The SOFIA pilot study: assessing feasibility and fidelity of coordinated care to reduce excess mortality and increase quality of life in patients with severe mental illness in a general practice setting; a cluster-randomised pilot trial.

OBJECTIVE: To evaluate the feasibility and fidelity of implementing and assessing the SOFIA coordinated care program aimed at lowering mortality and increasing quality of life in patients with severe mental illness by improving somatic health care in general practice. DESIGN: A cluster-randomised, non-blinded controlled pilot trial. SETTING: General Practice in Denmark. INTERVENTION: The SOFIA coordinated care program comprised extended structured consultations carried out by the GP, group-based training of GPs and staff, and a handbook with information on signposting patients to relevant municipal, health, and social initiatives. PATIENTS: Persons aged 18 years or older with a diagnosis of psychotic, bipolar, or severe depressive disorder. MAIN OUTCOME MEASURES: We collected quantitative data on the delivery, recruitment and retention rates of practices and patients, and response rates of questionnaires MMQ and EQ-5D-5 L. RESULTS: From November 2020 to March 2021, nine practices were enrolled and assigned in a 2:1 ratio to the intervention group (n = 6) or control group (n = 3). Intervention group practices included 64 patients and Control practices included 23. The extended consultations were delivered with a high level of fidelity in the general practices; however, thresholds for collecting outcome measures, and recruitment of practices and patients were not reached. CONCLUSION: Our findings suggest that delivering the coordinated care program in a fully powered trial in primary care is likely feasible. However, the recruitment methodology requires improvement to ensure sufficient recruitment and minimize selective inclusion. TRIAL REGISTRATION: The date of pilot trial protocol registration was 05/11/2020, and the registration number is NCT04618250.

The ties that bind the sagebrush biome: integrating genetic connectivity into range-wide conservation of greater sage-grouse.

Conserving genetic connectivity is fundamental to species persistence, yet rarely is made actionable into spatial planning for imperilled species. Climate change and habitat degradation have added urgency to embrace connectivity into networks of protected areas. Our two-step process integrates a network model with a functional connectivity model, to identify population centres important to maintaining genetic connectivity then to delineate those pathways most likely to facilitate connectivity thereamong for the greater sage-grouse (Centrocercus urophasianus), a species of conservation concern ranging across eleven western US states and into two Canadian provinces. This replicable process yielded spatial action maps, able to be prioritized by importance to maintaining range-wide genetic connectivity. We used these maps to investigate the efficacy of 3.2 million ha designated as priority areas for conservation (PACs) to encompass functional connectivity. We discovered that PACs encompassed 41.1% of cumulative functional connectivity-twice the amount of connectivity as random-and disproportionately encompassed the highest-connectivity landscapes. Comparing spatial action maps to impedances to connectivity such as cultivation and woodland expansion allows both planning for future management and tracking outcomes from past efforts.

BDEtools: A MATLAB Package for Boolean Delay Equation Modeling.

Boolean Delay Equations (BDEs) can simulate surprisingly complex behavior, despite their relative simplicity. In addition to steady-state dynamics, BDEs can also generate periodic and quasiperiodic oscillations, m:n frequency locking, and even chaos. Further, the enumerability of Boolean update functions and their compact parametrization means that BDEs can be leveraged to generate low-level descriptions of biological networks, from which more detailed formulations (e.g., differential equation models) can be constructed. However, although several studies have demonstrated the utility of BDE modeling in computational biology, a current barrier to the wider adoption of the BDE approach is the absence of freely available simulation software. In this work, we present BDEtools-an open-source MATLAB package for numerically solving BDE models. After giving a brief introduction to BDE modeling, we describe the package's solver algorithms, together with several utility functions that can be used to provide solver inputs and to process solver outputs. We also demonstrate the functionality of BDEtools by illustrating its application to an established model of a gene regulatory network that controls circadian rhythms. BDEtools makes it straightforward for researchers to quickly build reliable BDE models of biological networks. We hope that its ease of use and free availability will encourage more researchers to explore BDE formulations of their systems of interest. Through the continued use of BDEs by the computational biology community, we will, no doubt, discover their potential applicability to a broader class of biological networks.

What's Up With These Conversational Health Agents? From Users' Critiques to Implications for Design.

