Alternative uses for co-products: Harnessing the potential of valuable compounds from meat processing chains

peer-reviewedOpportunities for exploiting the inherent value of protein-rich meat processing co-products, in the context of increased global demand for protein and for sustainable processing systems, are discussed. While direct consumption maybe the most profitable route for some, this approach is influenced greatly by local and cultural traditions. A more profitable and sustainable approach may be found in recognizing this readily available and under-utilised resource can provide high value components, such as proteins, with targeted high value functionality of relevance to a variety of sectors. Applications in food & beverages, petfood biomedical and nutrition arenas are discussed. Utilization of the raw material in its entirety is a necessary underlying principle in this approach to help maintain minimum waste generation. Understanding consumer attitudes to these products, in particular when used in food or beverage systems, is critical in optimizing commercialization strategies.This work forms part of the ReValueProtein Research Project (Grant Award No. 11/F/043) which is supported by the Irish Department of Agriculture, Food and the Marine (DAFM) and the Food Institutional Research Measure (FIRM) both funded by the Irish Government under the National Development Plan 2007–2013.Department of Agriculture, Food and the Marin

Audit market structure, fees and choice in a period of structural change: evidence from the UK – 1998–2003

This paper presents evidence on audit market concentration and auditor fee levels in the UK market in the crucial period of structural change following the PricewaterhouseCoopers’ (PwC) merger and encompassing Andersen’s demise (1998–2003). Given the current interest in auditor choice, analysis is also undertaken at the individual audit firm level and by industry sector. There is evidence of significant upward pressure on audit fees since 2001 but only for smaller auditees. Audit fee income for top tier auditors (Big 5/4) did not change significantly while the number of auditees fell significantly, consistent with a move towards larger, less risky, clients. A decomposition analysis of the aggregate Big 5/4 concentration ratio changes over the period identifies the impact of four distinct consumer-based reasons for change: leavers; net joiners; non-par auditor switches; and (only for the audit fees measure) audit fee changes. Andersen’s demise markedly reduced the level of inequality among the top tier firms but PwC retained its position as a ‘dominant firm’. On switching to the new auditor, former Andersen clients experienced an initial audit fee rise broadly in line with inflation, with no evidence of fee premia or discounting. They also reported significantly lower NAS fees, consistent with audit firms and auditees responding to public concerns about perceptions of auditor independence. There is no general evidence of knowledge spillover effects or cross-subsidisation of the audit fee by NAS. The combined findings provide no evidence to indicate that recent structural changes have resulted in anticompetitive pricing; the key concerns remain the lack of audit firm choice and issues concerning the governance and accountability of audit firms

EGFR interacts with the fusion protein of respiratory syncytial virus strain 2-20 and mediates infection and mucin expression.

Respiratory syncytial virus (RSV) is the major cause of viral lower respiratory tract illness in children. In contrast to the RSV prototypic strain A2, clinical isolate RSV 2-20 induces airway mucin expression in mice, a clinically relevant phenotype dependent on the fusion (F) protein of the RSV strain. Epidermal growth factor receptor (EGFR) plays a role in airway mucin expression in other systems; therefore, we hypothesized that the RSV 2-20 F protein stimulates EGFR signaling. Infection of cells with chimeric strains RSV A2-2-20F and A2-2-20GF or over-expression of 2-20 F protein resulted in greater phosphorylation of EGFR than infection with RSV A2 or over-expression of A2 F, respectively. Chemical inhibition of EGFR signaling or knockdown of EGFR resulted in diminished infectivity of RSV A2-2-20F but not RSV A2. Over-expression of EGFR enhanced the fusion activity of 2-20 F protein in trans. EGFR co-immunoprecipitated most efficiently with RSV F proteins derived from "mucogenic" strains. RSV 2-20 F and EGFR co-localized in H292 cells, and A2-2-20GF-induced MUC5AC expression was ablated by EGFR inhibitors in these cells. Treatment of BALB/c mice with the EGFR inhibitor erlotinib significantly reduced the amount of RSV A2-2-20F-induced airway mucin expression. Our results demonstrate that RSV F interacts with EGFR in a strain-specific manner, EGFR is a co-factor for infection, and EGFR plays a role in RSV-induced mucin expression, suggesting EGFR is a potential target for RSV disease

Resisting Sleep Pressure:Impact on Resting State Functional Network Connectivity

In today's 24/7 society, sleep restriction is a common phenomenon which leads to increased levels of sleep pressure in daily life. However, the magnitude and extent of impairment of brain functioning due to increased sleep pressure is still not completely understood. Resting state network (RSN) analyses have become increasingly popular because they allow us to investigate brain activity patterns in the absence of a specific task and to identify changes under different levels of vigilance (e.g. due to increased sleep pressure). RSNs are commonly derived from BOLD fMRI signals but studies progressively also employ cerebral blood flow (CBF) signals. To investigate the impact of sleep pressure on RSNs, we examined RSNs of participants under high (19 h awake) and normal (10 h awake) sleep pressure with three imaging modalities (arterial spin labeling, BOLD, pseudo BOLD) while providing confirmation of vigilance states in most conditions. We demonstrated that CBF and pseudo BOLD signals (measured with arterial spin labeling) are suited to derive independent component analysis based RSNs. The spatial map differences of these RSNs were rather small, suggesting a strong biological substrate underlying these networks. Interestingly, increased sleep pressure, namely longer time awake, specifically changed the functional network connectivity (FNC) between RSNs. In summary, all FNCs of the default mode network with any other network or component showed increasing effects as a function of increased 'time awake'. All other FNCs became more anti-correlated with increased 'time awake'. The sensorimotor networks were the only ones who showed a within network change of FNC, namely decreased connectivity as function of 'time awake'. These specific changes of FNC could reflect both compensatory mechanisms aiming to fight sleep as well as a first reduction of consciousness while becoming drowsy. We think that the specific changes observed in functional network connectivity could imply an impairment of information transfer between the affected RSNs

