Distinguishing between direct and indirect effects of predators in complex ecosystems

1. Global declines in biodiversity have stimulated much research into the consequences of species loss for ecosystems and the goods and services they provide. Species at higher trophic levels are at greater risk of human-induced extinction yet remarkably little is known about the effects of consumer species loss across multiple trophic levels in natural complex ecosystems. Previous studies have been criticized for lacking experimental realism and appropriate temporal scale, running for short periods that are not sufficient to detect many of the mechanisms operating in the field.
2. We manipulated the presence of two predator species and two groups of their prey (primary consumers) and measured their independent and interactive effects on primary producers in a natural marine benthic system. The presence of predators and their prey was manipulated in the field for 14 months to distinguish clearly the direct and indirect effects of predators on primary producers and to identify mechanisms driving responses.
3. We found that the loss of either predator species had indirect negative effects on species diversity and total cover of primary producers. These cascading effects of predator species loss were mediated by the presence of intermediate consumers. Moreover, the presence of different intermediate consumers, irrespective of the presence or absence of their predators, determined primary producer assemblage structure. We identified direct negative effects of predators on their prey and several indirect effects of predators on primary producers but not all interactions could have been predicted based on trophic level.
4. Our findings demonstrate the importance of trophic cascade effects coupled with non-trophic interactions when predicting the effects of loss of predator species on primary producers and consequently for ecosystem functioning. There is a pressing need for improved understanding of the effects of loss of consumers, based on realistic scenarios of diversity loss, to test conceptual frameworks linking predator diversity to variation in ecosystem functioning and for the protection of biodiversity, ecosystem functioning and related services.

P2Y(1) antagonists: Combining receptor-based modeling and QSAR for a quantitative prediction of the biological activity based on consensus scoring

P2Y(1) is an ADP-activated G protein-coupled receptor (GPCR). Its antagonists impede platelet aggregation in vivo and are potential antithrombotic agents. Combining ligand and structure-based modeling we generated a consensus model (LIST-CM) correlating antagonist structures with their potencies. We docked 45 antagonists into our rhodopsin-based human P2Y(1) homology model and calculated docking scores and free binding energies with the Linear Interaction Energy (LIE) method in continuum-solvent. The resulting alignment was also used to build QSAR based on CoMFA, CoMSIA, and molecular descriptors. To benefit from the strength of each technique and compensate for their limitations, we generated our LIST-CM with a PLS regression based on the predictions of each methodology. A test set featuring untested substituents was synthesized and assayed in inhibition of 2-MeSADP-stimulated PLC activity and in radioligand binding. LIST-CM outperformed internal and external predictivity of any individual model to predict accurately the potency of 75% of the test set.

Predicting organic acid concentration from UV/vis spectrometry measurements - A comparison of machine learning techniques

The concentration of organic acids in anaerobic digesters is one of the most critical parameters for monitoring and advanced control of anaerobic digestion processes. Thus, a reliable online-measurement system is absolutely necessary. A novel approach to obtaining these measurements indirectly and online using UV/vis spectroscopic probes, in conjunction with powerful pattern recognition methods, is presented in this paper. An UV/vis spectroscopic probe from S::CAN is used in combination with a custom-built dilution system to monitor the absorption of fully fermented sludge at a spectrum from 200 to 750 nm. Advanced pattern recognition methods are then used to map the non-linear relationship between measured absorption spectra to laboratory measurements of organic acid concentrations. Linear discriminant analysis, generalized discriminant analysis (GerDA), support vector machines (SVM), relevance vector machines, random forest and neural networks are investigated for this purpose and their performance compared. To validate the approach, online measurements have been taken at a full-scale 1.3-MW industrial biogas plant. Results show that whereas some of the methods considered do not yield satisfactory results, accurate prediction of organic acid concentration ranges can be obtained with both GerDA and SVM-based classifiers, with classification rates in excess of 87% achieved on test data.

