Regional models of the influence of human disturbance and habitat quality on the distribution of breeding territories of common ringed plover Charadrius hiaticula and Eurasian oystercatcher Haematopus ostralegus

We estimated the influence of human disturbance and environmental factors on territory establishment in common ringed plovers Charadrius hiaticula and Eurasian oystercatchers Haematopus ostralegus, to inform the conservation of these species. We examined a 212 km stretch of coastline in the United Kingdom in 2003, mapping all breeding pairs of both study species, as well as the environmental characteristics of beaches and locations of visitors on the beach, the latter measured by filming from a light aircraft. Of the 1,003 200m sections of beach surveyed, 183 contained ringed plover territories (267 breeding pairs) and 117 contained oystercatcher territories (226 breeding pairs). 38,634 human visitors to the beach were mapped from three flights. Population densities of both ringed plovers and oystercatchers were lower in locations with high visitor numbers, even when accounting for the influence of the environmental characteristics of the beach. The two bird species showed similar rates of territory establishment at very low visitor rates, but oystercatchers showed a stronger negative response when visitor rates reached higher levels. Binary logistic regression models were used to identify areas where the birds would benefit most from reductions in the number of visitors and we illustrate how this information could be used to inform management around sites otherwise favourable for territory establishment.We would like to thank Viola Kimmel and Emma Coombes for digitising visitors from the aerial videos, the Tyndall centre, University of East Anglia, for funding the project, and English Nature, the National Trust and Landguard Bird Observatory for supplying some of the bird data (as described in the methods section)

Regional models of the influence of human disturbance and habitat quality on the distribution of breeding territories of common ringed plover Charadrius hiaticula and Eurasian oystercatcher Haematopus ostralegus

This is the final version. Available from Elsevier via the DOI in this record. We estimated the influence of human disturbance and environmental factors on territory establishment in common ringed plovers Charadrius hiaticula and Eurasian oystercatchers Haematopus ostralegus, to inform the conservation of these species. We examined a 212 km stretch of coastline in the United Kingdom in 2003, mapping all breeding pairs of both study species, as well as the environmental characteristics of beaches and locations of visitors on the beach, the latter measured by filming from a light aircraft. Of the 1003,200 m sections of beach surveyed, 183 contained ringed plover territories (267 breeding pairs) and 117 contained oystercatcher territories (226 breeding pairs). 38,634 human visitors to the beach were mapped from three flights. Population densities of both ringed plovers and oystercatchers were lower in locations with high visitor numbers, even when accounting for the influence of the environmental characteristics of the beach. The two bird species showed similar rates of territory establishment at very low visitor rates, but oystercatchers showed a stronger negative response when visitor rates reached higher levels. Binary logistic regression models were used to identify areas where the birds would benefit most from reductions in the number of visitors and we illustrate how this information could be used to inform management around sites otherwise favourable for territory establishment.Tyndall Centre for Climate Research, University of East Angli

Characterization of deposits formed on diesel injectors in field test and from thermal oxidative degradation of n-hexadecane in a laboratory reactor

Solid deposits from commercially available high-pressure diesel injectors (HPDI) were analyzed to study the solid deposition from diesel fuel during engine operation. The structural and chemical properties of injector deposits were compared to those formed from the thermal oxidative stressing of a diesel fuel range model compound, n-hexadecane at 160°C and 450 psi for 2.5 h in a flow reactor. Both deposits consist of polyaromatic compounds (PAH) with oxygen moieties. The similarities in structure and composition of the injector deposits and n-hexadecane deposits suggest that laboratory experiments can simulate thermal oxidative degradation of diesel in commercial injectors. The formation of PAH from n-hexadecane showed that aromatization of straight chain alkanes and polycondensation of aromatic rings was possible at temperatures as low as 160°C in the presence of oxygen. A mechanism for an oxygen-assisted aromatization of cylcoalkanes is proposed

