Targeting the EP1 receptor reduces Fas ligand expression and increases the antitumor immune response in an in vivo model of colon cancer

Despite studies demonstrating that inhibition of cyclooxygenase-2 (COX-2)-derived prostaglandin E2 (PGE2) has significant chemotherapeutic benefits in vitro and in vivo, inhibition of COX enzymes is associated with serious gastrointestinal and cardiovascular side effects, limiting the clinical utility of these drugs. PGE2 signals through four different receptors (EP1–EP4) and targeting individual receptor(s) may avoid these side effects, while retaining significant anticancer benefits. Here, we show that targeted inhibition of the EP1 receptor in the tumor cells and the tumor microenvironment resulted in the significant inhibition of tumor growth in vivo. Both dietary administration and direct injection of the EP1 receptor-specific antagonist, ONO-8713, effectively reduced the growth of established CT26 tumors in BALB/c mice, with suppression of the EP1 receptor in the tumor cells alone less effective in reducing tumor growth. This antitumor effect was associated with reduced Fas ligand expression and attenuated tumor-induced immune suppression. In particular, tumor infiltration by CD4+CD25+Foxp3+ regulatory T cells was decreased, whereas the cytotoxic activity of isolated splenocytes against CT26 cells was increased. F4/80+ macrophage infiltration was also decreased; however, there was no change in macrophage phenotype. These findings suggest that the EP1 receptor represents a potential target for the treatment of colon cancer.

Impact of the smoke-free workplace legislation on smoking behaviour, risk perception & stigmatisation

The Republic of Ireland became the first European country to implement nationwide smoke-free workplace legislation. Aims: To determine prevalence of smoking among bar workers and estimate the impact of the smoke-free workplace legislation on their smoking behaviour to that of a comparable general population sample. To approximate the influence of tobacco control measures on risk perception of second-hand smoke (SHS) among the general population. To explore the de-normalisation of smoking behaviour and the potential increased stigmatisation of smokers and their smoking. Methods: Prevalence estimates and behavioural changes were examined among a random sample of bar workers before and 1 year after the smoke-free legislation; comparisons made with a general population sub-sample. Changes in risk knowledge related to SHS exposure were based on general population data. Qualitative interviews were conducted among a purposive sample of smokers and non-smokers four years after the implementation of the legislation. Results: Smoking prevalence was extremely high among bar workers. Smoking prevalence dropped in bar workers and significantly among the general population 1 year post ban while cigarette consumption dropped significantly among bar workers. Disparity in knowledge between smokers and non-smoker of risk associated with SHS exposure reduced. Lack of understanding of the risk of ear infections in children posed by SHS exposure was notable. Evidence for advanced de-normalisation of smoking behaviour and intensification of stigma because of the introduction of the legislation was dependent on many factors, quality of smoking facilities played a key role. Conclusions: Ireland’s smoke-free legislation was associated with a drop in prevalence and cigarette consumption. Disparity in knowledge between smokers and non-smokers of the risk posed by SHS exposure reduced however the risk of ear infections in children needs to be effectively disseminated. The proliferation of ‘good’ smoking areas may diminish the potential to reduce smoking behaviour and de-normalise smoking.

