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Data set: Burn severity and soil chemistry are weak drivers of early vegetation succession following a boreal mega-fire in a production forest landscape
<p>Data used in the analyses of the study. Data set on soil chemistry (pH, organic content, nutrient content), plots distance to the fire perimeter, and plant communities (vascular plants and bryophytes) recorded in permanent plots on clearcuts in a burn-severity gradient two and five years following a wildfire. Data collected from a 13000 hectare wildfire that occurred in 2014, in boreal southern Sweden. Calculated trait means from data bases, and plant community data from unburned plots from another study, are are also included here.</p>
Data from: Severe childhood speech disorder: Gene discovery highlights transcriptional dysregulation
<p><b><span>Objective:</span></b><span> Determining the genetic basis of speech disorders provides insight into the neurobiology of human communication. Despite intensive investigation over the past two decades, the etiology of most children with speech disorder remains unexplained. Here we </span>searched for a genetic etiology in children with severe speech disorder, specifically childhood apraxia of speech (CAS).</p> <p><b>Methods:</b> Precise phenotyping together with research genome or exome analysis were performed on children referred with a primary diagnosis of CAS, as well as other medical or neurodevelopmental co-morbidities. Gene co-expression and gene set enrichment analyses analyses were conducted on high confidence gene candidates.</p> <p><b>Results:</b> 34 probands ascertained for CAS were studied. In 11/34 (32%) probands, we identified highly plausible pathogenic single nucleotide (n=10, <i>CDK13, EBF3, GNAO1, GNB1, DDX3X, MEIS2, POGZ, SETBP1, UPF2, ZNF142</i>) or copy number (n = 1, 5q14.3q21.1 locus) variants in novel genes or loci for CAS. Testing of parental DNA was available for nine probands and confirmed that the variants had arisen <i>de novo</i>. Eight genes encode proteins critical for regulation of gene transcription, and analyses of transcriptomic data found CAS-implicated genes were highly co-expressed in the developing human brain.</p> <p><b>Conclusion:</b><i> </i>We identify the likely genetic aetiology in 11 patients with CAS and implicate 9 genes for the first time. We find that CAS is often a sporadic monogenic disorder, and highly genetically heterogeneous. Highly penetrant variants implicate shared pathways in broad transcriptional regulation, highlighting the key role of transcriptional regulation in normal speech development. CAS is a distinctive, socially debilitating clinical disorder, and understanding its molecular basis is the first step towards identifying precision medicine approaches.</p>
MOSEV: A global burn severity database from MODIS (2000-2020)
<p>To advance in the fire discipline as well as in the study of CO<sub>2</sub> emissions it is of great interest to develop a global database with estimators of the degree of biomass consumed by fire, which is defined as burn severity. We present the first global burn severity database (MOSEV database), which is based on Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance and burned area (BA) products scenes since November 2000 to near real time. To build the database we combined Terra MOD09A1 and Aqua MYD09A1 surface reflectance products to obtain dense time series of the Normalized Burn Ratio (NBR) spectral index, and we used the MCD64A1 product to identify BA and the date of burning. Then, we calculated for each burned pixel the difference of the NBR (dNBR), and its relativized version (RdNBR), as well as the post-burn NBR which are the most commonly used burn severity spectral indices. The database also includes the pre-burn NBR used for calculations, the date of the pre- and post-burn NBR and the date of burning.</p>
Bits x la Marató: Looking for similar patients: the AI Doctor House conquers severe COVID-19!
