Essential and virulence-related protein interactions of pathogens revealed through deep learning.

Identification of bacterial protein-protein interactions and predicting the structures of the complexes could aid in the understanding of pathogenicity mechanisms and developing treatments for infectious diseases. Here, we developed a deep learning-based pipeline that leverages residue-residue coevolution and protein structure prediction to systematically identify and structurally characterize protein-protein interactions at the proteome-wide scale. Using this pipeline, we searched through 78 million pairs of proteins across 19 human bacterial pathogens and identified 1923 confidently predicted complexes involving essential genes and 256 involving virulence factors. Many of these complexes were not previously known; we experimentally tested 12 such predictions, and half of them were validated. The predicted interactions span core metabolic and virulence pathways ranging from post-transcriptional modification to acid neutralization to outer membrane machinery and should contribute to our understanding of the biology of these important pathogens and the design of drugs to combat them.

Laxative-prescribing habits: a summative impact evaluation of a constipation programme implemented in two hospitals in New Zealand.

AIMS: To evaluate the impact of a multifaceted intervention aimed at improving adherence to a list of preferred laxatives in two hospitals in New Zealand. METHODS: A constipation programme was developed at Capital & Coast District Health Board to improve adherence to safe and effective (preferred) laxatives over potentially dangerous and less effective (non-preferred) agents. The intervention included a new constipation guideline, a poster of preferred laxatives, a patient information leaflet, hospital formulary adjustments and staff education. The evaluation compared the number of dispensations of each laxative during two periods: a 12-month period prior to programme implementation and a 12-month period following programme implementation. Data were retrospectively gathered from multiple sources on all laxatives dispensed on 14 adult wards across two New Zealand hospitals. RESULTS: Prior to the programme, there were 111,771 laxatives dispensed, the majority of which (62%) were non-preferred agents. Following the programme, there were 91,005 laxatives dispensed, the majority of which (82%) were from the preferred list, indicating a large shift in prescribing habits. CONCLUSIONS: Inpatient laxative prescribing habits require attention and are amenable to quality improvement initiatives. This may reduce waste, prevent harm and improve patient outcomes.

Forecasting water temperature in lakes and reservoirs using seasonal climate prediction.

Seasonal climate forecasts produce probabilistic predictions of meteorological variables for subsequent months. This provides a potential resource to predict the influence of seasonal climate anomalies on surface water balance in catchments and hydro-thermodynamics in related water bodies (e.g., lakes or reservoirs). Obtaining seasonal forecasts for impact variables (e.g., discharge and water temperature) requires a link between seasonal climate forecasts and impact models simulating hydrology and lake hydrodynamics and thermal regimes. However, this link remains challenging for stakeholders and the water scientific community, mainly due to the probabilistic nature of these predictions. In this paper, we introduce a feasible, robust, and open-source workflow integrating seasonal climate forecasts with hydrologic and lake models to generate seasonal forecasts of discharge and water temperature profiles. The workflow has been designed to be applicable to any catchment and associated lake or reservoir, and is optimized in this study for four catchment-lake systems to help in their proactive management. We assessed the performance of the resulting seasonal forecasts of discharge and water temperature by comparing them with hydrologic and lake (pseudo)observations (reanalysis). Precisely, we analysed the historical performance using a data sample of past forecasts and reanalysis to obtain information about the skill (performance or quality) of the seasonal forecast system to predict particular events. We used the current seasonal climate forecast system (SEAS5) and reanalysis (ERA5) of the European Centre for Medium Range Weather Forecasts (ECMWF). We found that due to the limited predictability at seasonal time-scales over the locations of the four case studies (Europe and South of Australia), seasonal forecasts exhibited none to low performance (skill) for the atmospheric variables considered. Nevertheless, seasonal forecasts for discharge present some skill in all but one case study. Moreover, seasonal forecasts for water temperature had higher performance in natural lakes than in reservoirs, which means human water control is a relevant factor affecting predictability, and the performance increases with water depth in all four case studies. Further investigation into the skillful water temperature predictions should aim to identify the extent to which performance is a consequence of thermal inertia (i.e., lead-in conditions).

