cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.11297864
title: Supplementary Material for: Developmental Differences in Platelet Inhibition Response to Prostaglandin E1

description: <b><i>Background:</i></b> The mechanisms underlying neonatal platelets hyporesponsiveness are not fully understood. While previous studies have demonstrated developmental impairment of agonist-induced platelet activation, differences in inhibitory signaling pathways have been scarcely investigated. <b><i>Objective:</i></b> To compare neonatal and adult platelets with regard to inhibition of platelet reactivity by prostaglandin E1 (PGE<sub>1</sub>). <b><i>Methods:</i></b> Platelet-rich plasma from umbilical cord (CB) or adult blood was incubated with PGE<sub>1</sub> (0–1 μM). We assessed aggregation in response to adenosine diphosphate (ADP), collagen, and thrombin receptor activating peptide as well as cyclic adenosine 3′5′-monophosphate (cAMP) levels (ELISA). G<sub>αs</sub>, G<sub>αi2</sub>, and total- and phospho-protein kinase A (PKA) were evaluated in adult and CB ultrapure and washed platelets, respectively, by immunoblotting. <b><i>Results:</i></b> Neonatal (vs. adult) platelets display hypersensitivity to inhibition by PGE<sub>1</sub> of platelet aggregation induced by ADP and collagen (PGE<sub>1</sub> IC<sub>50</sub>: 14 and 117 nM for ADP and collagen, respectively, vs. 149 and 491 nM in adults). They also show increased basal and PGE<sub>1</sub>-induced cAMP levels. Mechanistically, PGE<sub>1</sub> acts by binding to the prostanoid receptor IP (prostacyclin receptor), which couples to the G<sub>αs</sub> protein-adenylate cyclase axis and increases intracellular levels of cAMP. cAMP activates PKA, which phosphorylates different target inhibitor proteins. Neonatal platelets showed higher basal and PGE<sub>1</sub>-induced cAMP levels, higher G<sub>αs</sub> protein expression, and a trend to increased PKA-dependent protein phosphorylation compared to adult platelets. <b><i>Conclusion:</i></b> Neonatal platelets have a functionally increased PGE<sub>1</sub>-cAMP-PKA axis. This finding supports a downregulation of inhibitory when going from neonate to adult contributing to neonatal platelet hyporesponsiveness.
DOI: 10.6084/m9.figshare.11297867
title: Supplementary Material for: Double Autosomal/Gonosomal Mosaic Trisomy 47,XXX/47,XX,+14 in a Newborn with Multiple Congenital Anomalies

description: Chromosomal trisomies are the most frequent major chromosomal anomalies in humans and can be present in a mosaic or a non-mosaic constitution. We report the first case of a newborn girl presenting with multiple congenital anomalies and a double mosaic trisomy involving chromosome 14 and the X chromosome detected by array CGH. Karyotype analysis revealed a double mosaic with 2 independent abnormal cell lines and the absence of 46,XX and 48,XXX,+14 cell lineages. The patient showed most of the clinical characteristics of mosaic trisomy 14. Analysis of autosomal DNA markers in the proband's blood sample did not support the presence of chimerism. Further analysis of chromosome X DNA markers suggests that the extra X chromosome most probably arose as a consequence of nondisjunction in meiosis II in the maternal lineage.
DOI: 10.6084/m9.figshare.11297864.v1
title: Supplementary Material for: Developmental Differences in Platelet Inhibition Response to Prostaglandin E1