<p>Clinical case reports for the task Looking for similar patients: the AI Doctor House conquers severe COVID-19! at the event Bits x la Marató: https://www.fib.upc.edu/en/la-marato</p> <p> </p> <p>There is a pressing need by healthcare professionals to access information relevant to clinical practice in a more effective way. Over 80% of clinically relevant data is essentially unstructured, mainly images like MRI and clinical texts.</p> <p>One of the challenges faced by doctors is finding patients and clinical cases that show particular similarities to a given case (similar symptoms, diagnosis, treatments, or other characteristics) amongst the rapidly growing amount of clinical records and medical publications and the complexity of the data. Detection of similarities among patients or groups of patients is key for evidence-based clinical practice, the selection of patients for clinical trials, prioritizing patients for vaccination and for understanding the variability in clinical outcomes.</p> <p>From a COVID-19 point of view, AI tools should distinguish between patients with and with no risk of a severe outcome, so that clinicians could intervene promptly. <strong>Specifically, this task aims to promote the development of systems able to detect similarities among a collection of clinical case texts.</strong></p> <p> </p> <p><strong>Technology point of view:</strong></p> <p>The objective is to be able to compute and measure similarity between patients represented by their clinical case, that is, the text describing their medical condition, previous morbidities, medical tests and treatments performed, diagnosis or outcome. This very complex scenario can in principle be approached by a diversity of methodologies ranging from text similarity techniques used to detect plagiarism, clinical concept detection, or even more advanced semantic textual similarity strategies dealing with the meaning of natural language through AI.</p> <p> </p> <p><strong>Healthcare point of view:</strong></p> <p>Access to medically relevant information hidden in clinical texts is one of the principal challenges for healthcare professionals in the AI digital age. Questions such as which are the symptoms of patients with a worse outcome, given similar comorbidities, medications or procedures are very difficult to answer without systematically processing clinical texts. Even simpler, epidemiological questions like how many days have passed before COVID-19 symptoms started or if patients had travelled to certain geographical areas can only be answered efficiently by means of computational tools. Similarities between patients can aid prognosis, diagnosis and decision making, saving vital time to healthcare practitioners.</p> <p> </p> <p>If you need some help, <a href="https://medium.com/@adriensieg/text-similarities-da019229c894">here</a> is a helpful resource that will help you get started.</p> <p> </p> <p><a href="https://www.youtube.com/playlist?list=PL5uSCzf1azhBeVCHyswazImBNpIW8gYTD">YouTube playlist with our session at BITSXLAMARATÓ</a></p>
Supplementary material 2 from: Stampar SN, Gamero-Mora E, Maronna MM, Fritscher JM, Oliveira BSP, Sampaio CLS, Morandini AC (2020) The puzzling occurrence of the upside-down jellyfish Cassiopea (Cnidaria: Scyphozoa) along the Brazilian coast: a result of several invasion events? Zoologia 37: 1-10. https://doi.org/10.3897/zoologia.37.e50834
Table S1. Genetic distance matrix over sequence pairs within Cassiopea andromeda. Values shown below diagonal are uncorrected pairwise distances. Above the diagonal are the number of bases that are not identical. 1. Cassiopea_Alagoas_1; 2. Cassiopea_Alagoas_2; 3. Cassiopea_Alagoas_3; 4. Cassiopea_Alagoas_4; 5. CandroHaw8; 6. CandroHaw10; 7. CandroHaw7; 8. CandroHaw9; 9. CandroHaw1; 10. CandroEgyRSea; 11. Cbrazil; 12. CxamaBerm3 13. CxamaBerm4 14. CandroHaw4 15. CxamaBerm1 16. CandroHaw5 17. CxamaBerm2 18. CxamaUSAFl1.
Supplementary material 1 from: Stampar SN, Gamero-Mora E, Maronna MM, Fritscher JM, Oliveira BSP, Sampaio CLS, Morandini AC (2020) The puzzling occurrence of the upside-down jellyfish Cassiopea (Cnidaria: Scyphozoa) along the Brazilian coast: a result of several invasion events? Zoologia 37: 1-10. https://doi.org/10.3897/zoologia.37.e50834
Figure S1. Map showing the collection localities of Cassiopea sequences used in the phylogenetic analysis. The green square refers to the site of collection of the population of C. andromeda from Alagoas, Brazil. Each color indicates a species. Cassiopea sp. 5 does not appear because of its unknown locality.
