Physical activity patterns in a nationally representative sample of adults in Ireland

Original article can be found at: http://journals.cambridge.org/ Copyright - the authors. DOI: 10.1079/PHN2001192Objective To evaluate habitual levels of physical activity in a nationally representative sample of adults in Ireland. Design Cross-sectional survey using a self-administered questionnaire. Usual levels of work, recreational and household activities were evaluated in relation to anthropometric, demographic and socio-economic characteristics. The amount and intensity of all activities were quantified by assigning metabolic equivalents (METS) to each activity. Setting Republic of Ireland and Northern Ireland, 1997–1999. Subjects Random sample of 1379 adults aged 18–64 years. Results Men were approximately twice as active in work and recreational activity (139.7 ± 83.9 METS) as women (68.5 ± 49.8 METS; P 28kg m−2) or obese (BMI > 30kg m−2). Fewer obese subjects reported higher levels of work and leisure activities. However, a higher percentage of obese women reported participation in the higher levels of household activities. Participation rates in recreational activities were low. Walking was the most important leisure activity of both men (41%) and women (60%). In terms of hours per week spent in vigorous physical activity, men were more active than women, professional and skilled non-manual women were more active than women in other social classes, and younger subjects (aged 18–35 years) were more active than older subjects. Conclusions The holistic approach used in the assessment of physical activity in this study has revealed important and subtle differences in the activity patterns of men and women. Failure to fully characterise the respective activity patterns of men and women could lead to ill-informed public health policy aimed at promoting and sustaining lifetime habits of physical activity. The results suggest that simple population-focused programmes to promote physical activity are unlikely to offer the same chance of long-term success as more sensitive and individualised strategies.Peer reviewe

Isolation and characterisation of a novel Nesterenkonia species from a human bloodstreaminfection

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CO-releasing Metal Carbonyl Compounds as Antimicrobial Agents in the Post-antibiotic Era

The possibility of a “post-antibiotic era” in the 21st century, in which common infections may kill, has prompted research into radically new antimicrobials. CO-releasing molecules (CORMs), mostly metal carbonyl compounds, originally developed for therapeutic CO delivery in animals, are potent antimicrobial agents. Certain CORMs inhibit growth and respiration, reduce viability, and release CO to intracellular hemes, as predicted, but their actions are more complex, as revealed by transcriptomic datasets and modeling. Progress is hindered by difficulties in detecting CO release intracellularly, limited understanding of the biological chemistry of CO reactions with non-heme targets, and the cytotoxicity of some CORMs to mammalian cells

Whiter, brighter, and more stable cellulose paper coated with antibacterial carboxymethyl starch stabilized ZnO nanoparticles

Small, carboxymethyl-starch-stabilised zinc oxide nanoparticles with a defined shape, size and morphology were prepared in situ in water at relatively low reaction temperatures using soluble carboxymethyl starch (CMS) as a combined crystallising, stabilising and solubilising agent and triethanolamine as the reducing agent. Aqueous colloidal solutions of these CMS-stabilised ZnO nanoparticles were used to deposit a coating of ZnO nanoparticles on cellulose paper by a wet-chemistry, polyelectrolyte, layer-by-layer approach using water as the only solvent. Such cellulose paper samples, coated with these CMS-stabilised ZnO nanoparticles, show higher brightness and whiteness than that of blank reference paper and are more stable to UV-radiation than the paper reference as well as demonstrating good antibacterial activity against MRSA and A. baumannii

Dietary dairy product intake and incident type 2 diabetes: a prospective study using dietary data from a 7-day food diary

The consumption of specific dairy types may be beneficial for the prevention of diabetes. Abstract: The aim of this study was to investigate the association between total and types of dairy product intake and risk of developing incident type 2 diabetes, using a food diary. Methods: A nested case-cohort within the EPIC-Norfolk Study was examined, including a random subcohort (n=4,000) and cases of incident diabetes (n=892, including 143 cases in the subcohort) followed-up for 11 years. Diet was assessed using a prospective 7-day food diary. Total dairy intake (g/day) was estimated and categorised into high-fat (≥3.9%) and low-fat (<3.9% fat) dairy, and by subtype into yoghurt, cheese and milk. Combined fermented dairy product intake (yoghurt, cheese, sour cream) was estimated and categorised into high- and low-fat. Prentice-weighted Cox regression HRs were calculated. Results: Total dairy, high-fat dairy, milk, cheese and high-fat fermented dairy product intakes were not associated with the development of incident diabetes. Low-fat dairy intake was inversely associated with diabetes in age- and sex-adjusted analyses (tertile [T] 3 vs T1, HR 0.81 [95% CI 0.66, 0.98]), but further adjustment for anthropometric, dietary and diabetes risk factors attenuated this association. In addition, an inverse association was found between diabetes and low-fat fermented dairy product intake (T3 vs T1, HR 0.76 [95% CI 0.60, 0.99]; ptrend=0.049) and specifically with yoghurt intake (HR 0.72 [95% CI 0.55, 0.95]; ptrend=0.017) in multivariable adjusted analyses. Conclusions/interpretation: Greater low-fat fermented dairy product intake, largely driven by yoghurt intake, was associated with a decreased risk of type 2 diabetes development in prospective analyses. These findings suggest that the consumption of specific dairy types may be beneficial for the prevention of diabetes, highlighting the importance of food group subtypes for public health messages