A population-based association study of SNPs of GSTP1, MnSOD, GPX2 and Barrett's esophagus and esophageal adenocarcinoma

Oxidative stress appears to be important in the pathogenesis of Barrett's esophagus (BE) and esophageal adenocarcinoma (EAC). Single-nucleotide polymorphisms (SNPs) of antioxidant enzyme genes may play a part in determining individual susceptibility to these diseases. The Factors Influencing the Barrett's Adenocarcinoma Relationship (FINBAR) study is a population-based, case-control study of BE and EAC in Ireland. DNA from EAC (n = 207), BE (> or =3 cm BE at endoscopy with specialized intestinal metaplasia on biopsy, n = 189) and normal population controls (n = 223) were analyzed. Several SNPs spanning the genes for glutathione S-transferase P1 (GSTP1), manganese superoxide dismutase (MnSOD) and glutathione peroxidase 2 (GPX2) were genotyped using multiplex polymerase chain reaction and SNaPshottrade mark. The chi(2) test was used to compare genotype and allele frequencies between case and control subjects. Linkage disequilibrium between SNPs was quantified using Lewontin's D' value and haplotype frequency estimates obtained using Haploview. Eleven SNPs were genotyped (six for GSTP1, three for MnSOD and two for GPX2); all were in Hardy-Weinberg equilibrium. None was significantly associated with EAC or BE even before Bonferroni correction. Odds ratios for EAC for individual SNPs ranged from 0.68 [95% confidence interval (CI) 0.43-1.08] to 1.25 (95% CI 0.73-2.16), and for BE from 0.84 (95% CI 0.52-1.30) to 1.30 (95% CI 0.85-1.97). SNPs in all three genes were in strong linkage disequilibrium (D' > 0.887) but haplotype analysis did not show any significant association with EAC or BE. SNPs involving the GSTP1, MnSOD and GPX2 genes were not associated with BE or EAC. Further studies aimed at identifying susceptibility genes should focus on different antioxidant genes or different pathways.

The breath test--a call for more regional use

Although the 13C-urea breath test is commonly used for detection of Helicobacter pylori infection and eradication, access to commercial testing centres for analysis may at times limit its use. We have addressed this issue by establishing a regional-based means of analysis as a Hospital-University collaboration.

Improving children's attitudes toward refugees: An evaluation of a school-based multicultural curriculum and an anti-racist intervention

We evaluated the impact of the Friendship Project, a program designed to improve elementary school children's attitudes toward refugees. Participants either received 4 weekly lessons based on the program, or they received no lessons. All participants completed attitude measures before and after implementation of the program. Half completed the post-test 1 week after completion of the program, while the other half completed the post-test 7 weeks after its completion. The program led to more positive attitudes toward refugees in the short term, but not in the long term. Moreover, although it did not increase empathy, the program increased the proportion of participants who preferred an acculturation strategy of integration and reduced the number of participants who had conflictual acculturative fit.

A single microphone capillary-based system for measuring the complex input impedance of musical wind instruments

Capillary-based systems for measuring the input impedance of musical wind instruments were first developed in the mid-20th century and remain in widespread use today. In this paper, the basic principles and assumptions underpinning the design of such systems are examined. Inexpensive modifications to a capillary-based impedance measurement set-up made possible due to advances in computing and data acquisition technology are discussed. The modified set-up is able to measure both impedance magnitude and impedance phase even though it only contains one microphone. In addition, a method of calibration is described that results in a significant improvement in accuracy when measuring high impedance objects on the modified capillary-based system. The method involves carrying out calibration measurements on two different objects whose impedances are well-known theoretically. The benefits of performing two calibration measurements (as opposed to the one calibration measurement that has been traditionally used) are demonstrated experimentally through input impedance measurements on two test objects and a Boosey and Hawkes oboe. © S. Hirzel Verlag · EAA.

Robust visual tracking based on online learning sparse representation

Handling appearance variations is a very challenging problem for visual tracking. Existing methods usually solve this problem by relying on an effective appearance model with two features: (1) being capable of discriminating the tracked target from its background, (2) being robust to the target's appearance variations during tracking. Instead of integrating the two requirements into the appearance model, in this paper, we propose a tracking method that deals with these problems separately based on sparse representation in a particle filter framework. Each target candidate defined by a particle is linearly represented by the target and background templates with an additive representation error. Discriminating the target from its background is achieved by activating the target templates or the background templates in the linear system in a competitive manner. The target's appearance variations are directly modeled as the representation error. An online algorithm is used to learn the basis functions that sparsely span the representation error. The linear system is solved via ℓ1 minimization. The candidate with the smallest reconstruction error using the target templates is selected as the tracking result. We test the proposed approach using four sequences with heavy occlusions, large pose variations, drastic illumination changes and low foreground-background contrast. The proposed approach shows excellent performance in comparison with two latest state-of-the-art trackers.