Pre-Clinical Drug Prioritization via Prognosis-Guided Genetic Interaction Networks

The high rates of failure in oncology drug clinical trials highlight the problems of using pre-clinical data to predict the clinical effects of drugs. Patient population heterogeneity and unpredictable physiology complicate pre-clinical cancer modeling efforts. We hypothesize that gene networks associated with cancer outcome in heterogeneous patient populations could serve as a reference for identifying drug effects. Here we propose a novel in vivo genetic interaction which we call ‘synergistic outcome determination’ (SOD), a concept similar to ‘Synthetic Lethality’. SOD is defined as the synergy of a gene pair with respect to cancer patients' outcome, whose correlation with outcome is due to cooperative, rather than independent, contributions of genes. The method combines microarray gene expression data with cancer prognostic information to identify synergistic gene-gene interactions that are then used to construct interaction networks based on gene modules (a group of genes which share similar function). In this way, we identified a cluster of important epigenetically regulated gene modules. By projecting drug sensitivity-associated genes on to the cancer-specific inter-module network, we defined a perturbation index for each drug based upon its characteristic perturbation pattern on the inter-module network. Finally, by calculating this index for compounds in the NCI Standard Agent Database, we significantly discriminated successful drugs from a broad set of test compounds, and further revealed the mechanisms of drug combinations. Thus, prognosis-guided synergistic gene-gene interaction networks could serve as an efficient in silico tool for pre-clinical drug prioritization and rational design of combinatorial therapies

Multiple-input multiple-output causal strategies for gene selection

Traditional strategies for selecting variables in high dimensional classification problems aim to find sets of maximally relevant variables able to explain the target variations. If these techniques may be effective in generalization accuracy they often do not reveal direct causes. The latter is essentially related to the fact that high correlation (or relevance) does not imply causation. In this study, we show how to efficiently incorporate causal information into gene selection by moving from a single-input single-output to a multiple-input multiple-output setting.Journal ArticleResearch Support, N.I.H. ExtramuralResearch Support, Non-U.S. Gov'tSCOPUS: ar.jinfo:eu-repo/semantics/publishe

Inferring the Transcriptional Landscape of Bovine Skeletal Muscle by Integrating Co-Expression Networks

Background: Despite modern technologies and novel computational approaches, decoding causal transcriptional regulation remains challenging. This is particularly true for less well studied organisms and when only gene expression data is available. In muscle a small number of well characterised transcription factors are proposed to regulate development. Therefore, muscle appears to be a tractable system for proposing new computational approaches. Methodology/Principal Findings: Here we report a simple algorithm that asks "which transcriptional regulator has the highest average absolute co-expression correlation to the genes in a co-expression module?" It correctly infers a number of known causal regulators of fundamental biological processes, including cell cycle activity (E2F1), glycolysis (HLF), mitochondrial transcription (TFB2M), adipogenesis (PIAS1), neuronal development (TLX3), immune function (IRF1) and vasculogenesis (SOX17), within a skeletal muscle context. However, none of the canonical pro-myogenic transcription factors (MYOD1, MYOG, MYF5, MYF6 and MEF2C) were linked to muscle structural gene expression modules. Co-expression values were computed using developing bovine muscle from 60 days post conception (early foetal) to 30 months post natal (adulthood) for two breeds of cattle, in addition to a nutritional comparison with a third breed. A number of transcriptional landscapes were constructed and integrated into an always correlated landscape. One notable feature was a 'metabolic axis' formed from glycolysis genes at one end, nuclear-encoded mitochondrial protein genes at the other, and centrally tethered by mitochondrially-encoded mitochondrial protein genes. Conclusions/Significance: The new module-to-regulator algorithm complements our recently described Regulatory Impact Factor analysis. Together with a simple examination of a co-expression module's contents, these three gene expression approaches are starting to illuminate the in vivo transcriptional regulation of skeletal muscle development

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability