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raw data - In classical Hodgkin lymphoma, the activity of Thymidine kinase-1 is not related to the tumor size.
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THE SPECIFIC FEATURES OF TEACHING DRAMA IN ENGLISH LITERATURE CLASSES: CLASSIC AND MODERN PLAYS
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Multiplexed spatial profiling of Hodgkin Reed-Sternberg cell neighborhoods in classic Hodgkin lymphoma
<p>Single-cell data from multiplexed imaging (Leica Cell DIVE) of 29 proteins in 587 fields of view across 30 classic Hodgkin lymphoma patients.</p> <p>Bulk RNA sequencing (NanoString IO360 panel) raw and normalized data for 32 classic Hodgkin lymphoma patients.</p> <p>Meta data containing information about patients, cell type and state information, and statistical comparisons.</p>
Do deaths from road traffic injuries follow a classical trimodal pattern in North West Ethiopia? A hospital based prospective cohort study
<p>The data set contains information collected from road traffic injury victims. The data was collected from all traffic injury victims, regardless of age and sex except those who were dead on arrival, comatose, and had no attendant. The variables included in this data includes, crash characteristics, hospital arrival time, road user category, availability of pre-hospital first aid, type of transportation used to transfer the victim, clinical findings, the outcome in the emergency department, and decision after evaluation at the emergency department.</p> <p> The primary outcome was time to death measured in hours between road traffic injury and the 30th day of injury. Accordingly, those victims who died between injury times to the 30th day of injury were events, and those who were still alive on the 30th day were censored cases. Secondary outcomes were pre-hospital first aid, length of hospital stay, and hospital arrival time. The exposure variable was having any degree of injury by any vehicle.</p> <p>The finding of the study showed, there were 80 deaths during the study time, (2.90 deaths per 10,000 person-hours of observation (95% CI: 2.77, 3.03). Being a driver, accidents at the inter urban locations, time from injury to hospital arrival time of 1 to 4 hours, systolic blood pressure on admission of less than 90mmHG, GCS of less than 8 on admission and poly trauma were found to be independent predictors of time to death.</p>
FIGURE 3 in Comparisons of two cryptic Ampedus species (Coleoptera: Elateridae) by using classical systematics, ecological niche modeling, and DNA barcoding
FIGURE 3. Evolutionary relationships optimal tree of examined and outgroup taxa.
FIGURE 4 in Comparisons of two cryptic Ampedus species (Coleoptera: Elateridae) by using classical systematics, ecological niche modeling, and DNA barcoding
FIGURE 4. Evolutionary relationships bootstrap consensus tree of examined and outgroup taxa.
Classical Center-Surround Receptive Fields Facilitate Novel Object Detection in Retinal Bipolar Cells
<p>Database and Figures in Igor format</p>
Figure 4 from: Binh HT, Ngoc NV, Tagane S, Toyama H, Mase K, Mitsuyuki C, Strijk JS, Suyama Y, Yahara T (2018) A taxonomic study of Quercus langbianensis complex based on morphology, and DNA barcodes of classic and next generation sequences. PhytoKeys 95: 37-70. https://doi.org/10.3897/phytokeys.95.21126
Figure 4 Comparison of Q. langbianensis complex between NJ tree (left, Clade M3 of Fig. 3) and Bayesian tree (right: Clade 2 of Fig. 2).
Figure 1 from: Binh HT, Ngoc NV, Tagane S, Toyama H, Mase K, Mitsuyuki C, Strijk JS, Suyama Y, Yahara T (2018) A taxonomic study of Quercus langbianensis complex based on morphology, and DNA barcodes of classic and next generation sequences. PhytoKeys 95: 37-70. https://doi.org/10.3897/phytokeys.95.21126
Figure 1 Collection sites in Vietnam and Cambodia in this study, including eight national parks, four nature reserves and two conservation areas.
Figure 7 from: Binh HT, Ngoc NV, Tagane S, Toyama H, Mase K, Mitsuyuki C, Strijk JS, Suyama Y, Yahara T (2018) A taxonomic study of Quercus langbianensis complex based on morphology, and DNA barcodes of classic and next generation sequences. PhytoKeys 95: 37-70. https://doi.org/10.3897/phytokeys.95.21126
Figure 7 Quercus bidoupensis Binh & Ngoc. A Leafy twig B Abaxial side of mature leaf C, D Side view and base view of the cupule, respectively E Inside of cupule F Nut. Materials: A–F from Tagane et al. V4328.
Figure 11 from: Binh HT, Ngoc NV, Tagane S, Toyama H, Mase K, Mitsuyuki C, Strijk JS, Suyama Y, Yahara T (2018) A taxonomic study of Quercus langbianensis complex based on morphology, and DNA barcodes of classic and next generation sequences. PhytoKeys 95: 37-70. https://doi.org/10.3897/phytokeys.95.21126
Figure 11 Quercus donnaiensis A.Camus. A Leafy twig B Infructescence, young fruits and abaxial side of mature leaf C Dried specimen. Materials: A, B from Tagane S., Wai J. V4398 C from Ngoc et al. V3208.
