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133 results for “quantitative methods”
UPLC-MS/MS Method for quantitation of the recently FDA approved combination of vaborbactam and meropenem in human plasma
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A new method to reconstruct quantitative food webs and nutrient flows from isotope tracer addition experiments
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Induced pluripotent stem cell-derived cardiomyocyte in vitro models: tissue fabrication protocols, assessment methods, and quantitative maturation metrics for benchmarking progress
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Supplementary figures from: Is 3D, a more accurate quantitative method than 2D, crucial for analyzing disparity patterns in extinct marine arthropods (Trilobita)?
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Efficient weighting methods for genomic best linear unbiased prediction (BLUP) adaption to the genetic architectures of quantitative traits
<p><a name="_Hlk19877414"></a>Genomic best linear unbiased prediction (GBLUP) assumes equal variance for all marker effects, which is suitable for traits that conform to the infinitesimal model. For traits controlled by major genes, Bayesian methods with shrinkage priors or genome-wide association study (GWAS) methods can be used to identify <a name="_Hlk24974556">causal variants</a> effectively. The information from Bayesian/GWAS methods can be used to construct the weighted genomic relationship matrix (<b>G</b>). However, it remains unclear which methods perform best for traits varying in genetic architecture. Therefore, we developed several methods to <a name="_Hlk23592218">optimize</a> the performance of weighted GBLUP and compare them with other available methods using simulated and real datasets. First, two types of methods (marker effects with local-shrinkage or normal prior) were used to obtain test statistics and estimates for each marker effect. Second, three weighted <b>G</b> matrices were constructed based on the marker information from the first step: (1) the genomic-feature weighted <b>G</b> (GFWG), (2) the estimated marker-variance weighted <b>G</b> (EVWG), and (3) the absolute value of estimated marker-effect weighted <b>G</b> (AEWG). Following the above process, six different weighted GBLUP methods (local-shrinkage/normal prior GF/EV/AE-WGBLUP) were proposed for genomic prediction. Analyses with both simulated and real data demonstrated that these options offer flexibility for optimizing the weighted GBLUP for traits with a broad spectrum of genetic architectures. The advantage of weighting methods over GBLUP in terms of accuracy were trait dependent, ranging from 14.8% to marginal for simulated traits and from 44% to marginal for real traits. Local-shrinkage prior EVWGBLUP is superior for traits mainly controlled by loci of large effect. Normal prior AEWGBLUP performs well for traits mainly controlled by loci of moderate effect. For traits controlled by some loci with large effects (<a name="_Hlk49869847">explain 25%~50% genetic variance</a>) and a range of loci with small effects, GFWGBLUP has advantages. In conclusion, the optimal weighted GBLUP method for genomic selection should take both the genetic architecture and number of QTLs of traits into consideration carefully.</p>
Supplementary material 1 from: Sharmin S, Sohrab MH, Moni F, Afroz F, Rony SR, Akhter S (2020) Simple RP-HPLC method for Aceclofenac quantitative analysis in pharmaceutical tablets. Pharmacia 67(4): 383-391. https://doi.org/10.3897/pharmacia.67.e57981
Table S1. HPLC Analytical methods for simultaneous estimation of Aceclofenac with other constituents
Data from: Methods for the quantitative comparison of molecular estimates of clade age and the fossil record
Approaches quantifying relative congruence, or incongruence, of molecular divergence estimates and the fossil record have been limited. Previously proposed methods are largely node specific, assessing incongruence at particular nodes for which both fossil data and molecular divergence estimates are available. These existing metrics, and other methods that quantify incongruence across topologies including entirely extinct clades, have so far not taken into account uncertainty surrounding both the divergence estimates and the ages of fossils. They have also treated molecular divergence estimates younger than previously assessed fossil minimum estimates of clade age as if they were the same as cases in which they were older. However, these cases are not the same. Recovered divergence dates younger than compared oldest known occurrences require prior hypotheses regarding the phylogenetic position of the compared fossil record and standard assumptions about the relative timing of morphological and molecular change to be incorrect. Older molecular dates, by contrast, are consistent with an incomplete fossil record and do not require prior assessments of the fossil record to be unreliable in some way. Here, we compare previous approaches and introduce two new descriptive metrics. Both metrics explicitly incorporate information on uncertainty by utilizing the 95% confidence intervals on estimated divergence dates and data on stratigraphic uncertainty concerning the age of the compared fossils. Metric scores are maximized when these ranges are overlapping. MDI (minimum divergence incongruence) discriminates between situations where molecular estimates are younger or older than known fossils reporting both absolute fit values and a number score for incompatible nodes. DIG range (divergence implied gap range) allows quantification of the minimum increase in implied missing fossil record induced by enforcing a given set of molecular-based estimates. These metrics are used together to describe the relationship between time trees and a set of fossil data, which we recommend be phylogenetically vetted and referred on the basis of apomorphy. Differences from previously proposed metrics and the utility of MDI and DIG range are illustrated in three empirical case studies from angiosperms, ostracods, and birds. These case studies also illustrate the ways in which MDI and DIG range may be used to assess time trees resultant from analyses varying in calibration regime, divergence dating approach or molecular sequence data analyzed.
