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Data from: Predictive power of food web models based on body size decreases with trophic complexity
Food web models parameterized using body size show promise to predict trophic Interaction Strengths (IS) and abundance dynamics. However, this remains to be rigorously tested in food webs beyond simple trophic modules, where indirect and intraguild interactions could be important and driven by traits other than body size. We systematically varied predator body size, guild composition and richness in microcosm insect webs and compared experimental outcomes with predictions of IS from models with allometrically scaled parameters. Body size was a strong predictor of IS in simple modules (r2=0.92), but with increasing complexity the predictive power decreased, with model IS being consistently overestimated. We quantify the strength of observed trophic interaction modifications, partition this into density-mediated vs. behaviour-mediated indirect effects and show that model shortcomings in predicting IS is related to the size of behaviour-mediated effects. Our findings encourage development of dynamical food web models explicitly including and exploring indirect mechanisms.
Data from: Characterization of advanced glycation end products and their receptor (RAGE) in an animal model of myocardial infarction
Circulating advanced glycation end products (AGE) and their receptor, RAGE, are increased after a myocardial infarction (MI) episode and seem to be associated with worse prognosis in patients. Despite the increasing importance of these molecules in the course of cardiac diseases, they have never been characterized in an animal model of MI. Thus, the aim of this study was to characterize AGE formation and RAGE expression in plasma and cardiac tissue during cardiac remodeling after MI in rats. Adult male Wistar rats were randomized to receive sham surgery (n = 15) or MI induction (n = 14) by left anterior descending coronary artery ligation. The MI group was stratified into two subgroups based on postoperative left ventricular ejection fraction: low (MIlowEF) and intermediate (MIintermEF). Echocardiography findings and plasma levels of AGEs, protein carbonyl, and free amines were assessed at baseline and 2, 30, and 120 days postoperatively. At the end of follow-up, the heart was harvested for AGE and RAGE evaluation. No differences were observed in AGE formation in plasma, except for a decrease in absorbance in MIlowEF at the end of follow-up. A decrease in yellowish-brown AGEs in heart homogenate was found, which was confirmed by immunodetection of N-ε-carboxymethyl-lysine. No differences could be seen in plasma RAGE levels among the groups, despite an increase in MI groups over the time. However, MI animals presented an increase of 50% in heart RAGE at the end of the follow-up. Despite the inflammatory and oxidative profile of experimental MI in rats, there was no increase in plasma AGE or RAGE levels. However, AGE levels in cardiac tissue declined. Thus, we suggest that the rat MI model should be employed with caution when studying the AGE-RAGE signaling axis or anti-AGE drugs for not reflecting previous clinical findings.
Data from: The size advantage model of sex allocation in the protandrous sex-changer Crepidula fornicata: role of the mating system, sperm storage, and male mobility
Sequential hermaphroditism is adaptive when the reproductive value of an individual varies with size or age, and this relationship differs between males and females. In this case, theory shows that the lifetime reproductive output of an individual is increased by changing sex (a hypothesis referred to as the size-advantage model). Sex-linked differences in size-fitness curves can stem from differential costs of reproduction, the mating system, and differences in growth and mortality between sexes. Detailed empirical data is required to disentangle the relative roles of each of these factors within the theory. Quantitative data are also needed to explore the role of sperm storage, which has not yet been considered with sequential hermaphrodites. Using experimental rearing and paternity assignment, we report relationships between size and reproductive success of Crepidula fornicata, a protandrous (male-first) gastropod. Male reproductive success increased with size due to the polygamous system and stacking behavior of the species, but females nonetheless had greater reproductive success than males of the same size, in agreement with the size-advantage theory. Sperm storage appeared to be a critical determinant of success for both sexes, and modeling the effect of sperm storage showed that it could potentially accelerate sex change in protandrous species.
