ALBERT

Description: Given the significance of animal dispersal to population dynamics and geographic variability, understanding how dispersal is impacted by landscape patterns has major ecological and conservation importance. Speaking to the importance of dispersal, the use of linear mixed models to compare genetic differentiation with pairwise resistance derived from landscape resistance surfaces has presented new opportunities to disentangle the menagerie of factors behind effective dispersal across a given landscape. Here, we combine these approaches with novel resistance surface parameterization to determine how the distribution of high- and low-quality seasonal habitat and individual landscape components shape patterns of gene flow for the greater sage-grouse ( Centrocercus urophasianus ) across Wyoming. We found that pairwise resistance derived from the distribution of low-quality nesting and winter, but not summer, seasonal habitat had the strongest correlation with genetic differentiation. Although the patterns were not as strong as with habitat distribution, multivariate models with sagebrush cover and landscape ruggedness or forest cover and ruggedness similarly had a much stronger fit with genetic differentiation than an undifferentiated landscape. In most cases, landscape resistance surfaces transformed with 17.33-km-diameter moving windows were preferred, suggesting small-scale differences in habitat were unimportant at this large spatial extent. Despite the emergence of these overall patterns, there were differences in the selection of top models depending on the model selection criteria, suggesting research into the most appropriate criteria for landscape genetics is required. Overall, our results highlight the importance of differences in seasonal habitat preferences to patterns of gene flow and suggest the combination of habitat suitability modeling and linear mixed models with our resistance parameterization is a powerful approach to discerning the effects of landscape on gene flow. We combine novel approaches to resistance parameterization and model selection to determine how the distribution of high and low quality seasonal habitat and individual landscape components shape patterns of gene flow for the greater sage-grouse ( Centrocercus urophasianus ) across Wyoming. We find that pairwise resistance derived from the distribution of low quality nesting and winter, but not summer, seasonal habitat had the strongest correlation with genetic differentiation. Overall our results highlight the importance of differences in seasonal habitat preferences to patterns of gene flow and suggests the combination of habitat suitability modeling and linear mixed models with our resistance parameterization is a powerful approach to discerning the effects of landscape on gene flow.

Description: A novel selective glucocorticoid receptor (GR) agonist, AZD2906, was found to increase the incidence of micronucleated immature erythrocytes (MIE) in the bone marrow of rats given two oral doses at the maximum tolerated level. Because GR agonists as a class are considered not to be genotoxic and AZD2906 showed no activity in the standard in vitro tests or in vivo in a rat liver comet assay, investigative studies were performed to compare AZD2906 with a reference traditional GR agonist, prednisolone. Emphasis was placed on blood and bone marrow parameters in these studies because GR activation has been reported to induce erythropoiesis which, in turn, is known to increase MIE in the bone marrow. Both compounds induced almost identical, small increases in micronucleus frequency at all doses tested. Directly comparable changes in haematological and bone marrow parameters were also seen with significant decreases in lymphoid cells in both compartments and significant increases in numbers of circulating neutrophils. Although no evidence of increased erythropoiesis was seen as increased immature erythrocyte numbers either in the blood or in the bone marrow, histopathological examination showed focal areas in the bone marrow where the erythroid population was enriched in association with an atrophic myeloid lineage. This could have been due to direct stimulation of the erythroid lineage or a secondary effect of myelosuppression inducing a rebound increase in erythropoiesis into the vacant haematopoietic cell compartment. It was concluded that the increased MIE frequencies induced by both AZD2906 and prednisolone are a consequence of their pharmacological effects on the bone marrow, either by directly inducing erythropoiesis or by some other unknown effect on cellular function, and do not indicate potential genotoxicity. This conclusion is supported by the lack of carcinogenic risk in man demonstrated by decades of clinical use of prednisolone and other GR agonists.

Description: Simplification is an unavoidable aspect of model usage. Even complex, physically based models are simplifications of reality. More profound simplification is required to construct the “lumped parameter” models of semi-physical basis that are often employed for simulation of large-scale processes operative over one or many watersheds. Simplification can lead to model predictive error beyond that which would be expected on the basis of study-area information deficits alone. Building on a recently developed mathematical description of the model simplification process, this work employs linear subspace methods to analyze in detail the nature and ramifications of that process when applied to a one-dimensional, Richards equation-based unsaturated zone model used to predict recharge to a groundwater system. Two simplified versions of this model are examined. The first achieves simplification through assuming vertical parameter uniformity. The second achieves simplification through use of a lumped parameter model in place of the Richards equation-based model. Relationships between parameters employed by the complex model and those used by each of the simplified models are analyzed. The nature of predictive errors incurred through simplification is explored. Also explored is the ability of the calibration process to decrease the propensity for model error in making some predictions, while increasing the propensity for model error in the making of others – an outcome that may be considered counter-intuitive from a Bayesian perspective, but which is a natural consequence of suboptimal simplification.