Nutraceutical and functional food bioactive peptides in beef

In recent years, the potential to positively modulate human health through dietary approaches has received considerable attention. Bioactive peptides which are released during the hydrolysis or fermentation of food proteins or following digestion may exert beneficial physiological effects in vivo. The aim of this work was to isolate, characterise and evaluate Angiotensin-І-converting enzyme (ACE-І) inhibitory, antimicrobial and antioxidant peptides from the bovine myofibrillar proteins actin and myosin. In order to generate these peptides, the myofibrillar proteins actin and myosin were hydrolysed with digestive enzymes pepsin, trypsin and α-chymotrypsin, or with the industrial thermolysin-like enzyme “Thermoase”, Amano Inc. It was found that each hydrolysate generated contained peptides which possessed ACE inhibitory, antioxidant and antimicrobial activity. The peptides responsible in part for the observed ACE inhibitory, antioxidant and antimicrobial activity of a number of hydrolysates were isolated using the method of RP-HPLC and the bioactive peptides contained within each active fraction was determined using either MALDI-TOF MS/MS or N-terminal peptide sequencing. During the course of this thesis six ACE inhibitory and five antimicrobial peptides were identified. It was determined that the reported antioxidant activity was a direct result of a number of peptides working in synergy with each other. The IC50 values of the six ACE inhibitory peptides ranged in values of 6.85 to 75.7 µM which compare favourably to values previously reported for other food derived ACE inhibitory peptides, particularly the well known milk peptides IPP and VPP, IC50 values of 5 and 9 µM respectively. All five antimicrobial peptides identified in this thesis displayed activity against Escherichia coli, Salmonella typhimurium, Staphylococcus aureus and Listeria innocua with MIC values ranging from 0.625 to10 mM. The activity of each antimicrobial peptide was strain specific. Furthermore the role and importance of charged amino acids to the activity of antimicrobial peptides was also determined. Generally the removal of charged amino acids from the sequence of antimicrobial peptides resulted in a loss of antimicrobial activity. In conclusion, this thesis revealed that a range of bioactive peptides exhibiting ACE inhibitory, antioxidant and antimicrobial activities were encrypted in bovine myofibrillar proteins that could be released using digestive and industrial enzymes. Finally enzymatic hydrolysates of muscle proteins could potentially be incorporated into functional foods; however, the potential health benefits would need to be proven in human clinical studies.

Reasoning with imprecise trade-offs in decision making under certainty and uncertainty

In many real world situations, we make decisions in the presence of multiple, often conflicting and non-commensurate objectives. The process of optimizing systematically and simultaneously over a set of objective functions is known as multi-objective optimization. In multi-objective optimization, we have a (possibly exponentially large) set of decisions and each decision has a set of alternatives. Each alternative depends on the state of the world, and is evaluated with respect to a number of criteria. In this thesis, we consider the decision making problems in two scenarios. In the first scenario, the current state of the world, under which the decisions are to be made, is known in advance. In the second scenario, the current state of the world is unknown at the time of making decisions. For decision making under certainty, we consider the framework of multiobjective constraint optimization and focus on extending the algorithms to solve these models to the case where there are additional trade-offs. We focus especially on branch-and-bound algorithms that use a mini-buckets algorithm for generating the upper bound at each node of the search tree (in the context of maximizing values of objectives). Since the size of the guiding upper bound sets can become very large during the search, we introduce efficient methods for reducing these sets, yet still maintaining the upper bound property. We define a formalism for imprecise trade-offs, which allows the decision maker during the elicitation stage, to specify a preference for one multi-objective utility vector over another, and use such preferences to infer other preferences. The induced preference relation then is used to eliminate the dominated utility vectors during the computation. For testing the dominance between multi-objective utility vectors, we present three different approaches. The first is based on a linear programming approach, the second is by use of distance-based algorithm (which uses a measure of the distance between a point and a convex cone); the third approach makes use of a matrix multiplication, which results in much faster dominance checks with respect to the preference relation induced by the trade-offs. Furthermore, we show that our trade-offs approach, which is based on a preference inference technique, can also be given an alternative semantics based on the well known Multi-Attribute Utility Theory. Our comprehensive experimental results on common multi-objective constraint optimization benchmarks demonstrate that the proposed enhancements allow the algorithms to scale up to much larger problems than before. For decision making problems under uncertainty, we describe multi-objective influence diagrams, based on a set of p objectives, where utility values are vectors in Rp, and are typically only partially ordered. These can be solved by a variable elimination algorithm, leading to a set of maximal values of expected utility. If the Pareto ordering is used this set can often be prohibitively large. We consider approximate representations of the Pareto set based on ϵ-coverings, allowing much larger problems to be solved. In addition, we define a method for incorporating user trade-offs, which also greatly improves the efficiency.