Family-based association studies of lipid gene polymorphisms in coronary artery disease

Dysfunction of lipid-metabolizing proteins is implicated in the pathogenesis of coronary artery disease. Single nucleotide polymorphisms in genes that encode sterol regulatory binding protein-la, adenosine triphosphate binding cassette-A1, hepatic lipase, lipoprotein lipase, and cholesteryl ester transfer protein were assessed as potential markers of disease susceptibility in a family-based study of 1,012 patients from 386 families. Association between single nucleotide polymorphisms and coronary artery disease was tested by the combined transmission disequilibrium test/sib transmission disequilibrium test and pedigree disequilibrium test. After Bonferroni's correction, the pedigree disequilibrium test demonstrated significant excess transmission (p < 0.0083) to affected patients of the hepatic lipase -514 T allele, which suggests that this may constitute a novel disease-susceptibility locus. (c) 2005 Elsevier Inc. All rights reserved.

Cognitive performance is related to cortical grey matter volumes in early stages of schizophrenia: A population-based study of first-episode psychosis

Background: Neuropsychological deficits have been reported in association with first-episode psychosis (FEP). Reductions in grey matter (GM) volumes have been documented in FEP subjects compared to healthy controls. However, the possible inter-relationship between the findings of those two lines of research has been scarcely investigated.

Objective: To investigate the relationship between neuropsychological deficits and GM volume abnormalities in a population-based sample of FEP patients compared to healthy controls from the same geographical area.

Methods: FEP patients (n = 88) and control subjects (n = 86) were evaluated by neuropsychological assessment (Controlled Oral Word Association Test, forward and backward digit span tests) and magnetic resonance imaging using voxel-based morphometry.

Results: Single-group analyses showed that prefrontal and temporo-parietal GM volumes correlated significantly (p < 0.05, corrected) with cognitive performance in FEP patients. A similar pattern of direct correlations between neocortical GM volumes and cognitive impairment was seen in the schizophrenia subgroup (n = 48). In the control group, cognitive performance was directly correlated with GM volume in the right dorsal anterior cingulate cortex and inversely correlated with parahippocampal gyral volumes bilaterally. Interaction analyses with "group status" as a predictor variable showed significantly greater positive correlation within the left inferior prefrontal cortex (BA46) in the FEP group relative to controls, and significantly greater negative correlation within the left parahippocampal gyrus in the control group relative to FEP patients.

Conclusion: Our results indicate that cognitive deficits are directly related to brain volume abnormalities in frontal and temporo-parietal cortices in FEP subjects, most specifically in inferior portions of the dorsolateral prefrontal cortex. (C) 2009 Elsevier B.V. All rights reserved.

Late industrialization and the increased merit selection hypothesis - Ireland as a test case

The Irish case provides a particularly appropriate test of the increasing merit selection hypothesis deriving from the liberal theory of industrialization. This is so not only because the lateness and speed of economic change allows us to capture such change through a set of national surveys conducted in the past three decades, but also because such change was based on a sustained policy of increased openness to international competitive forces. The functional requirements of the economy and a rapid increase in the supply of those with higher educational qualifications provided an ideal context in which to observe the movement from ascription to achievement predicted by the liberal theory. However, while changes in the class structure and a rapid expansion of educational opportunity had significant consequences in terms of absolute mobility, there was no evidence of a significant shift towards meritocratic principles. At the same time as the service class increased their advantage over other classes in the pursuit of educational qualifications, the impact of educational qualifications on class destination diminished. Controlling for education, we find that the impact of class origin effects is substantial and shows little sign of diminishing over time. In our conclusion we discuss the implications of our findings in the context of the recent debate on meritocracy.

