cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.11364896.v1
title: Supplementary Material for: Synergistic Ototoxicity of Gentamicin and Low-Dose Irradiation: Molecular Basis and Clinical Significance

description: <b><i>Background:</i></b> Inner ear structures may be included in the radiation fields when irradiation is used to treat patients with head and neck cancers. These patients may also have concurrent infections that require gentamicin treatment. Radiation and gentamicin are both potentially ototoxic, and their combined use has been shown to result in synergistic ototoxicity in animals. <b><i>Objective:</i></b> We aimed to confirm the synergistic ototoxicity of combined gentamicin and low-dose irradiation treatment and identify the underlying molecular mechanisms using an in vitro model. <b><i>Method:</i></b> We compared the ototoxic effects of gentamicin, low-dose irradiation, and their combination in the OC-k3 mouse cochlear cell line using cell viability assay, live/dead stain, apoptosis detection assay, oxidative stress detection, and studied the molecular mechanisms involved using immunoblot analysis. <b><i>Results:</i></b> Combined treatment led to prolonged oxidative stress, reduced cell viability, and synergistic apoptosis. Gentamicin induced the concurrent accumulation of LC3b-II and SQSTM1/p62, suggesting an impairment of autophagic flux. Low-dose irradiation induced transient p53 phosphorylation and persistent Akt phosphorylation in response to DNA damage. In combined treatment, gentamicin attenuated irradiation-induced Akt activation. <b><i>Conclusions:</i></b> Besides increased oxidative stress, synergistic apoptosis observed in combined treatment could be attributed to gentamicin-induced perturbation of autophagic flux and attenuation of Akt phosphorylation, which led to an impairment of radiation-induced DNA repair response.
DOI: 10.6084/m9.figshare.12865649
title: Figure 2 from manuscript Sparsely-Connected Autoencoder (SCA) for single cell RNAseq data mining

description: Dataset used to generate Figure 2 (/fig2.png). Fig. 2: SCA analysis using a TF-based latent space. A) five clusters were detected analysing setA with griph using log10 transformed counts table. Each cluster is made by more than 90% by one cell type. A little amount of HSC is contaminating B cells, monocytes and naïve T cells (/setA/results/setA). Latent space clustering was done with SIMLR (/setA/results/setATF_SIMLR) B) QCC violin plot (/setA/Results/setATF_SIMLR/5/setA_stabilityPlot.pdf). The metric is an extension of CSS and it measures the ability of latent space to keep aggregated cells belonging to predefined clusters, i.e. those in panel A. C) QCM violin plot (/setA/Results/setATF_SIMLR/5/setA_stabilityPlotUNBIAS.pdf), this metric is also an extension of CSS and it measures the ability of the neural network to generate consistent data over multiple SCA runs. Dashed red line indicates the defined threshold to consider the latent space information suitable to support cells’ clusters. Input counts table for SCA analysis is log10 transformed. <br>
DOI: 10.6084/m9.figshare.12865649.v1
title: Figure 2 from manuscript Sparsely-Connected Autoencoder (SCA) for single cell RNAseq data mining

description: Dataset used to generate Figure 2 (/fig2.png). Fig. 2: SCA analysis using a TF-based latent space. A) five clusters were detected analysing setA with griph using log10 transformed counts table. Each cluster is made by more than 90% by one cell type. A little amount of HSC is contaminating B cells, monocytes and naïve T cells (/setA/results/setA). Latent space clustering was done with SIMLR (/setA/results/setATF_SIMLR) B) QCC violin plot (/setA/Results/setATF_SIMLR/5/setA_stabilityPlot.pdf). The metric is an extension of CSS and it measures the ability of latent space to keep aggregated cells belonging to predefined clusters, i.e. those in panel A. C) QCM violin plot (/setA/Results/setATF_SIMLR/5/setA_stabilityPlotUNBIAS.pdf), this metric is also an extension of CSS and it measures the ability of the neural network to generate consistent data over multiple SCA runs. Dashed red line indicates the defined threshold to consider the latent space information suitable to support cells’ clusters. Input counts table for SCA analysis is log10 transformed. <br>
DOI: 10.6084/m9.figshare.11364593
title: MOESM1 of Saliva proteomics updates in biomedicine