Recent advancements in speech recognition technology in combination with increased access to smart speaker devices are expanding conversational interactions to ever-new areas of our lives - including our health and wellbeing. Prior human-computer interaction research suggests that Conversational Agents (CAs) have the potential to support a variety of health-related outcomes, due in part to their intuitive and engaging nature. Realizing this potential requires however developing a rich understanding of users' needs and experiences in relation to these still-emerging technologies. To inform the design of CAs for health and wellbeing, we analyze 2741 critical reviews of 485 Alexa health and fitness Skills using an automated topic modeling approach; identifying 15 subjects of criticism across four key areas of design (functionality, reliability, usability, pleasurability). Based on these findings, we discuss implications for the design of engaging CAs to support health and wellbeing.

Microstructural and Mechanical Characterization of Additive Friction Stir-Deposition of Aluminum Alloy 5083 Effect of Lubrication on Material Anisotropy.

Additive Friction Stir-Deposition (AFS-D) is a transformative, metallic additive manufacturing (AM) process capable of producing near-net shape components with a wide variety of material systems. The solid-state nature of the process permits many of these materials to be successfully deposited without the deleterious phase and thermally activated defects commonly observed in other metallic AM technologies. This work is the first to investigate the as-deposited microstructure and mechanical performance of a free-standing AA5083 deposition. An initial process parameterization was conducted to down-select optimal parameters for a large deposition to examine build direction properties. Microscopy revealed that constitutive particles were dispersed evenly throughout the matrix when compared to the rolled feedstock. Electron backscatter diffraction revealed a significant grain refinement from the inherent dynamic recrystallization from the AFS-D process. Tensile experiments determined a drop in yield strength, but an improvement in tensile strength in the longitudinal direction. However, a substantial reduction in tensile strength was observed in the build direction of the structure. Subsequent fractographic analysis revealed that the recommended lubrication applied to the feedstock rods, necessary for successful depositions via AFS-D, was ineffectively dispersed into the structure. As a result, lubrication contamination became entrapped at layer boundaries, preventing adequate bonding between layers.

Divergent climate change effects on widespread dryland plant communities driven by climatic and ecohydrological gradients.

Plant community response to climate change will be influenced by individual plant responses that emerge from competition for limiting resources that fluctuate through time and vary across space. Projecting these responses requires an approach that integrates environmental conditions and species interactions that result from future climatic variability. Dryland plant communities are being substantially affected by climate change because their structure and function are closely tied to precipitation and temperature, yet impacts vary substantially due to environmental heterogeneity, especially in topographically complex regions. Here, we quantified the effects of climate change on big sagebrush (Artemisia tridentata Nutt.) plant communities that span 76 million ha in the western United States. We used an individual-based plant simulation model that represents intra- and inter-specific competition for water availability, which is represented by a process-based soil water balance model. For dominant plant functional types, we quantified changes in biomass and characterized agreement among 52 future climate scenarios. We then used a multivariate matching algorithm to generate fine-scale interpolated surfaces of functional type biomass for our study area. Results suggest geographically divergent responses of big sagebrush to climate change (changes in biomass of -20% to +27%), declines in perennial C3 grass and perennial forb biomass in most sites, and widespread, consistent, and sometimes large increases in perennial C4 grasses. The largest declines in big sagebrush, perennial C3 grass and perennial forb biomass were simulated in warm, dry sites. In contrast, we simulated no change or increases in functional type biomass in cold, moist sites. There was high agreement among climate scenarios on climate change impacts to functional type biomass, except for big sagebrush. Collectively, these results suggest divergent responses to warming in moisture-limited versus temperature-limited sites and potential shifts in the relative importance of some of the dominant functional types that result from competition for limiting resources.

Personal information and public health: Design tensions in sharing and monitoring wellbeing in pregnancy.

Mobile technologies are valuable tools for the self-report of mental health and wellbeing. These systems pose many unique design challenges which have received considerable attention within HCI, including the engagement of users. However, less attention has been paid to the use of personal devices in public health. Integrating self-reported data within the context of clinical care suggests the need to design interfaces to support data management, sense-making, risk-assessment, feedback and patient-provider relationships. This paper reports on a qualitative design study for the clinical interface of a mobile application for the self-report of psychological wellbeing and depression during pregnancy. We examine the design tensions which arise in managing the expectations and informational needs of pregnant women, midwives, clinical psychologists, GPs and other health professionals with respect to a broad spectrum of wellbeing. We discuss strategies for managing these tensions in the design of technologies required to balance personal information with public health.