Antifungal synergy of theaflavin and epicatechin combinations against Candida albicans

New antifungal agents are required to compensate for the increase in resistance to standard antifungal agents of Candida albicans, which is an important opportunistic fungal pathogen that causes minor infections in many individuals but very serious infections in those who are immune-compromised. In this study, combinations of theaflavin and epicatechin are investigated as potential antifungal agents and also to establish whether antifungal synergy exists between these two readily accessible and cost-effective polyphenols isolated from black and green tea. The results of disc diffusion assays showed stronger antibacterial activity of theaflavin:epicatechin combinations against C. albicans NCTC 3255 and NCTC 3179, than that of theaflavin alone. Minimum inhibitory concentrations (MICs) of 1,024 μg/ml with theaflavin and 128-256 μg/ml with theaflavin:epicatechin combinations were found. The fractional inhibitory concentration indexes were calculated, and the synergy between theaflavin and epicatechin against both isolates of C. albicans was confirmed. Theaflavin:epicatechin combinations show real potential for future use as a treatment for infections caused by C. albicans

Effects of In vivo Emergent Tigecycline Resistance on the Pathogenic Potential of Acinetobacter baumannii.

Multidrug-resistant lineages of Acinetobacter baumannii (MDRAB) are important nosocomial pathogens. As tigecycline remains active against most MDRAB we sought to investigate whether tigecycline resistance impacts biological fitness. The effects of treatment-emergent tigecycline resistance were investigated in vitro and in vivo using two pre- (AB210; W6976) and post-therapy (AB211; W7282) clinical pairs, recovered from individual patients, where tigecycline resistance was associated with up-regulated efflux activity. All isolates belonged to the same epidemic UK lineage. Significant differences were observed in end-point survival proportions between AB210 and AB211, but not between W6976 and W7282, using the Galleria mellonella infection model. Isolate AB211 outcompeted AB210 in vivo, in contrast to isolate W7282, which was outcompeted by its pre-therapy counterpart, W6972. Whole-genome sequencing of isolates W6976 and W7282 revealed a mutation in the adeABC regulatory gene, adeS in W7282; resulting in a Ser-8 → Arg substitution. Previous whole-genome comparison of AB210 and AB211 also identified a non-synonymous mutation in adeS, among several other lesions in genes involved in biofilm formation and DNA mismatch repair; consistent with the phenotypic differences described here. In conclusion, the differing effects on the wider phenotype were not predictable from the antibiograms or clonal lineage, despite a common mechanism of tigecycline resistance.Pfize

Multi-omic prediction of incident type 2 diabetes.

AIMS/HYPOTHESIS: The identification of people who are at high risk of developing type 2 diabetes is a key part of population-level prevention strategies. Previous studies have evaluated the predictive utility of omics measurements, such as metabolites, proteins or polygenic scores, but have considered these separately. The improvement that combined omics biomarkers can provide over and above current clinical standard models is unclear. The aim of this study was to test the predictive performance of genome, proteome, metabolome and clinical biomarkers when added to established clinical prediction models for type 2 diabetes. METHODS: We developed sparse interpretable prediction models in a prospective, nested type 2 diabetes case-cohort study (N=1105, incident type 2 diabetes cases=375) with 10,792 person-years of follow-up, selecting from 5759 features across the genome, proteome, metabolome and clinical biomarkers using least absolute shrinkage and selection operator (LASSO) regression. We compared the predictive performance of omics-derived predictors with a clinical model including the variables from the Cambridge Diabetes Risk Score and HbA1c. RESULTS: Among single omics prediction models that did not include clinical risk factors, the top ten proteins alone achieved the highest performance (concordance index [C index]=0.82 [95% CI 0.75, 0.88]), suggesting the proteome as the most informative single omic layer in the absence of clinical information. However, the largest improvement in prediction of type 2 diabetes incidence over and above the clinical model was achieved by the top ten features across several omic layers (C index=0.87 [95% CI 0.82, 0.92], Δ C index=0.05, p=0.045). This improvement by the top ten omic features was also evident in individuals with HbA1c <42 mmol/mol (6.0%), the threshold for prediabetes (C index=0.84 [95% CI 0.77, 0.90], Δ C index=0.07, p=0.03), the group in whom prediction would be most useful since they are not targeted for preventative interventions by current clinical guidelines. In this subgroup, the type 2 diabetes polygenic risk score was the major contributor to the improvement in prediction, and achieved a comparable improvement in performance when added onto the clinical model alone (C index=0.83 [95% CI 0.75, 0.90], Δ C index=0.06, p=0.002). However, compared with those with prediabetes, individuals at high polygenic risk in this group had only around half the absolute risk for type 2 diabetes over a 20 year period. CONCLUSIONS/INTERPRETATION: Omic approaches provided marginal improvements in prediction of incident type 2 diabetes. However, while a polygenic risk score does improve prediction in people with an HbA1c in the normoglycaemic range, the group in whom prediction would be most useful, even individuals with a high polygenic burden in that subgroup had a low absolute type 2 diabetes risk. This suggests a limited feasibility of implementing targeted population-based genetic screening for preventative interventions