cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14510287
title: Protection against reinfection with D614- or G614-SARS-CoV-2 isolates in golden Syrian hamster

description: Reinfections with SARS-CoV-2 have already been documented in humans, although its real incidence is currently unknown. Besides having a great impact on public health, this phenomenon raises the question of immunity generated by a single infection is sufficient to provide sterilizing/protective immunity to a subsequent SARS-CoV-2 re-exposure. The Golden Syrian hamster is a manageable animal model to explore immunological mechanisms able to counteract COVID-19, as it recapitulates pathological aspects of mild to moderately affected patients. Here, we report that SARS-CoV-2-inoculated hamsters resolve infection in the upper and lower respiratory tracts within seven days upon inoculation with the Cat01 (G614) SARS-CoV-2 isolate. Three weeks after the primary challenge, and despite high titres of neutralizing antibodies, half of the animals were susceptible to reinfection by both identical (Cat01, G614) and variant (WA/1, D614) SARS-CoV-2 isolates. However, upon re-inoculation, only nasal tissues were transiently infected with much lower viral replication than those observed after the first inoculation. These data indicate that a primary SARS-CoV-2 infection is not sufficient to elicit a sterilizing immunity in hamster models but protects against lung disease.
DOI: 10.6084/m9.figshare.14510287.v1
title: Protection against reinfection with D614- or G614-SARS-CoV-2 isolates in golden Syrian hamster

description: Reinfections with SARS-CoV-2 have already been documented in humans, although its real incidence is currently unknown. Besides having a great impact on public health, this phenomenon raises the question of immunity generated by a single infection is sufficient to provide sterilizing/protective immunity to a subsequent SARS-CoV-2 re-exposure. The Golden Syrian hamster is a manageable animal model to explore immunological mechanisms able to counteract COVID-19, as it recapitulates pathological aspects of mild to moderately affected patients. Here, we report that SARS-CoV-2-inoculated hamsters resolve infection in the upper and lower respiratory tracts within seven days upon inoculation with the Cat01 (G614) SARS-CoV-2 isolate. Three weeks after the primary challenge, and despite high titres of neutralizing antibodies, half of the animals were susceptible to reinfection by both identical (Cat01, G614) and variant (WA/1, D614) SARS-CoV-2 isolates. However, upon re-inoculation, only nasal tissues were transiently infected with much lower viral replication than those observed after the first inoculation. These data indicate that a primary SARS-CoV-2 infection is not sufficient to elicit a sterilizing immunity in hamster models but protects against lung disease.
DOI: 10.5281/zenodo.10672774
title: IODP Expedition 393 Magnetic susceptibility (whole round)

description: Magnetic susceptibility was measured on whole-round sections (and rarely section halves) on the Whole-Round Multisensor Logger (WRMSL) and/or Special Task Multisensor Logger (STMSL) using a Bartington MS2 meter and a 90 mm or 80 mm MS2C loop. As volume of the sample is not controlled for this experiment, susceptibility units are recorded in instrument units and are not volume-corrected.
DOI: 10.5281/zenodo.10672775
title: IODP Expedition 393 Magnetic susceptibility (whole round)

description: Magnetic susceptibility was measured on whole-round sections (and rarely section halves) on the Whole-Round Multisensor Logger (WRMSL) and/or Special Task Multisensor Logger (STMSL) using a Bartington MS2 meter and a 90 mm or 80 mm MS2C loop. As volume of the sample is not controlled for this experiment, susceptibility units are recorded in instrument units and are not volume-corrected.
DOI: 10.6084/m9.figshare.12413183
title: Surrogate Residuals for Discrete Choice Models

description: Discrete choice models (DCMs) are a class of models for modeling response variables that take values from a set of alternatives. Examples include logistic regression, probit regression, and multinomial logistic regression. These models are also referred together as generalized linear models. Although there exist methods for the goodness of fit of DCMs, defining intuitive residuals for such models has been difficult due to the fact that the responses are categorical values instead of continuous numbers. In this article, we propose the surrogate residual for DCMs based on the surrogate approach (Liu and Zhang 2018), which deals with an ordinal response. We consider categorical responses that may or may not be ordered. We shall show that our residual can be used to diagnose misspecification in the aspects of mean structure, individual-specific coefficients, and interaction effects. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.12413183.v1
title: Surrogate Residuals for Discrete Choice Models

