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800 results for “mixtures”
Improved control of Septoria tritici blotch in durum wheat using cultivar mixtures
<p>Mixtures of cultivars with contrasting levels of resistance can suppress infectious diseases in wheat, as demonstrated in numerous field experiments. Most studies focused on airborne pathogens in bread wheat, while splash-dispersed pathogens have received less attention, and no studies have been conducted in durum wheat. We conducted a two-year field experiment in Tunisia, to evaluate the performance of cultivar mixtures with varying proportions of resistance (0–100%) in controlling the polycyclic, splash-dispersed disease Septoria tritici blotch (STB) in durum wheat. To measure STB severity, we used a high-throughput method based on digital image analysis of 3074 infected leaves collected from 42 and 40 experimental plots during the first and second years, respectively. This allowed us to quantify pathogen reproduction on wheat leaves and to acquire a large dataset that exceeds previous studies with respect to accuracy and precision. Our analyses show that introducing only 25% of a disease-resistant cultivar into a pure stand of a susceptible cultivar provides a substantial reduction of almost 50% in disease severity compared to the susceptible pure stand. However, comprising the resistant component of two cultivars instead of one did not further improve disease control, contrary to predictions of epidemiological theory. Susceptible cultivars can be agronomically superior to resistant cultivars or be better accepted by growers for other reasons. Hence, if mixtures with only a moderate proportion of the resistant cultivar provide a similar degree of disease control as resistant pure stands, as our analysis indicates, such mixtures are more likely to be accepted by growers.</p>
Data from: Functional diversity enhances, but exploitative traits reduce tree mixture effects on microbial biomass
1. Soil microorganisms play key roles in terrestrial biodiversity and ecosystem functions. Despite recent progress in elucidating the association between plant diversity and soil microorganisms, it remains unclear whether the functional properties of plant mixtures might alter this association. 2. We examined whether the effects of tree species mixtures on soil microbial biomass were impacted by the functional diversity (FD) and community-weighted-mean (CWM) of tree mixtures, by conducting a global meta-analysis involving 123 paired observations of tree mixtures and the corresponding monocultures from 38 studies in forests. 3. We found that the tree mixture effect on microbial biomass increased with the FD of specific leaf area (SLA), leaf N and P content, as well as the FD based on all of these traits plus leaf dry matter content. Meanwhile, the responses of microbial biomass to tree mixtures decreased with the CWM of SLA, leaf N, and P content. The effects of FD and CWM remained consistent, despite variable tree species richness, stand age and climatic factors. 4. Our results provide a new insight that the functional properties of plants may alter the magnitude of the association between plant diversity and soil microorganisms.
Supplementary information to the article by van Beijnum et al. "Integrating phenotypic search and phosphoproteomic profiling of active kinases for optimization of drug mixtures for RCC treatment"
<p>Supplementary information to the article "Integrating phenotypic search and phosphoproteomic profiling of active kinases for optimization of drug mixtures for RCC treatment".</p> <p><strong>Judy R. van Beijnum<sup>1</sup>, Andrea Weiss<sup>2, 3</sup>, Robert H. Berndsen<sup>1,2 </sup>, Tse J. Wong<sup>1</sup>, Louise C. Reckman<sup>1</sup>, Sander R. Piersma<sup>4,5</sup>, Marloes Zoetemelk<sup>2,3</sup>, Richard de Haas<sup>1,4,5</sup>, Olivier Dormond<sup>6</sup>, Axel Bex<sup>7,8</sup>, Alexander A. Henneman<sup>4,5</sup>, Connie R. Jimenez<sup>4,5</sup>, Arjan W. Griffioen<sup>1</sup>, Patrycja Nowak-Sliwinska<sup>2,3,9</sup>*</strong></p> <p> </p> <p><sup>1</sup> Angiogenesis Laboratory, Department of Medical Oncology, Amsterdam UMC, Vrije Universiteit Amsterdam, Medical Oncology, Cancer Center Amsterdam, De Boelelaan 1117, Amsterdam, Netherlands;</p> <p><sup>2</sup> Molecular Pharmacology Group, School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland*;</p> <p><sup>3 </sup>Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva, Switzerland</p> <p><sup>4 </sup>Department of Medical Oncology, Amsterdam UMC, Vrije Universiteit Amsterdam, Medical Oncology, Cancer Center Amsterdam, De Boelelaan 1117, Amsterdam, Netherlands</p> <p><sup>5</sup> OncoProteomics Laboratory, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands</p> <p><sup>6</sup> Department of Visceral surgery, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland<sup> </sup> </p> <p><sup>7</sup> Royal Free London NHS Foundation Trust, Renal Cancer Centre, UCL Division of Surgical and Interventional Science, London, UK</p> <p><sup>8</sup> Netherlands Cancer Institute, Amsterdam, The Netherlands</p> <p><sup>9 </sup> Translational Research Centre in Oncohaematology, Geneva, Switzerland</p> <p> Correspondence: <a href="mailto:Patrycja.Nowak-Sliwinska@unige.ch">Patrycja.Nowak-Sliwinska@unige.ch</a></p>
