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A higher intake of foods rich in flavonoids such as quercetin can reduce the risk of cardiovascular disease. Enzymatically modified isoquercitrin (EMIQ®) has a bioavailability 17-fold higher than quercetin aglycone and has shown potential cardiovascular disease moderating effects in animal studies. The present study aimed to determine if acute ingestion of EMIQ® improves endothelial function, blood pressure, and cognitive function in human volunteers at risk of cardiovascular disease. Twenty-five participants (12 males, 13 females) with at least one cardiovascular disease risk factor completed this randomized, controlled, crossover study. In a random order, participants were given EMIQ® (2 mg aglycone equivalent)/kg body weight or placebo alongside a standard breakfast meal. Endothelial function, assessed by flow mediated dilatation (FMD) of the brachial artery was measured before and 1.5 hrs after intervention. Blood pressure (BP), arterial stiffness, cognitive function, BP during cognitive stress and measures of quercetin metabolites, oxidative stress and markers of nitric oxide (NO) production were assessed post-intervention. After adjustment for pre-treatment measurements and treatment order, EMIQ® treatment resulted in a significantly higher FMD response compared to the placebo [0.60%, 95% CI: 0.03, 1.17 (p=0.04)]. Plasma concentrations of quercetin metabolites were significantly higher (p<0.001) after EMIQ® treatment compared to the placebo. No changes in blood pressure, arterial stiffness, cognitive function, or biochemical parameters were observed. In this human intervention study, the acute administration of EMIQ® significantly increased circulating quercetin metabolites and improved endothelial function. Further clinical trials are required to assess whether health benefits are associated with long-term EMIQ® consumption.
Space Infrared Telescope for Cosmology and Astrophysics (SPICA), the cryogenic infrared space telescope recently pre-selected for a ‘Phase A’ concept study as one of the three remaining candidates for European Space Agency (ESA's) fifth medium class (M5) mission, is foreseen to include a far-infrared polarimetric imager [SPICA-POL, now called B-fields with BOlometers and Polarizers (B-BOP)], which would offer a unique opportunity to resolve major issues in our understanding of the nearby, cold magnetised Universe. This paper presents an overview of the main science drivers for B-BOP, including high dynamic range polarimetric imaging of the cold interstellar medium (ISM) in both our Milky Way and nearby galaxies. Thanks to a cooled telescope, B-BOP will deliver wide-field 100–350
m images of linearly polarised dust emission in Stokes Q and U with a resolution, signal-to-noise ratio, and both intensity and spatial dynamic ranges comparable to those achieved by Herschel images of the cold ISM in total intensity (Stokes I). The B-BOP 200
m images will also have a factor
30 higher resolution than Planck polarisation data. This will make B-BOP a unique tool for characterising the statistical properties of the magnetised ISM and probing the role of magnetic fields in the formation and evolution of the interstellar web of dusty molecular filaments giving birth to most stars in our Galaxy. B-BOP will also be a powerful instrument for studying the magnetism of nearby galaxies and testing Galactic dynamo models, constraining the physics of dust grain alignment, informing the problem of the interaction of cosmic rays with molecular clouds, tracing magnetic fields in the inner layers of protoplanetary disks, and monitoring accretion bursts in embedded protostars.
Identify changes in the prevalence and antimicrobial resistance patterns of potentially pathogenic bacteria in urine cultures during a 2-year antimicrobial stewardship intervention program in nursing homes (NHs).
Before-and-after intervention study.
The study included 27 NHs in North Carolina.
We audited all urine cultures ordered before and during an antimicrobial stewardship intervention. Analyses compared culture rates, culture positive rates, and pathogen antimicrobial resistance patterns.
Of 6,718 total urine cultures collected, 68% were positive for potentially pathogenic bacteria. During the intervention, significant reductions in the urine culture and positive culture rates were observed (P = .014). Most of the identified potentially uropathogenic isolates were Escherichia coli (38%), Proteus spp (13%), and Klebsiella pneumoniae (12%). A significant decrease was observed during the intervention period in nitrofurantoin resistance among E. coli (P ≤ .001) and ciprofloxacin resistance among Proteus spp (P ≤ .001); however carbapenem resistance increased for Proteus spp (P ≤ .001). Multidrug resistance also increased for Proteus spp compared to the baseline. The high baseline resistance of E. coli to the commonly prescribed antimicrobials ciprofloxacin and trimethoprim-sulfamethoxazole (TMP/SMX) did not change during the intervention.
The antimicrobial stewardship intervention program significantly reduced urine culture and culture-positive rates. Overall, very high proportions of antimicrobial resistance were observed among common pathogens; however, antimicrobial resistance trended downward but reductions were too small and scattered to conclude that the intervention significantly changed antimicrobial resistance. Longer intervention periods may be needed to effect change in resistance patterns.
Determining infectious cross-transmission events in healthcare settings involves manual surveillance of case clusters by infection control personnel, followed by strain typing of clinical/environmental isolates suspected in said clusters. Recent advances in genomic sequencing and cloud computing now allow for the rapid molecular typing of infecting isolates.
To facilitate rapid recognition of transmission clusters, we aimed to assess infection control surveillance using whole-genome sequencing (WGS) of microbial pathogens to identify cross-transmission events for epidemiologic review.
Clinical isolates of Staphylococcus aureus, Enterococcus faecium, Pseudomonas aeruginosa, and Klebsiella pneumoniae were obtained prospectively at an academic medical center, from September 1, 2016, to September 30, 2017. Isolate genomes were sequenced, followed by single-nucleotide variant analysis; a cloud-computing platform was used for whole-genome sequence analysis and cluster identification.
