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Data from: Using striated tooth marks on bone to predict body size in theropod dinosaurs: a model based on feeding observations of Varanus komodoensis, the Komodo monitor
Mesozoic tooth marks on bone surfaces directly link consumers to fossil assemblage formation. Striated tooth marks are believed to form by theropod denticle contact, and attempts have been made to identify theropod consumers by comparing these striations with denticle widths of contemporaneous taxa. The purpose of this study is to test whether ziphodont theropod consumer characteristics may be accurately identified from striated tooth marks on fossil surfaces. There are three major objectives; 1) experimentally produce striated tooth marks and explain how they form; 2) determine whether body size characteristics are reflected in denticle widths; 3) determine whether denticle characters are accurately transcribed onto bone surfaces in the form of striated tooth marks. Controlled feeding trials were conducted with the dental analogue Varanus komodoensis (the Komodo monitor). Goat (Capra hircus) carcasses were introduced to captive, isolated individuals. Striated tooth marks were then identified, and striation width, number, and degree of divergence were recorded for each. Denticle widths and tooth/body size characters were taken from photographs and published accounts of both theropod and V. komodoensis skeletal material, and regressions were compared among and between the two groups. Striated marks tend to be regularly striated with a variable degree of branching, and may co-occur with scores. Striation morphology directly reflects contact between the mesial carina and bone surfaces during the rostral reorientation when defleshing. Denticle width is primarily influenced by tooth size, and correlates well with body size displaying negative allometry in both groups regardless of taxon or position. When compared, striation widths fall within or below the range of denticle widths extrapolated for similar sized V. komodoensis individuals. Striation width is directly influenced by the orientation of the carina during feeding, and may underestimate but cannot overestimate denticle width. Although body size may theoretically be estimated solely by a striated tooth mark under ideal circumstances, many caveats should be considered. These include the influence of negative allometry across taxa and throughout ontogeny, the existence of theropods with extreme denticle widths, and the potential for striations to underestimate denticle widths. This method may be useful under specific circumstances, especially for establishing a lower limit body size for potential consumers.
Data from: Using social parasitism to test reproductive skew models in a primitively eusocial wasp
Remarkable variation exists in the distribution of reproduction (skew) among members of cooperatively breeding groups, both within and between species. Reproductive skew theory has provided an important framework for understanding this variation. In the primitively eusocial Hymenoptera, two models have been routinely tested: concessions models, which assume complete control of reproduction by a dominant individual, and tug-of-war models, which assume on-going competition among group members over reproduction. Current data provide little support for either model, but uncertainty about the ability of individuals to detect genetic relatedness and difficulties in identifying traits conferring competitive ability mean that the relative importance of concessions versus tug-of-war remains unresolved. Here, we suggest that the use of social parasitism to generate meaningful variation in key social variables represents a valuable opportunity to explore the mechanisms underpinning reproductive skew within the social Hymenoptera. We present a direct test of concessions and tug-of-war models in the paper wasp Polistes dominulus by exploiting pronounced changes in relatedness and power structures that occur following replacement of the dominant by a congeneric social parasite. Comparisons of skew in parasitized and unparasitized colonies are consistent with a tug-of-war over reproduction within P. dominulus groups, but provide no evidence for reproductive concessions.
Data from: Understanding past population dynamics: Bayesian coalescent-based modeling with covariates
Effective population size characterizes the genetic variability in a population and is a parameter of paramount importance in population genetics and evolutionary biology. Kingman's coalescent process enables inference of past population dynamics directly from molecular sequence data, and researchers have developed a number of flexible coalescent-based models for Bayesian nonparametric estimation of the effective population size as a function of time. Major goals of demographic reconstruction include identifying driving factors of effective population size, and understanding the association between the effective population size and such factors. Building upon Bayesian nonparametric coalescent-based approaches, we introduce a flexible framework that incorporates time-varying covariates that exploit Gaussian Markov random fields to achieve temporal smoothing of effective population size trajectories. To approximate the posterior distribution, we adapt efficient Markov chain Monte Carlo algorithms designed for highly structured Gaussian models. Incorporating covariates into the demographic inference framework enables the modeling of associations between the effective population size and covariates while accounting for uncertainty in population histories. Furthermore, it can lead to more precise estimates of population dynamics. We apply our model to four examples. We reconstruct the demographic history of raccoon rabies in North America and find a significant association with the spatiotemporal spread of the outbreak. Next, we examine the effective population size trajectory of the DENV-4 virus in Puerto Rico along with viral isolate count data and find similar cyclic patterns. We compare the population history of the HIV-1 CRF02_AG clade in Cameroon with HIV incidence and prevalence data and find that the effective population size is more reflective of incidence rate. Finally, we explore the hypothesis that the population dynamics of musk ox during the Late Quaternary period were related to climate change.
