Dietary patterns, insulin sensitivity and inflammation in older adults.

Background/objectivesSeveral studies have linked dietary patterns to insulin sensitivity and systemic inflammation, which affect risk of multiple chronic diseases. The purpose of this study was to investigate the dietary patterns of a cohort of older adults, and to examine relationships of dietary patterns with markers of insulin sensitivity and systemic inflammation.Subjects/methodsThe Health, Aging and Body Composition (Health ABC) Study is a prospective cohort study of 3075 older adults. In Health ABC, multiple indicators of glucose metabolism and systemic inflammation were assessed. Food intake was estimated with a modified Block food frequency questionnaire. In this study, dietary patterns of 1751 participants with complete data were derived by cluster analysis.ResultsSix clusters were identified, including a 'healthy foods' cluster, characterized by higher intake of low-fat dairy products, fruit, whole grains, poultry, fish and vegetables. In the main analysis, the 'healthy foods' cluster had significantly lower fasting insulin and homeostasis model assessment of insulin resistance values than the 'breakfast cereal' and 'high-fat dairy products' clusters, and lower fasting glucose than the 'high-fat dairy products' cluster (P≤0.05). No differences were found in 2-h glucose. With respect to inflammation, the 'healthy foods' cluster had lower interleukin-6 than the 'sweets and desserts' and 'high-fat dairy products' clusters, and no differences were seen in C-reactive protein or tumor necrosis factor-α.ConclusionsA dietary pattern high in low-fat dairy products, fruit, whole grains, poultry, fish and vegetables may be associated with greater insulin sensitivity and lower systemic inflammation in older adults

Optical Performance Monitoring through signal processing in current and future optical communication systems

2011-2012 > Academic research: refereed > Invited conference paperVersion of RecordPublishe

Public health outcome of Tuberculosis Cluster Investigations, England 2010–2013

Objectives: Tuberculosis (TB) is a serious re-emergent public health problem in the UK. In response to rising case incidence a National TB Strain-Typing Service based on molecular strain-typing was established. This facilitates early detection and investigation of clusters, targeted public health action, and prevention of further transmission. We review the added public health value of investigating molecular TB straintyped (ST) clusters. Methods: A structured questionnaire for each ST cluster investigated in England between 1 January 2010 and 30 June 2013 was completed. Questions related to epidemiological links and public health action and the perceived benefits of ST cluster investigation. Results: There were 278 ST cluster investigations (CIs) involving 1882 TB cases. Cluster size ranged from 2 to 92. CIs identified new epidemiological links in 36% of clusters; in 18% STs were discordant refuting transmission thought to have occurred. Additional public health action was taken following 23% of CI. Conclusions: We found positive benefits of TB molecular ST and CI, in identifying new epidemiological links between cases and taking public health action and in refuting transmission and saving resources. This needs to be translated to a decrease in transmission to provide evidence of public health value in this low prevalence high resource setting

Like trainer, like bot? Inheritance of bias in algorithmic content moderation

The internet has become a central medium through which `networked publics' express their opinions and engage in debate. Offensive comments and personal attacks can inhibit participation in these spaces. Automated content moderation aims to overcome this problem using machine learning classifiers trained on large corpora of texts manually annotated for offence. While such systems could help encourage more civil debate, they must navigate inherently normatively contestable boundaries, and are subject to the idiosyncratic norms of the human raters who provide the training data. An important objective for platforms implementing such measures might be to ensure that they are not unduly biased towards or against particular norms of offence. This paper provides some exploratory methods by which the normative biases of algorithmic content moderation systems can be measured, by way of a case study using an existing dataset of comments labelled for offence. We train classifiers on comments labelled by different demographic subsets (men and women) to understand how differences in conceptions of offence between these groups might affect the performance of the resulting models on various test sets. We conclude by discussing some of the ethical choices facing the implementers of algorithmic moderation systems, given various desired levels of diversity of viewpoints amongst discussion participants.Comment: 12 pages, 3 figures, 9th International Conference on Social Informatics (SocInfo 2017), Oxford, UK, 13--15 September 2017 (forthcoming in Springer Lecture Notes in Computer Science

Contrasting ecological information content in whaling archives with modern cetacean surveys for conservation planning and identification of historical distribution changes.