Data from: Biophysically inspired model for functionalized nanocarrier adhesion to cell surface: roles of protein expression and mechanical factors
In order to achieve selective targeting of affinity–ligand coated nanoparticles to the target tissue, it is essential to understand the key mechanisms that govern their capture by the target cell. Next-generation pharmacokinetic (PK) models that systematically account for proteomic and mechanical factors can accelerate the design, validation and translation of targeted nanocarriers (NCs) in the clinic. Towards this objective, we have developed a computational model to delineate the roles played by target protein expression and mechanical factors of the target cell membrane in determining the avidity of functionalized NCs to live cells. Model results show quantitative agreement with in vivo experiments when specific and non-specific contributions to NC binding are taken into account. The specific contributions are accounted for through extensive simulations of multivalent receptor–ligand interactions, membrane mechanics and entropic factors such as membrane undulations and receptor translation. The computed NC avidity is strongly dependent on ligand density, receptor expression, bending mechanics of the target cell membrane, as well as entropic factors associated with the membrane and the receptor motion. Our computational model can predict the in vivo targeting levels of the intracellular adhesion molecule-1 (ICAM1)-coated NCs targeted to the lung, heart, kidney, liver and spleen of mouse, when the contributions due to endothelial capture are accounted for. The effect of other cells (such as monocytes, etc.) do not improve the model predictions at steady state. We demonstrate the predictive utility of our model by predicting partitioning coefficients of functionalized NCs in mice and human tissues and report the statistical accuracy of our model predictions under different scenarios.
Data from: Bayesian model selection with BAMM: effects of the model prior on the inferred number of diversification shifts
1. Understanding variation in rates of speciation and extinction -- both among lineages and through time -- is critical to the testing of many hypotheses about macroevolutionary processes. BAMM is a flexible Bayesian framework for inferring the number and location of shifts in macroevolutionary rate across phylogenetic trees and has been widely used in empirical studies. BAMM requires that researchers specify a prior probability distribution on the number of diversification rate shifts before conducting an analysis. The consequences of this "model prior" for inference are poorly known but could potentially influence both the probability of accepting models that are more (high error rate) or less (low power) complex than the generating model. 2. The hierarchical Poisson process prior in BAMM reduces to a simple geometric distribution on number of rate shifts and we use this property to increase the efficiency of model selection with Bayes factors. Using BAMM v2.5, we analyzed phylogenies simulated with and without diversification heterogeneity across a broad range of prior parameterizations. We also assessed the impact of the model prior on MCMC convergence times and on diversification rate estimates. 3. For all simulation scenarios, model evidence (Bayes factor support) for the number of shifts is not sensitive to the choice of model prior over the wide range examined here. The best-supported model found using BAMM rarely includes spurious shifts (<2% of all runs) when diversification models are selected using Bayes factors. BAMM was reliably able to infer the true number of diversification rate shifts across prior expectations that varied by three orders of magnitude. However, we find a strong effect of model prior on MCMC convergence properties: a flatter prior distribution (larger expected number of shifts) can dramatically increase the efficiency of the MCMC simulation. 4. Our results support the use of a liberal model prior in BAMM, as it reduces computation time without distorting the evidence for rate heterogeneity.
Data from: Estimating resource preferences of a native bumblebee: the effects of availability and use-availability models on preference estimatess
Identifying resource preference is considered essential for developing targeted conservation plans but, for many species, questions remain about the best way to estimate preference. Resource preferences for bees are particularly difficult to determine as the resources they collect, nectar and pollen, are challenging to estimate availability and collection. Resources are traditionally measured at the flower or inflorescence level, but these measures of availability do not correspond to the resources actually used by bees. Additionally, it is unclear as to whether common models including availability are appropriate for bees which may target resources regardless of available quantities. Here we first compare two common hypotheses of resource use – the 'random use hypothesis' and the 'linear preferences hypothesis' – using three different measures of availability (pollen, flower and inflorescence) – to determine if one measure of availability was better for understanding bee pollen use. Next, the superior model using availability was compared to a novel model of bee pollen use the 'target use hypothesis'. This model assumes that bees target some resources regardless of how much of each resource is available (but assuming resources are present at a site), and thus models preference without availability data. Of the models including availability, the linear preference model using inflorescence availability best explained the pollen use data. This suggests that bumblebee pollen use is non-random and that cues to identify and locate resources (i.e. display size and quantity) may be more important than the quantity of the resource available (i.e. pollen availability). Additionally, in most cases the target use model explained the data equal to or better than the other models suggesting bee resource use may be better modeled without measured availability data compared to linear models. These results could be important for expanding resource use analysis of bees that are difficult to quantify availability.