description: <b><i>Background:</i></b> The mechanisms underlying neonatal platelets hyporesponsiveness are not fully understood. While previous studies have demonstrated developmental impairment of agonist-induced platelet activation, differences in inhibitory signaling pathways have been scarcely investigated. <b><i>Objective:</i></b> To compare neonatal and adult platelets with regard to inhibition of platelet reactivity by prostaglandin E1 (PGE<sub>1</sub>). <b><i>Methods:</i></b> Platelet-rich plasma from umbilical cord (CB) or adult blood was incubated with PGE<sub>1</sub> (0–1 μM). We assessed aggregation in response to adenosine diphosphate (ADP), collagen, and thrombin receptor activating peptide as well as cyclic adenosine 3′5′-monophosphate (cAMP) levels (ELISA). G<sub>αs</sub>, G<sub>αi2</sub>, and total- and phospho-protein kinase A (PKA) were evaluated in adult and CB ultrapure and washed platelets, respectively, by immunoblotting. <b><i>Results:</i></b> Neonatal (vs. adult) platelets display hypersensitivity to inhibition by PGE<sub>1</sub> of platelet aggregation induced by ADP and collagen (PGE<sub>1</sub> IC<sub>50</sub>: 14 and 117 nM for ADP and collagen, respectively, vs. 149 and 491 nM in adults). They also show increased basal and PGE<sub>1</sub>-induced cAMP levels. Mechanistically, PGE<sub>1</sub> acts by binding to the prostanoid receptor IP (prostacyclin receptor), which couples to the G<sub>αs</sub> protein-adenylate cyclase axis and increases intracellular levels of cAMP. cAMP activates PKA, which phosphorylates different target inhibitor proteins. Neonatal platelets showed higher basal and PGE<sub>1</sub>-induced cAMP levels, higher G<sub>αs</sub> protein expression, and a trend to increased PKA-dependent protein phosphorylation compared to adult platelets. <b><i>Conclusion:</i></b> Neonatal platelets have a functionally increased PGE<sub>1</sub>-cAMP-PKA axis. This finding supports a downregulation of inhibitory when going from neonate to adult contributing to neonatal platelet hyporesponsiveness.
DOI: 10.6084/m9.figshare.11297867.v1
title: Supplementary Material for: Double Autosomal/Gonosomal Mosaic Trisomy 47,XXX/47,XX,+14 in a Newborn with Multiple Congenital Anomalies

description: Chromosomal trisomies are the most frequent major chromosomal anomalies in humans and can be present in a mosaic or a non-mosaic constitution. We report the first case of a newborn girl presenting with multiple congenital anomalies and a double mosaic trisomy involving chromosome 14 and the X chromosome detected by array CGH. Karyotype analysis revealed a double mosaic with 2 independent abnormal cell lines and the absence of 46,XX and 48,XXX,+14 cell lineages. The patient showed most of the clinical characteristics of mosaic trisomy 14. Analysis of autosomal DNA markers in the proband's blood sample did not support the presence of chimerism. Further analysis of chromosome X DNA markers suggests that the extra X chromosome most probably arose as a consequence of nondisjunction in meiosis II in the maternal lineage.
DOI: 10.6084/m9.figshare.11297825
title: Influence of age on the efficacy of immune checkpoint inhibitors in advanced cancers: a systematic review and meta-analysis

description: <b>Background:</b> Immune checkpoint inhibitors (ICIs) represent a paradigm shift in the development of cancer treatment. However, it remains to be clarified whether the benefits that they confer differ according to patient age. We conducted a systematic review and meta-analysis to assess age differences in the benefits of ICI treatment. <b>Methods:</b> We systematically searched the PubMed database for randomised controlled trials of ICIs, including PD-1, PD-L1 and CTLA-4 inhibitors across multiple cancer types, such as melanoma, lung cancer and gastric cancer. We extracted trials including hazard ratios (HRs) for death stratified by patient age (cut-off age, 65 years). The primary objective of this study was to assess the difference in ICI efficacy between younger and older patients. We calculated pooled HRs and 95% confidence intervals (CIs) for younger and older cancer patients, and assessed data heterogeneity. <b>Results:</b> We identified 3999 studies in our search. Of these, 24 eligible randomised trials, including a total of 8157 (57%) younger and 6104 (43%) older cancer patients, fulfilled the criteria for our study and were thus further analysed. The pooled HRs of the younger and older patients were 0.76 (95% CI: 0.69–0.84) and 0.80 (95% CI: 0.71–0.86), respectively; the difference in ICI efficacy between younger and older cancer patients was not significant (<i>p</i> = .82). Regarding the PD-1 and PD-L1 inhibitors, the survival benefit was similar in both age groups (HR: 0.74; <i>p</i> = .96), whereas for the CTLA-4 inhibitors, there tended to be less survival benefit for older versus younger patients (HR: 0.90 and 0.77, respectively; <i>p</i> = .26). <b>Conclusions:</b> The survival benefit conferred by ICI was not age-dependent, amongst patients aged 65 years or younger. However, age-dependent benefits may vary amongst different types of ICIs.
DOI: 10.6084/m9.figshare.11297825.v1
title: Influence of age on the efficacy of immune checkpoint inhibitors in advanced cancers: a systematic review and meta-analysis