description: Discrete choice models (DCMs) are a class of models for modeling response variables that take values from a set of alternatives. Examples include logistic regression, probit regression, and multinomial logistic regression. These models are also referred together as generalized linear models. Although there exist methods for the goodness of fit of DCMs, defining intuitive residuals for such models has been difficult due to the fact that the responses are categorical values instead of continuous numbers. In this article, we propose the surrogate residual for DCMs based on the surrogate approach (Liu and Zhang 2018), which deals with an ordinal response. We consider categorical responses that may or may not be ordered. We shall show that our residual can be used to diagnose misspecification in the aspects of mean structure, individual-specific coefficients, and interaction effects. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.11364608
title: MOESM1 of Systematic computational identification of prognostic cytogenetic markers in neuroblastoma

description: Additional file 1: Table S1. The copy number values of each chromosomal band on the Kocak dataset and the Pugh dataset.
DOI: 10.6084/m9.figshare.11364608.v1
title: MOESM1 of Systematic computational identification of prognostic cytogenetic markers in neuroblastoma

description: Additional file 1: Table S1. The copy number values of each chromosomal band on the Kocak dataset and the Pugh dataset.
DOI: 10.5281/zenodo.10672735
title: IODP Expedition 393 Photomicrographs

description: Microscopic images of discrete samples were acquired using stereo and upright light microscopes and captured on digital cameras. Image files were uploaded along with a brief description and a record of the microscopic and lighting conditions when the image was taken.
DOI: 10.5281/zenodo.10672736
title: IODP Expedition 393 Photomicrographs

description: Microscopic images of discrete samples were acquired using stereo and upright light microscopes and captured on digital cameras. Image files were uploaded along with a brief description and a record of the microscopic and lighting conditions when the image was taken.
DOI: 10.6084/m9.figshare.11364614
title: MOESM2 of Systematic computational identification of prognostic cytogenetic markers in neuroblastoma

description: Additional file 2: Table S2. A comprehensive list of chromosome bands with high frequency gain/loss events.
DOI: 10.6084/m9.figshare.11364614.v1
title: MOESM2 of Systematic computational identification of prognostic cytogenetic markers in neuroblastoma

description: Additional file 2: Table S2. A comprehensive list of chromosome bands with high frequency gain/loss events.
DOI: 10.6084/m9.figshare.17131786
title: Identification of key miRNA signature and pathways involved in multiple myeloma by integrated bioinformatics analysis

description: Multiple myeloma (MM) is one of the most common types of hematologic malignancy for which the underlying molecular mechanisms remain largely unclear. Dysregulated miRNA expression has been shown to be involved in MM tumorigenesis, progression and drug response. Therefore, a comprehensive analysis based on miRNA-level integrated strategy was performed. This study aimed to elucidate key miRNA signatures and pathways in MM by integrated bioinformatics analysis. Expression profiles GSE24371, GSE49261 and GSE54156 were obtained from the Gene Expression Omnibus database, and differentially expressed miRNAs (DEMirs) with <i>p</i> &lt; 0.05 were identified. The target genes of these DEMirs were obtained from ENCORI database, and functional enrichment, subpathway enrichment and protein–protein interaction network construction were performed. The key target genes were identified by random walk algorithm and survival verification was performed. <b>and discussion:</b> First, six up-regulated and four down-regulated DEMirs shared between any two GSE data sets were identified. Second, target genes (DEMirTGs) by up-regulated and down-regulated DEMirs were obtained. Functional and subpathway enrichment analysis showed that these up-regulated DEMirs are consistently involved in the Wnt signaling pathway. Moreover, enrichment of the down-regulated DEMirs is mainly in the MAPK signaling pathway. Finally, a protein–protein interaction sub-network for these DEMirTGs was constructed, the correlations between the two key genes were identified and survival in MM was evaluated using multiple independent data sets. We identified miRNA signatures and key target genes that were closely related to MM biology, and these genes might serve as potential therapeutic targets for MM patients.
DOI: 10.6084/m9.figshare.11364620
title: MOESM3 of Systematic computational identification of prognostic cytogenetic markers in neuroblastoma

description: Additional file 3: Table S3. A list of nonredundant chromosome bands by selecting the most frequently gained or lost bands from each cluster.
DOI: 10.6084/m9.figshare.17131786.v1
title: Identification of key miRNA signature and pathways involved in multiple myeloma by integrated bioinformatics analysis