FIGURE 2. Carineta trinidadensis n in The cicadas (Hemiptera: Cicadidae) of Trinidad and Tobago including the description of three new species and seven new records, with new records for several additional Caribbean Islands
FIGURE 2. Carineta trinidadensis n. sp.: A, holotype male and paratype female habitus; B, holotype male dorsum; C, holotype male timbal; D, holotype male operculum; E, paratype female operculum; F, holotype male lateral view of genitalia; G, holotype male posterior view of genitalia; H, paratype female lateral view of genitalia; I, paratype female ventral view of genitalia. Scale bar: A, 2 cm; B, 5 mm; C–E, 2 mm; F–G, 1 mm; H–I, 2 mm.
FIGURE 1. Calyria hyperochelabrys n in The cicadas (Hemiptera: Cicadidae) of Trinidad and Tobago including the description of three new species and seven new records, with new records for several additional Caribbean Islands
FIGURE 1. Calyria hyperochelabrys n. sp.: A, holotype male habitus; B, holotype male dorsum; C, holotype male timbal; D, holotype male operculum; E, holotype male lateral view of genitalia; F, holotype male posterior view of genitalia. Scale bar: A, 2 cm; B, 2 mm; C–F, 1 mm.
FIGURE 3. Herrera grammosticta n in The cicadas (Hemiptera: Cicadidae) of Trinidad and Tobago including the description of three new species and seven new records, with new records for several additional Caribbean Islands
FIGURE 3. Herrera grammosticta n. sp.: A, holotype male and paratype female habitus; B, holotype male dorsum; C, holotype male timbal; D, holotype male operculum; E, paratype female operculum; F, holotype male lateral view of genitalia; G, holotype male posterior view of genitalia; H, paratype female lateral view of genitalia; I, paratype female ventral view of genitalia. Scale bar: A, 2 cm; B, 5 mm; C, 1 mm; D–E, 2 mm; F–G, 1 mm; H–I, 2 mm.
Increased sCD163 and sCD14 plasmatic levels and depletion of peripheral blood pro-inflammatory monocytes, myeloid and plasmacytoid dendritic cells in patients with severe COVID-19 pneumonia
<p><strong>Background: </strong>Emerging evidence argues that monocytes, circulating innate immune cells, are principal players in COVID-19 pneumonia. The study aimed to investigate the role of soluble (s)CD163 and sCD14 plasmatic levels in predicting disease severity and characterize peripheral blood monocytes and dendritic cells (DCs), in patients with COVID-19 pneumonia (COVID-19 subjects). </p> <p><strong>Methods:</strong> On admission, in COVID-19 subjects sCD163 and sCD14 plasmatic levels, and peripheral blood monocyte and DC subsets were compared to healthy donors (HDs). According to clinical outcome, COVID-19 subjects were divided into ARDS and non-ARDS groups. </p> <p><strong>Results:</strong> Compared to HDs, COVID-19 subjects showed higher sCD163 (p<0.0001) and sCD14 (p<0.0001) plasmatic levels. We observed higher sCD163 plasmatic levels in the ARDS group compared to the non-ARDS one (p=0.002). The cut-off for sCD163 plasmatic level greater than 2032 ng/ml was predictive of disease severity (AUC: 0.6786, p=0.0022; sensitivity 56.7% [CI: 44.1-68.4] specificity 73.8% [CI: 58.9-84.7]). Positive correlation between plasmatic levels of sCD163, LDH and IL-6 and between plasmatic levels of sCD14, D-dimer and ferritin were found. Compared to HDs, COVID-19 subjects showed lower percentages of non-classical (p=0.0012) and intermediate monocytes (p=0.0447), slanDCs (p<0.0001), myeloid DCs (mDCs, p<0.0001) and plasmacytoid DCs (pDCs, p=0.0014). Compared to the non-ARDS group, the ARDS group showed lower percentages of non-classical monocytes (p=0.0006), mDCs (p=0.0346) and pDCs (p=0.0492). </p> <p><strong>Conclusions:</strong> The increase in sCD163 and sCD14 plasmatic levels, observed on hospital admission in COVID-19 subjects, especially in those who developed ARDS, and the correlations of these monocyte/macrophage activation markers with typical inflammatory markers of COVID-19 pneumonia, underline their potential use to assess the risk of progression of the disease. In an early stage of the disease, the assessment of sCD163 plasmatic levels could have clinical utility in predicting the severity of COVID-19 pneumonia. </p>
FIGURES 96–103 in Review of the genus Meganola Dyar, 1898 of Ivory Coast and adjacent areas with descriptions of 5 new species and several taxonomic updates (Lepidoptera Nolidae, Nolinae)-Taxonomic studies on West African Nolinae I.