Figure 13 from: Binh HT, Ngoc NV, Tagane S, Toyama H, Mase K, Mitsuyuki C, Strijk JS, Suyama Y, Yahara T (2018) A taxonomic study of Quercus langbianensis complex based on morphology, and DNA barcodes of classic and next generation sequences. PhytoKeys 95: 37-70. https://doi.org/10.3897/phytokeys.95.21126
Figure 13 Quercus langbianensis Hickel & A.Camus. A Leafy twig B Abaxial side of mature leaf C Infructescence and mature fruits D Apex of the nut E Basal scar of the nut F Inside of cupule. Materials: A, B from Tagane et al. V 4165 C–F from Tagane et al. V4166.
Figure 10 from: Binh HT, Ngoc NV, Tagane S, Toyama H, Mase K, Mitsuyuki C, Strijk JS, Suyama Y, Yahara T (2018) A taxonomic study of Quercus langbianensis complex based on morphology, and DNA barcodes of classic and next generation sequences. PhytoKeys 95: 37-70. https://doi.org/10.3897/phytokeys.95.21126
Figure 10 Quercus camusiae Trel. ex Hickel & A.Camus. A Branch with young fruit, B. Infructescence and young fruits C, D Abaxial side of young and mature leaf, E. Dried specimen. Materials: A–D from Tagane et al. V342 E from Toyama et al. V2173.
Figure 12 from: Binh HT, Ngoc NV, Tagane S, Toyama H, Mase K, Mitsuyuki C, Strijk JS, Suyama Y, Yahara T (2018) A taxonomic study of Quercus langbianensis complex based on morphology, and DNA barcodes of classic and next generation sequences. PhytoKeys 95: 37-70. https://doi.org/10.3897/phytokeys.95.21126
Figure 12 Quercus honbaensis Binh, Tagane & Yahara. A Leafy twig B Infructescence and mature fruits, C, D Side view and base view of the cupule, respectively, E. Inside of cupule, F. Nut. Materials: A–F from Toyama et al. V1378.
Figure 6 from: Binh HT, Ngoc NV, Tagane S, Toyama H, Mase K, Mitsuyuki C, Strijk JS, Suyama Y, Yahara T (2018) A taxonomic study of Quercus langbianensis complex based on morphology, and DNA barcodes of classic and next generation sequences. PhytoKeys 95: 37-70. https://doi.org/10.3897/phytokeys.95.21126
Figure 6 Quercus baolamensis Binh & Ngoc. A Leafy twig B Abaxial side of mature leaf C Mature fruit D Inside of cupule E Nut. Materials: A–E from Ngoc et al. V3191.
Figure 2 from: Binh HT, Ngoc NV, Tagane S, Toyama H, Mase K, Mitsuyuki C, Strijk JS, Suyama Y, Yahara T (2018) A taxonomic study of Quercus langbianensis complex based on morphology, and DNA barcodes of classic and next generation sequences. PhytoKeys 95: 37-70. https://doi.org/10.3897/phytokeys.95.21126
Figure 2 Bayesian phylogeny of 29 samples of Quercus and one Trigonobalanus (outgroup) based on rbcL, matK and ITS sequences. Braches are labelled with posterior probabilities.
Figure 3 from: Binh HT, Ngoc NV, Tagane S, Toyama H, Mase K, Mitsuyuki C, Strijk JS, Suyama Y, Yahara T (2018) A taxonomic study of Quercus langbianensis complex based on morphology, and DNA barcodes of classic and next generation sequences. PhytoKeys 95: 37-70. https://doi.org/10.3897/phytokeys.95.21126
Figure 3 NJ tree of 31 samples of Quercus and one Trigonobalanus (outgroup) based on presence/absence data of 16,809 MIG-seq loci. Branches are labelled with bootstrap supports (% of 1000 replicates).
Figure 9 from: Binh HT, Ngoc NV, Tagane S, Toyama H, Mase K, Mitsuyuki C, Strijk JS, Suyama Y, Yahara T (2018) A taxonomic study of Quercus langbianensis complex based on morphology, and DNA barcodes of classic and next generation sequences. PhytoKeys 95: 37-70. https://doi.org/10.3897/phytokeys.95.21126
Figure 9 Quercus cambodiensis Hickel & A.Camus. A Leafy twig B Abaxial side of mature leaf C Infructescence and fruits D Nut E Basal scar of the nut. Materials: A–E from Tagane et al. 4302.
Figure 8 from: Binh HT, Ngoc NV, Tagane S, Toyama H, Mase K, Mitsuyuki C, Strijk JS, Suyama Y, Yahara T (2018) A taxonomic study of Quercus langbianensis complex based on morphology, and DNA barcodes of classic and next generation sequences. PhytoKeys 95: 37-70. https://doi.org/10.3897/phytokeys.95.21126
Figure 8 Quercus blaoensis A.Camus A. Branch with fruits B Young fruit C Dried specimen Materials: A–C from Toyama et al. V1366.
Figure 5 from: Binh HT, Ngoc NV, Tagane S, Toyama H, Mase K, Mitsuyuki C, Strijk JS, Suyama Y, Yahara T (2018) A taxonomic study of Quercus langbianensis complex based on morphology, and DNA barcodes of classic and next generation sequences. PhytoKeys 95: 37-70. https://doi.org/10.3897/phytokeys.95.21126
Figure 5 Quercus baniensis A.Camus. A Leafy twig B Abaxial side of mature leaf C Infructescence and young fruits D Dried specimen. Materials: A, B from Hoang T.S. & Tagane S. V6922 C, D from Tagane et al. V3089.
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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.