Data from: Differential chromosome conformations as hallmarks of cellular identity revealed by mathematical polymer modeling
Inherently dynamic, chromosomes adopt many different conformations in response to DNA metabolism. Models of chromosome organization in the yeast nucleus obtained from genome-wide chromosome conformation data or biophysical simulations provide important insights into the average behavior but fail to reveal features from dynamic or transient events that are only visible in a fraction of cells at any given moment. We developed a method to determine chromosome conformation from relative positions of three fluorescently tagged DNA in living cells imaged in 3D. Cell type specific chromosome folding properties could be assigned based on positional combinations between three loci on yeast chromosome 3. We determined that the shorter left arm of chromosome 3 is extended in MATα cells, but can be crumpled in MATa cells. Furthermore, we implemented a new mathematical model that provides for the first time an estimate of the relative physical constraint of three linked loci related to cellular identity. Variations in this estimate allowed us to predict functional consequences from chromatin structural alterations in asf1 and recombination enhancer deletion mutant cells. The computational method is applicable to identify and characterize dynamic chromosome conformations in any cell type.
Data from: A computational model of flow between the microscale respiratory structures of fish gills
The gills of most teleost fishes are covered by plate-like structures, the secondary lamellae, that provide the bulk of the respiratory surface area. Water passing over the secondary lamellae exchanges gases with blood passing through the secondary lamellae, forming a system that has served as a classic model of counter-current exchange. In this study, a computational model of flow around the secondary lamellae is used to examine the hydrodynamic consequences of changes to the lamellar morphology. Consistent with previous studies, the interlamellar distance is found to strongly affect the hydrodynamic resistance of the gills. However, the presence of a small gap between the tips of the secondary lamellae is found to have a similar strong effect on the hydrodynamic resistance and flow patterns within the gills. The results from this model have been generally formulated, allowing the calculation of the hydrodynamic resistance for measured morphometric parameters. These results provide a new basis for comparing theoretical predictions of the gill resistance with measured values, and provide a general model for examining the diversity gill morphologies observed in teleost fishes.
Data from: Multi-scale model of CRISPR-induced coevolutionary dynamics: diversification at the interface of Lamarck and Darwin
The CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) system is a recently discovered type of adaptive immune defense in bacteria and archaea that functions via directed incorporation of viral and plasmid DNA into host genomes. Here, we introduce a multi-scale model of dynamic coevolution between hosts and viruses in an ecological context that incorporates CRISPR immunity principles. We analyze the model to test whether and how CRISPR immunity induces host and viral diversification and the maintenance of many coexisting strains. We show that hosts and viruses coevolve to form highly diverse communities. We observe the punctuated replacement of extant strains, so that populations have very low similarity compared over the long term. However in the short term, we observe evolutionary dynamics consistent with both incomplete selective sweeps of novel strains and the recurrence of previously rare strains. Coalitions of multiple dominant host strains are predicted to arise because host strains can have nearly identical immune phenotypes mediated by CRISPR defense albeit with different genotypes. We close by discussing how our explicit eco-evolutionary model of CRISPR immunity can help guide efforts to understand the drivers of diversity seen in microbial communities where CRISPR systems are active.
