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opencc-by-4.0Sep 2021View details →

Workflow notebooks for deriving parameter of SUEWS v2020 based on FLUXNET2015 dataset

This archive includes all supportive files (processing and simulation scripts and derived parameters) for revision of <a href="https://doi.org/10.5194/gmd-2020-148">GMD-2020-148</a>. 1. ana.zip: scripts for parameter derivation and and result analysis. 2. data.zip: preprocessed FLUXNET data and derived parameters. 3. sim.zip: scripts for conducting SUEWS simulations. Please note: due to the Zenodo upload restriction, the simulation results are archived separately at:

opennotspecifiedAug 2011View details →

Distribution. Sulawesi and adjacent Is (Buton, Kabaena, Muna, Peleng, Lembeh, and on some of the Togian Is); thought to be extinct on Selayar I. Pigs have been widely domesticated through the Indonesian archipelago and beyond. This primarily involved the Eurasian Wild Pig (S. scrofa), but also S. celebensis, the only other species of pig successfully domesticated. Mitochondrial DNA studies of the dispersion of these domesticated forms agree on three major dispersal events, two involving S. scrofa and one S. celebensis. Evidence supports an early human-mediated translocation of S. celebensis to Flores and Timor and two later, separate human-mediated dispersals of domestic pig through islands of SE Asia into Oceania. In addition to Flores and Timor, S. celebensis is also thought to occur in its domesticated form on Halmahera, Lendu, Roti, and Savur Is, and even on Simeulue and Nias Is to the W of Sumatra and far from its island of origin, Sulawesi. In the Moluccas, and possibly elsewhere in this region, introduced S. celebensis are thought to have hybridized with other introduced pigs of S. scrofa derivation, and apparent hybrids between these species are now reported to survive on a number of islands, including Salawatti, Great Kei, Dobu, Seram, Ambon, Bacan, Ternate, Morotai, and New Guinea. It is also reported that in the 19" century the sows of domestic pigs in Sulawesi frequently mated with wild animals, after which they returned to their villages. in Suidae

Distribution. Sulawesi and adjacent Is (Buton, Kabaena, Muna, Peleng, Lembeh, and on some of the Togian Is); thought to be extinct on Selayar I. Pigs have been widely domesticated through the Indonesian archipelago and beyond. This primarily involved the Eurasian Wild Pig (S. scrofa), but also S. celebensis, the only other species of pig successfully domesticated. Mitochondrial DNA studies of the dispersion of these domesticated forms agree on three major dispersal events, two involving S. scrofa and one S. celebensis. Evidence supports an early human-mediated translocation of S. celebensis to Flores and Timor and two later, separate human-mediated dispersals of domestic pig through islands of SE Asia into Oceania. In addition to Flores and Timor, S. celebensis is also thought to occur in its domesticated form on Halmahera, Lendu, Roti, and Savur Is, and even on Simeulue and Nias Is to the W of Sumatra and far from its island of origin, Sulawesi. In the Moluccas, and possibly elsewhere in this region, introduced S. celebensis are thought to have hybridized with other introduced pigs of S. scrofa derivation, and apparent hybrids between these species are now reported to survive on a number of islands, including Salawatti, Great Kei, Dobu, Seram, Ambon, Bacan, Ternate, Morotai, and New Guinea. It is also reported that in the 19" century the sows of domestic pigs in Sulawesi frequently mated with wild animals, after which they returned to their villages.

Single-cell RNA sequencing of CNS-infiltrating HSC-derived phagocytes of Ms4a3Ai14, BM chimeric mice (CD45.2 Csf2rb-/-: CD45.1 Csf2rb+/+ and CD45.2 Ifngr1-/-: CD45.1 Ifngr1+/+) using 10X Genomics platform. IFN-γ and GM-CSF control complementary differentiation programs in the monocyte to phagocyte transition during neuroinflammation.

