Biology subjects

Swanson, D.

Publications and source records attributed to Swanson, D..

5 recordsLinked to original sources

bioRxiv2024

Productivity and resilience of Chinook salmon compromised by Mixed-Maturation fisheries in marine waters

Most Chinook salmon (Oncorhynchus tshawytscha) in the northeast Pacific Ocean are harvested in mixed-stock marine fisheries. Here, multiple populations with varying abundance and productivities are encountered. In addition, many of these fisheries generally encounter both mature and immature Chinook. Hence, these fisheries are better described as mixed-stock and "mixed-maturation" (MM) fisheries. Harvest of immature fish can skew the age composition of Chinook populations towards younger, and hence smaller, individuals. Older Chinook are generally larger and contribute disproportionately to the productivity of their populations. We developed an individual-based demographic-genetic model of ocean-type Chinook to evaluate the effects of fisheries that harvest immature Chinook. We then compared those effects to terminal fisheries that harvest only mature fish. Our model provides the ability to assess the benefits of terminal Chinook fisheries to both landed catch and Chinook rebuilding. Recovered populations show a more archetypal age- and sex-structure than contemporary ocean-type Chinook subject to marine mixed-maturation fisheries. In our modeled scenarios of mixed-maturation fisheries, we found that immature Chinook can comprise up to 59% of the total numbers of fish caught, and 47% of the total weight of the catch. If instead, these Chinook were not harvested until they mature and reach terminal fisheries, they would contribute greater biomass to landed catches. These terminal fisheries allow a higher percentage of larger, older Chinook to escape, and would increase the fecundity and productivities of their populations. The benefits of terminal fisheries would accrue to fishers, sustainable wild harvesting, wildlife, and the rebuilding of depleted Chinook runs.

ecology↗

bioRxiv2024

Redefining FLASH RT: the impact of mean dose rate and dose per pulse in the gastrointestinal tract

BackgroundThe understanding of how varying radiation beam parameter settings affect the induction and magnitude of the FLASH effect remains limited. PurposeWe sought to evaluate how the magnitude of radiation-induced gastrointestinal (GI) toxicity (RIGIT) depends on the interplay between mean dose rate (MDR) and dose per pulse (DPP). MethodsC57BL/6J mice were subjected to total abdominal irradiation (11-14 Gy single fraction) under conventional irradiation (low DPP and low MDR, CONV) and various combinations of DPP and MDR up to ultra-high-dose-rate (UHDR) beam conditions. The effects of DPP were evaluated for DPPs of 1-6 Gy while the total dose and MDR were kept constant; the effects of MDR were evaluated for the range 0.3- 1440 Gy/s while the total dose and DPP were kept constant. RIGIT was quantified in non-tumor-bearing mice through the regenerating crypt assay and survival assessment. Tumor response was evaluated through tumor growth delay. ResultsWithin each tested total dose using a constant MDR (>100 Gy/s), increasing DPP led to better sparing of regenerating crypts, with a more prominent effect seen at 12 and 14 Gy TAI. However, at fixed DPPs >4 Gy, similar sparing of crypts was demonstrated irrespective of MDR (from 0.3 to 1440 Gy/s). At a fixed high DPP of 4.7 Gy, survival was equivalently improved relative to CONV for all MDRs from 0.3 Gy/s to 104 Gy/s, but at a lower DPP of 0.93 Gy, increasing MDR produced a greater survival effect. We also confirmed that high DPP, regardless of MDR, produced the same magnitude of tumor growth delay relative to CONV using a clinically relevant melanoma mouse model. ConclusionsThis study demonstrates the strong influence that the beam parameter settings have on the magnitude of the FLASH effect. Both high DPP and UHDR appeared independently sufficient to produce FLASH sparing of GI toxicity, while isoeffective tumor response was maintained across all conditions.

cancer biology↗

bioRxiv2018

Investigating Coordinated Architectures Across Clusters in Integrative Studies: a Bayesian Two-Way Latent Structure Model