Blame-Laden Moral Rebukes and the Morally Competent Robot: A Confucian Ethical Perspective.

Empirical studies have suggested that language-capable robots have the persuasive power to shape the shared moral norms based on how they respond to human norm violations. This persuasive power presents cause for concern, but also the opportunity to persuade humans to cultivate their own moral development. We argue that a truly socially integrated and morally competent robot must be willing to communicate its objection to humans' proposed violations of shared norms by using strategies such as blame-laden rebukes, even if doing so may violate other standing norms, such as politeness. By drawing on Confucian ethics, we argue that a robot's ability to employ blame-laden moral rebukes to respond to unethical human requests is crucial for cultivating a flourishing "moral ecology" of human-robot interaction. Such positive moral ecology allows human teammates to develop their own moral reflection skills and grow their own virtues. Furthermore, this ability can and should be considered as one criterion for assessing artificial moral agency. Finally, this paper discusses potential implications of the Confucian theories for designing socially integrated and morally competent robots.

CXCL10 increases in human skeletal muscle following damage but is not necessary for muscle regeneration.

CXCL10 is a chemokine for activated and memory T cells with many important immunological functions. We recently found that CXCL10 is upregulated in human muscle following contraction-induced damage. No information is available on the role of CXCL10 in the context of muscle damage or repair. In this study, we confirm that CXCL10 is elevated in human muscle at 2 and 3 days following damage and perform cell culture and animal studies to examine the role of CXCL10 in muscle repair. CXCL10 did not impact proliferation rates of human primary myoblasts but it did promote myogenic differentiation in vitro, suggesting a possible direct impact on muscle regeneration. To test if CXCL10 was dispensable for effective muscle regeneration in vivo, we measured functional and histological markers of muscle repair out to 14 days postmuscle injury caused by a myotoxin in wild-type (WT) mice and CXCL10 knockout (KO) mice. Between genotypes, no significant differences were found in loss or restoration of in situ muscle force, cross-sectional area of newly formed myofibers, or the number of embryonic myosin heavy chain-positive myofibers. In addition, KO animals were not deficient in T-cell accumulation in the damaged muscle following injury. Gene expression of the other two ligands (CXCL9 and 11) that bind to the same receptor as CXCL10 were also elevated in the damaged muscle of KO mice. Thus, other ligands may have compensated for the lack of CXCL10 in the KO mice. We conclude that CXCL10 is not necessary for effective muscle regeneration.

Integrated cost-effectiveness analysis of agri-environmental measures for water quality.

This paper presents an application of integrated methodological approach for identifying cost-effective combinations of agri-environmental measures to achieve water quality targets. The methodological approach involves linking hydro-chemical modelling with economic costs of mitigation measures. The utility of the approach was explored for the River Dee catchment in North East Scotland, examining the cost-effectiveness of mitigation measures for nitrogen (N) and phosphorus (P) pollutants. In-stream nitrate concentration was modelled using the STREAM-N and phosphorus using INCA-P model. Both models were first run for baseline conditions and then their effectiveness for changes in land management was simulated. Costs were based on farm income foregone, capital and operational expenditures. The costs and effects data were integrated using 'Risk Solver Platform' optimization in excel to produce the most cost-effective combination of measures by which target nutrient reductions could be attained at a minimum economic cost. The analysis identified different combination of measures as most cost-effective for the two pollutants. An important aspect of this paper is integration of model-based effectiveness estimates with economic cost of measures for cost-effectiveness analysis of land and water management options. The methodological approach developed is not limited to the two pollutants and the selected agri-environmental measures considered in the paper; the approach can be adapted to the cost-effectiveness analysis of any catchment-scale environmental management options.

Assessing recovery from acidification of European surface waters in the year 2010: evaluation of projections made with the MAGIC model in 1995.