description: <b>Background:</b> Immune checkpoint inhibitors (ICIs) represent a paradigm shift in the development of cancer treatment. However, it remains to be clarified whether the benefits that they confer differ according to patient age. We conducted a systematic review and meta-analysis to assess age differences in the benefits of ICI treatment. <b>Methods:</b> We systematically searched the PubMed database for randomised controlled trials of ICIs, including PD-1, PD-L1 and CTLA-4 inhibitors across multiple cancer types, such as melanoma, lung cancer and gastric cancer. We extracted trials including hazard ratios (HRs) for death stratified by patient age (cut-off age, 65 years). The primary objective of this study was to assess the difference in ICI efficacy between younger and older patients. We calculated pooled HRs and 95% confidence intervals (CIs) for younger and older cancer patients, and assessed data heterogeneity. <b>Results:</b> We identified 3999 studies in our search. Of these, 24 eligible randomised trials, including a total of 8157 (57%) younger and 6104 (43%) older cancer patients, fulfilled the criteria for our study and were thus further analysed. The pooled HRs of the younger and older patients were 0.76 (95% CI: 0.69–0.84) and 0.80 (95% CI: 0.71–0.86), respectively; the difference in ICI efficacy between younger and older cancer patients was not significant (<i>p</i> = .82). Regarding the PD-1 and PD-L1 inhibitors, the survival benefit was similar in both age groups (HR: 0.74; <i>p</i> = .96), whereas for the CTLA-4 inhibitors, there tended to be less survival benefit for older versus younger patients (HR: 0.90 and 0.77, respectively; <i>p</i> = .26). <b>Conclusions:</b> The survival benefit conferred by ICI was not age-dependent, amongst patients aged 65 years or younger. However, age-dependent benefits may vary amongst different types of ICIs.
DOI: 10.6084/m9.figshare.11297651
title: Probing long-range anisotropic interactions – A general and sign-sensitive strategy to measure 1H-1H residual dipolar couplings as a key advance for organic structure determination

description: Raw Bruker NMR data associated with the publication in Angewandte Chemie International Edition, 2020, DOI: 10.1002/anie.201915278<br>Residual dipolar couplings (RDCs) are amongst the most powerful NMR parameters for organic structure elucidation. In order to maximize their effectiveness in increasingly complex cases such as flexible compounds, a maximum of RDCs between nuclei sampling a large distribution of orientations is needed, including sign information. For this, the easily accessible one-bond <sup>1</sup>H-<sup>13</sup>C RDCs alone often fall short. Long-range <sup>1</sup>H-<sup>1</sup>H RDCs are both abundant and typically sample highly complementary orientations, but accessing them in a sign-sensitive way has been severely obstructed due to the overflow of <sup>1</sup>H-<sup>1</sup>H couplings. Here, we present a generally applicable strategy that allows the measurement of a large number of <sup>1</sup>H-<sup>1</sup>H RDCs, including the sign, that is based on a combination of the PSYCHEDELIC method and a new selective constant-time beta-COSY experiment. The potential of <sup>1</sup>H-<sup>1</sup>H RDCs to better determine molecular alignment and to discriminate between enantiomers and diastereomers is demonstrated.<br>
DOI: 10.6084/m9.figshare.11297651.v1
title: Probing long-range anisotropic interactions – A general and sign-sensitive strategy to measure 1H-1H residual dipolar couplings as a key advance for organic structure determination