Many species are restricted to a marginal or suboptimal fraction of their historical range due to anthropogenic impacts, making it hard to interpret their ecological preferences from modern-day data alone. However, inferring past ecological states is limited by the availability of robust data and biases in historical archives, posing a challenge for policy makers . To highlight how historical records can be used to understand the ecological requirements of threatened species and inform conservation, we investigated sperm whale (Physeter macrocephalus) distribution in the Western Indian Ocean. We assessed differences in information content and habitat suitability predictions based on whale occurrence data from Yankee whaling logs (1792-1912) and from modern cetacean surveys (1995-2020). We built maximum entropy habitat suitability models containing static (bathymetry-derived) variables to compare models comprising historical-only and modern-only data. Using both historical and modern habitat suitability predictions  we assessed marine protected area (MPA) placement by contrasting suitability in- and outside MPAs. The historical model predicted high habitat suitability in shelf and coastal regions near continents and islands, whereas the modern model predicted a less coastal distribution with high habitat suitability more restricted to areas of steep topography. The proportion of high habitat suitability inside versus outside MPAs was higher when applying the historical predictions than the modern predictions, suggesting that different marine spatial planning optimums can be reached from either data sources. Moreover, differences in relative habitat suitability predictions between eras were consistent with the historical depletion of sperm whales from coastal regions, which were easily accessed and targeted by whalers, resulting in a modern distribution limited more to steep continental margins and remote oceanic ridges. The use of historical data can provide important new insights and, through cautious interpretation, inform conservation planning and policy, for example, by identifying refugee species and regions of anticipated population recovery

The impact of anthelmintic treatment on human gut microbiota based on cross-sectional and pre- and postdeworming comparisons in Western Kenya

Murine studies suggest that the presence of some species of intestinal helminths is associated with changes in host microbiota composition and diversity. However, studies in humans have produced varied conclusions, and the impact appears to vary widely depending on the helminth species present. To demonstrate how molecular approaches to the human gut microbiome can provide insights into the complex interplay among disparate organisms, DNA was extracted from cryopreserved stools collected from residents of 5 rural Kenyan villages prior to and 3 weeks and 3 months following albendazole (ALB) therapy. Samples were analyzed by quantitative PCR (qPCR) for the presence of 8 species of intestinal parasites and by MiSeq 16S rRNA gene sequencing. Based on pretreatment results, the presence of neither Ascaris lumbricoides nor Necator americanus infection significantly altered the overall diversity of the microbiota in comparison with age-matched controls. Following ALB therapy and clearance of soil-transmitted helminths (STH), there were significant increases in the proportion of the microbiota made up by Clostridiales (P = 0.0002; average fold change, 0.57) and reductions in the proportion made up by Enterobacteriales (P = 0.0004; average fold change, -0.58). There was a significant posttreatment decrease in Chao1 richness, even among individuals who were uninfected pretreatment, suggesting that antimicrobial effects must be considered in any posttreatment setting. Nevertheless, the helminth-associated changes in Clostridiales and Enterobacteriales suggest that clearance of STH, and of N. americanus in particular, alters the gut microbiota.IMPORTANCE The gut microbiome is an important factor in human health. It is affected by what we eat, what medicines we take, and what infections we acquire. In turn, it affects the way we absorb nutrients and whether we have excessive intestinal inflammation. Intestinal worms may have an important impact on the composition of the gut microbiome. Without a complete understanding of the impact of mass deworming programs on the microbiome, it is impossible to accurately calculate the cost-effectiveness of such public health interventions and to guard against any possible deleterious side effects. Our research examines this question in a "real-world" setting, using a longitudinal cohort, in which individuals with and without worm infections are treated with deworming medication and followed up at both three weeks and three months posttreatment. We quantify the impact of roundworms and hookworms on gut microbial composition, suggesting that the impact is small, but that treatment of hookworm infection results in significant changes. This work points to the need for follow-up studies to further examine the impact of hookworm on the gut microbiota and determine the health consequences of the observed changes

Assortment optimisation under a general discrete choice model: A tight analysis of revenue-ordered assortments

The assortment problem in revenue management is the problem of deciding which subset of products to offer to consumers in order to maximise revenue. A simple and natural strategy is to select the best assortment out of all those that are constructed by fixing a threshold revenue $\pi$ and then choosing all products with revenue at least $\pi$. This is known as the revenue-ordered assortments strategy. In this paper we study the approximation guarantees provided by revenue-ordered assortments when customers are rational in the following sense: the probability of selecting a specific product from the set being offered cannot increase if the set is enlarged. This rationality assumption, known as regularity, is satisfied by almost all discrete choice models considered in the revenue management and choice theory literature, and in particular by random utility models. The bounds we obtain are tight and improve on recent results in that direction, such as for the Mixed Multinomial Logit model by Rusmevichientong et al. (2014). An appealing feature of our analysis is its simplicity, as it relies only on the regularity condition. We also draw a connection between assortment optimisation and two pricing problems called unit demand envy-free pricing and Stackelberg minimum spanning tree: These problems can be restated as assortment problems under discrete choice models satisfying the regularity condition, and moreover revenue-ordered assortments correspond then to the well-studied uniform pricing heuristic. When specialised to that setting, the general bounds we establish for revenue-ordered assortments match and unify the best known results on uniform pricing.Comment: Minor changes following referees' comment