Heteroplasmy Benchmark Dataset - mitochondrial DNA mixture model - MiSeq - U5-H1-M1-M2-M3-M4-M5 - BAM
<p>mtDNA mixture model of 2 mtDNA sequences belonging to haplogroups U5 and H1. Run on Illumina MiSeq with 3 different polymerases (Clontech, Herculase, NEB Taq), and different DNA extraction protocols - <strong>BAM FILES </strong></p> <p>M1 = Mixture 1:2 i.e. 50%</p> <p>M2 = Mixture 1:10 i.e. 10%</p> <p>M3 = Mixture 1:50 i.e. 2%</p> <p>M4 = Mixture 1:100 i.e. 1%</p> <p>M5 = Mixture 1:200 i.e. 0.5%</p>
Status quo in data availability and predictive models of nano-mixture toxicity
<p>Supplementary materials for manuscript: Status quo in data availability and predictive models of nano-mixture toxicity.</p> <p>This table contains the list of 183 curated literature used in this study.</p>
Effects of three-dimensional soil heterogeneity and species composition on plant biomass and biomass allocation of grass-mixtures
<p>Soil heterogeneity significantly affects plant dynamics such as plant growth and biomass. Most studies developed soil heterogeneity in two dimensions, i.e. either horizontally or vertically. However, soil heterogeneity in natural ecosystems varies both horizontally and vertically i.e. in three dimensions. Previous studies on plant biomass and biomass allocation rarely considered the joint effects of soil heterogeneity and species composition. Thus, to investigate such joint effects on plant biomass and biomass allocation, a controlled experiment was conducted, where three levels of soil heterogeneity and seven types of species compositions were applied. Such soil heterogeneity was developed by filling nutrient-rich and nutrient-poor substrates in an alternative pattern in pots with different patch sizes (small, medium or large), and species compositions was achieved by applying three plant species (i.e. Festuca elata, Bromus inermis, Elymus breviaristatus) in all possible combinations (growing either in monoculture or in mixtures). Results showed that patch size significantly impacted plant biomass and biomass allocation, which differed among plant species. Specially, at the pot scale, with increasing patch size, shoot biomass decreased, while root biomass and R: S ratio increased, and total biomass tended to show a unimodal pattern, where the medium patch supported higher total biomass. Moreover, at the substrate scale, more shoot biomass and total biomass were found in nutrient-rich substrate. Furthermore, at the community scale, two of the three target plant species growing in monoculture had more shoot biomass than those growing together with other species. Thus, our results indicate soil heterogeneity significantly affected plant biomass and biomass allocation, which differ among plant species, though more research is needed on the generalization on biomass allocation. We propose that soil heterogeneity should be considered more explicitly in studies with more species in long-term experiments.</p>
Data from: Estimating abundance of an open population with an N-mixture model using auxiliary data on animal movements
Accurate assessment of abundance forms a central challenge in population ecology and wildlife management. Many statistical techniques have been developed to estimate population sizes because populations change over time and space, and to correct for the bias resulting from animals that are present in a study area but not observed. The mobility of individuals makes it difficult to design sampling procedures that account for movement into and out of areas with fixed jurisdictional boundaries. Aerial surveys are the gold standard used to obtain data of large mobile species in geographic regions with harsh terrain, but these surveys can be prohibitively expensive and dangerous. Estimating abundance with ground based census methods have practical advantages, but it can be difficult to simultaneously account for temporary emigration and observer error to avoid biased results. Contemporary research in population ecology increasingly relies on telemetry observations of the states and locations of individuals to gain insight on vital rates, animal movements, and population abundance. Analytical models that use observations of movements to improve estimates of abundance have not been developed. Here we build upon existing multi-state mark recapture methods using a hierarchical N-mixture model with multiple sources of data, including telemetry data on locations of individuals, to improve estimates of population sizes. We used a state-space approach to model animal movements to approximate the number of marked animals present within the study area at any observation period, thereby accounting for a frequently changing number of marked individuals. We illustrate the approach using data on a population of elk (Cervus elaphus nelsoni) in Northern Colorado, USA. We demonstrate substantial improvement compared to existing abundance estimation methods and corroborate our results from the ground based surveys with estimates from aerial surveys during the same seasons. We develop a hierarchical Bayesian N-mixture model using multiple sources of data on abundance, movement and survival to estimate the population size of a mobile species that uses remote conservation areas. The model improves accuracy of inference relative to previous methods for estimating abundance of open populations.