A Mobile App for the Self-Report of Psychological Well-Being During Pregnancy (BrightSelf): Qualitative Design Study.

BACKGROUND: Maternal mental health impacts both parental well-being and childhood development. In the United Kingdom, 15% of women are affected by depression during pregnancy or within 1 year of giving birth. Suicide is a leading cause of perinatal maternal mortality, and it is estimated that >50% of perinatal depression cases go undiagnosed. Mobile technologies are potentially valuable tools for the early recognition of depressive symptoms, but complex design challenges must be addressed to enable their use in public health screening. OBJECTIVE: The aim of this study was to explore the issues and challenges surrounding the use of mobile phones for the self-report of psychological well-being during pregnancy. METHODS: This paper presents design research carried out as part of the development of BrightSelf, a mobile app for the self-report of psychological well-being during pregnancy. Design sessions were carried out with 38 participants, including pregnant women, mothers, midwives, and other health professionals. Overall, 19 hours of audio were fully transcribed and used as the basis of thematic analysis. RESULTS: The study highlighted anxieties concerning the pregnancy journey, challenges surrounding current approaches to the appraisal of well-being in perinatal care, and the midwife-patient relationship. Designers should consider the framing of perinatal mental health technologies, the experience of self-report, supporting self-awareness and disclosure, providing value to users through both self-report and supplementary features, and designing for longitudinal engagement. CONCLUSIONS: This study highlights the needs, motivations, and anxieties of women with respect to technology use in pregnancy and implications for the design of mobile health technologies.

Quantifying functional connectivity: The role of breeding habitat, abundance, and landscape features on range-wide gene flow in sage-grouse.

Functional connectivity, quantified using landscape genetics, can inform conservation through the identification of factors linking genetic structure to landscape mechanisms. We used breeding habitat metrics, landscape attributes, and indices of grouse abundance, to compare fit between structural connectivity and genetic differentiation within five long-established Sage-Grouse Management Zones (MZ) I-V using microsatellite genotypes from 6,844 greater sage-grouse (Centrocercus urophasianus) collected across their 10.7 million-km2 range. We estimated structural connectivity using a circuit theory-based approach where we built resistance surfaces using thresholds dividing the landscape into "habitat" and "nonhabitat" and nodes were clusters of sage-grouse leks (where feather samples were collected using noninvasive techniques). As hypothesized, MZ-specific habitat metrics were the best predictors of differentiation. To our surprise, inclusion of grouse abundance-corrected indices did not greatly improve model fit in most MZs. Functional connectivity of breeding habitat was reduced when probability of lek occurrence dropped below 0.25 (MZs I, IV) and 0.5 (II), thresholds lower than those previously identified as required for the formation of breeding leks, which suggests that individuals are willing to travel through undesirable habitat. The individual MZ landscape results suggested terrain roughness and steepness shaped functional connectivity across all MZs. Across respective MZs, sagebrush availability (<10%-30%; II, IV, V), tree canopy cover (>10%; I, II, IV), and cultivation (>25%; I, II, IV, V) each reduced movement beyond their respective thresholds. Model validations confirmed variation in predictive ability across MZs with top resistance surfaces better predicting gene flow than geographic distance alone, especially in cases of low and high differentiation among lek groups. The resultant resistance maps we produced spatially depict the strength and redundancy of range-wide gene flow and can help direct conservation actions to maintain and restore functional connectivity for sage-grouse.

Phenology largely explains taller grass at successful nests in greater sage-grouse.

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.

A bespoke mobile application for the longitudinal assessment of depression and mood during pregnancy: protocol of a feasibility study.

