cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25582/data.2023-02.2732074/2291420
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2712468/2291421
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2712477/2291422
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2718499/2291423
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2732023/2291424
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-02.2731585/2291425
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-02.2731865/2291426
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2717356/2291427
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2723374/2291428
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2722761/2291429
title: Data for EMSL Project 51287 from January 2023
DOI: 10.6084/m9.figshare.19498219
title: Additional file 2 of Decoding the multicellular ecosystem of vena caval tumor thrombus in clear cell renal cell carcinoma by single-cell RNA sequencing

description: Additional file 2: Table S1. Clinical variables for samples and patients.
DOI: 10.6084/m9.figshare.19498219.v1
title: Additional file 2 of Decoding the multicellular ecosystem of vena caval tumor thrombus in clear cell renal cell carcinoma by single-cell RNA sequencing

description: Additional file 2: Table S1. Clinical variables for samples and patients.
DOI: 10.6084/m9.figshare.19498222
title: Additional file 3 of Decoding the multicellular ecosystem of vena caval tumor thrombus in clear cell renal cell carcinoma by single-cell RNA sequencing

description: Additional file 3: Table S2. Differential expression results for all lymphoid clusters, differential expression results for CD8+ T cell clusters, CD8-C1 related gene signatures, and progenitor/terminally exhausted signature scores for all CD8+ T cells, related to Fig. 2.
DOI: 10.25582/data.2023-02.2731937/2291430
title: Data for EMSL Project 51287 from February 2023
DOI: 10.6084/m9.figshare.19498222.v1
title: Additional file 3 of Decoding the multicellular ecosystem of vena caval tumor thrombus in clear cell renal cell carcinoma by single-cell RNA sequencing

description: Additional file 3: Table S2. Differential expression results for all lymphoid clusters, differential expression results for CD8+ T cell clusters, CD8-C1 related gene signatures, and progenitor/terminally exhausted signature scores for all CD8+ T cells, related to Fig. 2.
DOI: 10.6084/m9.figshare.19498225
title: Additional file 4 of Decoding the multicellular ecosystem of vena caval tumor thrombus in clear cell renal cell carcinoma by single-cell RNA sequencing

description: Additional file 4: Table S3. Differential expression results for all myeloid cell clusters, for PT and TT from all TAMs clusters, and published gene signatures for GSEA, related to Fig. 3.
DOI: 10.6084/m9.figshare.19498225.v1
title: Additional file 4 of Decoding the multicellular ecosystem of vena caval tumor thrombus in clear cell renal cell carcinoma by single-cell RNA sequencing

description: Additional file 4: Table S3. Differential expression results for all myeloid cell clusters, for PT and TT from all TAMs clusters, and published gene signatures for GSEA, related to Fig. 3.
DOI: 10.25582/data.2023-01.2723538/2291431
title: Data for EMSL Project 51287 from January 2023
DOI: 10.4121/21071089
title: Data underlying the publication: Pinpointing stage-specific causes of recruitment bottlenecks to optimize seed-based wetland restoration

description: In this study, we intended to make seed-based wetland restoration predictive and inform management by (1) seeking integrated experimental evidence generalizing stage-specific causative factors for demographic loss/mortality and (2) developing predictors oriented toward site-specific bottlenecks. Specifically, this study is focused on seed retention and seedling emergence, since they represent the most vulnerable life stages that follow sowing. Firstly, by means of large-scale field experiments, we tested how seed retention and seedling emergence were affected by varied management options (i.e., seed-planting depth and species selection) and a wide range of physical settings (i.e., elevation, hydrodynamic intensity, bed-level dynamics and sediment properties). Variable screening was then implemented to identify stage-specific governing factors. Secondly, the resulting insights and dataset were used to develop stage-specific predictive models using machine learning. Model experiments under various scenarios were then conducted to assess site-specific feasibility of potential seed-based restoration practices.
<br>
These files include the data used to create each figure in the manuscript, organized as follows:
1. Field experiments
a) Physical conditions at all study locations
b) Manipulated experiment concerning seed retention
c) Manipulated experiment concerning seedling emergence
2. Machine learning
a) Developing machine learning predictors on seed retention
b) Developing machine learning predictors on seedling emergence
<br>
For a complete description, see 'Data description.docx'
DOI: 10.4121/21071089.v1
title: Data underlying the publication: Pinpointing stage-specific causes of recruitment bottlenecks to optimize seed-based wetland restoration