Data from: Critically evaluating the theory and performance of Bayesian analyis of macroevolutionary mixtures
Bayesian analysis of macroevolutionary mixtures (BAMM) has recently taken the study of lineage diversification by storm. BAMM estimates the diversification-rate parameters (speciation and extinction) for every branch of a study phylogeny and infers the number and location of diversification-rate shifts across branches of a tree. Our evaluation of BAMM reveals two major theoretical errors: (i) the likelihood function (which estimates the model parameters from the data) is incorrect, and (ii) the compound Poisson process prior model (which describes the prior distribution of diversification-rate shifts across branches) is incoherent. Using simulation, we demonstrate that these theoretical issues cause statistical pathologies; posterior estimates of the number of diversification-rate shifts are strongly influenced by the assumed prior, and estimates of diversification-rate parameters are unreliable. Moreover, the inability to correctly compute the likelihood or to correctly specify the prior for rate-variable trees precludes the use of Bayesian approaches for testing hypotheses regarding the number and location of diversification-rate shifts using BAMM.
A Convex Hull Formulation for the Design of Optimal Mixtures
<p>The files contain some of the formulations implemented in GAMS for this publication. All problems are solved in GAMS version 24.2.3 and are run on a single core of a dual 6 core Intel Xeon X5675 machine at 3.07 GHz.</p> <p>Supplementary files can be found at: <em>https://zenodo.org/record/35234</em></p>
Methanol-water mixtures obtained with the OPLS force field and SPCE water model
<p>These are Gromacs trajectories, 20 ps each, with MD information corresponding to pure water (one trajectory), methanol (one trajectory), and 2:1 molar mixtures of the two (10 trajectories). The pure water system contains 800 molecules, pure methanol contains 400 molecules, and each of the mixtures contains 400 water molecules and 200 methanol molecules. The force field employed is OPLS and water was simulated with the rigid SPCE model.</p> <p>These trajectories are made available with the main purpose of being used to run one of the DoSPT tutorials:</p> <p>http://dospt.org/index.php/Tutorial_2:_entropy_of_mixing_of_methanol%2Bwater</p>
More is not always better: Peat moss mixtures slightly enhance peatland stability
<p class="MsoNormal"><span>Species-poor peatlands challenge biodiversity–ecosystem function theory, which generally links high species diversity to stable ecosystem functions. An open question in ecosystem ecology is whether assemblages of naturally co-occurring peat mosses contribute to the stability of peatland ecosystem processes. We used a replacement series mesocosm experiment with mixtures of <em>Sphagnum cuspidatum</em> and <em>S. medium</em> to assess resistance, resilience, and recovery rates of net ecosystem CO<sub>2</sub> exchange (NEE) under a mild and a deep water table drawdown event. Our results show a positive effect of mild water table drawdown on NEE with no apparent role for the composition of the peat moss assemblage. Our study indicates that the carbon uptake capacity by peat moss assemblages is rather resilient to mild water table drawdown, but seriously affected by deeper drought conditions. Co-occurring peat moss species seem to enhance the resilience of the carbon uptake function – i.e. </span><span>ability of NEE to return to pre-perturbation levels – of peat moss mixtures only slightly. These findings suggest that assemblages of co-occurring <em>Sphagnum</em> moss species do only marginally contribute to the stability of ecosystem functions in peatlands under drought conditions. We did find increased recovery with a larger share of <em>S. cuspidatum</em> in the mixtures, aiding in the ecosystem's role as carbon sink. Above all, our results highlight that predicted severe droughts can gravely affect the sink capacity of peatlands, with only a small extenuating role for peat moss mixtures.</span></p>
Mixture of three fluorophores
<p>This data was used in the following publication:</p><p>Anne Bech Risum, Jesper Løve Hinrich and Åsmund Rinnan (2024): Multi-way decomposition followed by reconvolution of fluorescence time decay data, Analytical Chemistry. DOI: 10.1021/acs.analchem.3c00634</p><p>The data is in Matlab format, and a description of the content can be found in the ReadMe.txt file</p>
A synchrotron X-ray scattering study of the crystallization behavior of mixtures of confectionary triacylglycerides: effect of chemical composition and shear on polymorphism and kinetics
<p>Processed and raw data associated at the publication: <a href="https://www.sciencedirect.com/science/article/pii/S0963996923014126" target="_blank" rel="noopener">A synchrotron X-ray scattering study of the crystallization behavior of mixtures of confectionary triacylglycerides: effect of chemical composition and shear on polymorphism and kinetics - ScienceDirect</a></p>