Single-cell RNA sequencing of CNS-infiltrating HSC-derived phagocytes of Ms4a3Ai14 at onset and peak EAE,  BM chimeric mice (CD45.2 Csf2rb-/-: CD45.1 Csf2rb+/+ and CD45.2 Ifngr1-/-: CD45.1 Ifngr1+/+) using 10X Genomics platform. The sorted cells were loaded into 10x Genomics Chromium in parallel. Libraries were prepared as per the manufacturer's protocol (Chromium Next GEM Single Cell 3ʹ Reagent Kits v3.1 protocol) and sequenced on an Illumina NovaSeq sequencer according to 10X Genomics recommendations (paired-end reads, R1=28, i7=8, R2=91) to a depth of around 50,000 reads per cell. Initial processing was done using Cell Ranger (v3.1.0) mkfastq and count (reads were aligned to GENCODE reference build GRCm38.p6 Release M23 with added tdTomato sequence for the dataset from Ms4a3Ai14 mouse and collapse UMIs). Starting from the filtered gene-cell count matrix produced by CellRranger's in-built cell calling algorithms, we proceeded with Seurat v4 workflow.

Single-cell RNA sequencing of Lymph node-infiltrating HSC-derived phagocytes of Ms4a3Ai14 using 10X Genomics platform. IFN-γ and GM-CSF control complementary differentiation programs in the monocyte to phagocyte transition during neuroinflammation.

Single-cell RNA sequencing of Lymph node-infiltrating HSC-derived phagocytes of Ms4a3Ai14 at onset and peak EAE using 10X Genomics platform. The sorted cells were loaded into 10x Genomics Chromium in parallel. Libraries were prepared as per the manufacturer's protocol (Chromium Next GEM Single Cell 3ʹ Reagent Kits v3.1 protocol) and sequenced on an Illumina NovaSeq sequencer according to 10X Genomics recommendations (paired-end reads, R1=28, i7=8, R2=91) to a depth of around 50,000 reads per cell. Initial processing was done using Cell Ranger (v3.1.0) mkfastq and count (reads were aligned to GENCODE reference build GRCm38.p6 Release M23 with added tdTomato sequence for the dataset from Ms4a3Ai14 mouse and collapse UMIs). Starting from the filtered gene-cell count matrix produced by CellRranger's in-built cell calling algorithms, we proceeded with Seurat v4 workflow.

Single-cell RNA sequencing of Bone Marrow-infiltrating HSC-derived phagocytes of Ms4a3Ai14 using 10X Genomics platform. IFN-γ and GM-CSF control complementary differentiation programs in the monocyte to phagocyte transition during neuroinflammation.

Single-cell RNA sequencing of Bone Marrow-infiltrating HSC-derived phagocytes of Ms4a3Ai14 at onset and peak EAE using 10X Genomics platform. The sorted cells were loaded into 10x Genomics Chromium in parallel. Libraries were prepared as per the manufacturer's protocol (Chromium Next GEM Single Cell 3ʹ Reagent Kits v3.1 protocol) and sequenced on an Illumina NovaSeq sequencer according to 10X Genomics recommendations (paired-end reads, R1=28, i7=8, R2=91) to a depth of around 50,000 reads per cell. Initial processing was done using Cell Ranger (v3.1.0) mkfastq and count (reads were aligned to GENCODE reference build GRCm38.p6 Release M23 with added tdTomato sequence for the dataset from Ms4a3Ai14 mouse and collapse UMIs). Starting from the filtered gene-cell count matrix produced by CellRranger's in-built cell calling algorithms, we proceeded with Seurat v4 workflow.

Single-cell RNA sequencing of Blood-infiltrating HSC-derived phagocytes of Ms4a3Ai14 using 10X Genomics platform. IFN-γ and GM-CSF control complementary differentiation programs in the monocyte to phagocyte transition during neuroinflammation.

