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The presence of carcinoma in situ (CIS) is traditionally a contraindication to bladder-sparing approaches for muscle invasive bladder cancer (MIBC). Strategies that might aid in bladder preservation for this population require further investigation. We report a case of MIBC with CIS treated with both neoadjuvant systemic and intravesical chemotherapy prior to partial cystectomy.

Background: The current standard of care for men with muscle-invasive bladder cancer is radical cystoprostatectomy (RCP). One-third of RCP specimens demonstrate incidental prostate cancer, primarily reported in small series with limited follow-up. The aim of this study is to report mature outcomes, including patterns of failure and disease-specific recurrence rates, and survival, for a large cohort of men with incidental prostate cancer at RCP performed at a tertiary referral center. Methods: This retrospective study describes cancer control and survival rates for men who underwent RCP for bladder cancer and were found incidentally to have prostate cancer. Analysis of patient-, tumor-, and treatment-specific factors were analyzed for association with disease control and survival endpoints. Results: Between 2002 and 2010, 94 patients with incidental discovery of prostate cancer postRCP were identified for inclusion in this study. Forty-five patients (45%) underwent RCP for recurrent (rather than initial presentation of) bladder carcinoma. At a median follow-up of 40.3 months (71.2 months for survivors; range, 8.9–155.5 months), 42 patients were alive without recurrence and 52 patients had died (25 associated with disease). The estimated 5-year bladder cancer disease-free, urinary tract malignancy disease-free, and prostate specific antigen (PSA) relapse-free survivals were 76% [95% confidence interval (CI), 65–84%], 64% (52–74%), and 97% (79–100%), respectively. The estimated 5-year urinary tract malignancy-specific and overall survivals were 61% (49–71%) and 52% (41–62%), respectively. Univariate analysis demonstrated associations between pathologic T/N-stage and nodal ratio with bladder cancer disease-free, urinary tract malignancy disease-specific, and overall survivals, with patient age at diagnosis as an additional adverse factor associated with overall survival. Multivariate analysis confirmed pN-stage and age as independently associated with worse survival. Conclusion: For men undergoing RCP for bladder cancer, the present study suggests that incidentally discovered prostate cancers, irrespective of pathologic stage, Gleason score, or clinical significance, do not impact 5-year disease control or survival outcomes.

Road networks and their associated vehicular traffic disturb many terrestrial systems, but inventories of roads used to assess these effects often focus on the ‘where’ (e.g., local road type and density) and neglect the ‘when’ (e.g., temporal disturbance) or ‘how much’ (e.g., traffic volume disturbance). We developed annual estimates of the ‘when’ (road age) and ‘how much’ (vehicular traffic volume) across 148,172 km of highways, arterials, collectors, local, and gravel/graded roads within the state of Wyoming for the years 1986 to 2020 to provide a comprehensive dataset for future ecological investigations. We leveraged a suite of ancillary data on surface disturbances (e.g., oil & gas drilling operations, wind turbines, and open pit mines) with known establishment dates and combined them using graph theory and centrality metrics to estimate the age of each road. We then predicted traffic volume obtained from the Wyoming Department of Transportation for each year across Wyoming using a machine learning method, XGBoost, and a separate set of spatial covariates hypothesized to explain traffic patterns across large regions. We found that 132,476 km of these roads likely existed before 1986, but that 16,693 km (10.7 %) of roads have been built since 1986. Overall, our estimates of road age were 89 % accurate when assessed on a subset of 1,330 roads with high-resolution aerial imagery. Mean absolute error for predicting traffic volume ranged from 35.2 to 77.9 annual average daily traffic (aadt) for trucks and 269.2 to 516.7 aadt for all-vehicles across the 35 years. We found that mean traffic volume across the state increased by 23 % for both truck-only traffic and all vehicular traffic from 1986 to 2020. However, changes in traffic volume have varied substantially across the state (e.g., 100 % increases in volume in some areas, while other areas experienced declines of up to 1,786 %). We also illustrate a novel application of these data by predicting rates of reported wildlife-vehicle collisions (WVCs) along a subset of roads. We found evidence of a non-linear relationship that supported a threshold hypothesis for WVCs, wherein increases in traffic volume equate to increases in WVCs up to a threshold, above which increases in traffic volume result in declines in WVCs. The data provided here will enable better-informed studies of road ecology to address how roads may affect wildlife populations and key ecosystems across Wyoming.

Summary: Rad24-RFC (replication factor C) loads the 9-1-1 checkpoint clamp onto the recessed 5′ ends by binding a 5′ DNA at an external surface site and threading the 3′ single-stranded DNA (ssDNA) into 9-1-1. We find here that Rad24-RFC loads 9-1-1 onto DNA gaps in preference to a recessed 5′ end, thus presumably leaving 9-1-1 on duplex 3′ ss/double-stranded DNA (dsDNA) after Rad24-RFC ejects from DNA. We captured five Rad24-RFC-9-1-1 loading intermediates using a 10-nt gap DNA. We also determined the structure of Rad24-RFC–9-1-1 using a 5-nt gap DNA. The structures reveal that Rad24-RFC is unable to melt DNA ends and that a Rad24 loop limits the dsDNA length in the chamber. These observations explain Rad24-RFC’s preference for a preexisting gap of over 5-nt ssDNA and suggest a direct role of the 9-1-1 in gap repair with various TLS (trans-lesion synthesis) polymerases in addition to signaling the ATR kinase.