Description: Although the simultaneous engagement of multiple effector mechanisms is thought to characterize optimal CD8+ T-cell immunity and facilitate pathogen clearance, the differentiation pathways leading to the acquisition and maintenance of such polyfunctional activity are not well understood. Division-dependent profiles of effector molecule expression for virus-specific T cells are analyzed here by using a combination of carboxyfluorescein succinimidyl ester dilution and intracellular cytokine staining subsequent to T-cell receptor ligation. The experiments show that, although the majority of naive CD8+ T-cell precursors are preprogrammed to produce TNF-α soon after stimulation and a proportion make both TNF-α and IL-2, the progressive acquisition of IFN-γ expression depends on continued lymphocyte proliferation. Furthermore, the extensive division characteristic of differentiation to peak effector activity is associated with the progressive dominance of IFN-γ and the concomitant loss of polyfunctional cytokine production, although this is not apparent for long-term CD8+ T-cell memory. Such proliferation-dependent variation in cytokine production appears tied to the epigenetic signatures within the ifnG and tnfA proximal promoters. Specifically, those cytokine gene loci that are rapidly expressed following antigen stimulation at different stages of T-cell differentiation can be shown (by ChIP) to have permissive epigenetic and RNA polymerase II docking signatures. Thus, the dynamic changes in cytokine profiles for naive, effector, and memory T cells are underpinned by specific epigenetic landscapes that regulate responsiveness following T-cell receptor ligation.

Description: Triple-negative breast cancer (TNBC) is a heterogeneous and clinically aggressive disease for which there is no targeted therapy. BET bromodomain inhibitors, which have shown efficacy in several models of cancer, have not been evaluated in TNBC. These inhibitors displace BET bromodomain proteins such as BRD4 from chromatin by competing with their acetyl-lysine recognition modules, leading to inhibition of oncogenic transcriptional programs. Here we report the preferential sensitivity of TNBCs to BET bromodomain inhibition in vitro and in vivo, establishing a rationale for clinical investigation and further motivation to understand mechanisms of resistance. In paired cell lines selected for acquired resistance to BET inhibition from previously sensitive TNBCs, we failed to identify gatekeeper mutations, new driver events or drug pump activation. BET-resistant TNBC cells remain dependent on wild-type BRD4, which supports transcription and cell proliferation in a bromodomain-independent manner. Proteomic studies of resistant TNBC identify strong association with MED1 and hyper-phosphorylation of BRD4 attributable to decreased activity of PP2A, identified here as a principal BRD4 serine phosphatase. Together, these studies provide a rationale for BET inhibition in TNBC and present mechanism-based combination strategies to anticipate clinical drug resistance.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Shu, Shaokun -- Lin, Charles Y -- He, Housheng Hansen -- Witwicki, Robert M -- Tabassum, Doris P -- Roberts, Justin M -- Janiszewska, Michalina -- Huh, Sung Jin -- Liang, Yi -- Ryan, Jeremy -- Doherty, Ernest -- Mohammed, Hisham -- Guo, Hao -- Stover, Daniel G -- Ekram, Muhammad B -- Peluffo, Guillermo -- Brown, Jonathan -- D'Santos, Clive -- Krop, Ian E -- Dillon, Deborah -- McKeown, Michael -- Ott, Christopher -- Qi, Jun -- Ni, Min -- Rao, Prakash K -- Duarte, Melissa -- Wu, Shwu-Yuan -- Chiang, Cheng-Ming -- Anders, Lars -- Young, Richard A -- Winer, Eric P -- Letai, Antony -- Barry, William T -- Carroll, Jason S -- Long, Henry W -- Brown, Myles -- Liu, X Shirley -- Meyer, Clifford A -- Bradner, James E -- Polyak, Kornelia -- CA080111/CA/NCI NIH HHS/ -- CA103867/CA/NCI NIH HHS/ -- CA120184/CA/NCI NIH HHS/ -- CA168504/CA/NCI NIH HHS/ -- P50 CA168504/CA/NCI NIH HHS/ -- R01 CA103867/CA/NCI NIH HHS/ -- England -- Nature. 2016 Jan 21;529(7586):413-7. doi: 10.1038/nature16508. Epub 2016 Jan 6.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA. ; Department of Medicine, Brigham and Women's Hospital, and Department of Medicine, Harvard Medical School, Boston, Massachusetts 02115, USA. ; Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, and Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA. ; Princess Margaret Cancer Center/University Health Network, Toronto, Ontario M5G1L7, Canada. ; Department of Medical Biophysics, University of Toronto, Toronto, Ontario M5G2M9, Canada. ; Harvard University, Cambridge, Massachusetts 02138, USA. ; Cancer Research UK, Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK. ; Department of Pathology, Brigham and Women's Hospital, and Department of Pathology, Harvard Medical School, Boston, Massachusetts 02115, USA. ; Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA. ; Simmons Comprehensive Cancer Center, Departments of Biochemistry and Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas 75390, USA. ; Whitehead Institute for Biomedical Research, Cambridge, Massachusetts 02142, USA. ; Broad Institute, Cambridge, Massachusetts 02142, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/26735014" target="_blank"〉PubMed〈/a〉