Data from: Theoretical models of the influence of genomic architecture on the dynamics of speciation
A long-standing problem in evolutionary biology has been determining whether and how gradual, incremental changes at the gene level can account for rapid speciation and bursts of adaptive radiation. Using genome-scale computer simulations, we extend previous theory showing how gradual adaptive change can generate nonlinear population transitions, resulting in the rapid formation of new, reproductively isolated species. We show that these transitions occur via a mechanism rooted in a basic property of biological heredity: the organization of genes in genomes. Genomic organization of genes facilitates two processes: (i) the buildup of statistical associations among large numbers of genes, and (ii) the action of divergent selection on persistent combinations of alleles. When a population has accumulated a critical amount of standing, divergently selected variation, the combination of these two processes allows many mutations of small effect to act synergistically and precipitously split one population into two discontinuous, reproductively isolated groups. Periods of allopatry, chromosomal linkage among loci, and large-effect alleles can facilitate this process under some conditions, but are not required for it. Our results complement and extend existing theory on alternative stable states during population divergence, distinct phases of speciation, and the rapid emergence of multilocus barriers to gene flow. The results are thus a step toward aligning population genomic theory with modern empirical studies.
Data from: Cross-platform compatibility of de novo-aligned SNPs in a non-model butterfly genus
High-throughput sequencing methods for genotyping genome-wide markers are being rapidly adopted for phylogenetics of non-model organisms in conservation and biodiversity studies. However, the reproducibility of SNP genotyping and degree of marker overlap or compatibility between datasets from different methodologies have not been tested in non-model systems. Using double-digest restriction site associated DNA sequencing, we sequenced a common set of 22 specimens from the butterfly genus Speyeria on two different Illumina platforms, using two variations of library preparation. We then used a de novo approach to bioinformatic locus assembly and SNP discovery for subsequent phylogenetic analyses. We found a high rate of locus recovery despite differences in library preparation and sequencing platforms, as well as overall high levels of data compatibility after data processing and filtering. These results provide the first application of NGS methods for phylogenetic reconstruction in Speyeria, and support the use and long-term viability of SNP genotyping applications in non-model systems.
Data from: Patterns of male fitness conform to predictions of evolutionary models of late-life
We studied lifetime male virility, a male fitness component, in five populations of Drosophila melanogaster. Virility was measured as the number of females, out of eight total, that a male could fertilize in 24 hours. Individual males were measured at weekly intervals until they died. Virility declined in an approximately linear fashion for the first three weeks of adult life. It then stayed low but relatively constant for another three weeks, exhibiting a clear plateau. These observations are consistent with the evolutionary theories of late-life.The results were not consistent with a simple heterogeneity theory of late-life. This is the first demonstration of a late-life plateau for a male fitness component. We also found that the virility of males that were within seven days of death was significantly lower than similarly aged males that were not about to die. This rapid deterioration of virility prior to death, or death spiral, is similar to a decline in fecundity that we had previously documented.
Data from: Familiarity to a feed additive modulates its effects on brain responses in reward and memory regions in the pig model
Brain responses to feed flavors with or without a feed additive (FA) were investigated in piglets familiarized or not with this FA. Sixteen piglets were allocated to 2 dietary treatments from weaning until d 37: the naive group (NAI) received a standard control feed and the familiarized group (FAM) received the same feed added with a FA mainly made of orange extracts. Animals were subjected to a feed transition at d 16 post-weaning, and to 2-choice feeding tests at d 16 and d 23. Production traits of the piglets were assessed up to d 28 post-weaning. From d 26 onwards, animals underwent 2 brain imaging sessions (positron emission tomography of 18FDG) under anesthesia to investigate the brain activity triggered by the exposure to the flavors of the feed with (FA) or without (C) the FA. Images were analyzed with SPM8 and a region of interest (ROI)-based small volume correction (p < 0.05, k ≥ 25 voxels per cluster). The brain ROI were selected upon their role in sensory evaluation, cognition and reward, and included the prefrontal cortex, insular cortex, fusiform gyrus, limbic system and corpus striatum. The FAM animals showed a moderate preference for the novel post-transition FA feed compared to the C feed on d 16, i.e., day of the feed transition (67% of total feed intake). The presence or absence of the FA in the diet from weaning had no impact on body weight, average daily gain, and feed efficiency of the animals over the whole experimental period (p ≥ 0.10). Familiar feed flavors activated the prefrontal cortex. The amygdala, insular cortex, and prepyriform area were only activated in familiarized animals exposed to the FA feed flavor. The perception of FA feed flavor in the familiarized animals activated the dorsal striatum differently than the perception of the C feed flavor in naive animals. Our data demonstrated that the perception of FA in familiarized individuals induced different brain responses in regions involved in reward anticipation and/or perception processes than the familiar control feed flavor in naive animals. Chronic exposure to the FA might be necessary for positive hedonic effects, but familiarity only cannot explain them.
