Estimating trophic link density from quantitative but incomplete diet data

The trophic link density and the stability of food webs are thought to be related, but the nature of this relation is controversial. This article introduces a method for estimating the link density from diet tables which do not cover the complete food web and do not resolve all diet items to species level. A simple formula for the error of this estimate is derived. Link density is determined as a function of a threshold diet fraction below which diet items are ignored (

Networks for systems biology: conceptual connection of data and function

The purpose of this study is to survey the use of networks and network-based methods in systems biology. This study starts with an introduction to graph theory and basic measures allowing to quantify structural properties of networks. Then, the authors present important network classes and gene networks as well as methods for their analysis. In the last part of this study, the authors review approaches that aim at analysing the functional organisation of gene networks and the use of networks in medicine. In addition to this, the authors advocate networks as a systematic approach to general problems in systems biology, because networks are capable of assuming multiple roles that are very beneficial connecting experimental data with a functional interpretation in biological terms.

Network biology: a direct approach to study biological function

In this paper we discuss the dualism of gene networks and their role in systems biology. We argue that gene networks ( 1) can serve as a conceptual framework, forming a fundamental level of a phenomenological description, and ( 2) are a means to represent and analyze data. The latter point does not only allow a systems analysis but is even amenable for a direct approach to study biological function. Here we focus on the clarity of our main arguments and conceptual meaning of gene networks, rather than the causal inference of gene networks from data. (C) 2010 John Wiley & Sons, Inc. WIREs Syst Biol Med 2011 3 379-391 DOI: 10.1002/wsbm.134

Mapping biological to clinical phenotypes during the development (21 days) and resolution (21 days) of experimental gingivitis

Aim: To characterize and map temporal changes in the biological and clinical phenotype during a 21-day experimental gingivitis study. Materials and Methods: Experimental gingivitis was induced over 21 days in healthy human volunteers (n = 56), after which normal brushing was resumed (resolution phase). Gingival and plaque indices were assessed. Gingival crevicular fluid was collected from four paired test and contra-lateral control sites in each volunteer during induction (Days 0, 7, 14 and 21) and resolution (Days 28 and 42) of experimental gingivitis. Fluid volumes were measured and a single analyte was quantified from each site-specific, 30s sample. Data were evaluated by analysis of repeated measurements and paired sample tests. Results: Clinical indices and gingival crevicular fluid volumes at test sites increased from Day 0, peaking at Day 21 (test/control differences all p

A Robust Co-Localisation Measurement Utilising Z-Stack Image Intensity Similarities for Biological Studies

Background: Co-localisation is a widely used measurement in immunohistochemical analysis to determine if fluorescently labelled biological entities, such as cells, proteins or molecules share a same location. However the measurement of co-localisation is challenging due to the complex nature of such fluorescent images, especially when multiple focal planes are captured. The current state-of-art co-localisation measurements of 3-dimensional (3D) image stacks are biased by noise and cross-overs from non-consecutive planes.

Method: In this study, we have developed Co-localisation Intensity Coefficients (CICs) and Co-localisation Binary Coefficients (CBCs), which uses rich z-stack data from neighbouring focal planes to identify similarities between image intensities of two and potentially more fluorescently-labelled biological entities. This was developed using z-stack images from murine organotypic slice cultures from central nervous system tissue, and two sets of pseudo-data. A large amount of non-specific cross-over situations are excluded using this method. This proposed method is also proven to be robust in recognising co-localisations even when images are polluted with a range of noises.

Results: The proposed CBCs and CICs produce robust co-localisation measurements which are easy to interpret, resilient to noise and capable of removing a large amount of false positivity, such as non-specific cross-overs. Performance of this method of measurement is significantly more accurate than existing measurements, as determined statistically using pseudo datasets of known values. This method provides an important and reliable tool for fluorescent 3D neurobiological studies, and will benefit other biological studies which measure fluorescence co-localisation in 3D.