description: Additional file 1. Additional table.
DOI: 10.6084/m9.figshare.11364593.v1
title: MOESM1 of Saliva proteomics updates in biomedicine

description: Additional file 1. Additional table.
DOI: 10.6084/m9.figshare.11364395
title: MOESM3 of Gantenerumab reduces amyloid-β plaques in patients with prodromal to moderate Alzheimer’s disease: a PET substudy interim analysis

description: Additional file 3: Figure S1. Study Design With Dosing Schedule and Patient Disposition. (A) Schematic representation of the MR and SR OLE study designs and dose-titration schedules. All patients in the OLE (including those previously on placebo) received gantenerumab subcutaneously every 4 weeks. Dose-titration schedules for uptitration to 1200 mg were assigned based on APOEε4 carrier status and last treatment dose during the double-blind phase. (B) Patient disposition. a Including 1 patient who missed their week 52 visit.
DOI: 10.6084/m9.figshare.11364395.v1
title: MOESM3 of Gantenerumab reduces amyloid-β plaques in patients with prodromal to moderate Alzheimer’s disease: a PET substudy interim analysis

description: Additional file 3: Figure S1. Study Design With Dosing Schedule and Patient Disposition. (A) Schematic representation of the MR and SR OLE study designs and dose-titration schedules. All patients in the OLE (including those previously on placebo) received gantenerumab subcutaneously every 4 weeks. Dose-titration schedules for uptitration to 1200 mg were assigned based on APOEε4 carrier status and last treatment dose during the double-blind phase. (B) Patient disposition. a Including 1 patient who missed their week 52 visit.
DOI: 10.6084/m9.figshare.11364323
title: MOESM3 of CTCF modulates allele-specific sub-TAD organization and imprinted gene activity at the mouse Dlk1-Dio3 and Igf2-H19 domains

description: Additional file 3. RNA transcript levels of genes in the Igf2-H19 and Dlk1-Dio3 TADs in mono-parental ESCs (RNA-seq).
DOI: 10.6084/m9.figshare.11364314
title: MOESM2 of CTCF modulates allele-specific sub-TAD organization and imprinted gene activity at the mouse Dlk1-Dio3 and Igf2-H19 domains

description: Additional file 2. CTCF binding peaks in the Dlk1-Dio3 TAD in mono-parental ESCs (ChIP-seq).
DOI: 10.6084/m9.figshare.11364323.v1
title: MOESM3 of CTCF modulates allele-specific sub-TAD organization and imprinted gene activity at the mouse Dlk1-Dio3 and Igf2-H19 domains

description: Additional file 3. RNA transcript levels of genes in the Igf2-H19 and Dlk1-Dio3 TADs in mono-parental ESCs (RNA-seq).
DOI: 10.6084/m9.figshare.11364314.v1
title: MOESM2 of CTCF modulates allele-specific sub-TAD organization and imprinted gene activity at the mouse Dlk1-Dio3 and Igf2-H19 domains

description: Additional file 2. CTCF binding peaks in the Dlk1-Dio3 TAD in mono-parental ESCs (ChIP-seq).
DOI: 10.6084/m9.figshare.11364257
title: MOESM1 of Nucleotide composition of transposable elements likely contributes to AT/GC compositional homogeneity of teleost fish genomes

description: Additional file 1: Table S1. Species overview and their counts.
DOI: 10.6084/m9.figshare.11364260
title: MOESM2 of Nucleotide composition of transposable elements likely contributes to AT/GC compositional homogeneity of teleost fish genomes

