic peptide identified by MS/MS, the cut-off for peptide confidence scores was &gt; 95; % Sequence Coverage: the percentage of the protein sequence covered by identified peptides with confidence score &gt; 95.
DOI: 10.6084/m9.figshare.8039504.v1
title: Additional file 1: of Case report: reinitiating pembrolizumab treatment after small bowel perforation

description: Supplemental Materials. Table S1 Consideration of PD-L1 and/or tumor-mutation burden in clinical trials of immune checkpoint inhibitors in non-small cell lung cancer. Figure S1. Case timeline. (ZIP 74 kb)
DOI: 10.6084/m9.figshare.8039495.v1
title: MOESM2 of Quantitative assay of targeted proteome in tomato trichome glandular cells using a large-scale selected reaction monitoring strategy

description: Additional file 2: Table S1. Tomato trichome glandular cell (TGC) proteins identified by gel electrophoresis-assisted liquid chromatography-tandem mass spectrometry (GeLC–MS/MS) analysis. TGC proteins were identified using ProteinPilot (SCIEX) software with a false discovery rate (FDR) of 1%. Accession: accession ID in UniProtKB database; Protein Name: name of identified protein; Identified Peptide #: number of tryptic peptide identified by MS/MS, the cut-off for peptide confidence scores was &gt; 95; % Sequence Coverage: the percentage of the protein sequence covered by identified peptides with confidence score &gt; 95.
DOI: 10.6084/m9.figshare.8038994
title: Data.xlsx

description: Raw data for calculation of means, SD, and SE<br>
DOI: 10.6084/m9.figshare.8038994.v1
title: Data.xlsx

description: Raw data for calculation of means, SD, and SE<br>
DOI: 10.6084/m9.figshare.8038982
title: the dem and river in yangtze river

description: please contact the author for dowload
DOI: 10.6084/m9.figshare.8038982.v1
title: the dem and river in yangtze river

description: please contact the author for dowload
DOI: 10.6084/m9.figshare.8038913
title: The METLIN small molecule dataset for machine learning-based retention time prediction

description: <b>The METLIN Small Molecule Retention Time (SMRT) dataset</b>The METLIN SMRT is a reverse-phase retention time dataset covering a total of 80,038 small molecules. The SMRT dataset includes, for each molecule, the retention time (in seconds), the PubChem number, the molfiles containing the structure (SDF format), and molecular descriptors and extended connectivity fingerprints (ECFP) calculated with Dragon 7 (Kode Chemoinformatics, Pisa, Italy). <br>The SMRT is a freely available resource. Use and redistribution of the data, in whole or in part, requires explicit acknowledgment of the source material and the original publication:<br><br>Domingo-Almenara, X. et al. The METLIN small molecule dataset for machine learning-based retention time prediction. <i>Nature Communications </i>(2019)<i> </i>DOI: 10.1038/s41467-019-13680-7<br><br>
DOI: 10.23641/asha.8038505
title: Involvement of communication partners (Biggs et al., 2019)

description: <b>Purpose: </b>The purpose of this study was to inform practice and research by identifying and synthesizing research on interventions in which natural communication partners implemented aided augmentative and alternative communication (AAC) modeling strategies.<b>Method: </b>A scoping review yielded 29 studies. Data were charted related to participant characteristics, intervention characteristics, partner instruction and assessment, and partner perspectives of social validity.<b>Results: </b>More than 157 peer and 100 adult communication partners (e.g., parents, special educators, paraprofessionals) implemented aided AAC modeling strategies within included studies. To teach communication partners intervention strategies, researchers frequently reported using (a) oral instruction, (b) modeling, and (c) practice or application opportunities with performance feedback. Partner instruction frequently involved both training and concurrent support (e.g., coaching, facilitation, consultation, follow-up support).<b>Conclusion:</b> Findings from this review inform the design and delivery of aided AAC modeling interventions by children’s natural communication partners. Findings also highlight important avenues for enhancing the rigor of future research on interventions involving aided AAC modeling, including the quality of reporting and application of principles from implementation science.<br><b>Supplemental Material S1. </b>Coding definitions for all variables included in the review.<br>Biggs, E. E., Carter, E. W., & Gilson, C. B. (2019). A scoping review of the involvement of children’s communication partners in aided augmentative and alternative communication modeling interventions. <i>American Journal of Speech-Language Pathology, 28, </i>743–758<i>.</i> https://doi.org/10.1044/2018_AJSLP-18-0024<br>
DOI: 10.6084/m9.figshare.8038451
title: spherical isobaric collision

description: spherical isobaric collision
DOI: 10.23641/asha.8038505.v1
title: Involvement of communication partners (Biggs et al., 2019)

description: <b>Purpose: </b>The purpose of this study was to inform practice and research by identifying and synthesizing research on interventions in which natural communication partners implemented aided augmentative and alternative communication (AAC) modeling strategies.<b>Method: </b>A scoping review yielded 29 studies. Data were charted related to participant characteristics, intervention characteristics, partner instruction and assessment, and partner perspectives of social validity.<b>Results: </b>More than 157 peer and 100 adult communication partners (e.g., parents, special educators, paraprofessionals) implemented aided AAC modeling strategies within included studies. To teach communication partners intervention strategies, researchers frequently reported using (a) oral instruction, (b) modeling, and (c) practice or application opportunities with performance feedback. Partner instruction frequently involved both training and concurrent support (e.g., coaching, facilitation, consultation, follow-up support).<b>Conclusion:</b> Findings from this review inform the design and delivery of aided AAC modeling interventions by children’s natural communication partners. Findings also highlight important avenues for enhancing the rigor of future research on interventions involving aided AAC modeling, including the quality of reporting and application of principles from implementation science.<br><b>Supplemental Material S1. </b>Coding definitions for all variables included in the review.<br>Biggs, E. E., Carter, E. W., & Gilson, C. B. (2019). A scoping review of the involvement of children’s communication partners in aided augmentative and alternative communication modeling interventions. <i>American Journal of Speech-Language Pathology, 28, </i>743–758<i>.</i> https://doi.org/10.1044/2018_AJSLP-18-0024<br>
DOI: 10.6084/m9.figshare.8038448
title: ESI-MS and GC-MS raw data

description: ESI-MS and GC-MS raw data
DOI: 10.6084/m9.figshare.8035961
title: Industrial similarity between Greater London LSOAs, 2007-2014

description: These files present the industrial similarity between Greater London LSOAs (Lower Layer Super Output Areas) in 2007 and 2014, using the cosine similarity of their vectors of local units (entreprise plants) in each industry of the 2-digit SIC classification.<br>For 2007 and 2014, we have used the local<br>units file of the BSD database and extracted the units located in a London postcode. We then aggregated the industrial information (SIC) about these firms at LSOA level<br>and measured the vector similarity Sij of each pair of LSOAs, with the formula Sij = (direction of vector i . Direction of vector j) / (norm of vector i . norm of vector j). Therefore, the first column corresponds to a LSOA ID, the first column corresponds to a different LSOA ID and the third column corresponds the industrial similarity of the pair. High values of similarity mean the two areas have similar distribution of firms by industry, whereas low values indicate dissimilarity.<br><br>This work contains statistical data from ONS which is Crown Copyright. The use of the ONS statistical data in this work does not imply the endorsement of the ONS in relation to the interpretation or analysis of the statistical data. This work uses research datasets which may not exactly reproduce National Statistics aggregates.<br>
DOI: 10.6084/m9.figshare.8035958
title: Data and analysis.zip

description: Data for IGG experiment