INTRODUCTION: Depression is a common mental health disorder during pregnancy, with important consequences for mothers and their children. Despite this, it goes undiagnosed and untreated in many women attending antenatal care. Smartphones could help support the prompt identification of antenatal depression in this setting. In addition, these devices enable the implementation of ecological momentary assessment techniques, which could be used to assess how mood is experienced during pregnancy. With this study, we will assess the feasibility of using a bespoke mobile application (app) running on participants' own handsets for the longitudinal (6 months) monitoring of antenatal mood and screening of depression. METHODS AND ANALYSIS: We will use a randomised controlled study design to compare two types of assessment strategies: retrospective + momentary (consisting of the Edinburgh Postnatal Depression Scale plus five momentary and two contextual questions), and retrospective (consisting of the Edinburgh Postnatal Depression Scale only). We will assess the impact that these strategies have on participant adherence to a prespecified sampling protocol, dropout rates and timeliness of data completion. We will evaluate differences in acceptance of the technology through a short quantitative survey and open-ended questions. We will also assess the potential effect that momentary assessments could have on retrospective data. We will attempt to identify any patterns in app usage through the analysis of log data. ETHICS AND DISSEMINATION: This study has been reviewed and approved by the National Research Ethics Service Committee South East Coast-Surrey on 15 April 2016 as a notice of substantial amendment to the original submission (9 July 2015) under the Research Ethics Committee (REC) reference 15/LO/0977. This study is being sponsored by Imperial College London under the reference number 15IC2687 and has been included in the UK Clinical Research Network Study Portfolio under the Central Portfolio Management System number 19280. The findings of this study will be disseminated through academic peer-reviewed publications, poster presentations and abstracts at academic and professional conferences, discussion with peers, and social media. The findings of this study will also inform the PhD theses of JSMB and KD.

An investigation into the factors that influence toolmark identifications on ammunition discharged from semi-automatic pistols recovered from car fires.

Following a shooting incident where a vehicle is used to convey the culprits to and from the scene, both the getaway car and the firearm are often deliberately burned in an attempt to destroy any forensic evidence which may be subsequently recovered. Here we investigate the factors that influence the ability to make toolmark identifications on ammunition discharged from pistols recovered from such car fires. This work was carried out by conducting a number of controlled furnace tests in conjunction with real car fire tests in which three 9mm semi-automatic pistols were burned. Comparisons between pre-burn and post burn test fired ammunition discharged from these pistols were then performed to establish if identifications were still possible. The surfaces of the furnace heated samples and car fire samples were examined following heating/burning to establish what factors had influenced their surface morphology. The primary influence on the surfaces of the furnace heated and car fire samples was the formation of oxide layers. The car fire samples were altered to a greater extent than the furnace heated samples. Identifications were still possible between pre- and post-burn discharged cartridge cases, but this was not the case for the discharged bullets. It is suggested that the reason for this is a difference between the types of firearms discharge-generated toolmarks impressed onto the base of cartridge cases compared to those striated along the surfaces of bullets. It was also found that the temperatures recorded in the front foot wells were considerably less than those recorded on top of the rear seats during the car fires. These factors should be assessed by forensic firearms examiners when performing casework involving pistols recovered from car fires.

Wildfire, climate, and invasive grass interactions negatively impact an indicator species by reshaping sagebrush ecosystems.

Iconic sagebrush ecosystems of the American West are threatened by larger and more frequent wildfires that can kill sagebrush and facilitate invasion by annual grasses, creating a cycle that alters sagebrush ecosystem recovery post disturbance. Thwarting this accelerated grass-fire cycle is at the forefront of current national conservation efforts, yet its impacts on wildlife populations inhabiting these ecosystems have not been quantified rigorously. Within a Bayesian framework, we modeled 30 y of wildfire and climatic effects on population rates of change of a sagebrush-obligate species, the greater sage-grouse, across the Great Basin of western North America. Importantly, our modeling also accounted for variation in sagebrush recovery time post fire as determined by underlying soil properties that influence ecosystem resilience to disturbance and resistance to invasion. Our results demonstrate that the cumulative loss of sagebrush to direct and indirect effects of wildfire has contributed strongly to declining sage-grouse populations over the past 30 y at large spatial scales. Moreover, long-lasting effects from wildfire nullified pulses of sage-grouse population growth that typically follow years of higher precipitation. If wildfire trends continue unabated, model projections indicate sage-grouse populations will be reduced to 43% of their current numbers over the next three decades. Our results provide a timely example of how altered fire regimes are disrupting recovery of sagebrush ecosystems and leading to substantial declines of a widespread indicator species. Accordingly, we present scenario-based stochastic projections to inform conservation actions that may help offset the adverse effects of wildfire on sage-grouse and other wildlife populations.