description: Raw Bruker NMR data associated with the publication in Angewandte Chemie International Edition, 2020, DOI: 10.1002/anie.201915278<br>Residual dipolar couplings (RDCs) are amongst the most powerful NMR parameters for organic structure elucidation. In order to maximize their effectiveness in increasingly complex cases such as flexible compounds, a maximum of RDCs between nuclei sampling a large distribution of orientations is needed, including sign information. For this, the easily accessible one-bond <sup>1</sup>H-<sup>13</sup>C RDCs alone often fall short. Long-range <sup>1</sup>H-<sup>1</sup>H RDCs are both abundant and typically sample highly complementary orientations, but accessing them in a sign-sensitive way has been severely obstructed due to the overflow of <sup>1</sup>H-<sup>1</sup>H couplings. Here, we present a generally applicable strategy that allows the measurement of a large number of <sup>1</sup>H-<sup>1</sup>H RDCs, including the sign, that is based on a combination of the PSYCHEDELIC method and a new selective constant-time beta-COSY experiment. The potential of <sup>1</sup>H-<sup>1</sup>H RDCs to better determine molecular alignment and to discriminate between enantiomers and diastereomers is demonstrated.<br>
DOI: 10.6084/m9.figshare.11297480
title: Baker et al 2020 - Ecological impacts of tidal barrages

description: Environmental layers used in, and output from, Baker et al 2020 paper "Ecological impacts of tidal barrages". Used in the code here: https://github.com/EnvModellingGroup/baker_etal_2020<br>unaltered: raster layers for the unaltered (no barrage or present day) scenario<br>with_barrage: raster layers for the scenario with the Severn barrage in place<br>severn_sdm_web.zip: output from all 10 iterations for all 14 species when species are linked with a food web<br>severn_sdm.zip: as above, but no food web association used.
DOI: 10.6084/m9.figshare.11297123
title: MOESM4 of Gender and collaboration patterns in a temporal scientific authorship network

description: Additional file 4 INFORMS network dataset.
DOI: 10.6084/m9.figshare.11297123.v1
title: MOESM4 of Gender and collaboration patterns in a temporal scientific authorship network

description: Additional file 4 INFORMS network dataset.
DOI: 10.6084/m9.figshare.11297018
title: MOESM2 of Transcriptomic analysis of monocytes from HIV-positive men on antiretroviral therapy reveals effects of tobacco smoking on interferon and stress response systems associated with depressive symptoms

description: Additional file 2: Table S1. Fold-changes for all expressed probes: HIV+ TS+ vs. HIV- TS- limma model A. Table S2. Enriched gene ontology (GO) terms and associated genes: HIV+ TS+ vs. HIV- TS-. Table S3. Fold-changes for all expressed probes: HIV+ TS+ vs. HIV+ TS- limma model B. Table S4. Enriched gene ontology (GO) terms and associated genes: HIV+ TS+ vs. HIV+ TS-. Table S5. Fold-changes for all expressed probes: HIV+ TS- vs. HIV+ TS- limma model C. Table S6. Enriched gene ontology (GO) terms and associated genes: HIV+ TS- vs. HIV+ TS-. Table S7. Fold-changes for all expressed probes: HIV+ (HIV viral load ≤200) TS+ vs. HIV- TS- limma model for sensitivity analysis. Table S8. Enriched gene ontology (GO) terms and associated genes: HIV+ (HIV viral load ≤200) TS+ vs. HIV- TS-. Table S9. Fold-changes for all expressed probes: HIV+ (HIV viral load ≤200) TS+ vs. HIV+ (HIV viral load ≤200) TS- limma model for sensitivity analysis. Table S10. Enriched gene ontology (GO) terms and associated genes: HIV+ (HIV viral load ≤200) TS+ vs. HIV+ (HIV viral load ≤200) TS-.
DOI: 10.6084/m9.figshare.11297018.v1
title: MOESM2 of Transcriptomic analysis of monocytes from HIV-positive men on antiretroviral therapy reveals effects of tobacco smoking on interferon and stress response systems associated with depressive symptoms