Data from: Complex models of sequence evolution require accurate estimators as exemplified with the invariable site plus Gamma model
The invariable site plus Γ model is widely used to model rate heterogeneity among alignment sites in maximum likelihood and Bayesian phylogenetic analyses. The proof that the invariable site plus continuous Γ model is identifiable (model parameters can be inferred correctly given enough data) has increased the creditability of its application to phylogeny reconstruction. However, most phylogenetic software implement the invariable site plus discrete Γ model, whose identifiability is likely but unproven. How well the parameters of the invariable site plus discrete Γ model are estimated is still disputed. Especially the correlation of the fraction of invariable sites with the fractions of sites with a slow evolutionary rate is discussed as being problematic. We show that optimization heuristics as implemented in frequently used phylogenetic software cannot always reliably estimate the shape parameter, the proportion of invariable sites and the tree length. Here, we propose an improved optimization heuristic that accurately estimates the three parameters. While research efforts mainly focus on tree search methods, our results signify the equal importance of verifying and developing effective estimation methods for complex models of sequence evolution.
Data from: The 'golden kelp' Laminaria ochroleuca under global change: integrating multiple eco-physiological responses with species distribution models
1. The loss of marine foundation species, in particular kelps at temperate latitudes, has been linked to climatic drivers and co-occurring human perturbations. Ocean temperature and nutrients typically co-vary over local and regional scales and play a crucial role on kelp dynamics. Examining their independent and interactive effects on kelp physiological performance is essential to understand and predict patterns of kelp distribution, particularly under scenarios of global change. 2. Crossed combinations of ocean temperatures and availability of nutrients were experimentally tested on juveniles of the 'golden kelp', Laminaria ochroleuca, from the northwestern Iberian Peninsula. Eco-physiological responses included: survival, growth and total N content. Results were embedded into a Species Distribution Model (SDM), which relates presence records and climatic and non-climatic data to forecast distribution patterns of L. ochroleuca under different climate change scenarios. 3. Temperatures above 24.6 ºC were lethal irrespective of nutrients. Optimal growth of juvenile sporophytes occurred between 12 °C and 18 ºC and no nutrient limitation. The SDM, where ocean temperature was the main predictor of kelp distribution in line with temperature thresholds given by eco-physiological responses, suggests a future expansion towards northern latitudes and a retreat from the southern limit/boundary of the current distribution. 4. Synthesis. Range-shifting of the golden kelp can have severe ecological impacts at regional and local scales. The expansion or retraction of the species along the European coast seems to be modulated mainly by temperature, but nutrient availability would be key to maintain optimal physiological performance. Our work highlights that the combination of empirical and modelling approaches is accessible to researchers and crucial to build more robust predictions of ecological and biogeographic responses of habitat-forming species to forecasted environmental change.
Data from: Characterization of leukemia-inducing genes using a proto-oncogene/homeobox gene retroviral human cDNA library in a mouse in vivo model
The purpose of this research is to develop a method to screen a large number of potential driver mutations of acute myeloid leukemia (AML) using a retroviral cDNA library and murine bone marrow transduction-transplantation system. As a proof-of-concept, murine bone marrow (BM) cells were transduced with a retroviral cDNA library encoding well-characterized oncogenes and homeobox genes, and the virus-transduced cells were transplanted into lethally irradiated mice. The proto-oncogenes responsible for leukemia initiation were identified by PCR amplification of cDNA inserts from genomic DNA isolated from leukemic cells. In an initial screen of ten leukemic mice, the MYC proto-oncogene was detected in all the leukemic mice. Of ten leukemic mice, 3 (30%) had MYC as the only transgene, and seven mice (70%) had additional proto-oncogene inserts. We repeated the same experiment after removing MYC-related genes from the library to characterize additional leukemia-inducing gene combinations. Our second screen using the MYC-deleted proto-oncogene library confirmed MEIS1and the HOX family as cooperating oncogenes in leukemia pathogenesis. The model system we introduced in this study will be valuable in functionally screening novel combinations of genes for leukemogenic potential in vivo, and the system will help in the discovery of new targets for leukemia therapy.
