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8,038 results for “validation.”
Histological validation of per-bundle water diffusion metrics within a region of fiber crossing following axonal degeneration - Synthetic data
<p>Analysis of dMRI of the optic chiasm using CSD revealed unexpectedly high AFD of the intact bundle in the experimental animals. To evaluate whether this finding is an artifact produced by CSD, we used analytic synthetic data. Using the multi-tensor model, two sets of synthetic dMRI data were created consisting of 100 voxels, each with two tensors crossing at right angles. For each voxel, one tensor was modelled as an “intact” fiber bundle, following the DTI metrics observed in our experimental data (λ∥=0.64 and λ⟂=0.12 ×10-3 mm²/s), while the other tensor was modelled as an “injured” fiber bundle (λ∥=0.42 and λ⟂=0.22 ×10-3 mm²/s). Volume fractions were set as f=0.5 for both tensors. The multi-shell scheme to generate the synthetic signals consisted of 20 b=0 s/mm², and 160 DWI volumes, consisting of 80 diffusion gradient orientations, each with two distinct b values, namely b=1000 and 3000 s/mm². Signal-to-noise ratio was set at 20. </p> <p>Diffusion-weighted parameters are shown in the corresponding *protocol.txt files, organized as in the MRtrix gradient scheme (https://mrtrix.readthedocs.io/en/latest/concepts/dw_scheme.html), namely one row per volume, each containing the vector [x y z b], where x, y, and z, correspond to the components of the diffusion gradient direction, and b is the b value in s/mm^2.</p> <p>Refers to:</p> <p>Rojas-Vite, Gilberto, Coronado-Leija, Ricardo, Narvaez-Delgado, Omar, Ramirez-Manzanares, Alonso, Marroquin, Jose-Luis, Noguez-Imm, Ramses, Aranda, Marcos L, Scherrer, Benoit, Larriva-Sahd, Jorge, Concha, Luis: Histological validation of per-bundle water diffusion metrics within a region of fiber crossing following axonal degeneration , Available at bioRxiv, doi.org/10.1101/571539, 2019.</p>
Continuous Digital Monitoring of Walking Speed in Frail Elderly Patients: Noninterventional Validation Study and Longitudinal Clinical Trial (Data for interventional clinical trial)
<p>Digital technologies and advanced analytics have drastically improved our ability to capture and interpret health relevant data from patients. However, to date, limited data and results have been published detailing real-world patient compliance, demonstrating accuracy in target indications or examining what novel insights and clinical value can be derived. Here we present novel, digital mobility data from two studies: an independent, non-interventional validation study with elderly, naturally slow walking subjects, and a global, multi-site phase IIb clinical trial involving patients with age-related muscle loss and slow walking speed (sarcopenia). Based on these data, we validate the accuracy of a novel algorithm for capturing in-clinic and real-world gait speed in frail, slow-walking adults. We demonstrate the feasibility of continuous monitoring with a wearable inertial sensor in elderly adults in real-world settings, and propose minimum thresholds for compliance required for robust capture of gait behaviors in this population. We also show how simple, inferred contextual information, describing the length of a given walking bout, can explain some of the variation in real-world gait speed, and use this information to demonstrate for the first time a relationship between in-clinic performance and real-world gait speed behavior. This work lays a foundation for exploration of the clinical relevance and value of such measures and is a first step in building a more complete chain of evidence between standardized physical performance assessment, real-world behavior, and subjective perceptions of mobility, independence and health.</p> <p>This dataset contains data collected during the interventional clinical trial: derived data from raw accelerometry data, and summary performance data.</p> <p>The full dataset, including raw accelerometry data, is available here: <a href="https://mueller-et-al-2019.s3.amazonaws.com/index.html">https://mueller-et-al-2019.s3.amazonaws.com/index.html</a></p>
Figure 3 from: He L, Liao S, Applequist W, Chen S (2019) The valid publication of Salix suchowensis (Salicaceae). PhytoKeys 131: 27-35. https://doi.org/10.3897/phytokeys.131.37065
Figure 3 Salix suchowensis: A branchlet and leaf blades adaxially B female catkin C male catkin D leaf blades abaxially (photo credit: A, D by L. He B, C by Feiyi Guo).