Single-cell RNA sequencing of Blood-infiltrating HSC-derived phagocytes of Ms4a3Ai14 at onset and peak EAE using 10X Genomics platform. The sorted cells were loaded into 10x Genomics Chromium in parallel. Libraries were prepared as per the manufacturer's protocol (Chromium Next GEM Single Cell 3ʹ Reagent Kits v3.1 protocol) and sequenced on an Illumina NovaSeq sequencer according to 10X Genomics recommendations (paired-end reads, R1=28, i7=8, R2=91) to a depth of around 50,000 reads per cell. Initial processing was done using Cell Ranger (v3.1.0) mkfastq and count (reads were aligned to GENCODE reference build GRCm38.p6 Release M23 with added tdTomato sequence for the dataset from Ms4a3Ai14 mouse and collapse UMIs). Starting from the filtered gene-cell count matrix produced by CellRranger's in-built cell calling algorithms, we proceeded with Seurat v4 workflow.

opencc-by-4.0Dec 2021View details →

tRNA-derived fragment tRF-Glu49 inhibits cell proliferation, migration and invasion in cervical cancer by targeting FGL1

A transfer RNA (tRNA)-derived fragment was found to be a new possible biological marker and target in carcinoma therapy. However, the effect exerted by tRFs on cervical carcinoma is still unclear. We identify the potential tumor suppressor gene tRF-Glu49 in cervical carcinoma through tRF and ti-RNA microarray investigation. We then demonstrated that tRF-Glu49 showed downregulation within the cervical carcinoma tissue and was associated with less aggressive clinical features and a better prognosis. Phenotypic studies revealed that tRF-Glu49 inhibited cervical cell proliferation, migration, and invasion processes. Mechanistic investigation revealed that tRF-Glu49 directly regulated the oncogene, fibrinogen-like protein-1 (FGL1). In general, according to the result achieved in this study, tRF-Glu49 can modulate cervical cell proliferation, migration, and invasion processes through the target process for FGL1, and tRF-Glu49 is likely to be a possible prognostic biological marker in patients with cervical carcinoma.

openother-pdDec 2021View details →

BridgeDb: pathway identifier mapping database derived from Wikidata

First release of a BridgeDb pathway identifier mapping database. Currently supports Wikidata and WikiPathways identifiers. CCZero. <pre><code>[INFO]: Database finished. INFO: old database is Wikidata 1.0.0 (build: 20211211) INFO: new database is Wikidata 1.0.0 (build: 20211211) INFO: Number of ids in Wd (Wikidata): 905 (unchanged) INFO: Number of ids in Wp (WikiPathways): 900 (unchanged) INFO: new size is 2 Mb (changed +0.0%) INFO: total number of identifiers is 1805 INFO: total number of mappings is 1810 </code></pre>

opencc-by-4.0Dec 2020View details →

Long-term memory T cells as preventive anticancer immunity elicited by TuA-derived heteroclitic peptides

The host’s immune system may be primed against antigens during the lifetime (e.g. microorganisms antigens—MoAs), and swiftly recalled upon growth of a tumor expressing antigens similar in sequence and structure. C57BL/6 mice were immunized in a preventive setting with tumor antigens (TuAs) or corresponding heteroclitic peptides specific for TC-1 and B16 cell lines. AQ1 Immediately or 2- months after the end of the vaccination protocol, animals were implanted with cell lines. The specific anti-vaccine immune response as well as tumor growth were regularly evaluated for 2 months post-implantation. The preventive vaccination with TuA or their heteroclitic peptides (hPep) was able to delay (B16) or completely suppress (TC-1) tumor growth when cancer cells were implanted immediately after the end of the vaccination. More importantly, TC-1 tumor growth was significantly delayed, and suppressed in 6/8 animals, also when cells were implanted 2-months after the end of the vaccination. The vaccine-specific T cell response provided a strong immune correlate to the pattern of tumor growth. A preventive immunization with heteroclitic peptides resembling a TuA is able to strongly delay or even suppress tumor growth in a mouse model. More importantly, the same effect is observed also when tumor cells are implanted 2 months after the end of vaccination, which corresponds to 8 – 10 years in human life. The observed potent tumor control indicates that a memory T cell immunity elicited during the lifetime by a antigens similar to a TuA, i.e. viral antigens, may ultimately represent a great advantage for cancer patients and may lead to a novel preventive anti-cancer vaccine strategy.