FIGURES 96–103: female genitalia (all in coll. ANHRT unless otherwise indicated). 96, Meganola fontainei, Zambia, LGNA 3; 97, M. xantholeuca, Liberia, LGNA 977; 98, M. rhyssomorpha, Ivory Coast, LGNA 984; 99, M. mesothermoides, holotype, Ghana, NHMUK010315152 (prep. by Gy.M. László) (NHMUK); 100, M. spermophaga, Sierra Leone, LGNA 462; 101, M. pyrrhomorpha, Ivory Coast, LGNA 145; 102, M. canocolorata, Ivory Coast, LGNA 981; 103, M. foviferoides, Zambia, LGNA 37.
FIGURES 88–95 in Review of the genus Meganola Dyar, 1898 of Ivory Coast and adjacent areas with descriptions of 5 new species and several taxonomic updates (Lepidoptera Nolidae, Nolinae)-Taxonomic studies on West African Nolinae I.
FIGURES 88–95: female genitalia (all in coll. ANHRT unless otherwise indicated). 88, Meganola smithi sp. n., paratype, Liberia, LGNA 523; 89, M. endoscota, holotype, Ghana, NHMUK010315151 (prep. by Gy.M. László) (NHMUK); 90, M. microfascia, Ivory Coast, LGNA 418; 91, M. mesonephele, Ivory Coast, LGNA 151; 92, M. lucia, Ivory Coast, LGNA 420; 93, M. palaeographa, Ivory Coast, LGNA 24; 94, M. dananae, Guinea, LGNA 988; 95, M. taiana sp. n., paratype, Ivory Coast, LGNA 983.
FIGURES 84–87 in Review of the genus Meganola Dyar, 1898 of Ivory Coast and adjacent areas with descriptions of 5 new species and several taxonomic updates (Lepidoptera Nolidae, Nolinae)-Taxonomic studies on West African Nolinae I.
FIGURES 84–87: male genitalia (all in coll. ANHRT). 84, Meganola leucosigna, Ivory Coast, LGNA 263; 85, M. hackeri sp. n., holotype, Ivory Coast, LGNA 239; 86, M. ronkayiana, Ivory Coast, LGNA 225; 87, M. illaudata, Ivory Coast, LGNA 224.
FIGURES 57–65 in Review of the genus Meganola Dyar, 1898 of Ivory Coast and adjacent areas with descriptions of 5 new species and several taxonomic updates (Lepidoptera Nolidae, Nolinae)-Taxonomic studies on West African Nolinae I.
FIGURES 57–65: male genitalia (all in coll. ANHRT unless otherwise indicated). 57, Meganola smithi sp. n., holotype, Ivory Coast, LGNA 242; 58, M. endoscota, Liberia, LGNA 970; 59, M. microfascia, Ivory Coast, LGNA 250; 60, M. mesonephele, Ivory Coast, LGNA 149; 61, M. lucia, Ivory Coast, LGNA 472; 62, M. palaeographa, Ivory Coast, LGNA 235; 63, M. monofascia, Ivory Coast, LGNA 237; 64, M. monofascia, Cameroon, LGNA 568; 65, M. monofascia, Zambia, LGNA 103.