A Kinetic-Based Model of Radiation-Induced Intercellular Signalling

It is now widely accepted that intercellular communication can cause significant variations in cellular responses to genotoxic stress. The radiation-induced bystander effect is a prime example of this effect, where cells shielded from radiation exposure see a significant reduction in survival when cultured with irradiated cells. However, there is a lack of robust, quantitative models of this effect which are widely applicable. In this work, we present a novel mathematical model of radiation-induced intercellular signalling which incorporates signal production and response kinetics together with the effects of direct irradiation, and test it against published data sets, including modulated field exposures. This model suggests that these so-called "bystander" effects play a significant role in determining cellular survival, even in directly irradiated populations, meaning that the inclusion of intercellular communication may be essential to produce robust models of radio-biological outcomes in clinically relevant in vivo situations.

Assessing reproducibility of data obtained with instruments based on continuous measurements

Data obtained with any research tool must be reproducible, a concept referred to as reliability. Three techniques are often used to evaluate reliability of tools using continuous data in aging research: intraclass correlation coefficients (ICC), Pearson correlations, and paired t tests. These are often construed as equivalent when applied to reliability. This is not correct, and may lead researchers to select instruments based on statistics that may not reflect actual reliability. The purpose of this paper is to compare the reliability estimates produced by these three techniques and determine the preferable technique. A hypothetical dataset was produced to evaluate the reliability estimates obtained with ICC, Pearson correlations, and paired t tests in three different situations. For each situation two sets of 20 observations were created to simulate an intrarater or inter-rater paradigm, based on 20 participants with two observations per participant. Situations were designed to demonstrate good agreement, systematic bias, or substantial random measurement error. In the situation demonstrating good agreement, all three techniques supported the conclusion that the data were reliable. In the situation demonstrating systematic bias, the ICC and t test suggested the data were not reliable, whereas the Pearson correlation suggested high reliability despite the systematic discrepancy. In the situation representing substantial random measurement error where low reliability was expected, the ICC and Pearson coefficient accurately illustrated this. The t test suggested the data were reliable. The ICC is the preferred technique to measure reliability. Although there are some limitations associated with the use of this technique, they can be overcome.

Fatigue Life Assessment and Static Testing of Structural GFRP Tubes Based on Coupon Tests

Fiber-reinforced polymer (FRP) hollow tubes are used in structural applications, such as utility poles and pipelines. Concrete-filled FRP tubes (CFFTs) are also used as piles and bridge piers. Applications such as poles and marine piles are typically governed by cyclic bending. In this paper, the fatigue behavior of glass-FRP filament-wound tubes is studied using coupons cut from the tubes. Several coupon configurations were first examined in 24 tension and five compression monotonic loading tests. Fatigue tests were then conducted on 81 coupons to examine several parameters; namely, loading frequency as well as maximum-to-ultimate (max ult) and minimum-to-maximum (min max) stress ratios, including tension tension and tension compression, to simulate reversed bending. The study demonstrated the sensitivity of test results and failure mode to coupon configuration. The presence of compression loads reduced fatigue life, while increasing load frequency increased fatigue life. Stiffness degradation behavior was also established. To achieve at least one million cycles, it is recommended to limit (max ult) to 0.25. Models were used to simulate stiffness degradation and fatigue life curve of the tube. Fatigue life predictions of large CFFT beams showed good correlation with experimental results. © 2008 ASCE.

State Estimation for Anaerobic Digesters using the ADM1

The optimization of full-scale biogas plant operation is of great importance to make biomass a competitive source of renewable energy. The implementation of innovative control and optimization algorithms, such as Nonlinear Model Predictive Control, requires an online estimation of operating states of biogas plants. This state estimation allows for optimal control and operating decisions according to the actual state of a plant. In this paper such a state estimator is developed using a calibrated simulation model of a full-scale biogas plant, which is based on the Anaerobic Digestion Model No.1. The use of advanced pattern recognition methods shows that model states can be predicted from basic online measurements such as biogas production, CH4 and CO2 content in the biogas, pH value and substrate feed volume of known substrates. The machine learning methods used are trained and evaluated using synthetic data created with the biogas plant model simulating over a wide range of possible plant operating regions. Results show that the operating state vector of the modelled anaerobic digestion process can be predicted with an overall accuracy of about 90%. This facilitates the application of state-based optimization and control algorithms on full-scale biogas plants and therefore fosters the production of eco-friendly energy from biomass.