Contact Patterns Among Bighorn Sheep In and Around Glacier National Park

Identifying patterns of direct contacts among individual animals is important to understanding infectious disease transmission. Social behavior can be influenced by both intrinsic and extrinsic variables and can be explored at 3 levels: social network structure, dyad structure, and contact structure. We investigated drivers of contact structure using GPS locations of 87 male and female bighorn sheep (Ovis canadensis) in and around Glacier National Park in Montana, USA. Focusing on contacts between sheep moving separately, we examined relationships between contact locations and movement variables, land cover, distances to various resources, and variables known to influence survival using a resource selection function. Used and available points were defined as simultaneous locations within 25 m (the contact-used) and 13 km (largest step length- available) of another collared bighorn sheep, thus results of this analysis describe the strengths of these variables relative to habitat use. Data were analyzed separately according to dyad type (male-male, female-female, malefemale). Most contacts occurred in March for male-male and female-female dyads and in November, December, and January for male-female dyads. For male-male dyads, contacts occurred more than expected given habitat use in conifer land cover and locations farther from perennial water sources, high NDVI, little canopy cover, and low and high solar radiation index. For female-female dyads, contacts occurred less than expected given habitat use in grass and barren land cover and locations with intermediate terrain ruggedness, high NDVI, and low and high snow water equivalent. For male-female dyads, contacts occurred most during the night, least during the day, and at locations with intermediate elevation and farther from escape terrain. Together, these results suggest that more specific conditions apply to contact locations than general locations and that we can predict locations where contacts are most likely to occur, which may be useful for disease management

Bighorn sheep associations: understanding tradeoffs of sociality and implications for disease transmission

Sociality directly influences mating success, survival rates, and disease, but ultimately likely evolved for its fitness benefits in a challenging environment. The tradeoffs between the costs and benefits of sociality can operate at multiple scales, resulting in different interpretations of animal behavior. We investigated the influence of intrinsic (e.g., relatedness, age) and extrinsic factors (e.g., land cover type, season) on direct contact (simultaneous GPS locations ≤ 25 m) rates of bighorn sheep (Ovis canadensis) at multiple scales near the Waterton-Glacier International Peace Park. During 2002–2012, male and female bighorn were equipped with GPS collars. Indirect contact (GPS locations ≤ 25 m regardless of time) networks identified two major breaks whereas direct contact networks identified an additional barrier in the population, all of which corresponded with prior disease exposure metrics. More direct contacts occurred between same-sex dyads than female-male dyads and between bighorn groups with overlapping summer home ranges. Direct contacts occurred most often during the winter-spring season when bighorn traveled at low speeds and when an adequate number of bighorn were collared in the area. Direct contact probabilities for all dyad types were inversely related to habitat quality, and differences in contact probability were driven by variables related to survival such as terrain ruggedness, distance to escape terrain, and canopy cover. We provide evidence that probabilities of association are higher when there is greater predation risk and that contact analysis provides valuable information for understanding fitness tradeoffs of sociality and disease transmission potential

Hydrology influences carbon flux through metabolic pathways in the hypolimnion of a Mediterranean reservoir

Global change is modifying meteorological and hydrological factors that influence the thermal regime of water bodies. These modifications can lead to longer stratification periods with enlarged hypolimnetic anoxic periods, which can promote heterotrophic anaerobic processes and alter reservoir carbon cycling. Here, we quantified aerobic and anaerobic heterotrophic processes (aerobic respiration, denitrification, iron and manganese reduction, sulfate reduction, and methanogenesis) on dissolved inorganic carbon (DIC) production in the hypolimnion of a Mediterranean reservoir (El Gergal, Spain) under two contrasting hydrological conditions: a wet year with heavy direct rainfall and frequent water inputs from upstream reservoirs, and a dry year with scarce rainfall and negligible water inputs. During the wet year, water inputs and rainfall induced low water column thermal stability and earlier turnover. By contrast, thermal stratification was longer and more stable during the dry year. During wet conditions, we observed lower DIC accumulation in the hypolimnion, mainly due to weaker sulfate reduction and methanogenesis. By contrast, longer stratification during the dry year promoted higher hypolimnetic DIC accumulation, resulting from enhanced methanogenesis and sulfate reduction, thus increasing methane emissions and impairing reservoir water quality. Aerobic respiration, denitrification and metal reduction produced a similar amount of DIC in the hypolimnion during the two studied years. All in all, biological and geochemical (calcite dissolution) processes explained most of hypolimnetic DIC accumulation during stratification regardless of the hydrological conditions, but there is still ~ 30% of hypolimnetic DIC production that cannot be explained by the processes contemplated in this study and the assumptions made.This research was funded by project Alter-C (PID2020-114024GB-C31, PID2020-114024GB-C32, PID2020-114024GB-C33) of Spanish Ministry of Science and Innovation (Spanish Research Agency, AEI). JJM-P was supported by a Spanish FPI grant (RE2018-083596). EMASESA staff provide essential technical support during field surveys. R.M. acknowledges funding from Generalitat de Catalunya through the Consolidated Research Group 2017SGR1124 and the CERCA programme. Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. Funding for open access charge: Universidad de Málaga / CBUA

Extending the viability of human precision-cut intestinal slice model for drug metabolism studies

Human Precision-cut intestinal slices (hPCIS) are used to study intestinal physiology, pathophysiology, drug efficacy, toxicology, kinetics, and metabolism. However, the use of this ex vivo model is restricted to approximately a 24 h timeframe because of declining viability of the hPCIS during traditional culture. We hypothesized that we could extend the hPCIS viability by using organoid medium. Therefore, we cultured hPCIS for up to 72 h in organoid media [expansion medium (Emed) and differentiation medium (Dmed)]. After incubation, we assessed culture-induced changes on viability markers, specific cell type markers and we assessed the metabolic activity of enterocytes by measuring midazolam metabolite formation. We show that the adenosine triphosphate (ATP)/protein ratio of Emed-cultured hPCIS and morphology of both Emed- and Dmed-cultured hPCIS was improved compared to WME-cultured hPCIS. Emed-cultured hPCIS showed an increased expression of proliferation and stem cell markers, whereas Dmed-cultured hPCIS showed an increased expression of proliferation and enterocyte markers, along with increased midazolam metabolism. Using the Emed, the viability of hPCIS could be extended for up to 72 h, and proliferating stem cells remained preserved. Using Dmed, hPCS also remained viable for up to 72 h, and specifically rescued the metabolizing enterocytes during culture. In conclusion, by using two different organoid culture media, we could extend the hPCIS viability for up to 72 h of incubation and specifically steer stem cells or enterocytes towards their original function, metabolism, and proliferation, potentially allowing pharmacokinetic and toxicology studies beyond the 24 h timeframe

Impact of plasma-wall interaction and exhaust on the EU-DEMO design

In the present work, the role of plasma facing components protection in driving the EU-DEMO design will be reviewed, focusing on steady-state and, especially, on transients. This work encompasses both the first wall (FW) as well as the divertor. In fact, while the ITER divertor heat removal technology has been adopted, the ITER FW concept has been shown in the past years to be inadequate for EU-DEMO. This is due to the higher foreseen irradiation damage level, which requires structural materials (like Eurofer) able to withstand more than 5 dpa of neutron damage. This solution, however, limits the tolerable steady-state heat flux to ~1 MW/m2, i.e. a factor 3–4 below the ITER specifications. For this reason, poloidally and toroidally discontinuous protection limiters are implemented in EU-DEMO. Their role consists in reducing the heat load on the FW due to charged particles, during steady state and, more importantly, during planned and off-normal plasma transients. Concerning the divertor configuration, EU-DEMO currently assumes an ITER-like, lower single null (LSN) divertor, with seeded impurities for the dissipation of the power. However, this concept has been shown by numerous simulations in the past years to be marginal during steady-state (where a detached divertor is necessary to maintain the heat flux below the technological limit and to avoid excessive erosion) and unable to withstand some relevant transients, such as large ELMs and accidental loss of detachment. Various concepts, deviating from the ITER design, are currently under investigation to mitigate such risks, for example in-vessel coils for strike point sweeping in case of reattachment, as well as alternative divertor configurations. Finally, a broader discussion on the impact of divertor protection on the overall machine design is presented

UK Head and neck cancer surgical capacity during the second wave of the COVID—19 pandemic: Have we learned the lessons? COVIDSurg collaborative