Data from: Overexpression of Dyrk1A is implicated in several cognitive, electrophysiological and neuromorphological alterations found in a mouse model of Down syndrome
Down syndrome (DS) phenotypes result from the overexpression of several dosage-sensitive genes. The DYRK1A (dual-specificity tyrosine-(Y)-phosphorylation regulated kinase 1A) gene, which has been implicated in the behavioral and neuronal alterations that are characteristic of DS, plays a role in neuronal progenitor proliferation, neuronal differentiation and long-term potentiation (LTP) mechanisms that contribute to the cognitive deficits found in DS. The purpose of this study was to evaluate the effect of Dyrk1A overexpression on the behavioral and cognitive alterations in the Ts65Dn (TS) mouse model, which is the most commonly utilized mouse model of DS, as well as on several neuromorphological and electrophysiological properties proposed to underlie these deficits. In this study, we analyzed the phenotypic differences in the progeny obtained from crosses of TS females and heterozygous Dyrk1A (+/−) male mice. Our results revealed that normalization of the Dyrk1A copy number in TS mice improved working and reference memory based on the Morris water maze and contextual conditioning based on the fear conditioning test and rescued hippocampal LTP. Concomitant with these functional improvements, normalization of the Dyrk1A expression level in TS mice restored the proliferation and differentiation of hippocampal cells in the adult dentate gyrus (DG) and the density of GABAergic and glutamatergic synapse markers in the molecular layer of the hippocampus. However, normalization of the Dyrk1A gene dosage did not affect other structural (e.g., the density of mature hippocampal granule cells, the DG volume and the subgranular zone area) or behavioral (i.e., hyperactivity/attention) alterations found in the TS mouse. These results suggest that Dyrk1A overexpression is involved in some of the cognitive, electrophysiological and neuromorphological alterations, but not in the structural alterations found in DS, and suggest that pharmacological strategies targeting this gene may improve the treatment of DS-associated learning disabilities.
Data from: Avian diversification patterns across the K-Pg boundary: influence of calibrations, datasets and model misspecification
Birds represent the most diverse extant tetrapod clade, with ca. 10,000 extant species, and the timing of the crown avian radiation remains hotly debated. The fossil record supports a primarily Cenozoic radiation of crown birds, whereas molecular divergence dating analyses generally imply that this radiation was well underway during the Cretaceous. Furthermore, substantial differences have been noted between published divergence estimates. These have been variously attributed to clock model, calibration regime, and gene type. One underappreciated phenomenon is that disparity between fossil ages and molecular dates tends to be proportionally greater for shallower nodes in the avian Tree of Life. Here, we explore potential drivers of disparity in avian divergence dates through a set of analyses applying various calibration strategies and coding methods to a mitochondrial genome dataset and an 18-gene nuclear dataset, both sampled across 72 taxa. Our analyses support the occurrence of two deep divergences (i.e., the Palaeognathae/Neognathae split and the Galloanserae/Neoaves split) well within the Cretaceous, followed by a rapid radiation of Neoaves near the K-Pg boundary. However, 95% highest posterior density intervals for most basal divergences in Neoaves cross the boundary, and we emphasize that, barring unreasonably strict prior distributions, distinguishing between a rapid Early Paleocene radiation and a Late Cretaceous radiation may be beyond the resolving power of currently favored divergence dating methods. In contrast to recent observations for placental mammals, constraining all divergences within Neoaves to occur in the Cenozoic does not result in unreasonably high inferred substitution rates. Comparisons of nuclear DNA (nDNA) versus mitochondrial DNA (mtDNA) datasets and NT- versus RY-coded mitochondrial data reveal patterns of disparity that are consistent with substitution model misspecifications that result in tree compression/tree extension artifacts, which may explain some discordance between previous divergence estimates based on different sequence types. Comparisons of fully calibrated and nominally calibrated trees support a correlation between body mass and apparent dating error. Overall, our results are consistent with (but do not require) a Paleogene radiation for most major clades of crown birds.