description: Multiple myeloma (MM) is one of the most common types of hematologic malignancy for which the underlying molecular mechanisms remain largely unclear. Dysregulated miRNA expression has been shown to be involved in MM tumorigenesis, progression and drug response. Therefore, a comprehensive analysis based on miRNA-level integrated strategy was performed. This study aimed to elucidate key miRNA signatures and pathways in MM by integrated bioinformatics analysis. Expression profiles GSE24371, GSE49261 and GSE54156 were obtained from the Gene Expression Omnibus database, and differentially expressed miRNAs (DEMirs) with <i>p</i> &lt; 0.05 were identified. The target genes of these DEMirs were obtained from ENCORI database, and functional enrichment, subpathway enrichment and protein–protein interaction network construction were performed. The key target genes were identified by random walk algorithm and survival verification was performed. <b>and discussion:</b> First, six up-regulated and four down-regulated DEMirs shared between any two GSE data sets were identified. Second, target genes (DEMirTGs) by up-regulated and down-regulated DEMirs were obtained. Functional and subpathway enrichment analysis showed that these up-regulated DEMirs are consistently involved in the Wnt signaling pathway. Moreover, enrichment of the down-regulated DEMirs is mainly in the MAPK signaling pathway. Finally, a protein–protein interaction sub-network for these DEMirTGs was constructed, the correlations between the two key genes were identified and survival in MM was evaluated using multiple independent data sets. We identified miRNA signatures and key target genes that were closely related to MM biology, and these genes might serve as potential therapeutic targets for MM patients.
DOI: 10.6084/m9.figshare.11364620.v1
title: MOESM3 of Systematic computational identification of prognostic cytogenetic markers in neuroblastoma

description: Additional file 3: Table S3. A list of nonredundant chromosome bands by selecting the most frequently gained or lost bands from each cluster.
DOI: 10.6084/m9.figshare.11364626
title: MOESM4 of Systematic computational identification of prognostic cytogenetic markers in neuroblastoma

description: Additional file 4: Table S4. The detailed information of 3 NB datasets.
DOI: 10.6084/m9.figshare.11364626.v1
title: MOESM4 of Systematic computational identification of prognostic cytogenetic markers in neuroblastoma

description: Additional file 4: Table S4. The detailed information of 3 NB datasets.
DOI: 10.6084/m9.figshare.19753224.v1
title: Additional file 1 of Can a multitiered copayment system affect people’s healthcare-seeking behavior? A case study of Wenzhou, China

description: Additional file 1.
DOI: 10.6084/m9.figshare.19753224
title: Additional file 1 of Can a multitiered copayment system affect people’s healthcare-seeking behavior? A case study of Wenzhou, China

description: Additional file 1.
DOI: 10.6084/m9.figshare.11364632
title: MOESM5 of Systematic computational identification of prognostic cytogenetic markers in neuroblastoma

description: Additional file 5: Table S5. The combination of results yielded a total of 58 significant chromosome bands associated with patient prognosis.
DOI: 10.6084/m9.figshare.11364632.v1
title: MOESM5 of Systematic computational identification of prognostic cytogenetic markers in neuroblastoma

description: Additional file 5: Table S5. The combination of results yielded a total of 58 significant chromosome bands associated with patient prognosis.
DOI: 10.6084/m9.figshare.11364638
title: MOESM6 of Systematic computational identification of prognostic cytogenetic markers in neuroblastoma

description: Additional file 6: Table S6. Seven chromosome bands associated with patient survival after considering the confounding factors.
DOI: 10.6084/m9.figshare.11364638.v1
title: MOESM6 of Systematic computational identification of prognostic cytogenetic markers in neuroblastoma

description: Additional file 6: Table S6. Seven chromosome bands associated with patient survival after considering the confounding factors.
DOI: 10.5281/zenodo.10672733
title: IODP Expedition 393 Moisture and Density

description: Moisture and density (MAD) data were acquired on ~10 mL sediment or rock samples by measuring three out of four material parameters: wet (saturated) mass, wet volume, dry mass, and/or dry volume after 24 h drying in a convection oven at 105 degrees C. From the moisture and volume measurements, the following phase relationships are calculated: wet and dry water content, wet bulk density, dry bulk density, grain density, porosity, and void ratio. The combination of measurements is defined by the submethod chosen: A, B, C, or D. Wet (A, B, or C) and dry (A, B, C, or D) mass is determined using motion-compensated balances.  Wet volume is determined either by helium pycnometry (A) or by the sample's geometric dimensions using calipers (A or D).  Dry volume (C or D) is measured by helium pycnometry.  Submethods A and B are not recommended by IODP.  Submethod C is suitable for saturated materials such as fine-grained sediments.  Submethod D is suitable for unsaturated porous material such as certain limestones and basalts.
DOI: 10.5281/zenodo.10672734
title: IODP Expedition 393 Moisture and Density

