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1,667 results for “susceptibility”
Figure 5 in Influence of Temperature on Susceptibility of Cvs. Tifguard and Georgia-06G Peanut to Meloidogyne arenaria
Figure 5: Number of egg-laying females per gram of roots of the resistant cultivar Tifguard and susceptible cultivar Georgia-06G at 30 or 40 days after inoculation in Experiments 1 and 2, respectively. Bars followed by different letters from the same experiment indicate significant differences at P ≤ 0.05.
Figure 4 in Influence of Temperature on Susceptibility of Cvs. Tifguard and Georgia-06G Peanut to Meloidogyne arenaria
Figure 4: Number of Meloidogyne arenaria second-stage juveniles (J2) and females 30 days after inoculation (Experiment 1), and J2, females, and egg-laying females 40 days after inoculation (Experiment 2) on Tifguard.
Figure 2 in Influence of Temperature on Susceptibility of Cvs. Tifguard and Georgia-06G Peanut to Meloidogyne arenaria
Figure 2: Mean number of Meloidogyne arenaria in roots of Tifguard and Georgia-06G at 5-day intervals over a 40-day period in Experiment 2.
Fig. 2 in Susceptibility of Eucalyptus spp. (Myrtales: Myrtaceae) and clones to Leptocybe invasa (Hymenoptera: Eulophidae) in Paraná, Brazil
Fig. 2. Percentage of leaves and stems with galls caused by Leptocybe invasa in plants in each stratum (lower, middle, upper) of approx. 2-m-tall Eucalyptus spp. and clones at Umuarama, PR, Brazil, in 2013.
Fig. 3 in Effects of cold-acclimation, pathogen infection, and varying temperatures on insecticide susceptibility, feeding, and detoxifying enzyme levels in Diaphorina citri (Hemiptera: Liviidae)
Fig. 3. Correlations between mean percentage mortality of Diaphorina citri and temperature for field-collected and uninfected D. citri and field-collected and 'Candidatus' Liberibacter asiaticus–infected D. citri, when exposed to chlorpyriphos (A), fenpropathrin (B), imidacloprid (C), thiamethoxam (D), and spinetoram (E).
Fig. 1 in Effects of cold-acclimation, pathogen infection, and varying temperatures on insecticide susceptibility, feeding, and detoxifying enzyme levels in Diaphorina citri (Hemiptera: Liviidae)
Fig. 1. Comparison of cytochrome P450 (A), general esterase (B), and glutathione S-transferase (C) activity levels in laboratory susceptible Diaphorina citri adults at 5 temperatures. For glutathione S-transferase, means with the same uppercase letters are not significantly different from one another for imidacloprid-treated D. citri. Means with the same lowercase letters are not significantly different from one another for spinetoram-treated D. citri.
Fig. 1 in Regional susceptibilities of Rhopalosiphum padi (Hemiptera: Aphididae) to ten insecticides
Fig. 1. SaMpliNG reGioNs of Rhopalosiphum padi iN ChiNa. The reGioNs iNcluded BaicheNG of JiliN ProviNce (the populatioN code was NaMed as JLB), BaodiNG of Hebei ProviNce (HEB), LaNzhou of GaNsu ProviNce (GSL), TaiGu of ShaNxi ProviNce (SXT), Zibo of ShaNGdoNG ProviNce (SDZ), TaiaN of ShaNGdoNG ProviNce (SDT), XiaNyaNG of Shaaxi ProviNce (SAX), NaNyaNG of HeNaN ProviNce (HNN), Chuzhou of ANhui ProviNce (AHC), WuhaN of Hubei ProviNce (HBW), Beibei of ChoNGqiNG ProviNce (CQB), aNd GuiyaNG of Guizhou ProviNce (GZG).