A mathematical model of Aurora B activity in prophase and metaphase.

Aurora B kinase is a protein that controls several processes in mitosis when it is found associated with INCENP, Survivin and Borealin in a complex known as the Chromosomal Passenger Complex. Aurora B in complex with INCENP is phosphorylated on three sites, resulting in the full activation of Aurora B. In prophase and metaphase, Aurora B is activated at centromeres, the region of chromatin linking sister chromatids, due to an autophosphorylation mechanism, and it has been hypothesised that Aurora B is activated throughout the cytoplasm due to its concentration at centromeres. In this article, we first develop a time-dependent model of Aurora B activation that does not incorporate spatial variation. This model is used to demonstrate the various qualitative behaviours that the activation of Aurora B is capable of displaying for different model parameters. Next, we develop a spatio-temporal model of Aurora B activation that includes diffusion of soluble Aurora B and binding of Aurora B to immobile centromeric binding sites. This model describes the activation of Aurora B throughout the cytoplasm due to its concentration-dependent activation at centromeres. The models demonstrate the effects that a soluble phosphatase concentration, multisite phosphorylation and diffusion have on the activation of Aurora B.

Landscape characteristics influencing the genetic structure of greater sage-grouse within the stronghold of their range: a holistic modeling approach.

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.

Some mathematical models of intermolecular autophosphorylation.

Intermolecular autophosphorylation refers to the process whereby a molecule of an enzyme phosphorylates another molecule of the same enzyme. The enzyme thereby catalyses its own phosphorylation. In the present paper, we develop two generic models of intermolecular autophosphorylation that also include dephosphorylation by a phosphatase of constant concentration. The first of these, a solely time-dependent model, is written as one ordinary differential equation that relies upon mass-action and Michaelis-Menten kinetics. Beginning with the enzyme in its dephosphorylated state, it predicts a lag before the enzyme becomes significantly phosphorylated, for suitable parameter values. It also predicts that there exists a threshold concentration for the phosphorylation of enzyme and that for suitable parameter values, a continuous or discontinuous switch in the phosphorylation of enzyme are possible. The model developed here has the advantage that it is relatively easy to analyse compared with most existing models for autophosphorylation and can qualitatively describe many different systems. We also extend our time-dependent model of autophosphorylation to include a spatial dependence, as well as localised binding reactions. This spatio-temporal model consists of a system of partial differential equations that describe a soluble autophosphorylating enzyme in a spherical geometry. We use the spatio-temporal model to describe the phosphorylation of an enzyme throughout the cell due to an increase in local concentration by binding. Using physically realistic values for model parameters, our results provide a proof-of-concept of the process of activation by local concentration and suggest that, in the presence of a phosphatase, this activation can be irreversible.

Building the foundation for international conservation planning for breeding ducks across the U.S. and Canadian border.

We used publically available data on duck breeding distribution and recently compiled geospatial data on upland habitat and environmental conditions to develop a spatially explicit model of breeding duck populations across the entire Prairie Pothole Region (PPR). Our spatial population models were able to identify key areas for duck conservation across the PPR and predict between 62.1-79.1% (68.4% avg.) of the variation in duck counts by year from 2002-2010. The median difference in observed vs. predicted duck counts at a transect segment level was 4.6 ducks. Our models are the first seamless spatially explicit models of waterfowl abundance across the entire PPR and represent an initial step toward joint conservation planning between Prairie Pothole and Prairie Habitat Joint Ventures. Our work demonstrates that when spatial and temporal variation for highly mobile birds is incorporated into conservation planning it will likely increase the habitat area required to support defined population goals. A major goal of the current North American Waterfowl Management Plan and subsequent action plan is the linking of harvest and habitat management. We contend incorporation of spatial aspects will increase the likelihood of coherent joint harvest and habitat management decisions. Our results show at a minimum, it is possible to produce spatially explicit waterfowl abundance models that when summed across survey strata will produce similar strata level population estimates as the design-based Waterfowl Breeding Pair and Habitat Survey (r2 = 0.977). This is important because these design-based population estimates are currently used to set duck harvest regulations and to set duck population and habitat goals for the North American Waterfowl Management Plan. We hope this effort generates discussion on the important linkages between spatial and temporal variation in population size, and distribution relative to habitat quantity and quality when linking habitat and population goals across this important region.

