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FIG. 13. — A in Fungal biodiversity profiles 111-120
FIG. 13. — A Maximum Likelihood (ML) phylogram inferred from raxmlGUI 2.0 (Edler et al. 2021) on a concatenated dataset of nrITS and nrLSU sequence data of Phaeolus and related genera. One thousand bootstrap replicates were analyzed to obtain nodal support values. Bootstrap support values (>70 %) obtained from ML analysis are shown above or below the branches at nodes. Two collections of our novel Indian species are shown in red and the holotype in bold in the phylogram. See Table 1 for details on used vouchers for the phylogenetic analysis.
FIG. 2 in Fungal biodiversity profiles 111-120
FIG. 2. — Phylogenetic tree depicting the relationship of Entoloma aurantioalpinum Armada, Vila, Bellanger, Noordel., Krisai & Dima, sp. nov. and Entoloma nigroflavescens Armada, Bellanger, Noordel. & Dima, sp. nov. within subgen. Cyanula, clades /Sarcitulum and /Atrocoeruleum, respectively. The new species are highlighted in color rectangles. Newly generated sequences are in boldface. The analysis was inferred from nrDNA ITS sequences using PhyML 3.1 with the following settings: GTR+I+G model of evolution, gamma distribution of 10 rate categories, and tree topology search as SPR. Branch support was tested using the non-parametric, Shimodaira-Hasegawa version of the approximate likelihood-ratio test (SH-aLRT). PhyML SH-aLRT support values (>50) are indicated at the branches. Main clades within the subgenus are compressed. Clitopilus was chosen as outgroup. Bar indicates 0.05 expected change per site per branch.
FIG. 12 in Fungal biodiversity profiles 111-120
FIG. 12. — Inocybe leucophaea Eyssart. & Buyck, sp. nov. (holotype): A, fruiting bodies; B, basidia; C, cystidia; D, marginal cells of the gill edge; E, spores; F, pileipellis in section (detail). Scale bars: A, 1 cm; B-E, 10 μm. Drawings by G. Eyssartier.
FIG. 19 in Fungal biodiversity profiles 111-120
FIG. 19. — Maximum likelihood (ML) tree of Russula subgenus Heterophillidiae based on combined sequence data of nrLSU, rpb2 and tef1α. Bootstrap values from ML analysis ≥50 % and Posterior probabilities from Bayesian inference (BPP) ≥0.95 are shown at branch nodes. The newly generated sequences of R. ferruginea sp. nov. are highlighted in boldface and on coloured background. Data of sequences used for the tree are listed in Table 2. Protocols for DNA extraction, PCR and sequencing followed Vera et al. (2021). Sequences were edited in the BioEdit 7.2.5 sequence alignment editor (Hall 2013) and Geneious R10 (Kearse et al. 2012). Intra-individual polymorphic sites having more than one signal were marked with NC-IUPAC ambiguity codes. The datasets were aligned in MAFFT 7 using the E-INS-i strategy (Katoh & Standley 2013) and manually improved in Geneious R10 (Kearse et al. 2012). Divergent and ambiguously aligned positions in the nrLSU were removed with Gblocks (Castresana 2000) using the least stringent parameters. Intronic positions of rpb2 and tef1α were manually removed. For the BI analysis, the data set was divided into five partitions: 28S, the 1st+2nd, and 3rd codon positions of tef1, the 1st+2nd, and 3rd codon positions of rpb2. The best substitution model for each partition was computed jointly in PartitionFinder 1.1.1 (Lanfear et al. 2012). BI runs were computed twice in MrBayes 3.2.6 (Ronquist et al. 2012) with four Markov chain Monte Carlo (MCMC) chains for 10 million iterations until the standard deviation of split frequencies fell below the 0.01 threshold. Convergence of runs was visually assessed using the trace function in Tracer 1.6 (Rambaut et al. 2013). For the ML analysis, the concatenated alignment was loaded as a fasta file to CIPRES Science Gateway (Miller et al. 2010) and analyzed using RAxML-HPC2 on XSEDE (8.2.12) as a partitioned data set (as in the BI analysis) under the GTR+GAMMA model with 1000 bootstrap iterations as recommended by the RAxML user manual (Stamatakis 2014).
FIG. 18 in Fungal biodiversity profiles 111-120
FIG. 18. — Russula ferruginea subsp. ferruginea Corrales & Vera, subsp. nov. (HUA Corrales 944, holotype). Elements of the pileipellis drawn as seen by light microscopy. A, pileocystidia near the pileus margin; B, pileocystidia near the pileus center; C, hyphal terminations near the pileus margin; D, hyphal terminations near the pileus center. Cystidia with contents as observed in Congo Red. Scale bar: 10 μm. Drawings by Michelle Vera.