Data from: Assortative mating by an obliquely transmitted local cultural trait promotes genetic divergence: a model
The effect of learned culture (e.g., birdsong dialects and human languages) on genetic divergence is unclear. Previous theoretical research suggests that because oblique learning allows phenotype transmission from individuals with no offspring to an unrelated individual in the next generation, the effect of sexual selection on the learned trait is masked. However, I propose that migration and spatially constrained learning can form statistical associations between cultural and genetic traits, which may allow selection on the cultural traits to indirectly affect the genetic traits. Here, I build a population genetic model that allows such statistical associations to form, and find that sexual selection and divergent selection on the cultural trait can indeed help maintain genetic divergence through such statistical associations, while selection against genetic hybrids does not affect cultural trait divergence. Furthermore, I find that even when the cultural trait changes over time due to drift and mutation, it can still help maintain genetic divergence. These results suggest the role of obliquely transmitted traits in evolution may be underrated, and the lack of one-to-one associations between cultural and genetic traits may not be sufficient to disprove the role of culture in genetic divergence.
Data from: Using historical biogeography models to study color pattern evolution
Color is among the most striking features of organisms, varying not only in spectral properties like hue and brightness, but also in where and how it is produced on the body. Different combinations of colors on a bird's body are important in both environmental and social contexts. Previous comparative studies have treated plumage patches individually or derived plumage complexity scores from color measurements across a bird's body. However, these approaches do not consider the multivariate nature of plumages (allowing for plumage to evolve as a whole) or account for interpatch distances. Here, we leverage a rich toolkit used in historical biogeography to assess color pattern evolution in a cosmopolitan radiation of birds, kingfishers (Aves: Alcedinidae). We demonstrate the utility of this approach and test hypotheses about the tempo and mode of color evolution in kingfishers. Our results highlight the importance of considering interpatch distances in understanding macroevolutionary trends in color diversity and demonstrate how historical biogeography models are a useful way to model plumage color pattern evolution. Furthermore, they show that distinct color mechanisms (pigments or structural colors) spread across the body in different ways and at different rates. Specifically, net rates are higher for structural colors than pigment-based colors. Together, our study suggests a role for both development and selection in driving extraordinary color pattern diversity in kingfishers. We anticipate this approach will be useful for modeling other complex phenotypes besides color, such as parasite evolution across the body.
Data from: PartitionFinder: combined selection of partitioning schemes and substitution models for phylogenetic analyses.
In phylogenetic analyses of molecular sequence data, partitioning involves estimating independent models of molecular evolution for different sets of sites in a sequence alignment. Choosing an appropriate partitioning scheme is an important step in most analyses because it can affect the accuracy of phylogenetic reconstruction. Despite this, partitioning schemes are often chosen without explicit statistical justification. Here, we describe two new objective methods for the combined selection of best-fit partitioning schemes and nucleotide substitution models. These methods allow millions of partitioning schemes to be compared in realistic timeframes, and so permit the objective selection of partitioning schemes even for large multi-locus DNA datasets. We demonstrate that these methods significantly outperform previous approaches, including the ad hoc selection of partitioning schemes (e.g. partitioning by gene or codon position), and a recently proposed hierarchical clustering method. We have implemented these methods in an open-source program, PartitionFinder. This program allows users to select partitioning schemes and substitution models using a range of information-theoretic metrics (e.g. the BIC, AIC, and AICc). We hope that PartitionFinder will encourage the objective selection of partitioning schemes, and thus lead to improvements in phylogenetic analyses. PartitionFinder is written in Python and runs under Mac OSX 10.4 and above. The program, source code, and a detailed manual are freely available from .
Data from: The fitness of drug-resistant malaria parasites in a rodent model: multiplicity of infection
Malaria infections normally consist of more than one clonally-replicating lineage. Within-host interactions between sensitive and resistant parasites can have profound effects on the evolution of drug resistance. Here, using the Plasmodium chabaudi mouse malaria model, we ask whether the costs and benefits of resistance are affected by the number of co-infecting strains competing with a resistant clone. We found strong competitive suppression of resistant parasites in untreated infections and marked competitive release following treatment. The magnitude of competitive suppression depended on competitor identity. However, there was no overall effect of the diversity of susceptible parasites on the extent of competitive suppression or release. If these findings generalize, then transmission intensity will impact on resistance evolution because of its effect on the frequency of mixed infections, not because of its effect on the distribution of clones per host. This would greatly simplify the computational problems of adequately capturing within-host ecology in models of drug resistance evolution in malaria.