A review of dsb induction data for varying quality radiations

Purpose: This short review summarizes the data obtained with various techniques for measuring the yields of double strand breaks (dsb) produced by particle radiations of differing linear energy transfer (LET) in order to obtain relative biological effectiveness (RBE) values.

A Monte Carlo model of DNA double-strand break clustering and rejoining kinetics for the analysis of pulsed-field gel electrophoresis data

In studies of radiation-induced DNA fragmentation and repair, analytical models may provide rapid and easy-to-use methods to test simple hypotheses regarding the breakage and rejoining mechanisms involved. The random breakage model, according to which lesions are distributed uniformly and independently of each other along the DNA, has been the model most used to describe spatial distribution of radiation-induced DNA damage. Recently several mechanistic approaches have been proposed that model clustered damage to DNA. In general, such approaches focus on the study of initial radiation-induced DNA damage and repair, without considering the effects of additional (unwanted and unavoidable) fragmentation that may take place during the experimental procedures. While most approaches, including measurement of total DNA mass below a specified value, allow for the occurrence of background experimental damage by means of simple subtractive procedures, a more detailed analysis of DNA fragmentation necessitates a more accurate treatment. We have developed a new, relatively simple model of DNA breakage and the resulting rejoining kinetics of broken fragments. Initial radiation-induced DNA damage is simulated using a clustered breakage approach, with three free parameters: the number of independently located clusters, each containing several DNA double-strand breaks (DSBs), the average number of DSBs within a cluster (multiplicity of the cluster), and the maximum allowed radius within which DSBs belonging to the same cluster are distributed. Random breakage is simulated as a special case of the DSB clustering procedure. When the model is applied to the analysis of DNA fragmentation as measured with pulsed-field gel electrophoresis (PFGE), the hypothesis that DSBs in proximity rejoin at a different rate from that of sparse isolated breaks can be tested, since the kinetics of rejoining of fragments of varying size may be followed by means of computer simulations. The problem of how to account for background damage from experimental handling is also carefully considered. We have shown that the conventional procedure of subtracting the background damage from the experimental data may lead to erroneous conclusions during the analysis of both initial fragmentation and DSB rejoining. Despite its relative simplicity, the method presented allows both the quantitative and qualitative description of radiation-induced DNA fragmentation and subsequent rejoining of double-stranded DNA fragments. (C) 2004 by Radiation Research Society.

ISOLATION AND PRELIMINARY BIOLOGICAL CHARACTERIZATION OF KPNFIRFAMIDE, A NOVEL FMRFAMIDE-RELATED PEPTIDE FROM THE FREE-LIVING NEMATODE, PANAGRELLUS-REDIVIVUS

A novel FMRFamide-related heptapeptide, Lys-Pro-Asn-Phe-Ile-Arg-Phe-NH2 (KPNFIRFamide), was isolated and characterized from acid ethanol extracts of the free-living nematode, Panagrellus redivivus. Whole-worm extracts contained greater than or equal to 9 pmol KPNFIRFamide/g wet weight. A synthetic replicate of this peptide induced a rapid relaxation of tone and inhibited spontaneous contractility in isolated innervated and denervated body-wall muscle strips of the parasitic nematode, Ascaris suum. KPNFIRFamide (0.1 nM) induced measurable relaxations in 50% of the muscle preparations examined. Concentrations greater than or equal to 0.3 nM induced relaxation in 100% of muscle preparations examined. The relaxation was short-lived at concentrations of peptide greater than or equal to 1 mu M and displayed a profile typical of receptor desensitization. These data suggest the occurrence of a closely related peptide in A. suum and add further evidence to the concept of primary structural conservation of FaRPs within the nematodes.

Bagging statistical network inference from large-scale gene expression data.