Data from: Modelling competition and dispersal in a statistical phylogeographic framework
Competition between organisms influences the processes governing the colonization of new habitats. As a consequence, species or populations arriving first at a suitable location may prevent secondary colonization. While adaptation to environmental variables (e.g., temperature, altitude, etc.) is essential, the presence or absence of certain species at a particular location often depends on whether or not competing species co-occur. For example, competition is thought to play an important role in structuring mammalian communities assembly. It can also explain spatial patterns of low genetic diversity following rapid colonization events or the "progression rule" displayed by phylogenies of species found on archipelagos. Despite the potential of competition to maintain populations in isolation, past quantitative analyses have largely ignored it because of the difficulty in designing adequate methods for assessing its impact. We present here a new model that integrates competition and dispersal into a Bayesian phylogeographic framework. Extensive simulations and analysis of real data show that our approach clearly outperforms the traditional Mantel test for detecting correlation between genetic and geographic distances. But most importantly, we demonstrate that competition can be detected with high sensitivity and specificity from the phylogenetic analysis of genetic variation in space.
Data from: Phylodynamic model adequacy using posterior predictive simulations
Rapidly evolving pathogens, such as viruses and bacteria, accumulate genetic change at a similar timescale over which their epidemiological processes occur, such that it is possible to make inferences about their infectious spread using phylogenetic time-trees. For this purpose it is necessary to choose a phylodynamic model. However, the resulting inferences are contingent on whether the model adequately describes key features of the data. Model adequacy methods allow formal rejection of a model if it cannot generate the main features of the data. We present TreeModelAdequacy (TMA), a package for the popular BEAST2 software, that allows assessing the adequacy of phylodynamic models. We illustrate its utility by analysing phylogenetic trees from two viral outbreaks of Ebola and H1N1 influenza. The main features of the Ebola data were adequately described by the coalescent exponential-growth model, whereas the H1N1 influenza data was best described by the birth-death SIR model.
Data from: Mixed linear model approach for mapping quantitative trait loci underlying crop seed traits
The crop seed is a complex organ that may be composed of the diploid embryo, the triploid endosperm and the diploid maternal tissues. According to the genetic features of seed characters, two genetic models for mapping quantitative trait loci (QTLs) of crop seed traits are proposed, with inclusion of maternal effects, embryo or endosperm effects of QTL, environmental effects and QTL-by-environment (QE) interactions. The mapping population can be generated either from double back-cross of immortalized F2 (IF2) to the two parents, from random-cross of IF2 or from selfing of IF2 population. Candidate marker intervals potentially harboring QTLs are first selected through one-dimensional scanning across the whole genome. The selected candidate marker intervals are then included in the model as cofactors to control background genetic effects on the putative QTL(s). Finally, a QTL full model is constructed and model selection is conducted to eliminate false positive QTLs. The genetic main effects of QTLs, QE interaction effects and the corresponding P-values are computed by Markov chain Monte Carlo algorithm for Gaussian mixed linear model via Gibbs sampling. Monte Carlo simulations were performed to investigate the reliability and efficiency of the proposed method. The simulation results showed that the proposed method had higher power to accurately detect simulated QTLs and properly estimated effect of these QTLs. To demonstrate the usefulness, the proposed method was used to identify the QTLs underlying fiber percentage in an upland cotton IF2 population. A computer software, QTLNetwork-Seed, was developed for QTL analysis of seed traits.
Data from: Are Bitcoin bubbles predictable? Combining a generalized Metcalfe's law and the LPPLS model
We develop a strong diagnostic for bubbles and crashes in Bitcoin, by analyzing the coincidence (and its absence) of fundamental and technical indicators. Using a generalized Metcalfe's law based on network properties, a fundamental value is quantified and shown to be heavily exceeded, on at least four occasions, by bubbles that grow and burst. In these bubbles, we detect a universal super-exponential unsustainable growth. We model this universal pattern with the Log-Periodic Power Law Singularity (LPPLS) model, which parsimoniously captures diverse positive feedback phenomena, such as herding and imitation. The LPPLS model is shown to provide an ex-ante warning of market instabilities, quantifying a high crash hazard and probabilistic bracket of the crash time consistent with the actual corrections; although, as always, the precise time and trigger (which straw breaks the camel's back) being exogenous and unpredictable. Looking forward, our analysis identifies a substantial but not unprecedented overvaluation in the price of Bitcoin, suggesting many months of volatile sideways Bitcoin prices ahead (from the time of writing, March 2018).
