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Terrestrial water data synthesis for hydrological catchments around the world in the Anthropocene
<p>We here synthesise hydro-climatic data reported by previous studies for 65 hydrological catchments around the world [1-7] for further meta-analysis of how water fluxes of precipitation (P), runoff (R), and actual evapotranspiration (ET) on land change in the Anthropocene epoch, from before to after its start in the 1950's [8]. These water flux changes alter how much water ends up sustaining crops and other plants (evapotranspiration) and how much remains for the lateral water flows (runoff) through the landscape and the societal water uses and ecosystems they support. How this partitioning changes as integral part of global change is key for water and food security, and life on land and below water around the world’s land areas and coasts. </p> <p>To distinguish the impacts of direct human drivers on evapotranspiration and runoff changes based on instrumental data for wide-ranging water, human-activity and climate conditions around the world, the 65 study catchments are divided in two comparative sets. One set includes 52 large catchments, selected from two previous data compilations and studies [1,2] and is in the data files referred to as the world set of catchments. The study periods are 1901–2008 for 21 [2] and 1930–1979 for the other 31 [1] of these catchments. The second set includes 13 catchments selected from previous studies [3-7] of both the water flux changes and associated dominant human drivers of these for time periods that are largely consistent with those for the world set of catchments (within 1901-2016); this is in the data files referred to as the known human-shifted set of catchments. The dominant direct human drivers of water-flux changes in these catchments include expanded/intensified rainfed agriculture (RA), irrigated agriculture (IA), or dams and reservoirs for engineered flow regulation (FR), as listed and cited for each known human-shifted catchment in the data files. </p> <p>For each study catchment, we have quantified and report in the data files long-term average P, R and ET values over the total study period and changes in period-average values between two subperiods within it. The subperiods are 1901–1954 and 1955–2008 for 21 [2], and 1930–1954 and 1955–1979 for the other 31 [1] world catchments, and largely consistent for the known human-shifted catchments [3-7] (as listed in the data files). Each study catchment is also classified as water or energy limited by quantifying the associated Budyko-based aridity index PET/P, where PET is potential evapotranspiration. Average PET is estimated as PET≈325+21T+0.9T<sup>2</sup> where T is long-term annual and catchment average surface temperature in °C, calculated from monthly temperature data in the previous catchment studies [1-7]. The resulting PET/P index classifies actual ET/P in each catchment as energy limited for average PET/P < 1 or water limited for average PET/P > 1, as listed in the data files.</p> <p>Other catchment information included in the data files, uploaded in both pdf and xlsx formats, include source references, catchment name, area and station ID and continent and latitude location. Overall, this dataset provides a wide-ranging sample of catchment-wise related, water balance-constrained local-regional changes in average P, R and ET under major RA, IA, FR developments (known for the second human-shifted set of catchments [3-7]) and various other human-activity and climate developments around the world from before to after the Anthropocene start in the 1950’s [8]. </p>
A versatile "Synthesis Tag" (SynTag) for the chemical synthesis of aggregating peptides and proteins
<p>Raw data for the project "A versatile "Synthesis Tag" (SynTag) for the chemical synthesis of aggregating peptides and proteins".</p><p>Manuscript and supporting information available on ChemRxiv: https://doi.org/10.26434/chemrxiv-2023-7mz2c-v2.</p>
Synthesis of Sea level rise and carbon accumulation rates in United States tidal wetlands
Coastal wetlands accumulate soil carbon more efficiently than terrestrial systems, but sea level rise potentially threatens the persistence of this prominent carbon sink. Here, we combine a published dataset of 372 soil carbon accumulation rates from across the United States with new analysis of 131 sites in coastal Louisiana. The combined database featured 503 measurements of carbon accumulation, spanning broad gradients in mean annual temperature, tide range, and dominant vegetation.
