cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/96fnds8mpw.1
title: Data for the article “Mixing crop residues induces a synergistic effect on microbial biomass and an additive effect on soil organic matter priming”

description: This data supports the paper “Mixing crop residues induces a synergistic effect on microbial biomass and an additive effect on soil organic matter priming”. There are four datasheets: the sheet "Respiration" contains the data of respiration measured at one day after applying cover crop residues; the sheet "PLFA_total" contains total PLFA (Phospholipid-derived fatty acids) biomass measured by GC-FID; the sheet "PLFA_plant" includes PLFA biomass derived from plant residues which was measured by GC-C-IRMS; and the sheet "PLFA_SOM" includes PLFA biomass derived from soil organic matter (SOM). The PLFA derived from SOM was the difference between total biomass, plant-derived biomass, and the biomass in the soil without adding plant residues. The unit for respiration is ng g-1 h-1, and the unit for PLFA is µg C g-1, respectively.
DOI: 10.17632/5ttrnmvjjx.4
title: Tumors hijack erythropoiesis for myelopoiesis and immunosuppression

description: Despite the unprecedented success of immune checkpoint inhibitors (ICIs) as anti-cancer therapy, it remains a prevailing clinical need to identify additional mechanisms underlying ICIs therapeutic efficacy and potential drug resistance. Here, using lineage tracking in cancer patients and tumor-bearing mice, we demonstrate that erythroid progenitor cells lose their developmental potential and switch to the myeloid lineage. Single-cell transcriptome analyses reveal that, notwithstanding quantitative differences in erythroid gene expression, erythroid differentiated myeloid cells (EDMCs) are transcriptionally indistinguishable from their myeloid-originated counterparts. EDMCs possess multifaceted machinery to curtail T cell-mediated anti-tumor responses. Consequently, the EDMCs content within tumor tissues is negatively associated with T cell inflammation for the majority of solid cancers; moreover, EDMCs enrichment, in accordance with anemia manifestation, is predictive of poor prognosis in various cohorts of patients undergoing ICIs therapy. Together, our findings reveal a feed-forward mechanism by which tumors exploit anemia-triggered erythropoiesis for myeloid transdifferentiation and immunosuppression.
DOI: 10.17632/gtpc2k68km.1
title: MYCT1-COIP mass spectrometry RAW DATA

description: 1#MYCT1-KO MOUSE-IP
3#WT-MOUSE -IP
5# MYCT1-KO-IgG
7#WT-MOUSE-IgG
DOI: 10.17632/k3h6g875dt.1
title: Improving lithium dose prediction using population pharmacokinetics and pharmacogenomics: a cohort genome-wide association study in Sweden

description: Summary statistics from the article "Improving lithium dose prediction using population pharmacokinetics and pharmacogenomics: a cohort genome-wide association study in Sweden", https://doi.org/10.1016/S2215-0366(22)00100-6
DOI: 10.5281/zenodo.6540679
title: Passive breathing of earth-air: 'fingerprint' evidence from moisture records

description: <em>Data in Brief.</em>
description: no
DOI: 10.5281/zenodo.6540678
title: Passive breathing of earth-air: 'fingerprint' evidence from moisture records

description: <em>Data in Brief.</em>
description: no
DOI: 10.6084/m9.figshare.19750414
title: Data from: Seed sourcing in the genomics era: Multispecies provenance delineation for current and future climates