Antibiotic control of antibiotic resistance in hospitals: a simulation study

<p>Abstract</p> <p>Background</p> <p>Using mathematical deterministic models of the epidemiology of hospital-acquired infections and antibiotic resistance, it has been shown that the rates of hospital-acquired bacterial infection and frequency of antibiotic infections can be reduced by (i) restricting the admission of patients colonized with resistant bacteria, (ii) increasing the rate of turnover of patients, (iii) reducing transmission by infection control measures, and (iv) the use of second-line drugs for which there is no resistance. In an effort to explore the generality and robustness of the predictions of these deterministic models to the real world of hospitals, where there is variation in all of the factors contributing to the incidence of infection, we developed and used a stochastic model of the epidemiology of hospital-acquired infections and resistance. In our analysis of the properties of this model we give particular consideration different regimes of using second-line drugs in this process.</p> <p>Methods</p> <p>We developed a simple model that describes the transmission of drug-sensitive and drug-resistant bacteria in a small hospital. Colonized patients may be treated with a standard drug, for which there is some resistance, and with a second-line drug, for which there is no resistance. We then ran deterministic and stochastic simulation programs, based on this model, to predict the effectiveness of various treatment strategies.</p> <p>Results</p> <p>The results of the analysis using our stochastic model support the predictions of the deterministic models; not only will the implementation of any of the above listed measures substantially reduce the incidences of hospital-acquired infections and the frequency of resistance, the effects of their implementation should be seen in months rather than the years or decades anticipated to control resistance in open communities. How effectively and how rapidly the application of second-line drugs will contribute to the decline in the frequency of resistance to the first-line drugs depends on how these drugs are administered. The earlier the switch to second-line drugs, the more effective this protocol will be. Switching to second-line drugs at random is more effective than switching after a defined period or only after there is direct evidence that the patient is colonized with bacteria resistant to the first antibiotic.</p> <p>Conclusions</p> <p>The incidence of hospital-acquired bacterial infections and frequencies of antibiotic resistant bacteria can be markedly and rapidly reduced by different readily implemented procedures. The efficacy using second line drugs to achieve these ends depends on the protocol used for their administration.</p

A Self-Reference False Memory Effect in the DRM Paradigm: Evidence from Eastern and Western Samples

It is well established that processing information in relation to oneself (i.e., selfreferencing) leads to better memory for that information than processing that same information in relation to others (i.e., other-referencing). However, it is unknown whether self-referencing also leads to more false memories than other-referencing. In the current two experiments with European and East Asian samples, we presented participants the Deese-Roediger/McDermott (DRM) lists together with their own name or other people’s name (i.e., “Trump” in Experiment 1 and “Li Ming” in Experiment 2). We found consistent results across the two experiments; that is, in the self-reference condition, participants had higher true and false memory rates compared to those in the other-reference condition. Moreover, we found that selfreferencing did not exhibit superior mnemonic advantage in terms of net accuracy compared to other-referencing and neutral conditions. These findings are discussed in terms of theoretical frameworks such as spreading activation theories and the fuzzytrace theory. We propose that our results reflect the adaptive nature of memory in the sense that cognitive processes that increase mnemonic efficiency may also increase susceptibility to associative false memories

Complement Factor H Levels Associate With Plasmodium falciparum Malaria Susceptibility and Severity.

BACKGROUND: Plasmodium falciparum may evade complement-mediated host defense by hijacking complement Factor H (FH), a negative regulator of the alternative complement pathway. Plasma levels of FH vary between individuals and may therefore influence malaria susceptibility and severity. METHODS: We measured convalescent FH plasma levels in 149 Gambian children who had recovered from uncomplicated or severe P. falciparum malaria and in 173 healthy control children. We compared FH plasma levels between children with malaria and healthy controls, and between children with severe (n = 82) and uncomplicated malaria (n = 67). We determined associations between FH plasma levels and laboratory features of severity and used multivariate analyses to examine associations with FH when accounting for other determinants of severity. RESULTS: FH plasma levels differed significantly between controls, uncomplicated malaria cases, and severe malaria cases (mean [95% confidence interval], 257 [250 to 264], 288 [268 to 309], and 328 [313 to 344] µg/mL, respectively; analysis of variance P < .0001). FH plasma levels correlated with severity biomarkers, including lactate, parasitemia, and parasite density, but did not correlate with levels of PfHRP2, which represent the total body parasite load. Associations with severity and lactate remained significant when adjusting for age and parasite load. CONCLUSIONS: Natural variation in FH plasma levels is associated with malaria susceptibility and severity. A prospective study will be needed to strengthen evidence for causation, but our findings suggest that interfering with FH binding by P. falciparum might be useful for malaria prevention or treatment