description: Additional file 2: Table S1. Fold-changes for all expressed probes: HIV+ TS+ vs. HIV- TS- limma model A. Table S2. Enriched gene ontology (GO) terms and associated genes: HIV+ TS+ vs. HIV- TS-. Table S3. Fold-changes for all expressed probes: HIV+ TS+ vs. HIV+ TS- limma model B. Table S4. Enriched gene ontology (GO) terms and associated genes: HIV+ TS+ vs. HIV+ TS-. Table S5. Fold-changes for all expressed probes: HIV+ TS- vs. HIV+ TS- limma model C. Table S6. Enriched gene ontology (GO) terms and associated genes: HIV+ TS- vs. HIV+ TS-. Table S7. Fold-changes for all expressed probes: HIV+ (HIV viral load ≤200) TS+ vs. HIV- TS- limma model for sensitivity analysis. Table S8. Enriched gene ontology (GO) terms and associated genes: HIV+ (HIV viral load ≤200) TS+ vs. HIV- TS-. Table S9. Fold-changes for all expressed probes: HIV+ (HIV viral load ≤200) TS+ vs. HIV+ (HIV viral load ≤200) TS- limma model for sensitivity analysis. Table S10. Enriched gene ontology (GO) terms and associated genes: HIV+ (HIV viral load ≤200) TS+ vs. HIV+ (HIV viral load ≤200) TS-.
DOI: 10.6084/m9.figshare.11296913
title: MOESM1 of Improved metagenomic analysis with Kraken 2

description: Additional file 1: Table S1. Comparison of accuracy and computational performance. Table S2. Comparison of Kraken 2 with other classifiers, using various parameter values. Table S3. Genomes excluded in strain-exclusion simulation. Table S4. Thread scaling evaluation results. Table S5. Evaluation of FDA-ARGOS sequencing data. Table S6. Sequences used for evaluation of collision rates. Table S7. Minimizer collision evaluation results. Table S8. Hash table collision evaluation results. Table S9. Comparison of Kraken 2X with other classifiers, using various parameter values. Table S10. Database size evaluation results.
DOI: 10.6084/m9.figshare.11296913.v1
title: MOESM1 of Improved metagenomic analysis with Kraken 2

description: Additional file 1: Table S1. Comparison of accuracy and computational performance. Table S2. Comparison of Kraken 2 with other classifiers, using various parameter values. Table S3. Genomes excluded in strain-exclusion simulation. Table S4. Thread scaling evaluation results. Table S5. Evaluation of FDA-ARGOS sequencing data. Table S6. Sequences used for evaluation of collision rates. Table S7. Minimizer collision evaluation results. Table S8. Hash table collision evaluation results. Table S9. Comparison of Kraken 2X with other classifiers, using various parameter values. Table S10. Database size evaluation results.
DOI: 10.6084/m9.figshare.11296805
title: MOESM4 of The dynamics of the inflammatory response during BBN-induced bladder carcinogenesis in mice

description: Additional file 4. Table S1. Analysis of the leading edge subset of genes involved in innate and adaptive immunity.
DOI: 10.6084/m9.figshare.11296805.v1
title: MOESM4 of The dynamics of the inflammatory response during BBN-induced bladder carcinogenesis in mice

description: Additional file 4. Table S1. Analysis of the leading edge subset of genes involved in innate and adaptive immunity.
DOI: 10.6084/m9.figshare.11296724
title: MOESM1 of Transcriptome profiling of resistance response to Meloidogyne chitwoodi introgressed from wild species Solanum bulbocastanum into cultivated potato

description: Additional file 1. Gene Ontology results of all the enriched terms for the genes up-regulated in the resistant clone, PA99N82â€“4 at 48 hpi, 7 dpi, 14 dpi and 21 dpi.
DOI: 10.6084/m9.figshare.11296718
title: MOESM2 of DNA methylation associated with postpartum depressive symptoms overlaps findings from a genome-wide association meta-analysis of depression

description: Additional file 2. List of genes overlapping differentially methylated regions. List of the 92 genes overlapped by significant differentially methylated regions (DMRs).
DOI: 10.6084/m9.figshare.11296724.v1
title: MOESM1 of Transcriptome profiling of resistance response to Meloidogyne chitwoodi introgressed from wild species Solanum bulbocastanum into cultivated potato