FIGURES 1–20 in Review of the genus Meganola Dyar, 1898 of Ivory Coast and adjacent areas with descriptions of 5 new species and several taxonomic updates (Lepidoptera Nolidae, Nolinae)-Taxonomic studies on West African Nolinae I.
FIGURES 1–20: adults (all in coll. ANHRT unless otherwise indicated). 1, Meganola smithi sp. n., holotype, ♂, Ivory Coast; 2, M. smithi sp. n., paratype, ♂, Liberia; 3, M. smithi sp. n., paratype, ♀, Liberia; 4, M. endoscota, holotype, ♀, Ghana (NHMUK); 5, M. endoscota, ♂, Liberia; 6, M. endoscota, ♂, Guinea; 7, M. endoscota, ♂, Cameroon; 8, M. microfascia, ♂, Ivory Coast; 9, M. microfascia, ♀, Ivory Coast; 10, M. mesonephele, ♀, Ivory Coast; 11, M. lucia, ♂, Ivory Coast; 12, M. lucia, ♂, Cameroon; 13, M. lucia, ♀, Ivory Coast; 14, M. palaeographa, ♂, Ivory Coast; 15, M. palaeographa, ♀, Ivory Coast; 16, M. monofascia, ♂, Ivory Coast; 17, M. monofascia, ♂, Cameroon; 18, M. monofascia, ♀, Liberia; 19, M. dananae, ♂, Guinea; 20, M. dananae, ♀, Guinea.
FIGURES 75–83 in Review of the genus Meganola Dyar, 1898 of Ivory Coast and adjacent areas with descriptions of 5 new species and several taxonomic updates (Lepidoptera Nolidae, Nolinae)-Taxonomic studies on West African Nolinae I.
FIGURES 75–83: male genitalia (all in coll. ANHRT unless otherwise indicated). 75, Meganola chionea, holotype, Nigeria, BM Arct. 6467 (prep. by Gy. M. László) (NHMUK); 76, M. subchionea sp. n., holotype, Ivory Coast, LGNA 139; 77, M. cinereoparva sp. n., holotype, Ivory Coast, LGNA 397; 78, M. cinereoparva sp. n., paratype, Ivory Coast, LGNA 137; 79, M. mesothermoides, Liberia, LGNA 502; 80, M. spermophaga, Liberia, LGNA 547; 81, M. pyrrhomorpha, Ivory Coast, LGNA 565; 82, M. foviferoides, Togo, LGNA 597; 83, M. foviferoides, Zambia, LGNA 17.
FIGURES 41–56 in Review of the genus Meganola Dyar, 1898 of Ivory Coast and adjacent areas with descriptions of 5 new species and several taxonomic updates (Lepidoptera Nolidae, Nolinae)-Taxonomic studies on West African Nolinae I.
FIGURES 41–56: adults (all in coll. ANHRT). 41, Meganola pyrrhomorpha, ♂, Ivory Coast; 42, M. pyrrhomorpha, ♀, Ivory Coast; 43, M. canocolorata ♀, Ivory Coast; 44, M. foviferoides ♂, Togo; 45, M. foviferoides ♀, Zambia; 46, M. leucosigna, ♂, Ivory Coast; 47, M. leucosigna, ♀, Ivory Coast; 48, M. hackeri sp. n., holotype, ♂, Ivory Coast; 49, M. hackeri sp. n., paratype, ♂, Ivory Coast; 50, M. ronkayiana, ♂, Ivory Coast; 51, M. ronkayiana, ♂, Liberia; 52, M. pyrrhosoma, ♀, Ivory Coast; 53, M. pyrrhosoma, ♀, Liberia; 54, M. illaudata, ♂, Ivory Coast; 55, M. illaudata, ♂, Liberia; 56, M. illaudata, ♀, Liberia.
FIGURES 21–40 in Review of the genus Meganola Dyar, 1898 of Ivory Coast and adjacent areas with descriptions of 5 new species and several taxonomic updates (Lepidoptera Nolidae, Nolinae)-Taxonomic studies on West African Nolinae I.
