Supplemental Vitamins and Minerals for CVD Prevention and Treatment

The authors identified individual randomized controlled trials from previous meta-analyses and additional searches, and then performed meta-analyses on cardiovascular disease outcomes and all-cause mortality. The authors assessed publications from 2012, both before and including the U.S. Preventive Service Task Force review. Their systematic reviews and meta-analyses showed generally moderate- or low-quality evidence for preventive benefits (folic acid for total cardiovascular disease, folic acid and B-vitamins for stroke), no effect (multivitamins, vitamins C, D, β-carotene, calcium, and selenium), or increased risk (antioxidant mixtures and niacin [with a statin] for all-cause mortality). Conclusive evidence for the benefit of any supplement across all dietary backgrounds (including deficiency and sufficiency) was not demonstrated; therefore, any benefits seen must be balanced against possible risks

Suppression of rice methane emission by sulfate deposition in simulated acid rain

Sulfate in acid rain is known to suppress methane (CH4) emissions from natural freshwater wetlands. Here we examine the possibility that CH4 emissions from rice agriculture may be similarly affected by acid rain, a major and increasing pollution problem in Asia. Our findings suggest that acid rain rates of SO2-4 deposition may help to reduce CH4 emissions from rice agriculture. Emissions from rice plants treated with simulated acid rain at levels of SO2-4 consistent with the range of deposition in Asia were reduced by 24% during the grain filling and ripening stage of the rice season which accounts for 50% of the overall CH4 that is normally emitted in a rice season. A single application of SO2-4 at a comparable level reduced CH4 emission by 43%. We hypothesize that the reduction in CH4 emission may be due to a combination of effects. The first mechanism is that the low rates of SO2-4 may be sufficient to boost yields of rice and, in so doing, may cause a reduction in root exudates to the rhizosphere, a key substrate source for methanogenesis. Decreasing a major substrate source for methanogens is also likely to intensify competition with sulfate-reducing microorganisms for whom prior SO2-4 limitation had been lifted by the simulated acid rain S deposition

Simulation model to assess the validity of the clinical portfolio diet score used in the PortfolioDiet.app for dietary self-tracking: a secondary analysis of a randomized controlled trial in hyperlipidemic adults

IntroductionThe Portfolio Diet combines cholesterol-lowering plant foods for the management of cardiovascular disease risk. However, the translation of this dietary approach into clinical practice necessitates a user-friendly method for patients to autonomously monitor their adherence.ObjectiveThis study aimed to develop and validate the clinical-Portfolio Diet Score (c-PDS) as a food-based metric to facilitate self-tracking of the Portfolio Diet.MethodsUsing a simulation model to estimate the c-PDS, the validity was assessed in a secondary analysis of a completed trial of the Portfolio Diet in 98 participants with hyperlipidemia over 6 months. Concurrent and predictive validity of the estimated c-PDS were assessed against the reference measure (weighed 7-day diet records) and concomitant changes in LDL-C from baseline to 6 months. Bland–Altman analysis was used to assess the limits of agreement between the two methods.ResultsThe c-PDS was positively correlated with dietary adherence as measured using the 7-day diet records (r = 0.94, p < 0.001). The c-PDS was negatively correlated with change in LDL-C (r = −0.43, p < 0.001) with a 1-point increase in the c-PDS being associated with a − 0.04 mmol/L (CI:−0.06,−0.03; p < 0.001) or a 1.09% reduction in LDL-C. Visual evaluation of the Bland–Altman plots showed reasonable agreement.ConclusionThese findings indicate good validity of the c-PDS for primary prevention in adults with hyperlipidemia. The predictive validity findings have informed the goals and messaging within the PortfolioDiet.app, a digital health application for delivering the Portfolio Diet. Future research will assess the effectiveness of the intended combination of the c-PDS and the PortfolioDiet.app in supporting behavior change

Evaluating the impact of MEDLINE filters on evidence retrieval: study protocol

<p>Abstract</p> <p>Background</p> <p>Rather than searching the entire MEDLINE database, clinicians can perform searches on a filtered set of articles where relevant information is more likely to be found. Members of our team previously developed two types of MEDLINE filters. The 'methods' filters help identify clinical research of high methodological merit. The 'content' filters help identify articles in the discipline of renal medicine. We will now test the utility of these filters for physician MEDLINE searching.</p> <p>Hypothesis</p> <p>When a physician searches MEDLINE, we hypothesize the use of filters will increase the number of relevant articles retrieved (increase 'recall,' also called sensitivity) and decrease the number of non-relevant articles retrieved (increase 'precision,' also called positive predictive value), compared to the performance of a physician's search unaided by filters.</p> <p>Methods</p> <p>We will survey a random sample of 100 nephrologists in Canada to obtain the MEDLINE search that they would first perform themselves for a focused clinical question. Each question we provide to a nephrologist will be based on the topic of a recently published, well-conducted systematic review. We will examine the performance of a physician's unaided MEDLINE search. We will then apply a total of eight filter combinations to the search (filters used in isolation or in combination). We will calculate the recall and precision of each search. The filter combinations that most improve on unaided physician searches will be identified and characterized.</p> <p>Discussion</p> <p>If these filters improve search performance, physicians will be able to search MEDLINE for renal evidence more effectively, in less time, and with less frustration. Additionally, our methodology can be used as a proof of concept for the evaluation of search filters in other disciplines.</p

Discovery of 95 PTSD loci provides insight into genetic architecture and neurobiology of trauma and stress-related disorders