Quantitative susceptibility mapping of articular cartilage: ex vivo findings at multiple orientations and following different degradation treatments
<p>This dataset contains all the raw source data and MATLAB analysis functions that comprise the study:</p> <p><br> Quantitative susceptibility mapping of articular cartilage: Ex vivo findings at multiple orientations and following different degradation treatments</p> <p>Magnetic Resonance in Medicine | DOI: 10.1002/mrm.27216</p> <p>Nykänen Olli(1*), Rieppo Lassi(2,3), Töyräs Juha(1,4), Kolehmainen Ville(1), Saarakkala Simo(2,3,5), Shmueli Karin(6) and Nissi Mikko Johannes(1)</p> <p>(1) Department of Applied Physics, University of Eastern Finland, POB 1627, FI-70211 Kuopio, Finland<br> (2) Research Unit of Medical Imaging, Physics and Technology, University of Oulu, POB 5000, FI-90014 Oulu, Finland<br> (3) Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland<br> (4) Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland<br> (5) Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland<br> (6) Department of Medical Physics & Biomedical Engineering, University College London(UCL), London, United Kingdom</p> <p><br> *Corresponding author:<br> Olli Nykänen<br> Department of Applied Physics,<br> University of Eastern Finland<br> POB 1627<br> FI-70211, Kuopio, Finland<br> olli.nykanen@uef.fi<br> +358-50-5556357</p> <p><br> Keywords: cartilage, collagen matrix, quantitative susceptibility mapping, MRI, osteoarthritis</p> <p><br> Included folders and files are:<br> - article_figures: all figures published in the manuscript<br> - data: all MRI, histological, and PLM data used in this article<br> - matlab_functions: matlab functions used in data analysis with subfolders:<br> - aedes_plugins: plugins for aedes (http://aedes.uef.fi) for calculation of QS- and T2* maps<br> - fitting_functions: functions for fitting relaxation times or TKD-method for QSM, used by the functions in above folder<br> - miscellaneous_functions: small helper functions for a number of small tasks utilized by the other scripts and functions<br> - ReadMe.txt: this file</p> <p><br> Notes for setting up Aedes correctly for this dataset:<br> Run Aedes -> Tools -> Edit VNMR Defaults:<br> - Return: FT + K-space<br> - DC: off<br> - Zeropadding: off<br> - Sorting & fastread: on<br> - Precision: single<br> - Read_fcn: readvnmr<br> - Orient: no</p> <p>See more info in separate readme files included in each folder.</p> <p><br> (Olli Nykänen, Apr 17, 2018)</p>
Data sets for modeling double strand break susceptibility and interrogating structural variation in cancer
<p>This is data used and produced for the study of "Modeling double strand break susceptibility to interrogate structural variation in cancer". </p> <p><strong>Background: </strong>Structural variants (SVs) are known to play important roles in a variety of cancers, but their origins and functional consequences are still poorly understood. Many SVs are thought to emerge from errors in the repair processes following DNA double strand breaks (DSBs).</p> <p><strong>Results:</strong> We used experimentally quantified DSB frequencies in cell lines with matched chromatin and sequence features to derive the first quantitative genome-wide models of DSB susceptibility. These models are accurate and provide novel insights into the mutational mechanisms generating DSBs. Models trained in one cell type can be successfully applied to others, but a substantial proportion of DSBs appear to reflect cell type specific processes. Using model predictions as a proxy for susceptibility to DSBs in tumours, many SV-enriched regions appear to be poorly explained by selectively neutral mutational bias alone. A substantial number of these regions show unexpectedly high SV breakpoint frequencies given their predicted susceptibility to mutation and are therefore credible targets of positive selection in tumours. These putatively positively selected SV hotspots are enriched for genes previously shown to be oncogenic. In contrast, several hundred regions across the genome show unexpectedly low levels of SVs, given their relatively high susceptibility to mutation. These novel coldspot regions appear to be subject to purifying selection in tumours and are enriched for active promoters and enhancers.</p> <p><strong>Conclusions:</strong> We conclude that models of DSB susceptibility offer a rigorous approach to the inference of SVs putatively subject to selection in tumours.</p>
Data for [Inverse magnetic susceptibility fabrics in pelagic sediment: Implications for magnetofossil abundance and alignment]
<p>Data for [Inverse magnetic susceptibility fabrics in pelagic sediment: Implications for magnetofossil abundance and alignment]</p>
Figure. Mean pre-adult development time (in days) values for all strains. Vertical bars denote 0.95 confidence intervals. in Effects of artificial migration of susceptible individuals on resistance and fitness of a fenitrothion-resistant strain of Musca domestica (L.) Diptera
Figure. Mean pre-adult development time (in days) values for all strains. Vertical bars denote 0.95 confidence intervals.