MotivationUnsupervised clustering is important in disease subtyping, among having other genomic applications. As genomic data has become more multifaceted, how to cluster across data sources for more precise subtyping is an ever more important area of research. Many of the methods proposed so far, including iCluster and Cluster of Cluster Assignments, make an unreasonble assumption of a common clustering across all data sources, and those that do not are fewer and tend to be computationally intensive.\n\nResultsWe propose a Bayesian parametric model for integrative, unsupervised clustering across data sources. In our two-way latent structure model, samples are clustered in relation to each specific data source, distinguishing it from methods like Cluster of Cluster Assignments and iCluster, but cluster labels have across-dataset meaning, allowing cluster information to be shared between data sources. A common scaling across data sources is not required, and inference is obtained by a Gibbs Sampler, which we improve with a warm start strategy and modified density functions to robustify and speed convergence. Posterior interpretation allows for inference on common clusterings occurring among subsets of data sources. An interesting statistical formulation of the model results in sampling from closed-form posteriors despite incorporation of a complex latent structure. We fit the model with Gaussian and more general densities, which influences the degree of across-dataset cluster label sharing. Uniquely among integrative clustering models, our formulation makes no nestedness assumptions of samples across data sources so that a sample missing data from one genomic source can be clustered according to its existing data sources.\n\nWe apply our model to a Norwegian breast cancer cohort of ductal carcinoma in-situ and invasive tumors, comprised of somatic copy-number alteration, methylation and expression datasets. We find enrichment in the Her2 subtype and ductal carcinoma among those observations exhibiting greater cluster correspondence across expression and CNA data. In general, there are few pan-genomic clusterings, suggesting that models assuming a common clustering across genomic data sources might yield misleading results.\n\nImplementation and AvailabilityThe model is implemented in an R package called twl (\"two-way latent\"), available on CRAN. Data for analysis is available within the R package.\n\nContactdavid.swanson@medisin.uio.no\n\nSupplementary MaterialAppendices are available online and include additional Breast Cancer subtyping analysis and model runs, comparison with leading integrative clustering methods, fully general statistical formulation and description of improvements of the Gibbs sampler.

bioinformatics↗

bioRxiv2017

Statistical power of gene-set enrichment analysis is a function of gene set correlation structure

MotivationWe describe why statistical power for both self-contained and competitive gene-set tests is a function of the correlation structure of co-expressed genes, and why this characteristic is undesirable for gene-set analyses. Variable statistical power as a function of gene correlation structure has not been observed or studied previously. The observation is important in part because gene-set testing methodology is well-developed, yet this fundamental feature of many of its tests is unknown and has the potential to reinterpret past gene-set test results and guide future implementations, including those using sequence data. Type 1 error inflation is also amenable for study in our statistical framework; while it has been well-studied and described previously for both self-contained and competitive tests, it has less often been done in an analytical framework. Our observations apply to four commonly-used gene-set testing approaches for microarrays, including CAMERA, ROAST, SAFE, and GAGE, and a recently proposed one for RNAseq, MAST.\n\nResultsWe characterize situations in which power is especially small relative to effect sizes of genes in a set for both competitive and self-contained gene-set tests. We propose three alternative tests, one of which replicates the properties of permutation-based self-contained tests, but avoids the need for even recently proposed, rotation-based approximations to permutations. The two other proposed tests have the unique property that statistical power is not a function of co-expression correlation in the gene-set and therefore is the preferred methodology. We compare our proposed tests to leading gene-set tests and apply them to an already-published study of smoking exposure on pregnant women.\n\nContactdms866@mail.harvard.edu\n\nSupplementary MaterialOnline supplementary material includes additional simulation results supporting the relationship between the \"mixed\" and \"directional\" gene-set tests of ROAST and closed-form implementations of them.

bioinformatics↗

bioRxiv2017

Metabolism constrains bird and mammal ranges and predicts shifts in response to climate change

AimWe test whether physiological constraints on maximum metabolic rate and the factor by which endotherms can elevate their metabolism (metabolic expansibility) govern cold range limits for mammal and bird species.\n\nLocationGlobal\n\nMethodsWe examine metabolic expansibility at the cold range boundary (MEO_SCPLOWCRBC_SCPLOW) and its trait predictors and then use MEO_SCPLOWCRBC_SCPLOW to project range shifts for 210 mammal and 61 bird species.\n\nResultsWe find evidence for metabolic constraints: the distributions of metabolic expansibility at the cold range boundary peak at similar values for birds (2.7) and mammals (3.2). The right skewed distributions suggest some species have adapted to elevate or evade metabolic constraints. Mammals exhibit greater skew than birds, consistent with their diverse thermoregulatory adaptations and behaviors. Mammal and bird species that are small and occupy low trophic levels exhibit high levels of MEO_SCPLOWCRBC_SCPLOW. Mammals with high MEO_SCPLOWCRBC_SCPLOW tend to hibernate or use torpor. Predicted metabolic rates at the cold range boundaries represent large energetic expenditures (>50% of maximum metabolic rates). We project species to shift their cold range boundaries poleward by an average of 3.9{degrees} latitude by 2070.\n\nMain conclusionsOur analysis suggests that metabolic constraints provide a viable mechanism for projecting cold range boundaries and range shifts in response to climate change for endotherms.

ecology↗