FIGURE 8 in Two new species of erect Bryozoa (Gymnolaemata: Cheilostomata) and the application of non-destructive imaging methods for quantitative taxonomy
FIGURE 8. Scatter plots showing the volume (A), length (B), width (C) and depth (D) of zooidal and avicularian chambers automatically detected and measured on the virtual dataset (N = 16) for Smittina imragueni n. sp. As in Fig. 4, the horizontal axis represents an arbitrary numbering by the software Amira. A separation between zooidal (large values on the left) and avicularian chambers (small values on the right) is clearly visible.
FIGURE 9 in Two new species of erect Bryozoa (Gymnolaemata: Cheilostomata) and the application of non-destructive imaging methods for quantitative taxonomy
FIGURE 9. Scatter plots showing length (A) and width (B) of orifices and frontal pores automatically detected and measured on the virtual dataset (N = 503) for Smittina imragueni, showing a distinction between those two entities, with some datapoints plotting in between (see Discussion). As in Fig. 4, the horizontal axis represents an arbitrary numbering by the software Amira.
FIGURE 7 in Two new species of erect Bryozoa (Gymnolaemata: Cheilostomata) and the application of non-destructive imaging methods for quantitative taxonomy
FIGURE 7. Virtual reconstructions of the internal structure of Smittina imragueni n. sp. (paratype SMF 40010). A, broad side of a branch. B, narrow side of a branch. C, single autozooid with suboral avicularium. D, same as C, without the suboral avicularium. E, a single suboral avicularian chamber; the two frontal protuberances are frontal pores. F, automatically detected orifices and frontal pores. Scalebars: A, B, F, 500 µm; C, D, 250 Μm; E, 50 Μm.
FIGURE 6 in Two new species of erect Bryozoa (Gymnolaemata: Cheilostomata) and the application of non-destructive imaging methods for quantitative taxonomy
FIGURE 6. SEM micrographs of Smittina imragueni n. sp. A, aspect of colony fragments (right, holotype SMF 40005; left, paratype SMF 40006). B, cross-section through a branch, showing thick secondary calcification and different profiles of zooidal chambers (paratype SMF 40007). C, interior view of primary orifice and suboral avicularium (SMF 40007). D, autozooids showing a relatively early developmental stage of the peristome (SMF 40010). E, secondary orifice with an intermediately developed peristome (SMF 40006). F, immersed secondary orifice late in ontogeny; note the vertical orientation of the avicularium (SMF 40007). G, ancestrular area (paratype SMF 40008). H, transition between encrusting and erect growth (paratype SMF 40009). Scalebars: A, 2 mm; B, G, 500 µm; C, E, 100 µm; D, F, H, 200 Μm.
FIGURE 5 in Two new species of erect Bryozoa (Gymnolaemata: Cheilostomata) and the application of non-destructive imaging methods for quantitative taxonomy
FIGURE 5. Scatter plot showing the width of opesial (+) and rhizoidal (×) openings sorted by zooid rows (A) and columns (B) (N = 37) for Cellaria bafouri n. sp. The datapoints for opesiae not aligned to innermost or outermost columns, respectively, are those at a position in between.
FIGURE 4 in Two new species of erect Bryozoa (Gymnolaemata: Cheilostomata) and the application of non-destructive imaging methods for quantitative taxonomy
FIGURE 4. Scatter plot showing the width (A) and length (B) of opesial and rhizoidal openings detected and measured from the virtual datamodel (N = 37) for Cellaria bafouri n. sp. The horizontal axis represents an arbitrary numbering of the measured entities by the Amira software.
FIGURE 3 in Two new species of erect Bryozoa (Gymnolaemata: Cheilostomata) and the application of non-destructive imaging methods for quantitative taxonomy
FIGURE 3. Virtual reconstructions of the internal structure of Cellaria bafouri n. sp. (paratype SMF 40003). A–C, three views from different angles. In B, the branch is bent away from the viewer. D, enlargement of the centrodistal zooid in B. E, the same autozooid as in D, but from a different angle, showing the form of the rhizoidal tubules. Scalebars: A–C, 500 µm; D, E, 200 µm.
FIGURE 1 in Two new species of erect Bryozoa (Gymnolaemata: Cheilostomata) and the application of non-destructive imaging methods for quantitative taxonomy
FIGURE 1. Charts showing the positions of all stations investigated based on MSM 16-3 multibeam surveys. Stations in bold font are those where either C. bafouri n. sp. or S. imragueni n. sp. occurred. Black areas in the insets A–H denote data gaps. The bathymetry of the overview map is from CleanTOPO2, http://www.shadedrelief.com/cleantopo2/.