Figure 2. A in Susceptibility of Agriotes spp. larvae (Coleoptera: Elateridae) to stress-and-kill strategies using spinosad and the entomopathogenic fungus Metarhizium brunneum
Figure 2. A: MetarhIzIum brunneum strain ART2825 growth in the tracheae of AgrIotes obscurus 22 days posttreatment. B: ART2825 fungal colonization in the integument of A. obscurus 22 days posttreatment.
Figure 3. A in Susceptibility of Agriotes spp. larvae (Coleoptera: Elateridae) to stress-and-kill strategies using spinosad and the entomopathogenic fungus Metarhizium brunneum
Figure 3. A: Sporulation of MetarhIzIum brunneum strain 16P on AgrIotes sordIdus 21 days posttreatment (zoom ×6.7). B: M. brunneum strain 16P primary and secondary fungal growth, with melanotic spots (black arrow) on A. sordIdus (×6.7). C: ART2825 fungal growth on the cuticle of A. obscurus 22 days posttreatment. D: Fungal growth on the cuticle of A. obscurus, which could correspond to the secondary growth on the sclerites.
Figure 1. A in Susceptibility of Agriotes spp. larvae (Coleoptera: Elateridae) to stress-and-kill strategies using spinosad and the entomopathogenic fungus Metarhizium brunneum
Figure 1. A: Leg of AgrIotes obscurus exposed to MetarhIzIum brunneum strain ART2825 48 h posttreatment. B: intersegment area of A. obscurus exposed to M. brunneum strain F52 36 h posttreatment, C: Depression at the base of a setae of A. obscurus with F52 conidia 24 h posttreatment, D: Melanization on A. sordIdus exposed to M. brunneum strain 16P 21 days posttreatment (zoom x 6.7).
Fig. 1 in Susceptibility status to temephos in larval Aedes aegypti and Aedes albopictus (Diptera: Culicidae) populations from Quintana Roo, southeastern Mexico
Fig. 1. Susceptibility status to temephos (1× the discriminant dose) of Aedes albopictus (grey pie charts) and Aedes aegypti (black and white pie charts) larvae from 4 communities of Quintana Roo, Mexico.
Fig. 2 in Susceptibility of first instar Hippodamia convergens (Coleoptera: Coccinellidae) and Chrysoperla rufilabris (Neuroptera: Chrysopidae) to the insecticide sulfoxaflor
Fig. 2. Proportion of mortality (A) and developmental time (B) of Hippodamia convergens life stages afer exposure of first instars to dried insecticide residues. Afer exposure, individuals were reared to adults (L1, L2, L3, and L4 represent first, second, third, and fourth instars, respectively, and total represents first instar to adult). Within life stages, treatment means with the same letter are not significantly different (Tukey HSD, P> 0.05). FR = field rate of insecticide. Asterisks (*) indicate zeros.
Figs 2, 3 in Susceptibility of targets to the vampire bat Desmodus rotundus are proportional to their abundance in Atlantic Forest fragments?
Figs 2, 3. Two records of the approach of Desmodus rotundus (É. Geoffroy, 1810): 2, a bat landing on a trunk near a deer (Mazama americana); 3, a bat on the ground very close to a tapir (Tapirus terrestris).
Fig. 1 in Susceptibility of targets to the vampire bat Desmodus rotundus are proportional to their abundance in Atlantic Forest fragments?
Fig. 1. Study area located in the municipalities of ItajÁ and Aporé, state of GoiÁs, BraZil. Black dots represent the sites where the camera traps were set up.
Fig. 3 in Susceptibility of Spodoptera frugiperda (Lepidoptera: Noctuidae) field populations to the Cry1F Bacillus thuringiensis insecticidal protein
Fig. 3. Mean percentage of mortality and mean percentage of growth inhibition responses of Spodoptera frugiperda for 2012 and 2013 field-collected populations exposed to Cry1F Bacillus thuringiensis toxin.
Fig. 1 in Susceptibility of Spodoptera frugiperda (Lepidoptera: Noctuidae) field populations to the Cry1F Bacillus thuringiensis insecticidal protein
Fig. 1. EC50s estimated by nonlinear regression of growth inhibition fitted to a probit model and the 95% confidence intervals of Spodoptera frugiperda neonates field collected in 2012 and exposed to the Cry1F Bacillus thuringiensis toxin.
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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.