Posttraumatic stress disorder (PTSD) genetics are characterized by lower discoverability than most other psychiatric disorders. The contribution to biological understanding from previous genetic studies has thus been limited. We performed a multi-ancestry meta-analysis of genome-wide association studies across 1,222,882 individuals of European ancestry (137,136 cases) and 58,051 admixed individuals with African and Native American ancestry (13,624 cases). We identified 95 genome-wide significant loci (80 novel). Convergent multi-omic approaches identified 43 potential causal genes, broadly classified as neurotransmitter and ion channel synaptic modulators (e.g., GRIA1, GRM8, CACNA1E ), developmental, axon guidance, and transcription factors (e.g., FOXP2, EFNA5, DCC ), synaptic structure and function genes (e.g., PCLO, NCAM1, PDE4B ), and endocrine or immune regulators (e.g., ESR1, TRAF3, TANK ). Additional top genes influence stress, immune, fear, and threat-related processes, previously hypothesized to underlie PTSD neurobiology. These findings strengthen our understanding of neurobiological systems relevant to PTSD pathophysiology, while also opening new areas for investigation

Emissions from prescribed fires in temperate forest in south-east Australia: implications for carbon accounting

We estimated emissions of carbon, as equivalent CO2 (CO2e), from planned fires in four sites in a south-eastern Australian forest. Emission estimates were calculated using measurements of fuel load and carbon content of different fuel types, before and after burning, and determination of fuel-specific emission factors. Median estimates of emissions for the four sites ranged from 20 to 139 Mg CO2e ha−1. Variability in estimates was a consequence of different burning efficiencies of each fuel type from the four sites. Higher emissions resulted from more fine fuel (twigs, decomposing matter, near-surface live and leaf litter) or coarse woody debris (CWD; \u3e 25 mm diameter) being consumed. In order to assess the effect of declining information quantity and the inclusion of coarse woody debris when estimating emissions, Monte Carlo simulations were used to create seven scenarios where input parameters values were replaced by probability density functions. Calculation methods were (1) all measured data were constrained between measured maximum and minimum values for each variable; (2) as in (1) except the proportion of carbon within a fuel type was constrained between 0 and 1; (3) as in (2) but losses of mass caused by fire were replaced with burning efficiency factors constrained between 0 and 1; and (4) emissions were calculated using default values in the Australian National Greenhouse Accounts (NGA), National Inventory Report 2011, as appropriate for our sites. Effects of including CWD in calculations were assessed for calculation Method 1, 2 and 3 but not for Method 4 as the NGA does not consider this fuel type. Simulations demonstrate that the probability of estimating true median emissions declines strongly as the amount of information available declines. Including CWD in scenarios increased uncertainty in calculations because CWD is the most variable contributor to fuel load. Inclusion of CWD in scenarios generally increased the amount of carbon lost. We discuss implications of these simulations and how emissions from prescribed burns in temperate Australian forests could be improved

Modelling bushfire fuel hazard using biophysical parameters

© 2020 by the authors. Environmental gradients or biophysical parameters such as climate, topography and geology drive landscape-scale vegetation structure, species distribution and productivity. These gradients have the potential to provide detailed, fine-scale spatial prediction of the accumulation of bushfire fuels and hence fire hazard by elucidating patterns in field information in a consistent and repeatable way. Rapid visual assessment of bushfire fuel hazard via ratings provides fire and land management agencies with a measure of the probability of first attack success and general suppression difficulty of bushfires at a location. This study used generalised additive modelling to examine how measures of fuel hazard, recorded for locations in New South Wales, Australia, varied in response to environmental gradients and whether these gradients could be used to predict fuel hazard at a landscape scale. We found that time since last fire, temperature and precipitation were strong predictors of fuel hazard. Our model predictions for fuel hazard outperformed current operational methods; however, both methods tended to overestimate lower fuel hazard and underestimate higher fuel hazard. Biophysical modelling of fuel hazard provides significant advancement for predicting fuel hazard. These models have the capability to be improved and developed as additional fuel hazard data, fire history mapping and remote sensing of environmental variables advance both spatially and temporally

Vegetation type determines heterotrophic respiration in subalpine Australian ecosystems

Soils are the largest store of carbon in the biosphere and cool-cold climate ecosystems are notable for their carbon-rich soils. Characterizing effects of future climates on soil-stored C is critical to elucidating feedbacks to changes in the atmospheric pool of CO2. Subalpine vegetation in south-eastern Australia is characterized by changes over short distances (scales of tens to hundreds of metres) in community phenotype (woodland, shrubland, grassland) and in species composition. Despite common geology and only slight changes in landscape position, we measured striking differences in a range of soil properties and rates of respiration among three of the most common vegetation communities in subalpine Australian ecosystems. Rates of heterotrophic respiration in bulk soil were fastest in the woodland community with a shrub understorey, slowest in the grassland, and intermediate in woodland with grass understorey. Respiration rates in surface soils were 2.3 times those at depth in soils from woodland with shrub understorey. Surface soil respiration in woodlands with grass understorey and in grasslands was about 3.5 times that at greater depth. Both Arrhenius and simple exponential models fitted the data well. Temperature sensitivity (Q10) varied and depended on the model used as well as community type and soil depth - highlighting difficulties associated with calculating and interpreting Q10. Distributions of communities in these subalpine areas are dynamic and respond over relatively short time-frames (decades) to changes in fire regime and, possibly, to changes in climate. Shifts in boundaries among communities and possible changes in species composition as a result of both direct and indirect (e.g. via fire regime) climatic effects will significantly alter rates of respiration through plant-mediated changes in soil chemistry. Models of future carbon cycles need to take into account changes in soil chemistry and rates of respiration driven by changes in vegetation as well as those that are temperature- and moisture-driven