description: Additional file 2: Table S2. Datasets used for generating Figs. 1, 2, 3, 4 and Additional files 3 and 4: Figures S1-S2.
DOI: 10.6084/m9.figshare.11364257.v1
title: MOESM1 of Nucleotide composition of transposable elements likely contributes to AT/GC compositional homogeneity of teleost fish genomes

description: Additional file 1: Table S1. Species overview and their counts.
DOI: 10.6084/m9.figshare.11364260.v1
title: MOESM2 of Nucleotide composition of transposable elements likely contributes to AT/GC compositional homogeneity of teleost fish genomes

description: Additional file 2: Table S2. Datasets used for generating Figs. 1, 2, 3, 4 and Additional files 3 and 4: Figures S1-S2.
DOI: 10.6084/m9.figshare.11364233
title: MOESM3 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 3. Statistics for volcano plots. Statistics and annotations for the proteins that showed a fold change in expression over the sucrose control under each growth condition.
DOI: 10.6084/m9.figshare.11364230
title: MOESM33 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 33. Phoma CK108 predicted coding sequences. Phoma CK108 predicted coding sequences.
DOI: 10.6084/m9.figshare.11364230.v1
title: MOESM33 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 33. Phoma CK108 predicted coding sequences. Phoma CK108 predicted coding sequences.
DOI: 10.6084/m9.figshare.11364221
title: MOESM31 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 31. Embellisia CK46 predicted coding sequences. Embellisia CK46 predicted coding sequences.
DOI: 10.6084/m9.figshare.11364224
title: MOESM32 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 32. Chaetomium CK152 predicted coding sequences. Chaetomium CK152 predicted coding sequences.
DOI: 10.6084/m9.figshare.11364233.v1
title: MOESM3 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 3. Statistics for volcano plots. Statistics and annotations for the proteins that showed a fold change in expression over the sucrose control under each growth condition.
DOI: 10.6084/m9.figshare.11364224.v1
title: MOESM32 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 32. Chaetomium CK152 predicted coding sequences. Chaetomium CK152 predicted coding sequences.
DOI: 10.6084/m9.figshare.11364215
title: MOESM30 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 30. Coniochaeta CK134 predicted coding sequences. Coniochaeta CK134 predicted coding sequences.
DOI: 10.6084/m9.figshare.11364221.v1
title: MOESM31 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 31. Embellisia CK46 predicted coding sequences. Embellisia CK46 predicted coding sequences.
DOI: 10.6084/m9.figshare.11364209
title: MOESM2 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 2. Raw protein abundance data (from EMSL). Raw protein abundance data for each fungus, each condition, including all replicates.
DOI: 10.6084/m9.figshare.11364206
title: MOESM29 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 29. Aspergillus CK392 predicted coding sequences. Aspergillus CK392 predicted coding sequences.
DOI: 10.6084/m9.figshare.11364209.v1
title: MOESM2 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 2. Raw protein abundance data (from EMSL). Raw protein abundance data for each fungus, each condition, including all replicates.
DOI: 10.6084/m9.figshare.11364206.v1
title: MOESM29 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 29. Aspergillus CK392 predicted coding sequences. Aspergillus CK392 predicted coding sequences.
DOI: 10.6084/m9.figshare.11364215.v1
title: MOESM30 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 30. Coniochaeta CK134 predicted coding sequences. Coniochaeta CK134 predicted coding sequences.
DOI: 10.6084/m9.figshare.11364200
title: MOESM28 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 28. Phoma CK108 assembled contigs. Phoma CK108 genome.
DOI: 10.6084/m9.figshare.11364200.v1
title: MOESM28 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 28. Phoma CK108 assembled contigs. Phoma CK108 genome.
DOI: 10.6084/m9.figshare.11364191
title: MOESM27 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 27. Chaetomium CK152 assembled contigs. Chaetomium CK152 genome.
DOI: 10.6084/m9.figshare.11364191.v1
title: MOESM27 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 27. Chaetomium CK152 assembled contigs. Chaetomium CK152 genome.
DOI: 10.6084/m9.figshare.11364179
title: MOESM26 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 26. Embellisia CK46 assembled contigs. Embellisia CK46 genome.
DOI: 10.6084/m9.figshare.11364167
title: MOESM2 of Accounting for biases in survey-based estimates of population attributable fractions