FIGURE 7 in Kalanchoe ×forbesiae (Crassulaceae subfam. Kalanchooideae) derived from K. lubangensis × K. sexangularis: towards improved horticultural material

FIGURE 7. Kalanchoe ×forbesiae commemorates Helena M.L. Forbes (1900–1959). Photographer unknown. Photograph © of the South African National Biodiversity Institute. Reproduced with permission.

FIGURE 5 in Kalanchoe ×forbesiae (Crassulaceae subfam. Kalanchooideae) derived from K. lubangensis × K. sexangularis: towards improved horticultural material

FIGURE 5. The leaves of Kalanchoe ×forbesiae are weakly red-infused, but the peduncles, especially higher up, are more intensely redinfused. Photograph: Gideon F. Smith.

FIGURE 3 in Kalanchoe ×forbesiae (Crassulaceae subfam. Kalanchooideae) derived from K. lubangensis × K. sexangularis: towards improved horticultural material

FIGURE 3. Virtually all plant parts of the perennial Kalanchoe sexangularis are strongly red-infused. Photograph: Gideon F. Smith.

FIGURE 6 in Kalanchoe ×forbesiae (Crassulaceae subfam. Kalanchooideae) derived from K. lubangensis × K. sexangularis: towards improved horticultural material

FIGURE 6. The corolla tubes and corolla lobes of K. ×forbesiae are virtually the same yellow colour, with the tubes being only faintly greenish-infused. Photograph: Gideon F. Smith.

FIGURE 4 in Kalanchoe ×forbesiae (Crassulaceae subfam. Kalanchooideae) derived from K. lubangensis × K. sexangularis: towards improved horticultural material

FIGURE 4. The corolla tubes of Kalanchoe sexangularis are light green, like those of K. lubangensis. Photograph: Gideon F. Smith.

opencc-by-4.0Dec 2021View details →

Inhibition of Lung Microbiota-derived Proapoptotic Peptides Ameliorate Acute Exacerbation of Pulmonary Fibrosis

The files show the microarray data obtained during epitope mapping of the newly developed monoclonal antibodies against corisin, the complete protein sequences of newly isolated Staphylococcus haemolyticus strains (1b, 7b and 12b), and the raw data of all figures and tables.

opencc-by-4.0Dec 2021View details →

Data and derived products from airborne radar sounding survey over Devon Ice Cap, Canadian Arctic