Most strains of the 4 studied pathogens were unrelated, and 34 potential transmission clusters were present. The characteristics of the potential clusters were complex and likely not identifiable by traditional surveillance alone. Notably, only 1 cluster had been suspected by routine manual surveillance.
Our work supports the assertion that integration of genomic and clinical epidemiologic data can augment infection control surveillance for both the identification of cross-transmission events and the inclusion of missed and exclusion of misidentified outbreaks (ie, false alarms). The integration of clinical data is essential to prioritize suspect clusters for investigation, and for existing infections, a timely review of both the clinical and WGS results can hold promise to reduce HAIs. A richer understanding of cross-transmission events within healthcare settings will require the expansion of current surveillance approaches.
Salmonella enterica serovar Wangata (S. Wangata) is an important cause of endemic salmonellosis in Australia, with human infections occurring from undefined sources. This investigation sought to examine possible environmental and zoonotic sources for human infections with S. Wangata in north-eastern New South Wales (NSW), Australia. The investigation adopted a One Health approach and was comprised of three complimentary components: a case–control study examining human risk factors; environmental and animal sampling; and genomic analysis of human, animal and environmental isolates. Forty-eight human S. Wangata cases were interviewed during a 6-month period from November 2016 to April 2017, together with 55 Salmonella Typhimurium (S. Typhimurium) controls and 130 neighbourhood controls. Indirect contact with bats/flying foxes (S. Typhimurium controls (adjusted odds ratio (aOR) 2.63, 95% confidence interval (CI) 1.06–6.48)) (neighbourhood controls (aOR 8.33, 95% CI 2.58–26.83)), wild frogs (aOR 3.65, 95% CI 1.32–10.07) and wild birds (aOR 6.93, 95% CI 2.29–21.00) were statistically associated with illness in multivariable analyses. S. Wangata was detected in dog faeces, wildlife scats and a compost specimen collected from the outdoor environments of cases’ residences. In addition, S. Wangata was detected in the faeces of wild birds and sea turtles in the investigation area. Genomic analysis revealed that S. Wangata isolates were relatively clonal. Our findings suggest that S. Wangata is present in the environment and may have a reservoir in wildlife populations in north-eastern NSW. Further investigation is required to better understand the occurrence of Salmonella in wildlife groups and to identify possible transmission pathways for human infections.
We describe diet quality by demographic factors and weight status among Barbadian children and examine associations with excess energy intake (EI). A screening tool for the identification of children at risk of excess EI was developed.
In a cross-sectional survey, the Diet Quality Index–International (DQI-I) was used to assess dietary intakes from repeat 24h recalls among 362 children aged 9–10 years. Participants were selected by probability proportional to size. A model to identify excess energy intake from easily measured components of the DQI-I was developed.
Primary-school children in Barbados.
Over one-third of children were overweight/obese, and mean EI for boys (8644 (se 174·5) kJ/d (2066 (se 41·7) kcal/d)) and girls (8912 (se 169·9) kJ/d (2130 (se 40·6) kcal/d)) exceeded the RDA. Children consuming a variety of food groups, more vegetables and fruits, and lower percentage energy contribution from empty-calorie foods showed reduced likelihood of excess EI. Intake of more than 2400 mg Na/d and higher macronutrient and fatty acid ratios were positively related to the consumption of excess energy. A model using five DQI-I components (overall food group variety, variety for protein source, vegetables, fruits and empty calorie intake) had high sensitivity for identification of children at risk of excess EI.
Children’s diet quality, despite low intakes of fruit and vegetables, was within acceptable ranges as assessed by the DQI-I and RDA; however, portion size was large and EI high. A practical model for identification of children at risk of excess EI has been developed.
We evaluated the performance of three serological tests – an immunoglobulin G indirect enzyme linked immunosorbent assay (iELISA), a Rose Bengal test and a slow agglutination test (SAT) – for the diagnosis of bovine brucellosis in Bangladesh. Cattle sera (n = 1360) sourced from Mymensingh district (MD) and a Government owned dairy farm (GF) were tested in parallel. We used a Bayesian latent class model that adjusted for the conditional dependence among the three tests and assumed constant diagnostic accuracy of the three tests in both populations. The sensitivity and specificity of the three tests varied from 84.6% to 93.7%, respectively. The true prevalences of bovine brucellosis in MD and the GF were 0.6% and 20.4%, respectively. Parallel interpretation of iELISA and SAT yielded the highest negative predictive values: 99.9% in MD and 99.6% in the GF; whereas serial interpretation of both iELISA and SAT produced the highest positive predictive value (PPV): 99.9% in the GF and also high PPV (98.9%) in MD. We recommend the use of both iELISA and SAT together and serial interpretation for culling and parallel interpretation for import decisions. Removal of brucellosis positive cattle will contribute to the control of brucellosis as a public health risk in Bangladesh.
We introduce a Bayesian approach to conduct inferential analyses on dyadic data while accounting for interdependencies between observations through a set of additive and multiplicative effects (AME). The AME model is built on a generalized linear modeling framework and is thus flexible enough to be applied to a variety of contexts. We contrast the AME model to two prominent approaches in the literature: the latent space model (LSM) and the exponential random graph model (ERGM). Relative to these approaches, we show that the AME approach is (a) to be easy to implement; (b) interpretable in a general linear model framework; (c) computationally straightforward; (d) not prone to degeneracy; (e) captures first-, second-, and third-order network dependencies; and (f) notably outperforms ERGMs and LSMs on a variety of metrics and in an out-of-sample context. In summary, AME offers a straightforward way to undertake nuanced, principled inferential network analysis for a wide range of social science questions.