Data from: Habitat-based species distribution modelling of the Hawaiian deepwater snapper-grouper complex
Deepwater snappers and groupers are valuable components of many subtropical and tropical fisheries globally and understanding the habitat associations of these species is important for spatial fisheries management. Habitat-based species distribution models were developed for the deepwater snapper-grouper complex in the main Hawaiian Islands (MHI). Six eteline snappers (Pristipomoides spp., Aphareus rutilans, and Etelis spp.) and one endemic grouper (Hyporthodus quernus) comprise the species complex known as the Hawaiian Deep Seven Bottomfishes. Species occurrence was recorded using baited remote underwater video stations deployed between 30 and 365 m (n = 2381) and was modeled with 12 geomorphological covariates using GLMs, GAMs, and BRTs. Depth was the most important predictor across species, along with ridge-like features, rugosity, and slope. In particular, ridge-like features were important habitat predictors for E. coruscans and P. filamentosus. Bottom hardness was an important predictor especially for the two Etelis species. Along with depth, rugosity and slope were the most important habitat predictors for A. rutilans and P. zonatus, respectively. Models built using GAMs and BRTs generally had the highest predictive performance. Finally, using the BRT model output, we created species-specific distribution maps and demonstrated that areas with high predicted probabilities of occurrence were positively related to fishery catch rates.
Data from: Multiresponse algorithms for community-level modeling: review of theory, applications, and comparison to species distribution models
1.Community-level models (CLMs) consider multiple, co-occurring species in model fitting and are lesser known alternatives to species distribution models (SDMs) for analyzing and predicting biodiversity patterns. CLMs simultaneously model multiple species, including rare species, while reducing overfitting and implicitly considering drivers of co-occurrence. Many CLMs are direct extensions of well-known SDMs and therefore should be familiar to ecologists. However, CLMs remain underutilized, and there have been few tests of their potential benefits and no systematic reviews of their assumptions and implementations. Here we review this emerging field and provide examples in R to fit common CLMs. Our goal is to introduce CLMs to a broader audience, and discuss their attributes, benefits, and limitations relative to SDMs. 2.We review i) statistical implementations and applications of CLMs, ii) their advantages and limitations, and iii) comparative analyses of CLMs and SDMs. We also suggest directions for future research. 3.We identify seven CLM algorithms with similar data structures and predictive outputs as SDMs that should be most accessible to ecologists familiar with species-level modeling, including five methods that predict assemblage composition and individual species distributions and two methods that model compositional turnover along environmental gradients. CLMs have been applied to numerous taxa, regions, and spatial scales, and a variety of topics (e.g., studying drivers of community structure or assessing relationships between community composition and functional traits). Studies suggest that the relative benefits of CLMs and SDMs may be case specific, especially in terms of predicting species distributions and community composition. However, CLMs may offer advantages in terms of computational efficiency, modeling rare species, and projecting to no-analog climates. A major shortcoming of CLMs is their reliance on presence-absence community composition data. 4.Studies are needed to assess the relative merits of SDMs and CLMs, and different CLM algorithms, with a focus on three key areas: i) under which circumstances CLMs improve predictions for rare species, ii) how CLMs perform under different community compositions (e.g. relative abundance of rare vs. common species), including the extent to which co-occurrence patterns are structured by biotic interactions, and iii) ability to project across time/space.