description: <strong>Abstract</strong> Restoration interventions require knowledge on the suitability of seed sources. Provenance delineation for ecological restoration of degraded environments has begun to incorporate genome-wide information on adaptive variation, but this has only been completed on a small number of plant species. Rarely is provenance delineation using a genomics approach applied to species occurring across different habitats, and in the context of future climate scenarios, despite their potential importance for successful long-term restoration. Here, we use neutral genetic data to investigate patterns of genetic differentiation and a landscape genomics approach to model putatively adaptive genetic variation under multiple climate scenarios for two species co-occurring in a predominantly mesic environment, and two species co-occurring in a semi-arid environment. We then model the genomic similarity of seed sourcing locations to hypothetical restoration sites, both under current and future climate scenarios. We found that the geographical extent of provenances and the amount of genomic change required to track the projected climatic conditions over time differed within the pairs of co-occurring species and between habitats. Additionally, future climate scenarios had differing effects on provenance patterns between the two landscapes indicating a differential response to changing climate between species from mesic and arid habitats. This implies that provenance guidelines can be both species and habitat dependent. We discuss how these results can be utilised to design seed sourcing strategies for successful restoration, and how these methods could be more broadly applied to delineate provenances of other species and locations. <br> <strong>Usage Notes</strong> <strong>FST matrices</strong> Pairwise FST matrices of putatively adaptive genetic data for four species used in GDM analysis. Datasets have been previously published (see https://doi.org/10.5061/dryad.k3j9kd56n and https://doi.org/10.5061/dryad.0p2ngf1xn) and the versions utilised for this manuscript have been archived here. <strong>Climate and geographical information</strong> Climate and geographical information for four species used in GDM analysis. Climatic data was downloaded with 1 km cell resolution from the Worldclim 2.1 database (Fick & Hijmans, 2017; Hijmans et al. 2005). Bio3 = isothermality, bio4 = temperature seasonality, bio8 = mean temperature of the wettest quarter, bio10 = mean temperature of the warmest quarter, bio12 = annual precipitation, bio15 = precipitation seasonality, bio16 = precipitation of the wettest quarter, bio17 = precipitation of the driest quarter. <strong>R code</strong> R code for extrapolating GDMs to future climates and calculating genomic similarity to hypothetical restoration sites.
DOI: 10.6084/m9.figshare.19750414.v1
title: Data from: Seed sourcing in the genomics era: Multispecies provenance delineation for current and future climates

description: <strong>Abstract</strong> Restoration interventions require knowledge on the suitability of seed sources. Provenance delineation for ecological restoration of degraded environments has begun to incorporate genome-wide information on adaptive variation, but this has only been completed on a small number of plant species. Rarely is provenance delineation using a genomics approach applied to species occurring across different habitats, and in the context of future climate scenarios, despite their potential importance for successful long-term restoration. Here, we use neutral genetic data to investigate patterns of genetic differentiation and a landscape genomics approach to model putatively adaptive genetic variation under multiple climate scenarios for two species co-occurring in a predominantly mesic environment, and two species co-occurring in a semi-arid environment. We then model the genomic similarity of seed sourcing locations to hypothetical restoration sites, both under current and future climate scenarios. We found that the geographical extent of provenances and the amount of genomic change required to track the projected climatic conditions over time differed within the pairs of co-occurring species and between habitats. Additionally, future climate scenarios had differing effects on provenance patterns between the two landscapes indicating a differential response to changing climate between species from mesic and arid habitats. This implies that provenance guidelines can be both species and habitat dependent. We discuss how these results can be utilised to design seed sourcing strategies for successful restoration, and how these methods could be more broadly applied to delineate provenances of other species and locations. <br> <strong>Usage Notes</strong> <strong>FST matrices</strong> Pairwise FST matrices of putatively adaptive genetic data for four species used in GDM analysis. Datasets have been previously published (see https://doi.org/10.5061/dryad.k3j9kd56n and https://doi.org/10.5061/dryad.0p2ngf1xn) and the versions utilised for this manuscript have been archived here. <strong>Climate and geographical information</strong> Climate and geographical information for four species used in GDM analysis. Climatic data was downloaded with 1 km cell resolution from the Worldclim 2.1 database (Fick & Hijmans, 2017; Hijmans et al. 2005). Bio3 = isothermality, bio4 = temperature seasonality, bio8 = mean temperature of the wettest quarter, bio10 = mean temperature of the warmest quarter, bio12 = annual precipitation, bio15 = precipitation seasonality, bio16 = precipitation of the wettest quarter, bio17 = precipitation of the driest quarter. <strong>R code</strong> R code for extrapolating GDMs to future climates and calculating genomic similarity to hypothetical restoration sites.
DOI: 10.6084/m9.figshare.19746328
title: Loom files