Description: Much interest lies in the identification of manageable habitat variables that affect key vital rates for species of concern. For ground-nesting birds, vegetation surrounding the nest may play an important role in mediating nest success by providing concealment from predators. Height of grasses surrounding the nest is thought to be a driver of nest survival in greater sage-grouse ( Centrocercus urophasianus ; sage-grouse), a species that has experienced widespread population declines throughout their range. However, a growing body of the literature has found that widely used field methods can produce misleading inference on the relationship between grass height and nest success. Specifically, it has been demonstrated that measuring concealment following nest fate (failure or hatch) introduces a temporal bias whereby successful nests are measured later in the season, on average, than failed nests. This sampling bias can produce inference suggesting a positive effect of grass height on nest survival, though the relationship arises due to the confounding effect of plant phenology, not an effect on predation risk. To test the generality of this finding for sage-grouse, we reanalyzed existing datasets comprising 〉800 sage-grouse nests from three independent studies across the range where there was a positive relationship found between grass height and nest survival, including two using methods now known to be biased. Correcting for phenology produced equivocal relationships between grass height and sage-grouse nest survival. Viewed in total, evidence for a ubiquitous biological effect of grass height on sage-grouse nest success across time and space is lacking. In light of these findings, a reevaluation of land management guidelines emphasizing specific grass height targets to promote nest success may be merited. Following recent research demonstrating how commonly-used field protocols can conflate phenology with a positive effect of vegetation height surrounding nests, we reanalyze three datasets examining factors associated with nest survival in greater sage-grouse (Centrocercus urophasianus), a species of conservation concern in western North America. We demonstrate that accounting for biased timing of vegetation sampling between successful and failed nests largely accounts for the apparent relationship between grass height and daily nest survival. After correction, the strong positive effects previously found in all three datasets were diminished such that they became nonsignificant in two and diminished in magnitude in the third.

Description: We developed rangewide population and habitat models for Greater Sage-Grouse ( Centrocercus urophasianus ) that account for regional variation in habitat selection and relative densities of birds for use in conservation planning and risk assessments. We developed a probabilistic model of occupied breeding habitat by statistically linking habitat characteristics within 4 miles of an occupied lek using a nonlinear machine learning technique (Random Forests). Habitat characteristics used were quantified in GIS and represent standard abiotic and biotic variables related to sage-grouse biology. Statistical model fit was high (mean correctly classified = 82.0%, range = 75.4–88.0%) as were cross-validation statistics (mean = 80.9%, range = 75.1–85.8%). We also developed a spatially explicit model to quantify the relative density of breeding birds across each Greater Sage-Grouse management zone. The models demonstrate distinct clustering of relative abundance of sage-grouse populations across all management zones. On average, approximately half of the breeding population is predicted to be within 10% of the occupied range. We also found that 80% of sage-grouse populations were contained in 25–34% of the occupied range within each management zone. Our rangewide population and habitat models account for regional variation in habitat selection and the relative densities of birds, and thus, they can serve as a consistent and common currency to assess how sage-grouse habitat and populations overlap with conservation actions or threats over the entire sage-grouse range. We also quantified differences in functional habitat responses and disturbance thresholds across the Western Association of Fish and Wildlife Agencies (WAFWA) management zones using statistical relationships identified during habitat modeling. Even for a species as specialized as Greater Sage-Grouse, our results show that ecological context matters in both the strength of habitat selection (i.e., functional response curves) and response to disturbance.

Description: All computer models are simplified and imperfect simulators of complex natural systems. The discrepancy arising from simplification induces bias in model predictions, which may be amplified by the process of model calibration. This paper presents a new method to identify and quantify the predictive consequences of calibrating a simplified computer model. The method is based on linear theory and it scales efficiently to the large numbers of parameters and observations characteristic of groundwater and petroleum reservoir models. The method is applied to a range of predictions made with a synthetic integrated surface-water/groundwater model with thousands of parameters. Several different observation processing strategies and parameterization/regularization approaches are examined in detail, including use of the Karhunen-Loève parameter transformation. Predictive bias arising from model error is shown to be prediction specific and often invisible to the modeler. The amount of calibration-induced bias is influenced by several factors, including: how expert knowledge is applied in the design of parameterization schemes, the number of parameters adjusted during calibration, how observations and model-generated counterparts are processed and the level of fit with observations achieved through calibration. Failure to properly implement any of these factors in a prediction-specific manner may increase the potential for predictive bias in ways that are not visible to the calibration and uncertainty analysis process.