Synthesis Dataset of 4-hydrazinylphenyl benzenesulfonate
<p>Hydrazine is a reducing agent with a highly reactive base use in many medical, industrial applications, preparation of many heterocyclic compounds using hydrazine as a key of building block with two amines. 4-hydrazinylphenyl benzenesulfonate has been successfully synthesized employing reduction and diazotation methods as <strong>new hydrazine</strong> derivatives.</p>
Data_Figure 2_Impact of 17β‑HSD12, the 3‑ketoacyl‑CoA reductase of long‑chain fatty acid synthesis, on breast cancer cell proliferation and migration
<p>Data of figure 2 from Impact of 17β‑HSD12, the 3‑ketoacyl‑CoA reductase of long‑chain fatty acid synthesis, on breast cancer cell proliferation and migration</p> <p>Dataset (doi: 10.1007/s00018-019-03227-w) contains the original figure as TIF-format (10.1007_s00018-019-03227-w_CMLS_Fig2). Corresponding raw data obtained from a) Migration potential as four files in CSV format (31003A-179400_ date_examiner_17BHSD12_16_1_1-4. b) mRNA content analyzed by RT-PCR provided as ten files in CSV format (31003A-179400_date_examiner_17BHSD12_1_1-2_1-6) and proliferation investigation on xCELLigence provided as six files in CSV format (31003A-179400_date_examiner_17BHSD12_9_2_1-6). All further experiment related information and subsequent data analysis provided as four meta-data-files (31003A-179400_ date_examiner_17BHSD12_16/1/9_dataset_M_1) as TXT format.</p>
Data_Figure 6_Impact of 17β‑HSD12, the 3‑ketoacyl‑CoA reductase of long‑chain fatty acid synthesis, on breast cancer cell proliferation and migration
<p>Data of figure 6 from Impact of 17β‑HSD12, the 3‑ketoacyl‑CoA reductase of long‑chain fatty acid synthesis, on breast cancer cell proliferation and migration</p> <p>Dataset (doi: 10.1007/s00018-019-03227-w) contains the original figure as TIF-format (10.1194_jlr.M092908_Fig. 6). Corresponding raw data obtained from a1/2) cellomics HTC array scan analysis provided as six files in CSV format (31003A-179400_Date_examiner_17BHSD12_8_6_1-6), b1/2) oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) provided as 10 files in CSV format (31003A-179400_20190521_MT_17BHSD12_10_3-4_1-5); c 1/2 ), cellomics HTC array scan analysis provided as 12 files in CSV format (31003A-179400_Date_examiner_17BHSD12_8_7-8_1-8). d) Western blot and densitometry provided as eight files in CSV format (31003A-179400_Date_examiner_17BHSD12_2_3-4_1-5). All further experiment related information protocols and subsequent data analysis provided as meta-data-files (31003A-179400_date_examiner_17BHSD12_8/10/2_dataset_M_1) as TXT format and (31003A-179400_date_examiner_17BHSD12_2_dataset_M_2-3) as PNG format.</p>
Data_Figure 7_Impact of 17β‑HSD12, the 3‑ketoacyl‑CoA reductase of long‑chain fatty acid synthesis, on breast cancer cell proliferation and migration
<p>Data of figure 7 from Impact of 17β‑HSD12, the 3‑ketoacyl‑CoA reductase of long‑chain fatty acid synthesis, on breast cancer cell proliferation and migration</p> <p>Dataset (doi: 10.1007/s00018-019-03227-w) contains the original figure as TIF-format (10.1194_jlr.M092908_Fig. 7). Corresponding raw data obtained from a1/2) Western blot and densitometry provided as eight files in CSV format (31003A-179400_date_examiner_17BHSD12_2_5-6_1-6); b) mRNA content analyzed by RT-PCR provided as four files in CSV format (31003A-179400_date_examiner_17BHSD12_1_6_1-4); c 1/2) cellomics HTC array scan analysis provided as 11 files in CSV format (31003A-179400_Date_examiner_17BHSD12_8_9-10_1-6); d1/2); Western blot and densitometry provided as eight files in CSV format (31003A-179400_date_examiner_17BHSD12_2_7-8_1-6). All further experiment related information protocols and subsequent data analysis provided as meta-data-files (31003A-179400_date_examiner_17BHSD12_2/1/8_dataset_M_1) as TXT format and (31003A-179400_date_examiner_17BHSD12_2_dataset_M_2-3) as PNG format.</p>