Figure 2 from: He L, Liao S, Applequist W, Chen S (2019) The valid publication of Salix suchowensis (Salicaceae). PhytoKeys 131: 27-35. https://doi.org/10.3897/phytokeys.131.37065
Figure 2 Salix suchowensis: C.T. Yang 20640 (NF barcode 04801063!, ♀, lectotype), renumbered 20641 in herbarium.
Figure 3 from: Wu X-F, Ye D-P, Pan B, Lin X-Q, Jiang H, Liu Q (2019) Validation of Gastrochilus prionophyllus (Vandeae, Orchidaceae), a new species from Yunnan Province, China. In: Cai J, Yu W-B, Zhang T, Li D-Z (Eds) Revealing of the plant diversity in China's biodiversity hotspots. PhytoKeys 130: 161-169. https://doi.org/10.3897/phytokeys.130.34555
Figure 3 AGastrochilus corymbosus (A-1 Plant A-2 Inflorescence and flowers) BG. distichus (B-1 Plant B-2 Inflorescence and flowers) CG. prionophyllus (C-1 Plant C-2 Inflorescence and flowers) (Photographed by Q. Liu).
Figure 2 from: Wu X-F, Ye D-P, Pan B, Lin X-Q, Jiang H, Liu Q (2019) Validation of Gastrochilus prionophyllus (Vandeae, Orchidaceae), a new species from Yunnan Province, China. In: Cai J, Yu W-B, Zhang T, Li D-Z (Eds) Revealing of the plant diversity in China's biodiversity hotspots. PhytoKeys 130: 161-169. https://doi.org/10.3897/phytokeys.130.34555
Figure 2 Gastrochilus prionophyllus. A Plant habit B plant C front view of flower D lateral view of labellum and column E front view of column F pollinarium G anther cap H variation of leaf margin (Photographed by Q. Liu).
Figure 1 from: Wu X-F, Ye D-P, Pan B, Lin X-Q, Jiang H, Liu Q (2019) Validation of Gastrochilus prionophyllus (Vandeae, Orchidaceae), a new species from Yunnan Province, China. In: Cai J, Yu W-B, Zhang T, Li D-Z (Eds) Revealing of the plant diversity in China's biodiversity hotspots. PhytoKeys 130: 161-169. https://doi.org/10.3897/phytokeys.130.34555
Figure 1 Gastrochilus prionophyllus. A Adaxial view and abaxial view of plant B inflorescence C front view of flower D lateral sepal E petal F dorsal sepal G front view of column H margin of leaf I lateral view of labellum and column J pollinarium K abaxial and adaxial anther cap. All from the type collection (Qiang Liu, 359) and drawn by Bo Pan.
Figure 5 from: Tzankova D, Peikova L, Vladimirova S, Georgieva M (2019) Development and validation of RP-HPLC method for stability evaluation of model hydrazone, containing a pyrrole ring. Pharmacia 66(3): 127-134. https://doi.org/10.3897/pharmacia.66.e47035
Figure 5 Chromatogram of the separated mixture of the analyzed hydrazone D-5d (tR = 6.800) and its possible degradation products – the hydrazide D-5 (tR = 4.387) and the corresponding aldehyde d (tR = 1.387).
Figure 7 from: Tzankova D, Peikova L, Vladimirova S, Georgieva M (2019) Development and validation of RP-HPLC method for stability evaluation of model hydrazone, containing a pyrrole ring. Pharmacia 66(3): 127-134. https://doi.org/10.3897/pharmacia.66.e47035
Figure 7 Chromatograms indicating the behavior of D_5d in the presence of buffer with pH 2.0 and at 37°C at 0th min (A) and at 30th min (B).