In 1999 we used the MAGIC (Model of Acidification of Groundwater In Catchments) model to project acidification of acid-sensitive European surface waters in the year 2010, given implementation of the Gothenburg Protocol to the Convention on Long-Range Transboundary Air Pollution (LRTAP). A total of 202 sites in 10 regions in Europe were studied. These forecasts can now be compared with measurements for the year 2010, to give a "ground truth" evaluation of the model. The prerequisite for this test is that the actual sulfur and nitrogen deposition decreased from 1995 to 2010 by the same amount as that used to drive the model forecasts; this was largely the case for sulfur, but less so for nitrogen, and the simulated surface water [NO3(-)] reflected this difference. For most of the sites, predicted surface water recovery from acidification for the year 2010 is very close to the actual recovery observed from measured data, as recovery is predominantly driven by reductions in sulfur deposition. Overall these results show that MAGIC successfully predicts future water chemistry given known changes in acid deposition.

Atmospheric deposition of phosphorus to land and freshwater.

We compiled published and newly-obtained data on the directly-measured atmospheric deposition of total phosphorus (TP), filtered total phosphorus (FTP), and inorganic phosphorus (PO4-P) to open land, lakes, and marine coasts. The resulting global data base includes data for c. 250 sites, covering the period 1954 to 2012. Most (82%) of the measurement locations are in Europe and North America, with 44 in Africa, Asia, Oceania, and South-Central America. The deposition rates are log-normally distributed, and for the whole data set the geometric mean deposition rates are 0.027, 0.019 and 0.14 g m(-2) a(-1) for TP, FTP and PO4-P respectively. At smaller scales there is little systematic spatial variation, except for high deposition rates at some sites in Germany, likely due to local agricultural sources. In cases for which PO4-P was determined as well as one of the other forms of P, strong parallels between logarithmic values were found. Based on the directly-measured deposition rates to land, and published estimates of P deposition to the oceans, we estimate a total annual transfer of P to and from the atmosphere of 3.7 Tg. However, much of the phosphorus in larger particles (principally primary biological aerosol particles) is probably redeposited near to its origin, so that long-range transport, important for tropical forests, large areas of peatland and the oceans, mainly involves fine dust from deserts and soils, as described by the simulations of Mahowald et al. (Global Biogeochemical Cycles 22, GB4026, 2008). We suggest that local release to the atmosphere and subsequent deposition bring about a pseudo-diffusive redistribution of P in the landscape, with P-poor ecosystems, for example ombrotrophic peatlands and oligotrophic lakes, gaining at the expense of P-rich ones. Simple calculations suggest that atmospheric transport could bring about significant local redistribution of P among terrestrial ecosystems. Although most atmospherically transported P is natural in origin, local transfers from fertilised farmland to P-poor ecosystems may be significant, and this requires further research.

Controls on soil solution nitrogen along an altitudinal gradient in the Scottish uplands.

Nitrogen (N) deposition continues to threaten upland ecosystems, contributing to acidification, eutrophication and biodiversity loss. We present results from a monitoring study aimed at investigating the fate of this deposited N within a pristine catchment in the Cairngorm Mountains (Scotland). Six sites were established along an elevation gradient (486-908 m) spanning the key habitats of temperate maritime uplands. Bulk deposition chemistry, soil carbon content, soil solution chemistry, soil temperature and soil moisture content were monitored over a 5 year period. Results were used to assess spatial variability in soil solution N and to investigate the factors and processes driving this variability. Highest soil solution inorganic N concentrations were found in the alpine soils at the top of the hillslope. Soil carbon stock, soil solution dissolved organic carbon (DOC) and factors representing site hydrology were the best predictors of NO(3)(-) concentration, with highest concentrations at low productivity sites with low DOC and freely-draining soils. These factors act as proxies for changing net biological uptake and soil/water contact time, and therefore support the hypothesis that spatial variations in soil solution NO(3)(-) are controlled by habitat N retention capacity. Soil percent carbon was a better predictor of soil solution inorganic N concentration than mass of soil carbon. NH(4)(+) was less affected by soil hydrology than NO(3)(-) and showed the effects of net mineralization inputs, particularly at Racomitrium heath and peaty sites. Soil solution dissolved organic N concentration was strongly related to both DOC and temperature, with a stronger temperature effect at more productive sites. Due to the spatial heterogeneity in N leaching potential, a fine-scale approach to assessing surface water vulnerability to N leaching is recommended over the broad scale, critical loads approach currently in use, particularly for sensitive areas.