Data_Figure 5_Impact of 17β‑HSD12, the 3‑ketoacyl‑CoA reductase of long‑chain fatty acid synthesis, on breast cancer cell proliferation and migration
<p>Data of figure 5 from Impact of 17β‑HSD12, the 3‑ketoacyl‑CoA reductase of long‑chain fatty acid synthesis, on breast cancer cell proliferation and migration</p> <p>Dataset (doi: 10.1007/s00018-019-03227-w) contains the original figure as TIF-format (10.1194_jlr.M092908_Fig. 5). Corresponding raw data obtained from oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) provided as 10 files in CSV format (31003A-179400_20190521_MT_17BHSD12_10_1-2_1-5). All further experiment related information and subsequent data analysis provided as two meta-data-file: (31003A-179400_20190521_MT_17BHSD12_10_1-2_1) as TXT format.</p>
Data_Figure 4_Impact of 17β‑HSD12, the 3‑ketoacyl‑CoA reductase of long‑chain fatty acid synthesis, on breast cancer cell proliferation and migration
<p>Data of figure 4 from Impact of 17β‑HSD12, the 3‑ketoacyl‑CoA reductase of long‑chain fatty acid synthesis, on breast cancer cell proliferation and migration</p> <p>Dataset (doi: 10.1007/s00018-019-03227-w) contains the original figure as TIF-format (10.1194_jlr.M092908_Fig. 4). Corresponding raw data obtained from: a1/2) Migration potential as five files in CSV format (31003A-179400_date_examiner_17BHSD12_16_3_1-5); b 1/2) Migration potential as four files in CSV format (31003A-179400_date_examiner_17BHSD12_16_4_1-4); c1/2/3) mRNA content analyzed by RT-PCR provided as four files in CSV format (31003A-179400_date_examiner_17BHSD12_1_4_1-4); cellomics HTC array scan analysis provided as three files in CSV format (31003A-179400_Date_examiner_17BHSD12_8_3-4_1-4); d) Migration potential as five files in CSV format (31003A-179400_ date_examiner_17BHSD12_16_5_1-5); e) mRNA content analyzed by RT-PCR provided as six files in CSV format (31003A-179400_date_examiner_17BHSD12_1_5_1-6); f) Migration potential as four files in CSV format (31003A-179400_date_examiner_17BHSD12_16_6_1-4), cellomics HTC array scan analysis provided as three files in CSV format (31003A-179400_Date_examiner_17BHSD12_8_5_1-5); g) ELISA measurement provided as four files in CSV format (31003A-179400_date_examiner_17BHSD12_20_1_1-4). All further experiment related information protocols and subsequent data analysis provided as 10 meta-data-files (31003A-179400_date_examiner_17BHSD12_8/16/1/20_dataset_M_1) as TXT format.</p>
Data_supplemental figure 2_Impact of 17β‑HSD12, the 3‑ketoacyl‑CoA reductase of long‑chain fatty acid synthesis, on breast cancer cell proliferation and migration
<p>Data of supplemental figure 2 from Impact of 17β‑HSD12, the 3‑ketoacyl‑CoA reductase of long‑chain fatty acid synthesis, on breast cancer cell proliferation and migration</p> <p>Dataset (doi: 10.1007/s00018-019-03227-w) contains the original figure as TIF format (10.1194_jlr.M092908_Fig. S2). Corresponding raw data obtained from cellomics HTC array scan analysis provided as seven files in CSV format (31003A-179400_Date_examiner_17BHSD12_8_11-12_1-4) All further experiment related information protocols as meta-data-files (31003A-179400_date_examiner_17BHSD12_8_11-12_M_1) as TXT format.</p>
Fig. 12 in Palaearctic species of Charipinae (Hymenoptera, Figitidae): two new species, synthesis and identification key
Fig. 12. Alloxysta palearctica Ferrer-Suay & Pujade-Villar sp. nov. 1. Fore wing. 2. Detail of antenna. 3. Antenna. 4. Radial cell. 5. Pronotum. 6. Body. 7. Propodeum. Scale bars: 50 μm.
Fig. 11 in Palaearctic species of Charipinae (Hymenoptera, Figitidae): two new species, synthesis and identification key
Fig. 11. Alloxysta pascuali Ferrer-Suay sp. nov. 1. Fore wing. 2. Pronotum. 3. Antenna. 4. Body. 5. Propodeum. Scale bars: 50 μm.