description: There are loom files of each sample used in our project, which were used to perform velocity analysis.
DOI: 10.48567/tdvd-rp09
title: AGO-4 Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/0hhj-bx46
title: Austin Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/keks-0e95
title: Baldrick Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/11gh-4h89
title: Bear Peninsula Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/m622-cs25
title: Bonaparte Point Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/v79w-nk25
title: Byrd Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/a67r-ah88
title: Cape Bird Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/h93p-yd22
title: Cape Hallett Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/yn85-1q36
title: D-10 Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/7yw4-tv21
title: D-47 Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/vj95-dg62
title: D-85 Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/hezq-mw63
title: Dome C II Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/t2yw-th90
title: Dome Fuji Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/gq97-rv45
title: Elaine Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/16jf-av19
title: Elizabeth Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/596c-a102
title: Emilia Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/e752-t028
title: Emma Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/069d-0c80
title: Erin Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/h29t-3r55
title: Evans Knoll Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/wpkv-gc91
title: Ferrell Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/ypqr-1z54
title: Gill Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/97hz-kk55
title: Harry Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/05zk-3z66
title: Henry Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/3j4h-a562
title: Hugo Island Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/8d1f-5n97
title: JASE2007 Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/253f-7t09
title: Janet Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/ctwm-1885
title: Kathie Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/8bme-e229
title: Kominko-Slade Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/myef-5v62
title: Laurie II Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/tdgm-jf42
title: Lettau Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/ag95-fc10
title: Linda Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/w8m0-mg10
title: Lorne Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/6424-0c68
title: Manuela Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/yc5w-en15
title: Marble Point Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/b493-qm55
title: Marble Point II Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/h0hq-h416
title: Margaret Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/y8ar-vn48
title: Marilyn Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/vs7a-6514
title: Minna Bluff Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/zep9-6156
title: Mizuho Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/270c-qd61
title: Mount Siple Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/tpct-p584
title: Neko Harbor Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/j7s5-0329
title: Nico Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/zfqz-jq63
title: PANDA-South Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/1sgs-bg20
title: Pegasus North Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/srja-5240
title: Port Martin Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/207f-9298
title: Possession Island Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/k8pm-2928
title: Relay Station Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/te9r-pt36
title: Sabrina Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/zv3p-3861
title: Schwerdtfeger Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/gg34-pk64
title: Siple Dome Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/qctm-fs64
title: Theresa Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/e5rh-5579
title: Thurston Island Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/ks0w-0658
title: Vito Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/n7sa-dq63
title: White Island Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/y94b-3j51
title: Whitlock Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/n3tv-eh73
title: Willie Field Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.48567/t2vp-j458
title: Windless Bight Automatic Weather Station, 2016 unmodified ten-minute observational data.
DOI: 10.25439/rmt.19743178
title: 4.3 Supplementary Table 4.3 16S 16S Nails.pdf

description: Dataset 16S nails
DOI: 10.25439/rmt.19743178.v1
title: 4.3 Supplementary Table 4.3 16S 16S Nails.pdf

description: Dataset 16S nails
DOI: 10.25439/rmt.19743175
title: 5.1 Supplementary Table 5.1 ITS2 Dust.pdf

description: Dataset ITS2 Dust
DOI: 10.25439/rmt.19743175.v1
title: 5.1 Supplementary Table 5.1 ITS2 Dust.pdf

description: Dataset ITS2 Dust
DOI: 10.25439/rmt.19743169.v1
title: 6.1 Supplementary Table 6.1 Results.pdf