FIG. 23. — A in Fungal biodiversity profiles 111-120
FIG. 23. — A Maximum Likelihood (ML) phylogram inferred from raxmlGUI 2.0 (Edler et al. 2021) on a concatenated dataset of nrITS and nrLSU sequence data of Vuilleminia and related genera. One thousand bootstrap replicates were analyzed to obtain nodal support values. Bootstrap support values (>70 %) obtained from ML analysis are shown above or below the branches at nodes. Two collections of our novel Indian species are shown in red and the holotype in bold in the phylogram. See Table 3 for details on used vouchers for the phylogenetic analysis.
FIG. 10 in Fungal biodiversity profiles 111-120
FIG. 10. — Inocybe media Eyssart. & Buyck, sp. nov. (holotype): A, fruiting bodies; B, basidia; C, cystidia; D, marginal cells of the gill edge; E, spores; F, pileipellis in section (detail). Scale bars: A, 1 cm; B-E, 10 μm. Drawings by G. Eyssartier.
FIG. 15 in Fungal biodiversity profiles 111-120
FIG. 15. — Phaeolus sharmae Hembrom, A. Parihar, K. Das & A. Ghosh, sp. nov. (holotype): A, basidia, basidioles and basidiospores; B, section through trama showing gloeoplerous hyphae, basidia, basidioles and cystidia; C, hyphae from loose upper part of context; D, hyphae adjacent to tube regions of context; E, cystidia; F, hyphae from pileus surface. Scale bars: 10 µm.
FIG. 20 in Fungal biodiversity profiles 111-120
FIG. 20. — Maximum likelihood tree of Russula sect. Ingratae based on sequence data of the ITS region. The newly generated sequences are in boldface, two subspecies of R. ferruginea sp. nov. are highlighted by different colour backgrounds. Names of taxa are followed by GenBank accession numbers and country of origin of samples, newly generated sequences are annotated with collection numbers. Protocols for DNA extraction, PCR and sequencing followed Vera et al. (2021). Sequences were edited in the BioEdit 7.2.5 sequence alignment editor (Hall 2013) and Geneious R10 (Kearse et al. 2012). The data set was analyzed on the CIPRES Science Gateway (Miller et al. 2010) under the GTR+GAMMA model with 1000 bootstrap iterations (Stamatakis 2014).
FIG. 25 in Fungal biodiversity profiles 111-120
FIG. 25. — Vuilleminia tropica Hembrom, A. Ghosh, A. Parihar & K. Das, sp. nov. (holotype): A, basidia and basidioles; B, dendrohyphidia, hyphidia and thin to thick-walled hyphae; C, thick-walled basidiospores; D, part of indistinct subiculum below subhymenial layer; E, section through hymenium and subhymenium. Scale bars: 10 µm.
FIG. 22 in Fungal biodiversity profiles 111-120
FIG. 22. — Russula ferruginea subsp. panamensis Corrales & Manz, subsp. nov. (ARIZ Corrales 99, holotype). Elements of the pileipellis drawn as seen by light microscopy. A, pileocystidia near the margin of the pileus; B, pileocystidia near the center of the pileus; C, hyphal terminations near the margin of the pileus; D, hyphal terminations near the center of the pileus. Cystidia with contents as observed in Congo Red. Scale bar: 10 μm. Drawings by Michelle Vera.
FIG. 16 in Fungal biodiversity profiles 111-120
FIG. 16. — Basidiomata of Russula ferruginea Corrales & Vera, sp. nov. A, basidiomata of Russula ferruginea subsp. ferruginea Corrales & Vera, subsp. nov. in the field (HUA Corrales935); B, C, basidiomata of Russula ferruginea subsp. panamensis Corrales & Vera, subsp. nov. in the field (ARIZ Corrales099); D, basidiomata of Russula ferruginea subsp. panamensis Corrales & Vera, subsp. nov. (UCH Anna Giessel A28). Scale bars: 1 cm.