description: In this study, we intended to make seed-based wetland restoration predictive and inform management by (1) seeking integrated experimental evidence generalizing stage-specific causative factors for demographic loss/mortality and (2) developing predictors oriented toward site-specific bottlenecks. Specifically, this study is focused on seed retention and seedling emergence, since they represent the most vulnerable life stages that follow sowing. Firstly, by means of large-scale field experiments, we tested how seed retention and seedling emergence were affected by varied management options (i.e., seed-planting depth and species selection) and a wide range of physical settings (i.e., elevation, hydrodynamic intensity, bed-level dynamics and sediment properties). Variable screening was then implemented to identify stage-specific governing factors. Secondly, the resulting insights and dataset were used to develop stage-specific predictive models using machine learning. Model experiments under various scenarios were then conducted to assess site-specific feasibility of potential seed-based restoration practices.
<br>
These files include the data used to create each figure in the manuscript, organized as follows:
1. Field experiments
a) Physical conditions at all study locations
b) Manipulated experiment concerning seed retention
c) Manipulated experiment concerning seedling emergence
2. Machine learning
a) Developing machine learning predictors on seed retention
b) Developing machine learning predictors on seedling emergence
<br>
For a complete description, see 'Data description.docx'
DOI: 10.6084/m9.figshare.20444208
title: Additional file 1 of Physical activity and chronic obstructive pulmonary disease: a scoping review

description: Additional file 1. Detailed and additional data of this manuscript.
DOI: 10.25582/data.2023-02.2731557/2291432
title: Data for EMSL Project 51287 from February 2023
DOI: 10.6084/m9.figshare.19498228
title: Additional file 5 of Decoding the multicellular ecosystem of vena caval tumor thrombus in clear cell renal cell carcinoma by single-cell RNA sequencing

description: Additional file 5: Table S4. Differential expression results for all tumor cell clusters, for PT and TT from all tumor clusters, related to Fig. 4.
DOI: 10.6084/m9.figshare.20444208.v1
title: Additional file 1 of Physical activity and chronic obstructive pulmonary disease: a scoping review

description: Additional file 1. Detailed and additional data of this manuscript.
DOI: 10.6084/m9.figshare.19498228.v1
title: Additional file 5 of Decoding the multicellular ecosystem of vena caval tumor thrombus in clear cell renal cell carcinoma by single-cell RNA sequencing

description: Additional file 5: Table S4. Differential expression results for all tumor cell clusters, for PT and TT from all tumor clusters, related to Fig. 4.
DOI: 10.6084/m9.figshare.19498231
title: Additional file 6 of Decoding the multicellular ecosystem of vena caval tumor thrombus in clear cell renal cell carcinoma by single-cell RNA sequencing

description: Additional file 6: Table S5. Differential expression results for all endothelial clusters and all myofibroblast clusters, and published gene signatures for GSEA, related to Fig. 5.
DOI: 10.25582/data.2023-01.2718060/2291433
title: Data for EMSL Project 51287 from January 2023
DOI: 10.6084/m9.figshare.19498231.v1
title: Additional file 6 of Decoding the multicellular ecosystem of vena caval tumor thrombus in clear cell renal cell carcinoma by single-cell RNA sequencing

description: Additional file 6: Table S5. Differential expression results for all endothelial clusters and all myofibroblast clusters, and published gene signatures for GSEA, related to Fig. 5.
DOI: 10.25582/data.2023-01.2718313/2291434
title: Data for EMSL Project 51287 from January 2023
DOI: 10.6084/m9.figshare.19498234
title: Additional file 7 of Decoding the multicellular ecosystem of vena caval tumor thrombus in clear cell renal cell carcinoma by single-cell RNA sequencing