Data from: Avian malaria: a new lease of life for an old experimental model to study the evolutionary ecology of Plasmodium
Avian malaria has historically played an important role as a model in the study of human malaria, being a stimulus for the development of medical parasitology. Avian malaria has recently come back to the research scene as a unique animal model to understand the ecology and evolution of the disease, both in the field and in the laboratory. Avian malaria is highly prevalent in birds and mosquitoes around the world and is amenable to laboratory experimentation at each stage of the parasite's life cycle. Here, we take stock of 5 years of experimental laboratory research carried out using Plasmodium relictum SGS1, the most prevalent avian malaria lineage in Europe, and its natural vector, the mosquito Culex pipiens. For this purpose, we compile and analyse data obtained in our laboratory in 14 different experiments. We provide statistical relationships between different infection-related parameters, including parasitaemia, gametocytaemia, host morbidity (anaemia) and transmission rates to mosquitoes. This analysis provides a wide-ranging picture of the within-host and between-host parameters that may bear on malaria transmission and epidemiology.
Data from: Does gene tree discordance explain the mismatch between macroevolutionary models and empirical patterns of tree shape and branching times?
Classic null models for speciation and extinction give rise to phylogenies that differ in distribution from empirical phylogenies. In particular, empirical phylogenies are less balanced and have branching times closer to the root compared to phylogenies predicted by common null models. This difference might be due to null models of the speciation and extinction process being too simplistic, or due to the empirical datasets not being representative of random phylogenies. A third possibility arises because phylogenetic reconstruction methods often infer gene trees rather than species trees, producing an incongruity between models that predict species tree patterns and empirical analyses that consider gene trees. We investigate the extent to which the difference between gene trees and species trees under a combined birth–death and multispecies coalescent model can explain the difference in empirical trees and birth–death species trees. We simulate gene trees embedded in simulated species trees and investigate their difference with respect to tree balance and branching times. We observe that the gene trees are less balanced and typically have branching times closer to the root than the species trees. Empirical trees from TreeBase are also less balanced than our simulated species trees, and model gene trees can explain an imbalance increase of up to 8% compared to species trees. However, we see a much larger imbalance increase in empirical trees, about 100%, meaning that additional features must also be causing imbalance in empirical trees. This simulation study highlights the necessity of revisiting the assumptions made in phylogenetic analyses, as these assumptions, such as equating the gene tree with the species tree, might lead to a biased conclusion.
Data from: A prediction model of compressor with variable geometry diffuser based on elliptic equation and Partial Least Squares
In order to fulfill more and more extensive intake air flow range of diesel engine, variable geometry compressor (VGC) is introduced into turbocharged diesel engine. However, due to the variable diffuser vanes angle (DVA), the prediction for the performance of VGC becomes more difficult than normal compressor. In the present study, a prediction model comprised of elliptical equation and PLS (Partial Least Squares) model was proposed to predict the performance of VGC. The speed lines of pressure ratio map and efficiency map with elliptical equation were fitted, and the coefficients of elliptical equation was introduced into PLS model to build the polynomial relationship between the coefficients and relative speed, DVA. And further, the maximal order of polynomical was detailed investigated to reduce the number of sub-coefficients and acceptable fit accuracy simultaneously. The prediction model was validated with sample data and in order to present the superiority in compressor performance prediction, the prediction results of this model were compared with those of look-up table and BPNN. The validation and comparison results show that the prediction accuracy of the new developed model is acceptable, and this model is much more suitable than look-up table and BPNN under the same condition in the VGA performance prediction. Moreover, the new developed prediction model provides a novel and effective prediction solution for VGC and can be used to improve the accuracy of the thermodynamic model for turbocharged diesel engines in the future.