Data and derived products used in Rutishauser et al., “Radar sounding survey over Devon Ice Cap indicates the potential for a diverse hypersaline subglacial hydrological environment”, accepted for publication, The Cryosphere, <a href="https://doi.org/10.5194/tc-2021-220">https://doi.org/10.5194/tc-2021-220</a> Corresponding author: <a href="mailto:rutishauser.anja@gmail.com">rutishauser.anja@gmail.com</a>   Description of datasets: ------------------------------------------ 2018_DIC_UTIG.IR2HI1B.kml Geolocation of the SRH1 profile lines. Coordinates in EPSG: 4326 - WGS 84 (latitude, longitude) ------------------------------------------ 2018_DIC_UTIG.IR2HI1B.tgz HiCARS 2 L1B echo strength profiles (radargrams) in NetCDF format. The naming of the files has the structure IR2HI1B_YYYYDOY_PST_x (e.g. IR2HI1B_2018153_DEV_JKB2t_Y87b_000.nc), where YYYY is the survey year (e.g. 2018), DOY is the survey day of the year (e.g. 153), PST is the profile name (e.g. DEV_JKB2t_Y87b), and x is the segment number if the profile was split in two (e.g. 000). For each profile, a PDF file showing the profile location and the radargram is included. ------------------------------------------ 2018_DIC_UTIG.Level2.tgz  Level 2 datasets for each profile, organized in the following folders: <ul> <li>2018_DIC_UTIG.ILUTP2: Laser altimeter geolocated surface elevation</li> <li>2018_DIC_UTIG.IR2HI2: HiCARS 2 unfocused (pik1) geolocated ice thickness, ice surface elevation, bed elevation, surface- and bed reflection coefficients, and aircraft roll</li> <li>2018_DIC_UTIG.IRHFOC2: HiCARS 2 focused (foc1) geolocated ice thickness, ice surface elevation, bed elevation, surface- and bed reflection coefficients, and aircraft roll</li> <li>2018_DIC_UTIG.IRSPC2: HiCARS 2 derived basal interface specularity content</li> </ul> ------------------------------------------ Devon_basal_ice_temperature.tif: Modeled basal ice temperature [ºC] using a 1D advection diffusion model. 500 m grid cell size, coordinates in EPSG: 32617 - WGS 84 / UTM zone 17N. ------------------------------------------ Devon_bedrockDEM.tif: Digital elevation model (DEM) of the bedrock topography beneath Devon Ice Cap [m asl.]. 500 m grid cell size, coordinates in EPSG: 32617 - WGS 84 / UTM zone 17N. ------------------------------------------ Devon_gridded_RMSD_bedrock.tif: Root mean square deviation (RMDS) of the bedrock topography [m]. The RMSD was computed along each profile line, then interpolated on a 500x500m grid using the QGIS GDAL moving average grid interpolation. 500 m grid cell size, coordinates in EPSG: 32617 - WGS 84 / UTM zone 17N. ------------------------------------------ Devon_gridded_specularity.tif: Specularity content from along the profile lines interpolated on a 500x500m grid using the QGIS GDAL moving average grid interpolation. 500 m grid cell size, coordinates in EPSG: 32617 - WGS 84 / UTM zone 17N. ------------------------------------------ Devon_ice_thickness.tif: Gridded ice thickness [m] generated by subtracting the bedrock DEM from ice surface elevations derived from the ArcticDEM, Polar Geospatial Center from DigitalGlobe Inc. imagery. 500 m grid cell size, coordinates in EPSG: 32617 - WGS 84 / UTM zone 17N. ------------------------------------------ Devon_modeled_Geology.zip <ul> <li>Devon_modeled_subglacial_geology.tif: Map of the projected geological units beneath Devon Ice Cap. The assigned numbers correspond to the following geological units: 1: pPe, 2: Cm-cf, 3: Oe, 4: Ocb, 5: Oct. Details on the geological units can be found in (Harrison et al., 2016; Mayr, 1980; Thorsteinsson & Mayr, 1987). 500 m grid cell size, coordinates in EPSG: 32617 - WGS 84 / UTM zone 17N.</li> <li>{pPe, Oe, Oct, Ocb,Cm_rb}_Model.stl: 3D geometry of the modeled geological units beneath Devon Ice Cap, originally published in (Rutishauser et al., 2018). Coordinates in EPSG: 32617 - WGS 84 / UTM zone 17N.</li> <li>Devon_load_geology_stl_files.py: Python script to load and plot the 3D geology layers in the .stl files.</li> </ul> ------------------------------------------ Devon_subgl_hydraulic_head.tif: Subglacial hydraulic head [m] beneath Devon Ice Cap. 500 m grid cell size, coordinates in EPSG: 32617 - WGS 84 / UTM zone 17N. ------------------------------------------ Devon_subgl_hydraulic_slope.tif Slope [º] of the subglacial hydraulic head beneath Devon Ice Cap. 500 m grid cell size, coordinates in EPSG: 32617 - WGS 84 / UTM zone 17N. ------------------------------------------ Devon_subgl_lakes_brine_network.zip <ul> <li>Devon_subgl_lake_outline.shp: Shoreline of the subglacial lakes beneath Devon Ice Cap (identified in this study). Coordinates in EPSG: 32617 - WGS 84 / UTM zone 17N.</li> <li>Devon_brine_network_outline.shp: Outlines of the mapped subglacial brine network beneath Devon Ice Cap. Coordinates in EPSG: 32617 - WGS 84 / UTM zone 17N.</li> </ul> ------------------------------------------ Devon_subgl_water_routes.zip <ul> <li>Devon_modeled_subgl_water_routes_{1, 2, 3}std.tif: Modeled subglacial water routes derived via application of a flow accumulation algorithm to the hydraulic head. The model is run 1000 times with normally distributed random errors of 1, 2 and 3 standard deviations of the hydraulic head uncertainty added to the hydraulic head (represented in the file name). Pixel values represent the model counts for which the cell has a minimum of 10 upstream cells draining into it. 500 m grid cell size, coordinates in EPSG: 32617 - WGS 84 / UTM zone 17N.</li> <li>Devon_extracted_subgl_water_routes.shp: Modeled subglacial water routes derived via the application of a flow accumulation algorithm to the hydraulic head. Coordinates in EPSG: 32617 - WGS 84 / UTM zone 17N.</li> </ul> ------------------------------------------ SpecularityJustification.zip Jupyter notebook and example datafile to show the justification for the chosen specularity threshold of 0.4 for declaring a detection of possible subglacial water. ------------------------------------------   Acknowledgments The aerogeophysical survey and subsequent standard data processing were funded by the Weston Family Foundation. We also thank the G. Unger Vetlesen Foundation and the UTIG Postdoctoral Fellowship program who provided further funding for data analysis. M.L.S. was partially supported by NASA NNX16AJ64G and NASA 80NSSC20K1134. We thank PCSP and Kenn Borek Air Ltd. for logistical support, and the Nunavut Research Institute and the peoples of Grise Fjord and Resolute Bay for permission to conduct airborne surveys over Devon Ice Cap. Finally, we thank Scott Kempf for assistance with data processing, and Sam Christian and Miguel Liu-Schiaffini for help with radar reflection picking. References Harrison, J. C., Lynds, T., Ford, A., & Rainbird, R. H. (2016). Geology, simplified tectonic assemblage map of the Canadian Arctic Islands, Northwest Territories - Nunavut. Geological Survey of Canada, Canadian Geoscience, Map 80. https://doi.org/10.4095/297416 Mayr, U. (1980). Stratigraphy and correlation of lower Paleozoic formations, subsurface of Bathurst Island and adjacent smaller islands, Canadian Arctic Archipelago. Geological Survey of Canada, Bulletin, 306. https://doi.org/10.4095/102157 Rutishauser, A., Blankenship, D. D., Sharp, M., Skidmore, M. L., Greenbaum, J. S., Grima, C., Schroeder, D. M., Dowdeswell, J. A., & Young, D. A. (2018). Discovery of a hypersaline subglacial lake complex beneath Devon Ice Cap, Canadian Arctic. Science Advances, 4(4), eaar4353. https://doi.org/10.1126/sciadv.aar4353 Thorsteinsson, R., & Mayr, U. (1987). The sedimentary rocks of Devon island, canadian arctic archipelago. https://doi.org/10.4095/122451