description: Additional file 7: Table S6. Ligand-receptor means and p-values for all cell interactions in ART, PT and TT (from CellPhoneDB v2.0) and created gene signatures, related to Fig. 6.
DOI: 10.6084/m9.figshare.19498234.v1
title: Additional file 7 of Decoding the multicellular ecosystem of vena caval tumor thrombus in clear cell renal cell carcinoma by single-cell RNA sequencing

description: Additional file 7: Table S6. Ligand-receptor means and p-values for all cell interactions in ART, PT and TT (from CellPhoneDB v2.0) and created gene signatures, related to Fig. 6.
DOI: 10.25582/data.2023-02.2731516/2291435
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2720863/2291436
title: Data for EMSL Project 51287 from January 2023
DOI: 10.6084/m9.figshare.7439621
title: Additional file 1: of Comparative genomics of 84 Pectobacterium genomes reveals the variations related to a pathogenic lifestyle

description: Table S1. The biochemical characters and pathogenicity of 32 Chinese Pectobacterium carotovorum strains. Table S2. Selected phenotypic characteristics of Pectobacterium carotovorum subsp. brasiliense, P. carotovorum subsp. carotovorum and P. carotovorum subsp. odoriferum. Table S3. Eighty-four Pectobacterium genomes used in this study, with accession number, host origin and location information. Table S4. The general genomic features of the 84 Pectobacterium genomes. Table S5. The CRISPR-Cas systems identified in the 84 Pectobacterium genomes. Table S6. Presence of genes encoding general virulence factors in the 84 Pectobacterium genomes. Table S6â 1. The position of rmsB, the RNA fragment related to virulence in the 84 Pectobacterium genomes. Table S7. Gene clusters for TNSSs identified in the 84 Pectobacterium genomes. Table S8. Presence of the T6SSc gene cluster in the 203 Enterobacterales genomes. Table S9. Presence of the srl operon in the 203 Enterobacterales genomes. (XLSX 751 kb)
DOI: 10.6084/m9.figshare.7439621.v1
title: Additional file 1: of Comparative genomics of 84 Pectobacterium genomes reveals the variations related to a pathogenic lifestyle

description: Table S1. The biochemical characters and pathogenicity of 32 Chinese Pectobacterium carotovorum strains. Table S2. Selected phenotypic characteristics of Pectobacterium carotovorum subsp. brasiliense, P. carotovorum subsp. carotovorum and P. carotovorum subsp. odoriferum. Table S3. Eighty-four Pectobacterium genomes used in this study, with accession number, host origin and location information. Table S4. The general genomic features of the 84 Pectobacterium genomes. Table S5. The CRISPR-Cas systems identified in the 84 Pectobacterium genomes. Table S6. Presence of genes encoding general virulence factors in the 84 Pectobacterium genomes. Table S6â 1. The position of rmsB, the RNA fragment related to virulence in the 84 Pectobacterium genomes. Table S7. Gene clusters for TNSSs identified in the 84 Pectobacterium genomes. Table S8. Presence of the T6SSc gene cluster in the 203 Enterobacterales genomes. Table S9. Presence of the srl operon in the 203 Enterobacterales genomes. (XLSX 751 kb)
DOI: 10.25582/data.2023-01.2722666/2291437
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2731961/2291438
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2719509/2291439
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2720944/2291440
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2718071/2291441
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2723442/2291442
title: Data for EMSL Project 51287 from January 2023
DOI: 10.6084/m9.figshare.7439639
title: Additional file 1: of A high-fat diet alters genome-wide DNA methylation and gene expression in SM/J mice

description: Supplement. (ZIP 4328 kb)
DOI: 10.6084/m9.figshare.7439639.v1
title: Additional file 1: of A high-fat diet alters genome-wide DNA methylation and gene expression in SM/J mice

description: Supplement. (ZIP 4328 kb)
DOI: 10.25582/data.2023-02.2731976/2291443
title: Data for EMSL Project 51287 from February 2023
DOI: 10.6084/m9.figshare.12682523
title: Metadata record for the manuscript: Unique gap junction- and cofilin-dependent cellular protrusions mediate cancer cell migration by tethering to osteogenic cells