Modern biology and medicine aim at hunting molecular and cellular causes of biological functions and diseases. Gene regulatory networks (GRN) inferred from gene expression data are considered an important aid for this research by providing a map of molecular interactions. Hence, GRNs have the potential enabling and enhancing basic as well as applied research in the life sciences. In this paper, we introduce a new method called BC3NET for inferring causal gene regulatory networks from large-scale gene expression data. BC3NET is an ensemble method that is based on bagging the C3NET algorithm, which means it corresponds to a Bayesian approach with noninformative priors. In this study we demonstrate for a variety of simulated and biological gene expression data from S. cerevisiae that BC3NET is an important enhancement over other inference methods that is capable of capturing biochemical interactions from transcription regulation and protein-protein interaction sensibly. An implementation of BC3NET is freely available as an R package from the CRAN repository. © 2012 de Matos Simoes, Emmert-Streib.

Job Strain and Alcohol Intake:A Collaborative Meta-Analysis of Individual-Participant Data from 140 000 Men and Women

BACKGROUND: The relationship between work-related stress and alcohol intake is uncertain. In order to add to the thus far inconsistent evidence from relatively small studies, we conducted individual-participant meta-analyses of the association between work-related stress (operationalised as self-reported job strain) and alcohol intake. METHODOLOGY AND PRINCIPAL FINDINGS: We analysed cross-sectional data from 12 European studies (n?=?142 140) and longitudinal data from four studies (n?=?48 646). Job strain and alcohol intake were self-reported. Job strain was analysed as a binary variable (strain vs. no strain). Alcohol intake was harmonised into the following categories: none, moderate (women: 1-14, men: 1-21 drinks/week), intermediate (women: 15-20, men: 22-27 drinks/week) and heavy (women: >20, men: >27 drinks/week). Cross-sectional associations were modelled using logistic regression and the results pooled in random effects meta-analyses. Longitudinal associations were examined using mixed effects logistic and modified Poisson regression. Compared to moderate drinkers, non-drinkers and (random effects odds ratio (OR): 1.10, 95% CI: 1.05, 1.14) and heavy drinkers (OR: 1.12, 95% CI: 1.00, 1.26) had higher odds of job strain. Intermediate drinkers, on the other hand, had lower odds of job strain (OR: 0.92, 95% CI: 0.86, 0.99). We found no clear evidence for longitudinal associations between job strain and alcohol intake. CONCLUSIONS: Our findings suggest that compared to moderate drinkers, non-drinkers and heavy drinkers are more likely and intermediate drinkers less likely to report work-related stress.

Job Strain and Tobacco Smoking:An Individual-Participant Data Meta-Analysis of 166 130 Adults in 15 European Studies

BACKGROUND: Tobacco smoking is a major contributor to the public health burden and healthcare costs worldwide, but the determinants of smoking behaviours are poorly understood. We conducted a large individual-participant meta-analysis to examine the extent to which work-related stress, operationalised as job strain, is associated with tobacco smoking in working adults. METHODOLOGY AND PRINCIPAL FINDINGS: We analysed cross-sectional data from 15 European studies comprising 166 130 participants. Longitudinal data from six studies were used. Job strain and smoking were self-reported. Smoking was harmonised into three categories never, ex- and current. We modelled the cross-sectional associations using logistic regression and the results pooled in random effects meta-analyses. Mixed effects logistic regression was used to examine longitudinal associations. Of the 166 130 participants, 17% reported job strain, 42% were never smokers, 33% ex-smokers and 25% current smokers. In the analyses of the cross-sectional data, current smokers had higher odds of job strain than never-smokers (age, sex and socioeconomic position-adjusted odds ratio: 1.11, 95% confidence interval: 1.03, 1.18). Current smokers with job strain smoked, on average, three cigarettes per week more than current smokers without job strain. In the analyses of longitudinal data (1 to 9 years of follow-up), there was no clear evidence for longitudinal associations between job strain and taking up or quitting smoking. CONCLUSIONS: Our findings show that smokers are slightly more likely than non-smokers to report work-related stress. In addition, smokers who reported work stress smoked, on average, slightly more cigarettes than stress-free smokers.