IODP Expedition 354 Laser height profile (section half)
<p>Height profile data were measured on the Section Half Multisensor Logger (SHMSL) by a rangefinding laser and recorded in uncorrected height units in millimeters in CSV files.</p>
Peripheral T-cell profiling reveals downregulated exhaustion marker and increased diversity in lymphedema post-lymphatic venous anastomosis
<p>In this study, we compared T cell receptor (TCR) repertoire diversity between patients with lymphedema, post-lymphatic venous anastomosis and healthy controls (HCs). TCR diversity was decreased in lymphedema compared with HCs; such TCR skewing was drastically improved in post-LVA.</p>
Integrated single-cell profiling dissects cell-state-specific enhancer landscapes of human tumor-infiltrating CD8+ T cells_Supplemental_Data
<p>Processed Datasets for:</p> <p>EGA Study ID: EGAS00001006141</p> <p>EGA Dataset ID: EGAD00001008662</p> <p> </p> <p>Find processed files and arrow files</p> <p> </p> <p>Abstract:</p> <p>Despite extensive studies on the chromatin landscape of exhausted T cells, the transcriptional wiring underlying the heterogeneous functional and dysfunctional states of human tumor-infiltrating lymphocytes (TILs) is incompletely understood. Here, we identify gene-regulatory landscapes in a wide breadth of functional and dysfunctional CD8<sup>+</sup> TIL states covering four cancer entities using single-cell chromatin profiling. We map enhancer-promoter interactions in human TILs by integrating single-cell chromatin accessibility with single-cell RNA-seq data from tumor-entity-matching samples and prioritize cell-state-specific genes by super-enhancer analysis. Besides revealing entity-specific chromatin remodeling in exhausted TILs, our analyses identify a common chromatin trajectory to TIL dysfunction and determine key enhancers, transcriptional regulators, and deregulated genes involved in this process. Finally, we validate enhancer regulation at immunotherapeutically relevant loci by targeting non-coding regulatory elements with potent CRISPR activators and repressors. In summary, our study provides a framework for understanding and manipulating cell-state-specific gene-regulatory cues from human tumor-infiltrating lymphocytes.</p>
TEAMx-PC22 (TEAMx pre-campaign 2022) – Vertical profiles and Multi-Point In-Situ Measurements at Nafingalm collected with the SWUF-3D UAS fleet
<p>This dataset contains aggregated measurements from a fleet of multicopter UAS. The data was measured during the period 21 June 2022 through 27 June 2022 at Nafingalm, Austria with the SWUF-3D fleet. The data was collected in association to the TEAMx-PC22 field campaign. A maximum of three UAS were operated simultaneously. Processed level-2 data is provided. For level-2 data, time synchronization between individual UAS was done through interpolation, if multiple UAS are operated simultaneously.</p> <p>In this dataset vertical profiles (swuf3dvpro) between 10m and 120m above ground level and time series of UAS hovering for approx. 10 minutes at fixed positions (swuf3dhover) are provided with a temporal resolution of 1 Hz.</p> <p>The data are provided in NetCDF format with metadata and variable descriptions in the style of the SAMD Product standard: Jahnke-Bornemann, Annika. (2022, August 18). The SAMD Product Standard (Standardized Atmospheric Measurement Data) (Version 2.2). http://doi.org/10.25592/uhhfdm.10416</p>
CNETML: maximum likelihood inference of phylogeny from copy number profiles of multiple samples
<p>This folder includes simulated and real data used in validating CNETML, a new maximum likelihood method designed to reconstruct the evolutionary history of multiple samples of a single patient which may be taken at different locations and/or times, which can take as input (relative) total integer copy numbers called from shallow whole genome sequencing data.</p>
IODP Expedition 369 Laser height profile (section half)
<p>Height profile data were measured on the Section Half Multisensor Logger (SHMSL) by a rangefinding laser and recorded in uncorrected height units in millimeters in CSV files.</p>
Renewable Generation Profiles and Weather Correlated Loads Used in CEC EPC-19-056 Final Report
<p>This repository contains 8760 hour time series data for load and renewable generation utilized in the <br> CEC EPC-19-056 Final Report: Assessing the Value of LDES in California. The details of how these profiles were constructed can be found in Appendix B of the report.</p> <p>The load balancing authorities and renewable resources modeled in this study are consistent with those found in the 2019-20 CPUC IRP Inputs and Assumptions, which can be found here: https://www.cpuc.ca.gov/-/media/cpuc-website/divisions/energy-division/documents/integrated-resource-plan-and-long-term-procurement-plan-irp-ltpp/2019-2020-irp-events-and-materials/inputs--assumptions-2019-2020-cpuc-irp_20191106.pdf</p>
Supplementary materials for: Multiple ruptures on the North Sofia fault at Gorni Bogrov from scarp profile and shallow geophysics
<p>The data set contains resistivity data of two profiles that were measured at Gorno Bogrov site in the Sofia basin in Bulgaria. The resistivity survey was performed to study the North Sofia fault.</p> <p>The resistivity data in files r1ohm.tx and r2ohm.txt should be inverted using the BERT software (http://resistivity.net/) with configuration files r1cfg.txt and r2icfg.txt, respectively. The file bog2.txt contains fault coordinates for constraining the inversion mesh of the shorter profile (files r2ohm.txt, r2icfg.txt).</p> <p>The data set was collected within the project Assessment of Earthquake Ground Motion Amplification in the Sofia Basin (<a href="http://sofiabasin.atwebpages.com/">http://sofiabasin.atwebpages.com/</a>), funded by the Bulgarian National Science Fund, contract number KP-06-N64/1 from 15.12.2022.</p>
ScienceDex guides
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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.