description: This metadata record provides details of the data supporting the claims of the related manuscript: “Unique gap junction- and cofilin-dependent cellular protrusions mediate cancer cell migration by tethering to osteogenic cells”. The data consist of 10 files.<br>The related study investigated migration and invasion of metastatic cancer cells and discovered an alternative “migration-by-tethering” mechanism through which cancer cells gain the momentum to migrate by adhering to mesenchymal stem cells or osteoblasts.<br>The data files are as follows:<b>- FlowCytometryParameters.wsp</b> - Underlying Figure 4 e in the related manuscript.<b>- Incucyte Timelapse Transwell Data.txt</b> - Underlying Supplementary Figure 1 e.<b>- Muscarella et al Final Submission Raw Data.xlsx</b> - Underlying all figures in the related manuscript and all supplementary figures. This file contains many tabs labelled by which figure they relate to.<b>- Muscarella et al Revision Supplemental Figures.pdf</b> - Containing all supplementary figures and Supplementary - <b>Table 1.mp4</b> - See the Results section of the related manuscript for details.<b>- Supplementary Video 1.mp4</b> - See the Results section of the related manuscript for details.<b>- Supplementary Video 2.mp4</b> - See the Results section of the related manuscript for details.<b>- Supplementary Video 3.avi</b> - See the Results section of the related manuscript for details.<b>- Supplementary Video 4.mp4</b> - See the Results section of the related manuscript for details.<b>- Supplementary Video 5.mp4</b> - See the Results section of the related manuscript for details.<b>- Supplementary Video 6.mp4</b> - See the Results section of the related manuscript for details.<br>
DOI: 10.6084/m9.figshare.12682523.v1
title: Metadata record for the manuscript: Unique gap junction- and cofilin-dependent cellular protrusions mediate cancer cell migration by tethering to osteogenic cells

description: This metadata record provides details of the data supporting the claims of the related manuscript: “Unique gap junction- and cofilin-dependent cellular protrusions mediate cancer cell migration by tethering to osteogenic cells”. The data consist of 10 files.<br>The related study investigated migration and invasion of metastatic cancer cells and discovered an alternative “migration-by-tethering” mechanism through which cancer cells gain the momentum to migrate by adhering to mesenchymal stem cells or osteoblasts.<br>The data files are as follows:<b>- FlowCytometryParameters.wsp</b> - Underlying Figure 4 e in the related manuscript.<b>- Incucyte Timelapse Transwell Data.txt</b> - Underlying Supplementary Figure 1 e.<b>- Muscarella et al Final Submission Raw Data.xlsx</b> - Underlying all figures in the related manuscript and all supplementary figures. This file contains many tabs labelled by which figure they relate to.<b>- Muscarella et al Revision Supplemental Figures.pdf</b> - Containing all supplementary figures and Supplementary - <b>Table 1.mp4</b> - See the Results section of the related manuscript for details.<b>- Supplementary Video 1.mp4</b> - See the Results section of the related manuscript for details.<b>- Supplementary Video 2.mp4</b> - See the Results section of the related manuscript for details.<b>- Supplementary Video 3.avi</b> - See the Results section of the related manuscript for details.<b>- Supplementary Video 4.mp4</b> - See the Results section of the related manuscript for details.<b>- Supplementary Video 5.mp4</b> - See the Results section of the related manuscript for details.<b>- Supplementary Video 6.mp4</b> - See the Results section of the related manuscript for details.<br>
DOI: 10.25582/data.2023-02.2726455/2291444
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2713571/2291445
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2718410/2291446
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2719398/2291447
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2726426/2291448
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-02.2731849/2291449
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2718393/2291450
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2719486/2291451
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2732112/2291452
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2714508/2291453
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2717349/2291454
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2726140/2291455
title: Data for EMSL Project 51287 from January 2023
DOI: 10.6084/m9.figshare.7439705
title: Additional file 1: of Transient increase in CSF GAP-43 concentration after ischemic stroke