FIGURE 2 in Two new species of erect Bryozoa (Gymnolaemata: Cheilostomata) and the application of non-destructive imaging methods for quantitative taxonomy
FIGURE 2. SEM micrographs of Cellaria bafouri n. sp. A, infertile segment (paratype SMF 40003). B, fertile autozooid (holotype SMF 40001). C, distal tip of an internode, showing the bases of the joints (SMF 40001). D, internode with distal autozooids having rhizoidal pores (SMF 40003). E, close-up of rhizoidal pores (SMF 40003). Scalebars: A, B, 250 µm; C, E, 100 µm; D, 500 µm.
Tractography derived quantitative estimates of tissue microstructure depend on streamline length: A characterization and method of adjustment.
<p>In respect of the brain imaging files upon which these analyses are based, three participants provided consent for their exemplar, pseudo-anonymised, data to be placed in the public domain. The example R code can be used to analyse these data.</p>
Validation data Set: Development and validation of a quantitative method for 15 antiviral drugs in poultry muscle using liquid chromatography coupled to tandem mass spectrometry
<p>Validation dataset for paper published in the Journal of Chromatography A.</p> <p> </p> <p>Clément Douillet, Mary Moloney, Melissa Di Rocco, Christopher Elliott, Martin Danaher,<br> Development and validation of a quantitative method for 15 antiviral drugs in poultry muscle using liquid chromatography coupled to tandem mass spectrometry, Journal of Chromatography A, Volume 1665, 2022, 462793, ISSN 0021-9673,</p> <p><br> Abstract:</p> <p>The objective of this work was to develop a quantitative multi-residue method for analysing antiviral drug residues and their metabolites in poultry meat samples. Antiviral drugs are not licensed for the treatment of influenza in food producing animals. However, there have been some reports indicating their illegal use in poultry. In this study, a method was developed for the analysis of 15 antiviral drug residues in poultry muscle (chicken, duck, quail and turkey) using liquid chromatography coupled to tandem mass spectrometry. This included 13 drugs against influenza and associated metabolites, but also two drugs employed for the treatment of herpes (acyclovir and ganciclovir). The method required the development of a novel chromatographic separation using a hydrophilic interaction chromatographic (HILIC) BEH amide column, which was necessary to retain the highly polar compounds. The analytes were detected using a triple quadrupole mass spectrometer operating in positive electrospray ionization mode. A range of different sample preparation protocols suitable for polar compounds were evaluated. The most effective procedure was based on a simple acetonitrile-based protein precipitation step followed by a further dilution in a methanol/water solution. The confirmatory method was validated according to the EU 2021/808 guidelines on different species including chicken, duck, turkey and quail. The validation was performed using various calibration curves ranging from 0.1 µg kg−1to 200 µg kg−1, according to the analyte. Depending on the analyte sensitivity, decision limits achieved ranged from 0.12 µg kg−1 for arbidol to 34.7 µg kg−1 for ribavirin. Overall, the reproducibility precision values ranged from 2.8% to 22.7% and the recoveries from 84% to 127%. The method was applied to 120 commercial poultry samples from the Irish market, which were all found to be residue-free.<br> Keywords: Antiviral drug residues; Influenza; HILIC; LC-MS/MS; Poultry muscle</p>
Quantitative and qualitative methods complementing: Bridging modelling and policy-making efforts to realise the European bioeconomy
<p>The European Bioeconomy Strategy aims to facilitate the transition from a take-make-dispose fossil economy into one fostering circular bio-based value chains linking sustainable land use with cutting-edge products. Optimised designs, implementation and monitoring rely on continuous interactions between policymakers and modellers who run multiple scenarios for environmentally, economically and socially desirable futures. "Bridging modelling and policy-making efforts to realise the European bioeconomy" leverages a multi-layered framework that cross-references 39 policies and 32 models to assess how they address the five principle objectives of the Bioeconomy Strategy in terms of accompanying sectors, value-chains, and multi-dimensional indicators. The framework identifies gaps in bioeconomy knowledge both in policy and modelling. The analysis stemming from this framework matching policies and models based on their scope and aim, and reviewing how each addresses bioeconomy objectives, sectors, value chain stages and indicators, was built using mixed methods. The files complement the Supplementary Files of "Bridging modelling and policy-making efforts to realise the European bioeconomy" to produce a comprehensive compendium of the key findings extracted from the main publication. </p>
Six supplementary figures from: 3D, a more accurate quantitative method than 2D: crucial for analyzing disparity patterns in extinct marine arthropods (Trilobita)?
<p>The pdf file is structured to provide six supplementary figures from: 3D, a more accurate quantitative method than 2D: crucial for analyzing disparity patterns in extinct marine arthropods (Trilobita)?</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.