Data from: Ultrasonic cavitation induces necrosis and impairs growth in three-dimensional models of pancreatic ductal adenocarcinoma
Introduction: Pancreatic ductal adenocarcinoma (PDAC) is a rapidly increasing cause of mortality whose dismal prognosis is mainly due to overwhelming chemoresistance. New therapeutic approaches include physical agents such as ultrasonic cavitation, but clinical applications require further insights in the mechanisms of cytotoxicity. Three dimensional in vitro culture models such as spheroids exploit realistic spatial, biochemical and cellular heterogeneity that may bridge some of the experimental gap between conventional in vitro and in vivo experiments. Purpose: to assess the feasibility and efficiency of inertial cavitation associated or not with chemotherapy, in a spheroid model of PDAC. Methods: we used DT66066 cells ,derived from a genetically-engineered murine PDAC, isolated from KPC-transgenic mice (LSL-KrasG12D/+; LSL-Trp53R172H/+; Pdx-1- Cre). Spheroids were obtained by either a standard centrifugation-based method, or by using a magnetic nano-shuttle method allowing the formation of spheroids within 24 hours and facilitating their handling. The spheroids were exposed to ultrasonic inertial cavitation in a specially designed setup. Four conditions were studied: control, gemcitabine alone , US cavitation alone , US cavitation + gemcitabine. Five US inertial cavitation indexes, corresponding to increased US intensities, were evaluated . The effectiveness of treatment was assessed after 24 hours with the following criteria: spheroid size (growth), ratio of phase S cells (proliferation), proportion of cells in apoptosis or necrosis (cellular mortality). These parameters were assessed by quantitative immunofluorescence techniques. Results: The 3D culture model presented excellent reproducibility. Eight or nine spheroids were analyzed for each condition. Cavitation induced a significant decrease in the size of spheroids , an effect significantly correlated to an increasing cavitation index (p < 0.0001). The treatment induced cell death whose predominant mechanism was necrosis (p < 0.0001). There was a tendency to a synergistic effect of US cavitation and gemcitabine at 5μM concentration, however significant in only one of the cavitation indexes used (p = 0. 013). Conclusion: Ultrasonic inertial cavitation induced a significant reduction of tumor growth in a spheroid model of PDAC., with necrosis rather than apoptosis as a Cell dominant mechanism of cell death. More investigations are needed to understand the potential role of inertial cavitation in overcoming chemoresistance.
Data from: General models for the spectra of surface area scaling strategies of cells and organisms: fractality, geometric dissimilitude, and internalization
Surface areas and volumes of biological systems—from molecules to organelles, cells, and organisms—affect their biological rates and kinetics. Therefore, surface-area-to-volume ratios and the scaling of surface area with volume profoundly influences ecology, physiology, and evolution. The zeroth-order geometric expectation is that surface area scales with body mass or volume as a power law with an exponent of two-thirds, with consequences for surface-area-to-volume (SA:V) ratios and constraints on size; however, organisms have adaptations for altering the surface area scaling and SA:V ratios of their bodies and structures. The strategies fall into three groups: (i) fractal-like surface convolutions and crinkles; (ii) classic geometric dissimilitude through elongating, flattening, fattening, and hollowing; and (iii) internalization of surfaces. Here I develop general quantitative theory to model the spectra of effects of these strategies on SA:V ratios and surface area scaling, from exponents of less than two-thirds to superlinear scaling and mixed-power laws. Applying the theory to cells helps quantitatively evaluate the effects of membrane fractality, shape-shifting, vacuoles, vesicles, and mitochondria on surface area scaling, informing understanding of cell allometry, morphology, and evolution. Analysis of compiled data indicates that through hollowness and surface internalization eukaryotic phytoplankton increase their effective surface area scaling, attaining near-linear scaling in larger cells. This unifying theory highlights the fundamental role of biological surfaces in metabolism and morphological evolution.
Data from: Bounds to parapatric speciation: A dobzhansky-muller incompatibility model involving autosomes, X chromosomes and mitochondria
We investigate the conditions for the origin and maintenance of postzygotic isolation barriers, so called (Bateson-)Dobzhansky-Muller incompatibilities or DMIs, among populations that are connected by gene flow. Specifically, we compare the relative stability of pairwise DMIs among autosomes, X chromosomes, and mitochondrial genes. In an analytical approach based on a continent-island framework, we determine how the maximum permissible migration rates depend on the genomic architecture of the DMI, on sex bias in migration rates, and on sex-dependence of allelic and epistatic effects, such as dosage compensation. Our results show that X-linkage of DMIs can enlarge the migration bounds relative to autosomal DMIs or autosome-mitochondrial DMIs, in particular in the presence of dosage compensation. The effect is further strengthened with male-biased migration. This mechanism might contribute to a higher density of DMIs on the X chromosome (large X-effect) that has been observed in several species clades. Furthermore, our results agree with empirical findings of higher introgression rates of autosomal compared to X-linked loci.
ScienceDex guides
Understand access before you commit
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.