description: Table of t and p values across the different white matter lesion status and brain atrophy status groups, up to 9 days and, after 9 days past the stroke. (XLSX 9 kb)
DOI: 10.6084/m9.figshare.7439705.v1
title: Additional file 1: of Transient increase in CSF GAP-43 concentration after ischemic stroke

description: Table of t and p values across the different white matter lesion status and brain atrophy status groups, up to 9 days and, after 9 days past the stroke. (XLSX 9 kb)
DOI: 10.25582/data.2023-02.2732134/2291456
title: Data for EMSL Project 51287 from February 2023
DOI: 10.6084/m9.figshare.19498330
title: Additional file 15 of CircSCAP interacts with SF3A3 to inhibit the malignance of non-small cell lung cancer by activating p53 signaling

description: Additional file 15: Worksheet. The list of differentially identified proteins by the Mass spectrometry (MS) assay.
DOI: 10.6084/m9.figshare.19498330.v1
title: Additional file 15 of CircSCAP interacts with SF3A3 to inhibit the malignance of non-small cell lung cancer by activating p53 signaling

description: Additional file 15: Worksheet. The list of differentially identified proteins by the Mass spectrometry (MS) assay.
DOI: 10.25582/data.2023-02.2731890/2291457
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-02.2731919/2291458
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-02.2731899/2291459
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-02.2732000/2291460
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2714778/2291461
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2722624/2291462
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2732157/2291463
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25549/usctheses-ouc11287823
title: jdickson_chapters-1-through-5_06-26-14_jld
DOI: 10.25582/data.2023-01.2718673/2291464
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2720954/2291465
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2718065/2291466
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2731940/2291467
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2722607/2291468
title: Data for EMSL Project 51287 from January 2023
DOI: 10.6084/m9.figshare.7439738
title: Additional file 2: of Dosage imbalance of B- and C-class genes causes petaloid-stamen relating to F1 hybrid variation

description: Sequences isolated in this article. (TXT 9 kb)
DOI: 10.25582/data.2023-01.2717450/2291469
title: Data for EMSL Project 51287 from January 2023
DOI: 10.6084/m9.figshare.7439738.v1
title: Additional file 2: of Dosage imbalance of B- and C-class genes causes petaloid-stamen relating to F1 hybrid variation

description: Sequences isolated in this article. (TXT 9 kb)
DOI: 10.25582/data.2023-01.2718276/2291470
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2717472/2291471
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2732015/2291472
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2718818/2291473
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2731537/2291474
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-02.2731729/2291475
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-02.2731836/2291476
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-02.2731521/2291477
title: Data for EMSL Project 51287 from February 2023
DOI: 10.6084/m9.figshare.19498399
title: Additional file 4 of GmSPX8, a nodule-localized regulator confers nodule development and nitrogen fixation under phosphorus starvation in soybean

description: Additional file 4: Table S1. Transcriptome data showing all the DEGs.
DOI: 10.6084/m9.figshare.19498399.v1
title: Additional file 4 of GmSPX8, a nodule-localized regulator confers nodule development and nitrogen fixation under phosphorus starvation in soybean

description: Additional file 4: Table S1. Transcriptome data showing all the DEGs.
DOI: 10.6084/m9.figshare.19498402
title: Additional file 5 of GmSPX8, a nodule-localized regulator confers nodule development and nitrogen fixation under phosphorus starvation in soybean

description: Additional file 5: Table S2. Cycle threshold (CT) Value of RT-PCR.
DOI: 10.6084/m9.figshare.19498402.v1
title: Additional file 5 of GmSPX8, a nodule-localized regulator confers nodule development and nitrogen fixation under phosphorus starvation in soybean

description: Additional file 5: Table S2. Cycle threshold (CT) Value of RT-PCR.
DOI: 10.25582/data.2023-01.2718437/2291478
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2718954/2291479
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2732124/2291480
title: Data for EMSL Project 51287 from February 2023
DOI: 10.6084/m9.figshare.19498413
title: Additional file 1 of Genome-wide identification and expression analysis of the plant-specific PLATZ gene family in Tartary buckwheat (Fagopyrum tataricum)

description: Additional file 1: Table S1. CDS and protein sequences of FtPLATZs identified in this study.