Rare disruptive mutations in ciliary function genes contribute to testicular cancer susceptibility

Testicular germ cell tumour (TGCT) is the most common cancer in young men. Here we sought to identify risk factors for TGCT by performing whole-exome sequencing on 328 TGCT cases from 153 families, 634 sporadic TGCT cases and 1,644 controls. We search for genes that are recurrently affected by rare variants (minor allele frequency <0.01) with potentially damaging effects and evidence of segregation in families. A total of 8.7% of TGCT families carry rare disruptive mutations in the cilia-microtubule genes (CMG) as compared with 0.5% of controls (P=2.1 × 10¯⁸). The most significantly mutated CMG is DNAAF1 with biallelic inactivation and loss of DNAAF1 expression shown in tumours from carriers. DNAAF1 mutation as a cause of TGCT is supported by a dnaaf1hu²⁵⁵h(+/−) zebrafish model, which has a 94% risk of TGCT. Our data implicate cilia-microtubule inactivation as a cause of TGCT and provide evidence for CMGs as cancer susceptibility genes

Nematode and Arthropod Genomes Provide New Insights into the Evolution of Class 2 B1 GPCRs

Nematodes and arthropods are the most speciose animal groups and possess Class 2 B1 G-protein coupled receptors (GPCRs). Existing models of invertebrate Class 2 B1 GPCR evolution are mainly centered on Caenorhabditis elegans and Drosophila melanogaster and a few other nematode and arthropod representatives. The present study reevaluates the evolution of metazoan Class 2 B1 GPCRs and orthologues by exploring the receptors in several nematode and arthropod genomes and comparing them to the human receptors. Three novel receptor phylogenetic clusters were identified and designated cluster A, cluster B and PDF-R-related cluster. Clusters A and B were identified in several nematode and arthropod genomes but were absent from D. melanogaster and Culicidae genomes, whereas the majority of the members of the PDF-R-related cluster were from nematodes. Cluster A receptors were nematode and arthropod-specific but shared a conserved gene environment with human receptor loci. Cluster B members were orthologous to human GCGR, PTHR and Secretin members with which they probably shared a common origin. PDF-R and PDF-R related clusters were present in representatives of both nematodes and arthropods. The results of comparative analysis of GPCR evolution and diversity in protostomes confirm previous notions that C. elegans and D. melanogaster genomes are not good representatives of nematode and arthropod phyla. We hypothesize that at least four ancestral Class 2 B1 genes emerged early in the metazoan radiation, which after the protostome-deuterostome split underwent distinct selective pressures that resulted in duplication and deletion events that originated the current Class 2 B1 GPCRs in nematode and arthropod genomes.This work was supported by the Portuguese Foundation for Science and Technology (FCT) project PTDC/BIA-BCM/114395/2009, by the European Regional Development Fund through COMPETE and FCT under the project ‘‘PEst-C/MAR/LA0015/2011.’’ RCF is in receipt of an FCT grant (SFRH/BPD/89811/2012) and JCRC is supported by auxiliary research contract FCT Pluriannual funds attributed to CCMAR. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Endocrine disruptors and obesity

The purpose of this review is to summarise current evidence that some environmental chemicals may be able to interfere in endocrine regulation of energy metabolism and adipose tissue structure. Recent findings demonstrate that such endocrine disrupting chemicals, termed “obesogens”, can promote adipogenesis and cause weight gain. This includes compounds to which the human population is exposed in daily life through their use in pesticides/herbicides, industrial and household products, plastics, detergents, flame retardants and ingredients in personal care products. Animal models and epidemiological studies have shown that an especially sensitive time for exposure is in utero or the neonatal period. In summarising the actions of obesogens, it is noteworthy that as their structures are mainly lipophilic, their ability to increase fat deposition has the added consequence of increasing the capacity for their own retention. This has the potential for a vicious spiral not only of increasing obesity but also increasing retention of other lipophilic pollutant chemicals with an even broader range of adverse actions. This might offer an explanation as to why obesity is an underlying risk factor for so many diseases including cancer

Maximum Likelihood Estimation of the Negative Binomial Dispersion Parameter for Highly Overdispersed Data, with Applications to Infectious Diseases

BACKGROUND: The negative binomial distribution is used commonly throughout biology as a model for overdispersed count data, with attention focused on the negative binomial dispersion parameter, k. A substantial literature exists on the estimation of k, but most attention has focused on datasets that are not highly overdispersed (i.e., those with k≥1), and the accuracy of confidence intervals estimated for k is typically not explored. METHODOLOGY: This article presents a simulation study exploring the bias, precision, and confidence interval coverage of maximum-likelihood estimates of k from highly overdispersed distributions. In addition to exploring small-sample bias on negative binomial estimates, the study addresses estimation from datasets influenced by two types of event under-counting, and from disease transmission data subject to selection bias for successful outbreaks. CONCLUSIONS: Results show that maximum likelihood estimates of k can be biased upward by small sample size or under-reporting of zero-class events, but are not biased downward by any of the factors considered. Confidence intervals estimated from the asymptotic sampling variance tend to exhibit coverage below the nominal level, with overestimates of k comprising the great majority of coverage errors. Estimation from outbreak datasets does not increase the bias of k estimates, but can add significant upward bias to estimates of the mean. Because k varies inversely with the degree of overdispersion, these findings show that overestimation of the degree of overdispersion is very rare for these datasets