description: Additional file 1. Gene Ontology results of all the enriched terms for the genes up-regulated in the resistant clone, PA99N82â€“4 at 48 hpi, 7 dpi, 14 dpi and 21 dpi.
DOI: 10.6084/m9.figshare.11296709
title: MOESM3 of Arsenic metabolism in technical biogas plants: possible consequences for resident microbiota and downstream units

description: Additional file 3. Additional electronic material (Qiime2 files).
DOI: 10.6084/m9.figshare.11296703
title: MOESM2 of Arsenic metabolism in technical biogas plants: possible consequences for resident microbiota and downstream units

description: Additional file 2. Additional electronic material, which provides full dataset of Figure 1 (Qiime2 files).
DOI: 10.6084/m9.figshare.11296709.v1
title: MOESM3 of Arsenic metabolism in technical biogas plants: possible consequences for resident microbiota and downstream units

description: Additional file 3. Additional electronic material (Qiime2 files).
DOI: 10.6084/m9.figshare.11296703.v1
title: MOESM2 of Arsenic metabolism in technical biogas plants: possible consequences for resident microbiota and downstream units

description: Additional file 2. Additional electronic material, which provides full dataset of Figure 1 (Qiime2 files).
DOI: 10.6084/m9.figshare.11296676
title: MOESM2 of 547 transcriptomes from 44 brain areas reveal features of the aging brain in non-human primates

description: Additional file 2. Supplementary Tables S1â€“S10.
DOI: 10.6084/m9.figshare.11296595
title: MOESM4 of AMON: annotation of metabolite origins via networks to integrate microbiome and metabolome data

description: Additional file 4: Table S4. MIMOSA Results Table from Case Study Data
DOI: 10.6084/m9.figshare.11296589
title: MOESM3 of AMON: annotation of metabolite origins via networks to integrate microbiome and metabolome data

description: Additional file 3: Table S3. Example Output of AMON Pathway Enrichment Table
DOI: 10.6084/m9.figshare.11296595.v1
title: MOESM4 of AMON: annotation of metabolite origins via networks to integrate microbiome and metabolome data

description: Additional file 4: Table S4. MIMOSA Results Table from Case Study Data
DOI: 10.6084/m9.figshare.11296580
title: MOESM1 of AMON: annotation of metabolite origins via networks to integrate microbiome and metabolome data

description: Additional file 1: Table S1. Table of Metabolites with KEGG Annotations from LC/MS of Human Plasma
DOI: 10.6084/m9.figshare.11296583
title: MOESM2 of AMON: annotation of metabolite origins via networks to integrate microbiome and metabolome data

description: Additional file 2: Table S2. Example Output of AMON Metabolite Origin Table
DOI: 10.6084/m9.figshare.11296589.v1
title: MOESM3 of AMON: annotation of metabolite origins via networks to integrate microbiome and metabolome data

description: Additional file 3: Table S3. Example Output of AMON Pathway Enrichment Table
DOI: 10.6084/m9.figshare.11296571
title: MOESM4 of CRIMoClo plasmids for modular assembly and orthogonal chromosomal integration of synthetic circuits in Escherichia coli

description: Additional file 4: Table S3. Primers used in this study.
DOI: 10.6084/m9.figshare.11296574
title: MOESM5 of CRIMoClo plasmids for modular assembly and orthogonal chromosomal integration of synthetic circuits in Escherichia coli

description: Additional file 5. Plasmid maps of the 32 CRIMoClo plasmids.
DOI: 10.6084/m9.figshare.11296580.v1
title: MOESM1 of AMON: annotation of metabolite origins via networks to integrate microbiome and metabolome data

description: Additional file 1: Table S1. Table of Metabolites with KEGG Annotations from LC/MS of Human Plasma
DOI: 10.6084/m9.figshare.11296583.v1
title: MOESM2 of AMON: annotation of metabolite origins via networks to integrate microbiome and metabolome data

description: Additional file 2: Table S2. Example Output of AMON Metabolite Origin Table
DOI: 10.6084/m9.figshare.11296568
title: MOESM3 of CRIMoClo plasmids for modular assembly and orthogonal chromosomal integration of synthetic circuits in Escherichia coli

description: Additional file 3: Table S2. CRIMoClo vectors generated in this study.