description: Additional file 2. This is a Microsoft Excel file containing race/ethnic- and gender-specific PAF estimates used to estimate PAFpe and PAFpd in TableÂ 4.
DOI: 10.6084/m9.figshare.11364173
title: MOESM25 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 25. Coniochaeta CK134 assembled contigs. Coniochaeta CK134 genome.
DOI: 10.6084/m9.figshare.11364179.v1
title: MOESM26 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 26. Embellisia CK46 assembled contigs. Embellisia CK46 genome.
DOI: 10.6084/m9.figshare.11364164
title: MOESM24 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 24. Aspergillus CK392 assembled contigs. Aspergillus CK392 genome.
DOI: 10.6084/m9.figshare.11364167.v1
title: MOESM2 of Accounting for biases in survey-based estimates of population attributable fractions

description: Additional file 2. This is a Microsoft Excel file containing race/ethnic- and gender-specific PAF estimates used to estimate PAFpe and PAFpd in TableÂ 4.
DOI: 10.6084/m9.figshare.11364173.v1
title: MOESM25 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 25. Coniochaeta CK134 assembled contigs. Coniochaeta CK134 genome.
DOI: 10.6084/m9.figshare.11364158
title: MOESM1 of Accounting for biases in survey-based estimates of population attributable fractions

description: Additional file 1. This is a Stata do-file containing commands to fit clog-log discrete time survival models.
DOI: 10.6084/m9.figshare.11364155
title: MOESM23 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 23. CAZymes involved in plant biomass degradation. Summary table listing the numbers of CAZYme hits in each fungal genome in each of the CAZy categories corresponding to plant biomass degradation, organized by substrate.
DOI: 10.6084/m9.figshare.11364164.v1
title: MOESM24 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 24. Aspergillus CK392 assembled contigs. Aspergillus CK392 genome.
DOI: 10.6084/m9.figshare.11364146
title: MOESM21 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 21. DbCAN hits. Table showing DbCAN hits in each fungal genome. The output of hmmscan.
DOI: 10.6084/m9.figshare.11364152
title: MOESM22 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 22. Table showing Pfam hits in each fungal genome. The output of hmmscan.
DOI: 10.6084/m9.figshare.11364158.v1
title: MOESM1 of Accounting for biases in survey-based estimates of population attributable fractions