Data from: A synthetic biology and green bioprocess approach to recreate agarwood sesquiterpenoid mixtures
<p>Certain endangered Thymelaeaceous trees are major sources of the fragrant and highly valued resinous agarwood, comprised of hundreds of oxygenated sesquiterpenoids (STPs). Despite growing pressure on natural agarwood sources, the chemical complexity of STPs severely limits synthetic production. Here, we catalogued the chemical diversity in 58 agarwood samples by two-dimensional gas chromatography–mass spectrometry and partially recreated complex STP mixtures through synthetic biology. We improved STP yields in the unicellular alga <em>Chlamydomonas reinhardtii </em>by combinatorial engineering to biosynthesise nine macrocyclic STP backbones found in agarwood. A bioprocess following green-chemistry principles was developed that exploits 'milking' of STPs without cell lysis, solvent–solvent STP extraction, solvent–STP nanofiltration, and bulk STP oxy-functionalisation to obtain terpene mixtures like those of agarwood. This process occurs with total solvent recycling and enables continuous production. Our synthetic-biology approach offers a sustainable alternative to harvesting agarwood trees to obtain mixtures of complex, fragrant, oxygenated STPs.</p>
Data from: using camera traps and N-mixture models to estimate population abundance: model selection really matters
<p>Estimating the abundance or density of wildlife populations is a critical part of species conservation and management, but estimates can vary greatly in precision and accuracy according to the data collection and statistical methods, sampling and ecological variation, and sample size. N-mixture models are a common method which has been applied to a wide range of taxa for estimating population abundance from non-invasive data representing the distribution of the species. We used population estimates from an aerial survey of moose and videos from camera traps to assess the sensitivity of N-mixture models to ecological conditions, the spatial scale at which they were measured, the criteria used to define independent detections, and model choice based on the common statistical criterion of parsimony. The most parsimonious N-mixture models were considerably biased, producing implausibly large and considerably imprecise estimates of the abundance of moose. Most of the other models produced estimates of abundance that were ecologically realistic and relatively accurate. The accuracy of population estimates produced by N-mixture models were not overly sensitive to the formulation of models, the scale at which ecological conditions were measured, or the criteria used to define independent detection and by extension sample size. Our results suggest that parsimony was a poor measure of the predictive accuracy of the population estimates produced with the N-mixture model. Collecting and processing data from the aerial survey was less expensive and took less time, but data from camera traps can provide valuable information on behavior of the target species as well as insights into multiple species in the community.</p>
Fig. 1 in Assessing The Abundance Of Caucasian Salamander, Mertensiella Caucasica (Caudata, Salamandridae), With N-Mixture Model In Northeastern Anatolia
Fig. 1. General view of study area.
Crystalline Morphology Formation in Phase-Field Simulations of Binary Mixtures
<p>Simulation data used for the publication "Crystalline Morphology Formation in Phase-Field Simulations of Binary Mixtures" in Journal of Materials Chemistry C, Royal Society of Chemistry (2023). See README file for more details.</p>
Permeability of granular mixtures under shear - videos for shear rate 213 s-1
<p>A granular column comprising Ballotini glass beads of diameters 250 μm, 125 μm, 90 μm and 63 μm is sheared at shear rate 213 s-1, while simultanouesly being fluidised with an increasing air flux rate. The data set includes videos of the granular column for each size fraction.</p>
Permeability of granular mixtures under shear - videos for zero shear rate
<p><strong>Videos of fluidisation experiments</strong></p> <p>A static granular column comprising Ballotini glass beads of diameters 250 μm, 125 μm, 90 μm and 63 μm is fluidised with an increasing air flux rate. The data set includes videos of the granular column for each size fraction.</p>
Permeability of granular mixtures under shear
<p><strong>Data set for fluidisation experiments</strong></p> <p>A granular column cmprising Ballotini glass beads of diameters 250 μm, 125 μm, 90 μm and 63 μm is sheared at a range of shear rates, γ˙ = 0, 16, 49, 115, 213 s−1, whilst simultaneously being fluidised with an increasing air flux rate. The data set includes the values of the pressure gradient across the granular column, Δp (Pa) and the corresponding air flux rate, Q (L min-1), for each size fraction and each shear rate.</p> <p> </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.