description: Moisture and density (MAD) data were acquired on ~10 mL sediment or rock samples by measuring three out of four material parameters: wet (saturated) mass, wet volume, dry mass, and/or dry volume after 24 h drying in a convection oven at 105 degrees C. From the moisture and volume measurements, the following phase relationships are calculated: wet and dry water content, wet bulk density, dry bulk density, grain density, porosity, and void ratio. The combination of measurements is defined by the submethod chosen: A, B, C, or D. Wet (A, B, or C) and dry (A, B, C, or D) mass is determined using motion-compensated balances.  Wet volume is determined either by helium pycnometry (A) or by the sample's geometric dimensions using calipers (A or D).  Dry volume (C or D) is measured by helium pycnometry.  Submethods A and B are not recommended by IODP.  Submethod C is suitable for saturated materials such as fine-grained sediments.  Submethod D is suitable for unsaturated porous material such as certain limestones and basalts.
DOI: 10.6084/m9.figshare.11364647
title: MOESM7 of Systematic computational identification of prognostic cytogenetic markers in neuroblastoma

description: Additional file 7: Table S7. Ten prognosis-associated chromosome bands on the Pugh dataset.
DOI: 10.6084/m9.figshare.11364647.v1
title: MOESM7 of Systematic computational identification of prognostic cytogenetic markers in neuroblastoma

description: Additional file 7: Table S7. Ten prognosis-associated chromosome bands on the Pugh dataset.
DOI: 10.6084/m9.figshare.19753226
title: Additional file 1 of Systemic necrosis induced by overexpression of wheat yellow mosaic virus 14K suppresses the replication of other viruses in Nicotiana benthamiana

description: Additional file 1: Table S1. The complete nucleotide sequence of wheat yellow mosaic virus RNA 1. The nucleotide sequence of 14K is underlined and indicated in red; Table S2. Primers used in this study..
DOI: 10.6084/m9.figshare.19753226.v1
title: Additional file 1 of Systemic necrosis induced by overexpression of wheat yellow mosaic virus 14K suppresses the replication of other viruses in Nicotiana benthamiana

description: Additional file 1: Table S1. The complete nucleotide sequence of wheat yellow mosaic virus RNA 1. The nucleotide sequence of 14K is underlined and indicated in red; Table S2. Primers used in this study..
DOI: 10.6084/m9.figshare.11364653
title: MOESM8 of Systematic computational identification of prognostic cytogenetic markers in neuroblastoma

description: Additional file 8: Table S8. Dataset summary.
DOI: 10.6084/m9.figshare.11364653.v1
title: MOESM8 of Systematic computational identification of prognostic cytogenetic markers in neuroblastoma

description: Additional file 8: Table S8. Dataset summary.
DOI: 10.6084/m9.figshare.19753208
title: Additional file 1 of QTL mapping of drought-related traits in the hybrids of Populus deltoides ‘Danhong’×Populus simonii ‘Tongliao1’

description: Additional file 1: Table S1. QTLs of drought-related traits under control, drought stress, and drought index.
DOI: 10.6084/m9.figshare.19753208.v1
title: Additional file 1 of QTL mapping of drought-related traits in the hybrids of Populus deltoides ‘Danhong’×Populus simonii ‘Tongliao1’

description: Additional file 1: Table S1. QTLs of drought-related traits under control, drought stress, and drought index.
DOI: 10.6084/m9.figshare.19753211
title: Additional file 2 of QTL mapping of drought-related traits in the hybrids of Populus deltoides ‘Danhong’×Populus simonii ‘Tongliao1’

description: Additional file 2: Table S2. Functional annotation of candidate genes for QTLs in drought environment.
DOI: 10.6084/m9.figshare.19753211.v1
title: Additional file 2 of QTL mapping of drought-related traits in the hybrids of Populus deltoides ‘Danhong’×Populus simonii ‘Tongliao1’

description: Additional file 2: Table S2. Functional annotation of candidate genes for QTLs in drought environment.
DOI: 10.5281/zenodo.10672704
title: IODP Expedition 393 Section-half images