description: Additional file 1. This is a Stata do-file containing commands to fit clog-log discrete time survival models.
DOI: 10.6084/m9.figshare.11364143
title: MOESM20 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 20. CAZymes. Table listing the numbers of CAZyme hits in each CAZy family in each fungal genome.
DOI: 10.6084/m9.figshare.11364152.v1
title: MOESM22 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 22. Table showing Pfam hits in each fungal genome. The output of hmmscan.
DOI: 10.6084/m9.figshare.11364155.v1
title: MOESM23 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 23. CAZymes involved in plant biomass degradation. Summary table listing the numbers of CAZYme hits in each fungal genome in each of the CAZy categories corresponding to plant biomass degradation, organized by substrate.
DOI: 10.6084/m9.figshare.11364146.v1
title: MOESM21 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 21. DbCAN hits. Table showing DbCAN hits in each fungal genome. The output of hmmscan.
DOI: 10.6084/m9.figshare.11364134
title: MOESM19 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 19. Annotated proteins. BLASTP top hits to the nr database for each of the coding sequences in each of the fungal genomes.
DOI: 10.6084/m9.figshare.11364140
title: MOESM1 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 1. Protein homologs in all fungi. List of proteins encoded by genes that had homologs in all of the fungal genomes. This data was from the SPOCS clique analysis.
DOI: 10.6084/m9.figshare.11364134.v1
title: MOESM19 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 19. Annotated proteins. BLASTP top hits to the nr database for each of the coding sequences in each of the fungal genomes.
DOI: 10.6084/m9.figshare.11364140.v1
title: MOESM1 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 1. Protein homologs in all fungi. List of proteins encoded by genes that had homologs in all of the fungal genomes. This data was from the SPOCS clique analysis.
DOI: 10.6084/m9.figshare.11364143.v1
title: MOESM20 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 20. CAZymes. Table listing the numbers of CAZyme hits in each CAZy family in each fungal genome.
DOI: 10.6084/m9.figshare.11364128
title: MOESM18 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 18. Fungal toxins and secondary metabolites. Lists of fungal toxins ‘Toxins’ tab and secondary metabolites ‘Aspergillus SMs’ and ‘Phoma, Chaetomium SMs’ tabs, and evidence describing whether or not each of the fungal genomes encodes candidate genes for their biosynthesis.
DOI: 10.6084/m9.figshare.11364131
title: MOESM8 of Visit-to-visit variability of glycemia and vascular complications: the Hoorn Diabetes Care System cohort

description: Additional file 8: Table S5. Odds ratios of medication use (metformin, SU, insulin) across intervals. The lowest quintile is used as the reference group.
DOI: 10.6084/m9.figshare.11364131.v1
title: MOESM8 of Visit-to-visit variability of glycemia and vascular complications: the Hoorn Diabetes Care System cohort

description: Additional file 8: Table S5. Odds ratios of medication use (metformin, SU, insulin) across intervals. The lowest quintile is used as the reference group.
DOI: 10.6084/m9.figshare.11364116
title: MOESM6 of Visit-to-visit variability of glycemia and vascular complications: the Hoorn Diabetes Care System cohort

description: Additional file 6: Table S3. Unadjusted and adjusted effect sizes of models with FG-CV for each quintile.
DOI: 10.6084/m9.figshare.11364119
title: MOESM17 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 17. SMIPS output. Output of the SMIPS program (secondary metabolite anchor genes) for each fungal genome.
DOI: 10.6084/m9.figshare.11364128.v1
title: MOESM18 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 18. Fungal toxins and secondary metabolites. Lists of fungal toxins ‘Toxins’ tab and secondary metabolites ‘Aspergillus SMs’ and ‘Phoma, Chaetomium SMs’ tabs, and evidence describing whether or not each of the fungal genomes encodes candidate genes for their biosynthesis.
DOI: 10.6084/m9.figshare.11364116.v1
title: MOESM6 of Visit-to-visit variability of glycemia and vascular complications: the Hoorn Diabetes Care System cohort

description: Additional file 6: Table S3. Unadjusted and adjusted effect sizes of models with FG-CV for each quintile.
DOI: 10.6084/m9.figshare.11364119.v1
title: MOESM17 of Genomes and secretomes of Ascomycota fungi reveal diverse functions in plant biomass decomposition and pathogenesis

description: Additional file 17. SMIPS output. Output of the SMIPS program (secondary metabolite anchor genes) for each fungal genome.
DOI: 10.6084/m9.figshare.11364110
title: MOESM5 of Visit-to-visit variability of glycemia and vascular complications: the Hoorn Diabetes Care System cohort

description: Additional file 5: Figure S3. Characterization of individuals based on their HbA1c-CV. Unadjusted outcome against the five quintiles with the fifth quintile being the group with the highest FG-CV against (a) sex (% males) (b) age at diagnosis (c) BMI (d) % smokers (e) total cholesterol levels (f) HDL-C levels (g) triglycerides levels (h) DBP (i) SBP (j) eGFR. Lines represent loess smoothed levels over 5-year average values of outcomes.