Data from: Dynamic occupancy modeling reveals a hierarchy of competition among fishers, grey foxes, and ringtails
1. Determining how species coexist is critical for understanding functional diversity, niche partitioning and interspecific interactions. Identifying the direct and indirect interactions among sympatric carnivores that enable their coexistence are particularly important to elucidate because they are integral for maintaining ecosystem function. 2. We studied the effects of removing 9 fishers (Pekania pennanti) on their population dynamics and used this perturbation to elucidate the interspecific interactions among fishers, grey foxes (Urocyon cinereoargenteus), and ringtails (Bassariscus astutus). Grey foxes (family: Canidae) are likely to compete with fishers due to their similar body sizes and dietary overlap, and ringtails (family: Procyonidae), like fishers, are semi-arboreal species of conservation concern. We used spatial capture-recapture to investigate fisher population numbers and dynamic occupancy models that incorporated interspecific interactions to investigate the effects members of these species had on the colonization and persistence of each other's site occupancy. 3. The fisher population showed no change in density for up to three years following the removals of fishers for translocations. In contrast, fisher site occupancy decreased in the years immediately following the translocations. During this same time period, site occupancy by grey foxes increased and remained elevated through the end of the study. 4. We found a complicated hierarchy among fishers, foxes, and ringtails. Fishers affected grey fox site persistence negatively but had a positive effect on their colonization. Foxes had a positive effect on ringtail site colonization. Thus, fishers were the dominant small carnivore where present and negatively affected foxes directly and ringtails indirectly. 5. Coexistence among the small carnivores we studied appears to reflect dynamic spatial partitioning. Conservation and management efforts should investigate how intraguild interactions may influence the recolonization of carnivores to previously occupied landscapes.
Data from: The response of migratory populations to phenological change: a Migratory Flow Network modelling approach
1. Declines in migratory species have been linked to anthropogenic climate change through phenological mismatch, which arises due to asynchronies between the timing of life-history events (such as migration) and the phenology of available resources. Long-distance migratory species may be particularly vulnerable to phenological change in their breeding ranges, since the timing of migration departure is based on environmental cues at distant non-breeding sites. 2. Migrants may, however, be able to adjust migration speed en route to the breeding grounds and thus ability of migrants to update their timing of migration may depend critically on stopover frequency during migration; however, understanding how migratory strategy influences population dynamics is hindered by a lack of predictive models explicitly linking habitat quality to demography and movement patterns throughout the migratory cycle. 3. Here, we present a novel modelling framework, the Migratory Flow Network (MFN), in which the seasonally varying attractiveness of breeding, winter, and stopover regions drives the direction and timing of migration based on a simple general flux law. 4. We use the MFN to investigate how populations respond to shifts in breeding site phenology based on their frequency of stopover and ability to detect and adapt to these changes. 5. With perfect knowledge of advancing phenology, 'jump' migrants (low frequency stopover) require more adaptation for populations to recover than 'hop' and 'skip' (high or medium frequency stopover) migrants. If adaptation depends on proximity, hop and skip migrants' populations can recover but jump migrants cannot adjust and decline severely. 6. These results highlight the importance of understanding migratory strategies and maintaining high-quality stopover habitat to buffer migratory populations from climate-induced mismatch. 7. We discuss how MFNs could be applied to diverse migratory taxa, and highlight the potential of MFNs as a tool for exploring how migrants respond to other environmental changes such as habitat loss.
Data from: The contribution of marine aggregate-associated bacteria to the accumulation of pathogenic bacteria in oysters: an agent-based model
Bivalves process large volumes of water, leading to their accumulation of bacteria, including potential human pathogens (e.g., vibrios). These bacteria are captured at low efficiencies when freely suspended in the water column, but they also attach to marine aggregates, which are captured with near 100% efficiency. For this reason, and because they are often enriched with heterotrophic bacteria, marine aggregates have been hypothesized to function as important transporters of bacteria into bivalves. The relative contribution of aggregates and unattached bacteria to the accumulation of these cells, however, is unknown. We developed an agent-based model to simulate accumulation of vibrio-type bacteria in oysters. Simulations were conducted over a realistic range of concentrations of bacteria and aggregates and incorporated the dependence of pseudofeces production on particulate matter. The model shows that the contribution of aggregate-attached bacteria depends strongly on the unattached bacteria, which form the colonization pool for aggregates and are directly captured by the simulated oysters. The concentration of aggregates is also important, but its effect depends on the concentration of unattached bacteria. At high bacterial concentrations, aggregates contribute the majority of bacteria in the oysters. At low concentrations of unattached bacteria, aggregates have a neutral or even a slightly negative effect on bacterial accumulation. These results provide the first evidence suggesting that the concentration of aggregates could influence uptake of pathogenic bacteria in bivalves and show that the tendency of a bacterial species to remain attached to aggregates is a key factor for understanding species-specific accumulation.
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.