description: Digital section images were taken of the flat face of split cores on the Section Half Imaging Logger (SHIL) using a linescan camera at a resolution of 20 lines/mm (50 micron pixels). Cores were imaged as soon as possible after splitting to minimize color changes that occur through oxidation and drying. The SHIL produces TIF files as well as reduced-size JPG files. The TIF files are not kept online but users may request them from the IODP-JRSO Data Librarian.
DOI: 10.5281/zenodo.10672705
title: IODP Expedition 393 Section-half images

description: Digital section images were taken of the flat face of split cores on the Section Half Imaging Logger (SHIL) using a linescan camera at a resolution of 20 lines/mm (50 micron pixels). Cores were imaged as soon as possible after splitting to minimize color changes that occur through oxidation and drying. The SHIL produces TIF files as well as reduced-size JPG files. The TIF files are not kept online but users may request them from the IODP-JRSO Data Librarian.
DOI: 10.5281/zenodo.10672702
title: IODP Expedition 393 Magnetic susceptibility (Kappabridge)

description: Bulk magnetic susceptibility and anisotropy of magnetic susceptibility (AMS) were measured on discrete samples using an Agico KLY-4 Kappabridge susceptibility meter. Report includes individual and average principal susceptibilities, inclination and declination of principal susceptibilities, and volume-corrected bulk susceptibility.
DOI: 10.5281/zenodo.10672703
title: IODP Expedition 393 Magnetic susceptibility (Kappabridge)

description: Bulk magnetic susceptibility and anisotropy of magnetic susceptibility (AMS) were measured on discrete samples using an Agico KLY-4 Kappabridge susceptibility meter. Report includes individual and average principal susceptibilities, inclination and declination of principal susceptibilities, and volume-corrected bulk susceptibility.
DOI: 10.6084/m9.figshare.19753383
title: Additional file 4 of Blended teaching of medical ethics during COVID-19: practice and reflection

description: Additional file 4.
DOI: 10.6084/m9.figshare.19753383.v1
title: Additional file 4 of Blended teaching of medical ethics during COVID-19: practice and reflection

description: Additional file 4.
DOI: 10.6084/m9.figshare.19753347
title: Additional file 2 of Palbociclib-based high-throughput combination drug screening identifies synergistic therapeutic options in HPV-negative head and neck squamous cell carcinoma

description: Additional file 2: Table S1. Information of 162 chemicals. Table S2. Epithelial and Mesenchymal Gene lists. Table S3. Primers in this study. Table S4. Primary antibodies. Table S5. Genetic annotation of cell lines in this study. Table S6. Average ExcessHSA scores of all compounds. Table S7. Genetic annotation of PDX models.
DOI: 10.6084/m9.figshare.19753347.v1
title: Additional file 2 of Palbociclib-based high-throughput combination drug screening identifies synergistic therapeutic options in HPV-negative head and neck squamous cell carcinoma

description: Additional file 2: Table S1. Information of 162 chemicals. Table S2. Epithelial and Mesenchymal Gene lists. Table S3. Primers in this study. Table S4. Primary antibodies. Table S5. Genetic annotation of cell lines in this study. Table S6. Average ExcessHSA scores of all compounds. Table S7. Genetic annotation of PDX models.
DOI: 10.6084/m9.figshare.19753371
title: Additional file 2 of Immunogenomic intertumor heterogeneity across primary and metastatic sites in a patient with lung adenocarcinoma

description: Additional file 2.
DOI: 10.6084/m9.figshare.19753371.v1
title: Additional file 2 of Immunogenomic intertumor heterogeneity across primary and metastatic sites in a patient with lung adenocarcinoma

description: Additional file 2.
DOI: 10.25387/g3.16607783
title: Supplemental Materials for Zhou et al 2021 (in review)

description: Raw data from yeast screens
DOI: 10.6084/m9.figshare.7170602
title: Additional file 16: of Rice stripe virus-derived siRNAs play different regulatory roles in rice and in the insect vector Laodelphax striatellus

description: Table S4. List of 17 down-regulated rice genes that are potentially targeted by rice-specific vsiRNAs. (XLS 34 kb)
DOI: 10.6084/m9.figshare.7170602.v1
title: Additional file 16: of Rice stripe virus-derived siRNAs play different regulatory roles in rice and in the insect vector Laodelphax striatellus

description: Table S4. List of 17 down-regulated rice genes that are potentially targeted by rice-specific vsiRNAs. (XLS 34 kb)