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SUPPLEMENTARY TABLE 3 in Importance of genetic data in resolving cryptic species: A century old problem of understanding the distribution of Minervarya syhadrensis Annandale 1919 (Anura: Dicroglossidae)
SUPPLEMENTARY TABLE 3. (Continued)
SUPPLEMENTARY TABLE 3 in Importance of genetic data in resolving cryptic species: A century old problem of understanding the distribution of Minervarya syhadrensis Annandale 1919 (Anura: Dicroglossidae)
SUPPLEMENTARY TABLE 3. (Continued)
SUPPLEMENTARY TABLE 3 in Importance of genetic data in resolving cryptic species: A century old problem of understanding the distribution of Minervarya syhadrensis Annandale 1919 (Anura: Dicroglossidae)
SUPPLEMENTARY TABLE 3. (Continued)
SUPPLEMENTARY TABLE 3 in Importance of genetic data in resolving cryptic species: A century old problem of understanding the distribution of Minervarya syhadrensis Annandale 1919 (Anura: Dicroglossidae)
SUPPLEMENTARY TABLE 3. (Continued)
SUPPLEMENTARY TABLE 3 in Importance of genetic data in resolving cryptic species: A century old problem of understanding the distribution of Minervarya syhadrensis Annandale 1919 (Anura: Dicroglossidae)
SUPPLEMENTARY TABLE 3. (Continued)
SUPPLEMENTARY TABLE 3 in Importance of genetic data in resolving cryptic species: A century old problem of understanding the distribution of Minervarya syhadrensis Annandale 1919 (Anura: Dicroglossidae)
SUPPLEMENTARY TABLE 3. (Continued)
SUPPLEMENTARY TABLE 3 in Importance of genetic data in resolving cryptic species: A century old problem of understanding the distribution of Minervarya syhadrensis Annandale 1919 (Anura: Dicroglossidae)
SUPPLEMENTARY TABLE 3. (Continued)
SUPPLEMENTARY TABLE 3 in Importance of genetic data in resolving cryptic species: A century old problem of understanding the distribution of Minervarya syhadrensis Annandale 1919 (Anura: Dicroglossidae)
SUPPLEMENTARY TABLE 3. (Continued)
SUPPLEMENTARY TABLE 3 in Importance of genetic data in resolving cryptic species: A century old problem of understanding the distribution of Minervarya syhadrensis Annandale 1919 (Anura: Dicroglossidae)
SUPPLEMENTARY TABLE 3. (Continued)
Data from: Contemporary climate-driven range shifts: putting evolution back on the table
As the climate continues to change, species are moving to track their historical niches. Although we are gaining a clearer picture of where and how quickly species ranges are moving, a mechanistic understanding of these changes is still nascent. Evolutionary changes in ranges and range-limiting traits over contemporary timescales has received relatively little attention, possibly due to the mismatch in scale between rapid contemporary range shifts and the historical evolution of species ranges over millions of years. But recent experimental work has shown that range-limiting traits can evolve rapidly over decadal timescales, effectively putting evolution back on the table towards the goal of a mechanistic understanding of contemporary range shifts. Here I review the role of evolution in shaping range shift responses to recent climate change from the perspective of the past (shared evolutionary history, or phylogenetic signal in range shifts and range-limiting traits), present (variation in range-limiting traits), and future (incorporating evolution of range-limiting traits into range forecasts from species distribution models). In each of these areas, I found a critical role for evolution in understanding historical constraints and future changes in species ranges over contemporary timescales: shared evolutionary history may constrain range shift responses for some taxa; compensatory mechanisms of phenotypic plasticity and adaptive evolution can modulate the range shift response; and incorporating evolution into species distribution models can qualitatively alter forecasts of future range shifts. Yet, more can be done in this context, and so I conclude by outlining near- and long-term goals for improving our understanding of the role of evolution in shaping species ranges in a rapidly changing world.