A mathematical model of CENP-A incorporation in mammalian centromeres.

Centromere Protein A (CENP-A) is a histone H3 variant found at mammalian centromeres. Unlike canonical histones which are incorporated at centromeres in S phase, CENP-A is deposited at centromeric chromatin in G1. Although recent studies have elucidated many of the molecular details associated with the CENP-A incorporation pathway, some aspects of the process are still not fully understood. CENP-A incorporation in G1 requires multiple assembly factors for its recruitment and maintenance. In this study, the first mathematical model of the CENP-A incorporation pathway is developed. The model is based on what is currently known about the pathway and is calibrated by comparing numerical simulations with experimental observations taken from the literature. The model succinctly collates a large body of knowledge accumulated in recent decades concerning the pathway and produces results that are consistent with experimental findings. It identifies possible gaps in what is currently known about the pathway and suggests possible directions for future research. It is envisaged that the model will be expanded upon and improved as more information concerning the pathway comes to light.

Loss of a 20S proteasome activator in Saccharomyces cerevisiae downregulates genes important for genomic integrity, increases DNA damage, and selectively sensitizes cells to agents with diverse mechanisms of action.

Cytoprotective functions of a 20S proteasome activator were investigated. Saccharomyces cerevisiae Blm10 and human 20S proteasome activator 200 (PA200) are homologs. Comparative genome-wide analyses of untreated diploid cells lacking Blm10 and growing at steady state at defined growth rates revealed downregulation of numerous genes required for accurate chromosome structure, assembly and repair, and upregulation of a specific subset of genes encoding protein-folding chaperones. Blm10 loss or truncation of the Ubp3/Blm3 deubiquitinating enzyme caused massive chromosomal damage and cell death in homozygous diploids after phleomycin treatments, indicating that Blm10 and Ubp3/Blm3 function to stabilize the genome and protect against cell death. Diploids lacking Blm10 also were sensitized to doxorubicin, hydroxyurea, 5-fluorouracil, rapamycin, hydrogen peroxide, methyl methanesulfonate, and calcofluor. Fluorescently tagged Blm10 localized in nuclei, with enhanced fluorescence after DNA replication. After DNA damage that caused a classic G2/M arrest, fluorescence remained diffuse, with evidence of nuclear fragmentation in some cells. Protective functions of Blm10 did not require the carboxyl-terminal region that makes close contact with 20S proteasomes, indicating that protection does not require this contact or the truncated Blm10 can interact with the proteasome apart from this region. Without its carboxyl-terminus, Blm10((-339aa)) localized to nuclei in untreated, nonproliferating (G(0)) cells, but not during G(1) S, G(2), and M. The results indicate Blm10 functions in protective mechanisms that include the machinery that assures proper assembly of chromosomes. These essential guardian functions have implications for ubiquitin-independent targeting in anticancer therapy. Targeting Blm10/PA200 together with one or more of the upregulated chaperones or a conventional treatment could be efficacious.

Win-win for wind and wildlife: a vision to facilitate sustainable development.

Wind energy offers the potential to reduce carbon emissions while increasing energy independence and bolstering economic development. However, wind energy has a larger land footprint per Gigawatt (GW) than most other forms of energy production, making appropriate siting and mitigation particularly important. Species that require large unfragmented habitats and those known to avoid vertical structures are particularly at risk from wind development. Developing energy on disturbed lands rather than placing new developments within large and intact habitats would reduce cumulative impacts to wildlife. The U.S. Department of Energy estimates that it will take 241 GW of terrestrial based wind development on approximately 5 million hectares to reach 20% electricity production for the U.S. by 2030. We estimate there are ∼7,700 GW of potential wind energy available across the U.S., with ∼3,500 GW on disturbed lands. In addition, a disturbance-focused development strategy would avert the development of ∼2.3 million hectares of undisturbed lands while generating the same amount of energy as development based solely on maximizing wind potential. Wind subsidies targeted at favoring low-impact developments and creating avoidance and mitigation requirements that raise the costs for projects impacting sensitive lands could improve public value for both wind energy and biodiversity conservation.