A fundamental goal of population ecologists is to identify drivers responsible for temporal variation in abundance. Understanding whether variation is associated with environmental stochasticity or anthropogenic disturbances, which are more amenable to management action, is crucial yet difficult to achieve. Here, we present a hierarchical monitoring framework that models rates of change in abundance from spatially structured populations and identifies when local declines fall out of synchrony with trends at larger spatial scales. Importantly, the framework provides signals that alert managers to the categorical significance of observed declines while avoiding signals where declines result from drivers operating at larger spatial scales (e.g., periodic reductions in primary productivity owing to drought). We demonstrate utility through application to a rapidly declining sagebrush (Artemisia spp.) indicator species (greater sage-grouse; Centrocercus urophasianus) using 30 years (1990–2019) of count data collected from greater than 4,400 leks (habitual breeding sites) distributed across the western United States. Results revealed population declines, immediately preceding triggers (2–4-year period), ranging between 58 and 68%. Conversely, population trends unassociated with triggers showed little-to-no sign of decline. Retrospective application of the monitoring framework indicated an average annual rate of 1.7% of leks or 1.3% of neighborhood clusters (lek aggregations) would have required management intervention to reverse range-wide declines and stabilize the U.S. population as a whole.

Identifying habitat needs for species with large distributions is challenging because species-habitat associations may vary across scales and regions (spatial nonstationarity). Furthermore, management efforts often cross jurisdictional boundaries, complicating the development of cohesive conservation strategies among management entities. The greater sage-grouse (Centrocercus urophasianus) is a rapidly declining species that spans 11 U.S. states and responds to habitat conditions across a wide range of spatial scales and regions. Allowing for regional variance in species-habitat associations and suitability predictions could systematically identify important habitats at levels relevant to management. We collaboratively developed a model with Bureau of Land Management (BLM) biologists that: (1) evaluated the scale of effect for different environmental covariates; (2) accounted for regional differences in population-level responses; and (3) predicted probabilities of persistence across the U.S. occupied range. We modeled range-wide lek persistence data (6615 communal breeding sites classified as active or inactive) as a function of environmental covariates. Environmental covariates included sagebrush cover, pinyon-juniper cover, topography, precipitation, point and line disturbance densities, and landscape configuration metrics. Our model treated habitat assessment areas – regionally delineated by BLM biologists – as random intercepts and slopes that allowed for geographic variation in species-habitat associations and predicted probabilities of lek persistence. Our final model indicated support for 12 environmental covariates predicting lek persistence at scales extending between 1- to 15-km radii from lek centers, and a covariate measuring distance to the occupied range boundary. Five of these covariates showed significant regionally varying responses: sagebrush clumpiness (a measure of habitat aggregation), pinyon-juniper cover, point disturbance of anthropogenic features such as energy infrastructure and communication towers, elevation, and a topographic index associated with mesic habitats. This spatial nonstationarity indicates unitary range-wide recommendations, or rules-of-thumb with respect to their effects on lek persistence, may be problematic for these environmental conditions. For covariates that did not include random slopes, and which were potentially amenable to management actions, we found that leks were predicted to become extirpated when sagebrush cover fell below 9.6 % (summarized at the 3.2-km radius extent), and the proportion of classified sagebrush habitat fell below 0.7 (1-km). We produced a continuous predictive probability surface of lek persistence which we binned based on model sensitivity thresholds to produce habitat quality categories. The highest quality habitat (capturing 50 % of active leks) covered 25.5 % of the occupied range, while the combined lowest through highest quality habitats (capturing 95 % of active leks) covered 65.0 %. Accommodating regional environmental differences in models that are relevant to habitat management planning will help ensure their applicability to targeted goals. Continuous collaboration between modelers and land managers early in the modeling process increases the likelihood of this outcome.

Identifying, protecting, and restoring habitats for declining wildlife populations is foundational to conservation and recovery planning for any species at risk of decline. Resource selection analysis is a key tool to assess habitat and prescribe management actions. Yet, it can be challenging to map suitable resource conditions across a wide range of ecological contexts and use the resulting models to identify effective and universal habitat improvement actions. We developed a management-centric modeling approach that sought to balance the need to evaluate the consistency of key habitat conditions and improvement actions across multiple, distinct populations, while allowing context-specific environmental variables and spatial scales to nuance selection responses that form the basis of location-specific management prescriptions. To demonstrate this approach, we developed a set of habitat selection models for Gunnison sage-grouse (Centrocercus minimus), a threatened species under the U.S. Endangered Species Act. Conservation, species recovery, and habitat management efforts are needed in six isolated satellite populations (San Miguel, Crawford, Piñon Mesa, Dove Creek, Cerro Summit-Cimarron-Sims, and Poncha Pass) where environmental conditions differ, and the already small number of birds are declining. We used multi-scale and seasonal resource selection analyses to quantify relationships between environmental conditions and sites used by animals. All models included key habitat variables often altered through management actions to assess their differential influences across models. We found important similarities and differences among satellites, indicating that, although some rules of thumb are generally well-grounded, the consideration of population-specific environmental differences could increase the efficiency of local habitat improvement actions. Sage-grouse also had diverse responses to resource conditions at different scales, indicating that regional spatial (e.g., landscape) and local patch scale can differentially influence expected habitat improvements associated with where such management actions are implemented. Although context variables such as topography cannot be manipulated, sage-grouse associations revealed information that could guide the siting of improvement actions. This approach to balancing management objectives associated with habitat assessment may benefit spatially-structured populations with different environmental contexts and species with complex habitat needs and associations.