Figure 4 from: Tzankova D, Peikova L, Vladimirova S, Georgieva M (2019) Development and validation of RP-HPLC method for stability evaluation of model hydrazone, containing a pyrrole ring. Pharmacia 66(3): 127-134. https://doi.org/10.3897/pharmacia.66.e47035
Figure 4 Chromatogram of standard solution of the aldehyde d (tR = 1.283) as possible degradation product.
Figure 3 from: Tzankova D, Peikova L, Vladimirova S, Georgieva M (2019) Development and validation of RP-HPLC method for stability evaluation of model hydrazone, containing a pyrrole ring. Pharmacia 66(3): 127-134. https://doi.org/10.3897/pharmacia.66.e47035
Figure 3 Chromatogram of standard solution of the hydrazide D-5 (tR = 4.380) as possible degradation product.
Figure 8 from: Tzankova D, Peikova L, Vladimirova S, Georgieva M (2019) Development and validation of RP-HPLC method for stability evaluation of model hydrazone, containing a pyrrole ring. Pharmacia 66(3): 127-134. https://doi.org/10.3897/pharmacia.66.e47035
Figure 8 Chromatograms indicating the behavior of D_5d in the presence of buffer with pH 9.0 and at 37°C at 0th min (A) and at 210th min (B).
Figure 9 from: Tzankova D, Peikova L, Vladimirova S, Georgieva M (2019) Development and validation of RP-HPLC method for stability evaluation of model hydrazone, containing a pyrrole ring. Pharmacia 66(3): 127-134. https://doi.org/10.3897/pharmacia.66.e47035
Figure 9 Chromatograms indicating the behavior of D_5d in the presence of buffer with pH 13.0 and at 37°C at 0th min (A) and at 30th min (B).
Figure 4 in Earthworm, a novel in vivo system to validate antimitotic compounds
Figure 4. Immunohistochemistry study with mitosis-specific antibodies: Panels A, B, and C show the analysis of worms treated with water, colchicine, or aqueous extract of rhizomes, respectively, and tested with PCNA antibody. A) High number of PCNA positive cells is shown with 40× lens. Lower number of PCNA-positive cells is shown in panels B and C. Panels D, E, and F show the analysis of worms treated with water, colchicine, or aqueous extract of rhizomes respectively, treated with phospho serine 10 histone H3 antibody. D) A low number of histone H3-positive cells is shown with 40× magnification. A high number of H3-positive cells is shown in panels E and F. Quantitative analysis of positive cells with PCNA (G) and histone H3 (H) cells are shown with mean ± SEM bar and P value (**:P <0.05). Scale bar equals 50 µm.
Fig. 4 in Intraspecific Variability of Melasis buprestoides (Linnaeus, 1761) Challenges the Validity of Melasis fermini Sánchez-Ruiz and Rosa, 2003 (Coleoptera: Eucnemidae)
Fig. 4. Length (a) and width (b) measurements of antennomere 9 of Melasis.
Supplementary Material - From in-silico screening to in-vivo validation in the zebrafish - A framework for Reeling in the Right Psychobiotics
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PHARAOH: A Collaborative Crowdsourcing Platform for PHenotyping And Regional Analysis Of Histology: KIRK Validation Cohort Grades 3 and 4
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PHARAOH: A Collaborative Crowdsourcing Platform for PHenotyping And Regional Analysis Of Histology: KIRK Validation Cohort Grades 1 and 2
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FIGURE 25 in The reinstatement and rediagnosis of the madagascan genus Rhodocodon (Asparagaceae, Scilloideae), with validation and remarks on H. Perrier's taxa
FIGURE 25. Lectotype of Rhodocodon urgineoides Baker: Forsyth Major 44 (G 00168520!).
FIGURE 2 in The reinstatement and rediagnosis of the madagascan genus Rhodocodon (Asparagaceae, Scilloideae), with validation and remarks on H. Perrier's taxa
FIGURE 2. Rhodocodon urgineoides Baker, taken from Hooker's Icon. Pl. 25: t. 2492 (1896).
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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.