Objectives The aim of this study was to evaluate the differences in surgical capacity for head and neck cancer in the UK between the first wave (March-June 2020) and the current wave (Jan-Feb 2021) of the COVID-19 pandemic. Design REDcap online-based survey of hospital capacity. Setting UK secondary and tertiary hospitals providing head and neck cancer surgery. Participants One representative per hospital was asked to report the capacity for head and neck cancer surgery in that institution. Main outcome measures The principal measures of interests were new patient referrals, capacity in outpatients, theatres and critical care; therapeutic compromises constituting delay to surgery, de-escalated surgery and therapeutic migration to non-surgical primary modality. Results Data were returned from approximately 95% of UK hospitals with a head and neck cancer surgery specialist service. 50% of UK head and neck cancer patients requiring surgery have significantly compromised treatments during the second wave: 28% delayed, 10% have received radiotherapy-based treatment instead of surgery, and 12% have received de-escalated surgery. Surgical capacity has been more severely constrained in the second wave (58% of pre-pandemic level) compared with the first wave (62%) despite the time to prepare. Conclusions Some hospitals are overwhelmed by COVID-19 and unable to offer essential cancer surgery, but all have neighbouring hospitals in their region retaining good (or even normal) capacity. It is noteworthy that very few patients have been appropriately redirected away from the hospitals most constrained by their burden of COVID-19. The paucity of an effective central or regional strategic response to this evident mismatch between demand and surgical capacity is to the detriment of our head and neck cancer patients

Development of a concept and basis for the DEMO diagnostic and control system

An initial concept for the plasma diagnostic and control (D&C) system has been developed as part of European studies towards the development of a demonstration tokamak fusion reactor (DEMO). The main objective is to develop a feasible, integrated concept design of the DEMO D&C system that can provide reliable plasma control and high performance (electricity output) over extended periods of operation. While the fusion power is maximized when operating near to the operational limits of the tokamak, the reliability of operation typically improves when choosing parameters significantly distant from these limits. In addition to these conflicting requirements, the D&C development has to cope with strong adverse effects acting on all in vessel components on DEMO (harsh neutron environment, particle fluxes, temperatures, electromagnetic forces, etc.). Moreover, space allocation and plasma access are constrained by the needs for first wall integrity and optimization of tritium breeding. Taking into account these boundary conditions, the main DEMO plasma control issues have been formulated, and a list of diagnostic systems and channels needed for plasma control has been developed, which were selected for their robustness and the required coverage of control issues. For a validation and refinement of this concept, simulation tools are being refined and applied for equilibrium, kinetic and mode control studies

Demographic uncertainty and disease risk influence climate-informed management of an alpine species

Climate change is expected to disproportionately affect species occupying ecosystems with relatively hard boundaries, such as alpine ecosystems. Wildlife managers must identify actions to conserve and manage alpine species into the future, while considering other issues and uncertainties. Climate change and respiratory pathogens associated with widespread pneumonia epidemics in bighorn sheep (Ovis canadensis) may negatively affect mountain goat (Oreamnos americanus) populations. Mountain goat demographic and population data are challenging to collect and sparsely available, making population management decisions difficult. We developed predictive models incorporating these uncertainties and analyzed results within a structured decision making framework to make management recommendations and identify priority information needs in Montana, USA. We built resource selection models to forecast occupied mountain goat habitat and account for uncertainty in effects of climate change, and a Leslie matrix projection model to predict population trends while accounting for uncertainty in population demographics and dynamics. We predicted disease risks while accounting for uncertainty about presence of pneumonia pathogens and risk tolerance for mixing populations during translocations. Our analysis predicted that new introductions would produce more area occupied by mountain goats at mid-century, regardless of the effects of climate change. Population augmentations, carnivore management, and harvest management may improve population trends, although this was associated with considerable uncertainty. Tolerance for risk of disease transmission affected optimal management choices because translocations are expected to increase disease risks for mountain goats and sympatric bighorn sheep. Expected value of information analyses revealed that reducing uncertainty related to population dynamics would affect the optimal choice among management strategies to improve mountain goat trends. Reducing uncertainty related to the presence of pneumonia-associated pathogens and consequences of mixing microbial communities should reduce disease risks if translocations are included in future management strategies. We recommend managers determine tolerance for disease risks associated with translocations that they and constituents are willing to accept. From this, an adaptive management program can be constructed wherein a portfolio of management actions are chosen based on risk tolerance in each population range, combined with the amount that uncertainty is reduced when paired with monitoring, to ultimately improve achievement of fundamental objectives

Computational personality recognition in social media

A variety of approaches have been recently proposed to automatically infer users' personality from their user generated content in social media. Approaches differ in terms of the machine learning algorithms and the feature sets used, type of utilized footprint, and the social media environment used to collect the data. In this paper, we perform a comparative analysis of state-of-the-art computational personality recognition methods on a varied set of social media ground truth data from Facebook, Twitter and YouTube. We answer three questions: (1) Should personality prediction be treated as a multi-label prediction task (i.e., all personality traits of a given user are predicted at once), or should each trait be identified separately? (2) Which predictive features work well across different on-line environments? (3) What is the decay in accuracy when porting models trained in one social media environment to another