Two non-synonymous markers in PTPN21, identified by genome-wide association study data-mining and replication, are associated with schizophrenia

We conducted data-mining analyses of genome wide association (GWA) studies of the CATIE and MGS-GAIN datasets, and found 13 markers in the two physically linked genes, PTPN21 and EML5, showing nominally significant association with schizophrenia. Linkage disequilibrium (LD) analysis indicated that all 7 markers from PTPN21 shared high LD (r(2)>0.8), including rs2274736 and rs2401751, the two non-synonymous markers with the most significant association signals (rs2401751, P=1.10 × 10(-3) and rs2274736, P=1.21 × 10(-3)). In a meta-analysis of all 13 replication datasets with a total of 13,940 subjects, we found that the two non-synonymous markers are significantly associated with schizophrenia (rs2274736, OR=0.92, 95% CI: 0.86-0.97, P=5.45 × 10(-3) and rs2401751, OR=0.92, 95% CI: 0.86-0.97, P=5.29 × 10(-3)). One SNP (rs7147796) in EML5 is also significantly associated with the disease (OR=1.08, 95% CI: 1.02-1.14, P=6.43 × 10(-3)). These 3 markers remain significant after Bonferroni correction. Furthermore, haplotype conditioned analyses indicated that the association signals observed between rs2274736/rs2401751 and rs7147796 are statistically independent. Given the results that 2 non-synonymous markers in PTPN21 are associated with schizophrenia, further investigation of this locus is warranted.

PRIMARY STRUCTURES AND BIOLOGICAL-ACTIVITIES OF SUBSTANCE-P-RELATED PEPTIDES FROM THE BRAIN OF THE DOGFISH, SCYLIORHINUS-CANICULA

Two peptides with substance-P-like immunoreactivity were isolated in pure form from an extract of the brain of the elasmobranch fish, Scyliorhinus canicula (european common dogfish). One peptide was identical to scyliorhinin I, previously identified in dogfish intestine, and the second was the undecapeptide Lys-Pro-Arg-Pro-Gly-Gln-Phe-Phe-Gly-Leu-Met-CONH2 which is structurally similar to mammalian substance P Scyliorhinin II or a peptide analogous to mammalian neurokinin A were not detected in the extract. Synthetic dogfish substance P ([Lys1, Arg3, Gly5]substance P) was approximately threefold more potent than mammalian substance P (K(d) = 0.21 +/- 0.11 nM versus K(d)= 0.74 +/- 0.17 nM; mean +/- SD; n = 6) in inhibiting the binding of I-125-labelled substance P to neurokinin (NK1) receptors in rat submandibular gland membranes. The vasodilator action of tachykinins in mammals is mediated primarily through interaction with NK1 receptors. Bolus intravenous injections of [Lys1, Arg3, Gly5]substance P (100 pmol) and scyliorhinin I (100 pmol) produced appreciable (>4 kPa) decreases in arterial blood pressure in the rat whereas intravenous injections of up to 5 nmol of the peptides into conscious, unrestrained dogfish produced no change in arterial blood pressure, pulse amplitude or heart rate. Injections of greater amounts of the peptides (10-50 nmol) produced a slight increase (400-667 Pa) in blood pressure. The data indicate that mammalian-type NK1 tachykinin receptors are not involved in cardiovascular regulation in elasmobranch fish.

Exploring Scale Effects of Best/Worst Rank Ordered Choice Data to Estimate Benefits of Tourism in Alpine Grazing Commons

In many environmental valuation applications standard sample sizes for choice modelling surveys are impractical to achieve. One can improve data quality using more in-depth surveys administered to fewer respondents. We report on a study using high quality rank-ordered data elicited with the best-worst approach. The resulting "exploded logit" choice model, estimated on 64 responses per person, was used to study the willingness to pay for external benefits by visitors for policies which maintain the cultural heritage of alpine grazing commons. We find evidence supporting this approach and reasonable estimates of mean WTP, which appear theoretically valid and policy informative. © The Author (2011).