FIGURES 21–40: adults (all in coll. ANHRT unless otherwise indicated). 21, Meganola furvitincta, lectotype, ♂, Sierra Leone (NHMUK); 22, M. furvitincta, ♂, Liberia; 23, M. aarviki, ♂, Ivory Coast; 24, M. spherographa, ♂, Ivory Coast; 25, M. spherographa, ♀, Liberia; 26, M. taiana sp. n., holotype, ♂, Ivory Coast; 27, M. taiana sp. n., paratype, ♂, Liberia; 28, M. taiana sp. n., paratype, ♀, Ivory Coast; 29, M. xantholeuca, ♀, Ivory Coast; 30, M. xantholeuca, ♀, Liberia; 31, M. rhyssomorpha, ♂, Ivory Coast; 32, M. rhyssomorpha, ♀, Ivory Coast; 33, M. chionea, holotype, ♂, Nigeria (NHMUK); 34, M. subchionea sp. n., holotype, ♂, Ivory Coast; 35, M. cinereoparva sp. n., holotype, ♂, Ivory Coast; 36, M. cinereoparva sp. n., paratype, ♂, Ivory Coast; 37, M. mesothermoides, holotype, ♀, Ghana (NHMUK); 38, M. mesothermoides, ♂, Liberia; 39, M. spermophaga, ♂, Liberia; 40, M. spermophaga, ♀, Sierra Leone.
FIGURES 66–74 in Review of the genus Meganola Dyar, 1898 of Ivory Coast and adjacent areas with descriptions of 5 new species and several taxonomic updates (Lepidoptera Nolidae, Nolinae)-Taxonomic studies on West African Nolinae I.
FIGURES 66–74: male genitalia (all in coll. ANHRT unless otherwise indicated). 66, Meganola dananae, Guinea, LGNA 975; 67, M. furvitincta, lectotype, Sierra Leone, BM Arct. 6469 (prep. by Gy. M. László) (NHMUK); 68, M. furvitincta, Liberia, LGNA 491; 69, M. aarviki, Ivory Coast, LGNA 980; 70, M. spherographa, Ivory Coast, LGNA 228; 71, M. taiana sp. n., holotype, Ivory Coast, LGNA 142; 72, M. taiana sp. n., paratype, Liberia, LGNA 487; 73, M. fontainei, Zambia, LGNA 1; 74, M. rhyssomorpha, Ivory Coast, LGNA 233.
Data from: Natural resistance to worms exacerbates bovine tuberculosis severity independently of worm coinfection
<p class="CxSpFirst">Pathogen interactions arising during coinfection can exacerbate disease severity, for example, when the immune response mounted against one pathogen negatively affects defense of another. It is also possible that host immune responses to a pathogen, shaped by historical evolutionary interactions between host and pathogen, may modify host immune defenses in ways that have repercussions for other pathogens. In this case, negative interactions between two pathogens could emerge even in the absence of concurrent infection. Parasitic worms and tuberculosis (TB) are involved in one of the most geographically extensive of pathogen interactions, and during coinfection, worms can exacerbate TB disease outcomes. Here, we show that in a wild mammal, natural resistance to worms affects bovine tuberculosis (BTB) severity independently of active worm infection. We found that worm-resistant individuals were more likely to die of BTB than were non-resistant individuals, and their disease progressed more quickly. Anthelmintic treatment moderated, but did not eliminate, the resistance effect, and the effects of resistance and treatment were opposite and additive with untreated, resistant individuals experiencing the highest mortality. Furthermore, resistance and anthelmintic treatment had non-overlapping effects on BTB pathology. The effects of resistance manifested in the lungs (the primary site of BTB infection), while the effects of treatment manifested almost entirely in the lymph nodes (the site of disseminated disease), suggesting that resistance and active worm infection affect BTB progression via distinct mechanisms. Our findings reveal that interactions between pathogens can occur as a consequence of processes arising on very different timescales.</p>
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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.