Supplemental figures and tables of a European multicenter validation study of the External Genitalia Score
<p><b>Context: </b>Standardized description of external genitalia is needed in the assessment of children with atypical genitalia.</p> <p><b>Objectives:<i> </i></b>To validate the External Genitalia Score (EGS), to present reference values for preterm and term babies up to 24 months and correlate obtained scores with anogenital distances (AGDs).</p> <p><b>Design, Setting: </b>A<b> </b>European multicentre (n=8) validation study was conducted from 07/2016 until 07/2018.</p> <p><b>Patients and Methods: </b>EGS is based on the external masculinization score but uses a gradual scale from female to male (range 0-12) and terminology appropriate for both sexes. The reliability of EGS and AGD's were determined by the interclass correlation coefficient (ICC). Cross-sectional data were obtained in 686 term (0-24 months), and 181 preterm babies and 111 babies with atypical genitalia.</p> <p><b>Results:<i> </i></b>ICC of EGS in typical and atypical genitalia is excellent and good. Median EGS (10<sup>th </sup>-<sup> </sup>90<sup>th </sup>centile) in males < 28 weeks gestation is 10 (8.6-11.5); in males 28-32 weeks 11.5 (9.2-12); in males 33-36 weeks 11.5 (10.5-12) and in full-term males 12 (10.5-12). In all female babies, EGS is 0 (0-0). The mean (SD) AGDl/u is 0.45 (0.1), with significant difference between AGDl/u in males 0.49 (0.1) and females 0.39 (0.1) and in-between values in DSD 0.43 (0.1). AGDl/u correlates with EGS in males with typical genitalia and in atypical genitalia.</p> <p><b>Conclusions: </b>EGS is a reliable and valid tool to describe external genitalia in premature and term babies up to 24 months. EGS correlates with AGDl/u in males. It facilitates standardized assessment, clinical decision-making and multicenter research.</p>
Fecal calprotectin as a predictor of gastrointestinal immune-related adverse events (CF-19): A prospective study - Excel data and supplementary tables
<p class="cuerpo"><b>Background: </b>Colitis is a frequent immune-related toxicity, without any biomarker that may predict its onset. It is endoscopically similar to intestinal inflammatory diseases, where fecal calprotectin (FC) is used as a biomarker to early-detect a relapse. We found contradictory evidence about FC and immunotherapy and no prospective study was already published. </p> <p class="cuerpo"><b>Methods:</b> We present an analytical, observational and prospective study of one year's duration. We analyzed FCbasal, and then prior to each cycle until the sixth, ending with quarterly follow-up. For evaluating the predictive value of FC we estimated the area under the ROC curve for basal absolute values and for each cycle, and calculated its relative percentage change with respect to basal. We also planned to estimate sensitivity, specificity and predictive values indexes for different cut-off points. Because of lack of recruitment we did a preliminary analysis at the end of the initially estimated period before suggesting its prolongation. </p> <p class="cuerpo"><b>Results:</b> 24 patients were included (19 male), diagnosed from lung cancer (n=15), head and neck, renal, bladder and colorectal cancer (n=2, each), melanoma (n=1). They were treated with Anti PD-1/PDL-1 mono therapy (n=18), combo with chemo (n=2), or combo with anti-CTLA4 (n=2). Three patients had G1 colitis and two, >=G2, all treated with anti-PD1 and before 6th cycle, as described on literature. ROC curve presents AUC 0,559 (CI95%:0,32-0,798) and RR for colitis taking FC value is 1,001 for each 10 units (p=0,493).</p> <p class="cuerpo"><b>Conclusion:</b> Even though we must take into account the limitations of the study we cannot conclude that FC could be used as a predictor for detecting immune-mediated colitis. </p>
Decorative Relief Marble Table
Decorative Relief. Rablerine Table Source: Objaverse 1.0 / Sketchfab
Table S1: Wheat curl mite collection data
<p>Table S1. Plant samples list with information on WCM presence and WSMV infection.</p> <p> </p> <p>Tabela S1. Wykaz prób roślinnych sprawdzonych pod kątem obecności WCM i infekcji WSMV.</p>
Table S1
<p>Supplementary table with clinical and analytical parameters</p>
Data for Table 1 and Figure 2
<p>Data for Table 1 and Figure 2.</p>
Impacts Summary Table
<p>This table summarizes the impacts calculated for "Estimating Economic Damage from Climate Change in the United States". Each sheet describes a separate impact. Within that sheet, the results are broken up into columns for aggregated to each region, with weights determined by the second column (and generally specific to each sector), and time periods. Within each period, the 5%, 17%, 50%, 83% and 95% quantiles are reported.</p> <p>The regions reported are the national average result, a result for each NCA region, and a result for each state.</p> <p>Each sheet has 4 tables, one for each RCP, starting with RCP 8.5 at the top, and ending with RCP 2.6 at the bottom.</p>
Colonization history of the Western Corn Rootworm: Dataset, ABC reference tables and ABC parameter files
<p>This data archive is associated with the article “Colonization history of the Western Corn Rootworm (<em>Diabrotica virgifera virgifera</em>) in North America: insights from random forest ABC using microsatellite data”. Authors: Eric Lombaert, Marc Ciosi, Nicholas J. Miller, Thomas W. Sappington, Aurélie Blin & Thomas Guillemaud.</p> <p>The zip files contains the microsatellite dataset, the parameter files and scripts for simulating and summarizing datasets, the ABC reference tables, and the R scripts for analyzing the data. See the Readme file for details.</p>
supplementary tables for physical activity and sedentary behavior on gut microbiota.
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Dataset to reproduce the figures and table in "An Outsized Role for the Labrador Sea in the Multidecadal Variability of the Atlantic Overturning Circulation" in Science Advances
Climate models are essential tools for investigating intrinsic North Atlantic variability related to variations in the Atlantic meridional overturning circulation (AMOC), but recent observations have called into question the fidelity of models that emphasize the importance of Labrador Sea processes. A multi-century pre-industrial climate simulation that resolves ocean mesoscale eddies has a realistic representation of key observed subpolar Atlantic phenomena, including the dominance of density-space overturning in the eastern subpolar gyre, and thus provides uniquely credible context for interpreting short observational records. Despite weak mean surface diapycnal transformation in the Labrador Sea, multidecadal AMOC variability can be traced to anomalous production of dense Labrador Sea Water with local buoyancy forcing in the interior Labrador Sea playing a significant driving role. The files included here are the post-processed model output fields and associated codes needed to reproduce the figures and table in Yeager et al., 2021, An Outsized Role for the Labrador Sea in the Multidecadal Variability of the Atlantic Overturning Circulation, doi:10.31223/X5ZP68.
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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.