Fig. 10 in Palaearctic species of Charipinae (Hymenoptera, Figitidae): two new species, synthesis and identification key
Fig. 10. Types of fore wing. 1. Phaenoglyphis evenhuisi Pujade-Villar & Paretas-Martínez, 2006. 2. Alloxysta brevis (Thomson, 1862). 3. A. darci (Girault, 1933). Scale bars: 50 μm.
Fig. 8 in Palaearctic species of Charipinae (Hymenoptera, Figitidae): two new species, synthesis and identification key
Fig. 8. Types of pronotum. 1. Alloxysta arcuata (Kieffer, 1902). 2. A. brevis (Thomson, 1862). 3. Phaenoglyphis americana Baker, 1896. Scale bars: 50 μm.
Fig. 7 in Palaearctic species of Charipinae (Hymenoptera, Figitidae): two new species, synthesis and identification key
Fig. 7. Types of mesoscutum of Phaenoglyphis Förster, 1869. 1. P. abbreviata (Thomson, 1877). 2. P. evenhuisi Pujade-Villar & Paretas-Martínez, 2006. 3. P. fuscicornis (Thomson, 1877). 4. P. heterocera (Hartig, 1841). 5. P. insperatus Belizin, 1973. 6. P. insularis (Belizin, 1973). 7. P. longicornis (Hartig, 1840). 8. P. moldavica Ionescu, 1969. 9. P. nigripes (Thomson, 1877). 10. P. proximus Belizin, 1966. 11. P. pubicollis (Thomson, 1877). 12. P. ruficornis (Förster, 1869). 13. P. salicis (Cameron, 1883). 14. P. stricta (Thomson, 1877). 15. P. villosa (Hartig, 1841). 16. P. xanthochroa Förster, 1869. Scale bars: 50 μm.
Fig. 6 in Palaearctic species of Charipinae (Hymenoptera, Figitidae): two new species, synthesis and identification key
Fig. 6. Types of antenna of Dilyta Förster, 1869 and Phaenoglyphis Förster, 1869. 1. D. aleevae Pujade-Villar & Paretas-Martínez, 2011. 2. D. japonica Paretas-Martínez & Ferrer-Suay, 2011. 3. D. longinqua Paretas-Martínez & Pujade-Villar, 2011. 4. D. rathmanae. 5. D. sinica Ferrer-Suay & Paretas-Martínez, 2011. 6. D. subclavata Förster, 1869. 7. P. abbreviata (Thomson, 1877). 8. P. evenhuisi Pujade-Villar & Paretas-Martínez, 2006. 9. P. fuscicornis (Thomson, 1877). 10. P. heterocera (Hartig, 1841). 11. P. insperatus Belizin, 1973. 12. P. insularis (Belizin, 1973). 13. P. longicornis (Hartig, 1840). 14. P. moldavica Ionescu, 1969. 15. P. nigripes (Thomson, 1877). 16. P. proximus Belizin, 1966. 17. P. pubicollis (Thomson, 1877). 18. P. ruficornis (Förster, 1869). 19. P. salicis (Cameron, 1883). 20. P. stricta (Thomson, 1877). 21. P. villosa (Hartig, 1841). 22. P. xanthochroa Förster, 1869. Scale bars: 50 μm.
Fig. 4 in Palaearctic species of Charipinae (Hymenoptera, Figitidae): two new species, synthesis and identification key
Fig. 4. Types of radial cell of Alloxysta Förster, 1869. 1. A. abdera Fergusson, 1986. 2. A. aperta (Hartig, 1841). 3. A. arcuata (Kieffer, 1902). 4. A. aurata Belizin, 1968. 5. A. basimacula (Cameron, 1886). 6. A. brachycera Hellén, 1963. 7. A. brevis (Thomson, 1862). 8. A. brevitarsis (Thomson, 1862). 9. A. castanea (Hartig, 1841). 10. A. circumscripta (Hartig, 1841). 11. A. citripes (Thomson, 1862). 12. A. consobrina (Zetterstedt, 1838). 13. A. crassa (Cameron, 1889). 14. A. crassicornis (Thomson, 1862). 15. A. fracticornis (Thomson, 1862). 16. A. fuscipes (Thomson, 1862). 17. A. heptatoma Hellén, 1963. 18. A. kovilovica Ferrer-Suay & Pujade-Villar, 2013. 19. A. leunisii (Hartig, 1841). 20. A. longipennis (Hartig, 1841). 21. A. macrophadna (Hartig, 1841). 22. A. marshalliana (Kieffer, 1900). 23. A. melanogaster (Hartig, 1840). 24. A. mullensis (Cameron, 1883). Scale bars: 50 μm.