opencc-zeroDec 2021View details →

Supplementary material 3 from: Vasiliţa C, Popovici OA, Talamas E, Johnson N, Masner L, Tortorici F, Fusu L (2021) Molecular analysis reveals Latonius planus Kononova to be a derived species of Trissolcus Ashmead. In: Lahey Z, Talamas E (Eds) Advances in the Systematics of Platygastroidea III. Journal of Hymenoptera Research 87: 267-289. https://doi.org/10.3897/jhr.87.63533

Phylogenetic reconstruction on the partitioned data set of Taekul et al. (2014), Bayesian analysis. Posterior probability indicated at nodes

opencc-zeroDec 2021View details →

Supplementary material 1 from: Vasiliţa C, Popovici OA, Talamas E, Johnson N, Masner L, Tortorici F, Fusu L (2021) Molecular analysis reveals Latonius planus Kononova to be a derived species of Trissolcus Ashmead. In: Lahey Z, Talamas E (Eds) Advances in the Systematics of Platygastroidea III. Journal of Hymenoptera Research 87: 267-289. https://doi.org/10.3897/jhr.87.63533

Phylogenetic reconstruction on the non-partitioned data set of Taekul et al. (2014) with a degenerated COI alignment, ML analysis

opencc-by-4.0Jan 2022View details →

Data linked to publication entitled "Biochar derived from Acai agroindustry waste enhances nutritional status and biomass in young Eucalyptus urophylla plants: Evidence connected to root development and leaf performance"

Data linked to publication entitled "Biochar derived from Acai agroindustry waste enhances nutritional status and biomass in young Eucalyptus urophylla plants: Evidence connected to root development and leaf performance"