description: Dataset terbinafine susceptibility
DOI: 10.25439/rmt.19743169
title: 6.1 Supplementary Table 6.1 Results.pdf

description: Dataset terbinafine susceptibility
DOI: 10.25439/rmt.19743166
title: 4.2 Supplementary Table 4.2. ITS2 Nails.pdf

description: Data ITS2 Nails
DOI: 10.25439/rmt.19743166.v1
title: 4.2 Supplementary Table 4.2. ITS2 Nails.pdf

description: Data ITS2 Nails
DOI: 10.25439/rmt.19743163
title: 5.2 Supplementary Table 5.2. 16S Dust.pdf

description: Data from 16S analysis of dust
DOI: 10.25439/rmt.19743163.v1
title: 5.2 Supplementary Table 5.2. 16S Dust.pdf

description: Data from 16S analysis of dust
DOI: 10.25921/p353-x959
title: EK60 Water Column Sonar Data Collected During EX2101
DOI: 10.48567/rn4q-t745
title: AGO-4 Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/wte6-h375
title: Austin Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/pyjn-zt26
title: Baldrick Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/rca8-3t68
title: Bear Peninsula Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/78wj-8m92
title: Bonaparte Point Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/9133-tb94
title: Byrd Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/82rb-h902
title: Cape Bird Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/qspw-hn78
title: Cape Hallett Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/2864-a234
title: D-10 Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/3t35-4w84
title: D-47 Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/2t5r-pr48
title: D-85 Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/4f9t-2k48
title: Dismal Island Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/a3gq-w277
title: Dome C II Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/e9aj-qp26
title: Dome Fuji Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/sd26-p433
title: Elaine Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/8bav-8972
title: Elizabeth Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/a345-4581
title: Emilia Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/md4f-1e57
title: Emma Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/jzsa-vh33
title: Erin Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/9bmh-c426
title: Evans Knoll Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/me0y-an97
title: Ferrell Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/64p5-jb37
title: Gill Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/v870-nj73
title: Harry Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/86k9-2y03
title: Henry Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/e9z3-g836
title: JASE2007 Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/c5cr-ac15
title: Janet Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/ee3t-gp98
title: Kathie Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/9c54-ed18
title: Kominko-Slade Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/hm73-6b93
title: Laurie II Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/san6-fw64
title: Lettau Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/bpgm-ny39
title: Linda Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/b1ft-bq81
title: Lorne Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/bza9-d835
title: Manuela Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/8q7k-ty72
title: Marble Point Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/nhv4-pp05
title: Marble Point II Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/err3-c766
title: Margaret Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/gfs2-w881
title: Marilyn Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/5a4v-gc38
title: Minna Bluff Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/6c37-xw55
title: Mizuho Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/8jva-d158
title: Mount Siple Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/1mzm-a613
title: Nico Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/6ad9-1q03
title: PANDA-South Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/yhf9-wc92
title: Pegasus North Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/xx98-ff74
title: Phoenix Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/0asx-5t86
title: Port Martin Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/bwkj-k505
title: Possession Island Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/1c3r-yb39
title: Relay Station Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/cczz-hr43
title: Sabrina Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/2cgt-n156
title: Schwerdtfeger Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/01rb-5375
title: Siple Dome Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/m7t9-bx59
title: Theresa Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/t9w2-rh89
title: Thurston Island Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/2e6r-8a55
title: Vito Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/nenc-6e96
title: White Island Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/7kdv-s807
title: Whitlock Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/gcpf-9491
title: Willie Field Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.48567/ydme-0990
title: Windless Bight Automatic Weather Station, 2017 unmodified ten-minute observational data.
DOI: 10.5281/zenodo.6539072
title: Dataset for solar forecasting in Rizhao, Shandong

description: This dataset is for solar forecasting research in Rizhao, Shandong.
DOI: 10.5281/zenodo.6539071
title: Dataset for solar forecasting in Rizhao, Shandong

description: This dataset is for solar forecasting research in Rizhao, Shandong.