Fig. 1 in Palaearctic species of Charipinae (Hymenoptera, Figitidae): two new species, synthesis and identification key
Fig. 1. Types of mesosoma and metasoma of the Charipinae Dalla Torre & Kieffer, 1910. 1. Mesosoma of Phaenoglyphis spp. 2. Mesosoma of Alloxysta spp. 3. Metasoma of Alloxysta spp. 4. Metasoma of Apocharips spp. Scale bars: 50 μm.
Fig. 3 in Palaearctic species of Charipinae (Hymenoptera, Figitidae): two new species, synthesis and identification key
Fig. 3. Types of antenna of Alloxysta Förster, 1869. 1. A. pedestris (Curtis, 1838). 2. A. piceomaculata (Cameron, 1883). 3. A. pilipennis (Hartig, 1840). 4. A. pleuralis (Cameron, 1879). 5. A. postica (Hartig, 1841). 6. A. proxima Belizin, 1962. 7. A. pusilla (Kieffer, 1902). 8. A. quedenfeldti (Kieffer, 1909). 9. A. ramulifera (Thomson, 1862). 10. A. rufiventris (Hartig, 1840). 11. A. salicicola Belizin, 1973. 12. A. sawoniewiczi Kierych, 1988. 13. A. semiaperta Fergusson, 1986. 14. A. slovenica Ferrer-Suay & Pujade-Villar, 2013. 15. A. soluta Hellén, 1963. 16. A. tscheki (Giraud, 1860). 17. A. victrix (Westwood, 1833). 18. A. xanthocera (Thomson, 1862). 19. A. xanthopa (Thomson, 1862). 20. A. trapezoidea (Hartig, 1841). Scale bars: 50 μm.
Fig. 9. Tortonian fish otoliths from northern Italy. A in Tortonian teleost otoliths from northern Italy: taxonomic synthesis and stratigraphic significance
Fig. 9. Tortonian fish otoliths from northern Italy. A. Echiodon heinzelini Huyghebaert & Nolf, 1979, Torrente Stirone (IRSNB P 9787). B. Hoplobrotula aff. armata (Temminck & Schlegel, 1846), Sant'Alosio (IRSNB P 9788). C. Neobythites auriculatus sp. nov., Sant'Alosio (IRSNB P 9688 (holotype). D–E. Carapus acus (Brünnich, 1768); D. Torrente Stirone, E. Sant'Agata Fossili (IRSNB P 9789–P 9790). F–G. Bythitidae indet., Torrente Stirone (IRSNB P 9791–P 9792). H. Grammonus bassolii (Nolf, 1980), Torrente Stirone (IRSNB P 9793). I. Chaunax lobatus (Bassoli, 1906), Montegibbio (IRSNB P 9794). J–L. Scopelogadus sp.; J. Alba, Tanaro (5 m), K. Stazzano, L. Alba, Tanaro (50 m) (IRSNB P 9795–P 9797). M. Mugilidae indet., Sant'Alosio (IRSNB P 9798). N. Phycis musicki Cohen & Lavenberg, 1984, Torrente Stirone (IRSNB P 9799). O. Melamphaes sp., Alba, Tanaro (50 m) (IRSNB P 9802). P. Micromesistius planatus (Bassoli & Schubert, 1906), Montegibbio (IRSNB P 9803). Q–R. "Scorpaena" zibinica (Bassoli, 1909), Torrente Stirone (IRSNB P 9800–P 9801). 1 = ventral view; 2 = inner view; 3 = anterior view. Scale bars = 1 mm.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.