Quantifying the Area at Risk in Reperfused ST-Segment-Elevation Myocardial Infarction Patients Using Hybrid Cardiac Positron Emission Tomography-Magnetic Resonance Imaging

BACKGROUND: Hybrid positron emission tomography and magnetic resonance allows the advantages of magnetic resonance in tissue characterizing the myocardium to be combined with the unique metabolic insights of positron emission tomography. We hypothesized that the area of reduced myocardial glucose uptake would closely match the area at risk delineated by T2 mapping in ST-segment-elevation myocardial infarction patients. METHODS AND RESULTS: Hybrid positron emission tomography and magnetic resonance using (18)F-fluorodeoxyglucose (FDG) for glucose uptake was performed in 21 ST-segment-elevation myocardial infarction patients at a median of 5 days. Follow-up scans were performed in a subset of patients 12 months later. The area of reduced FDG uptake was significantly larger than the infarct size quantified by late gadolinium enhancement (37.2±11.6% versus 22.3±11.7%; P<0.001) and closely matched the area at risk by T2 mapping (37.2±11.6% versus 36.3±12.2%; P=0.10, R=0.98, bias 0.9±4.4%). On the follow-up scans, the area of reduced FDG uptake was significantly smaller in size when compared with the acute scans (19.5 [6.3%-31.8%] versus 44.0 [21.3%-55.3%]; P=0.002) and closely correlated with the areas of late gadolinium enhancement (R 0.98) with a small bias of 2.0±5.6%. An FDG uptake of ≥45% on the acute scans could predict viable myocardium on the follow-up scan. Both transmural extent of late gadolinium enhancement and FDG uptake on the acute scan performed equally well to predict segmental wall motion recovery. CONCLUSIONS: Hybrid positron emission tomography and magnetic resonance in the reperfused ST-segment-elevation myocardial infarction patients showed reduced myocardial glucose uptake within the area at risk and closely matched the area at risk delineated by T2 mapping. FDG uptake, as well as transmural extent of late gadolinium enhancement, acutely can identify viable myocardial segments

A Retrospective Cohort Study of the Potency of lipid-lowering therapy and Race-gender Differences in LDL cholesterol control

<p>Abstract</p> <p>Background</p> <p>Reasons for race and gender differences in controlling elevated low density lipoprotein (LDL) cholesterol may be related to variations in prescribed lipid-lowering therapy. We examined the effect of lipid-lowering drug treatment and potency on time until LDL control for black and white women and men with a baseline elevated LDL.</p> <p>Methods</p> <p>We studied 3,484 older hypertensive patients with dyslipidemia in 6 primary care practices over a 4-year timeframe. Potency of lipid-lowering drugs calculated for each treated day and summed to assess total potency for at least 6 and up to 24 months. Cox models of time to LDL control within two years and logistic regression models of control within 6 months by race-gender adjust for: demographics, clinical, health care delivery, primary/specialty care, LDL measurement, and drug potency.</p> <p>Results</p> <p>Time to LDL control decreased as lipid-lowering drug potency increased (P < 0.001). Black women (N = 1,440) received the highest potency therapy (P < 0.001) yet were less likely to achieve LDL control than white men (N = 717) (fully adjusted hazard ratio [HR] 0.66 [95% CI 0.56-0.78]). Black men (N = 666) and white women (N = 661) also had lower adjusted HRs of LDL control (0.82 [95% CI 0.69, 0.98] and 0.75 [95% CI 0.64-0.88], respectively) than white men. Logistic regression models of LDL control by 6 months and other sensitivity models affirmed these results.</p> <p>Conclusions</p> <p>Black women and, to a lesser extent, black men and white women were less likely to achieve LDL control than white men after accounting for lipid-lowering drug potency as well as diverse patient and provider factors. Future work should focus on the contributions of medication adherence and response to treatment to these clinically important differences.</p

Cardiac Complications in Patients with Community-Acquired Pneumonia: A Systematic Review and Meta-Analysis of Observational Studies

Vicente Corrales-Medina and colleagues report estimates of the risk of cardiac complications among patients with community-acquired pneumonia from a systematic review and meta-analysis

Malaria risk factors in north-east Tanzania

BACKGROUND: Understanding the factors which determine a household's or individual's risk of malaria infection is important for targeting control interventions at all intensities of transmission. Malaria ecology in Tanzania appears to have reduced over recent years. This study investigated potential risk factors and clustering in face of changing infection dynamics. METHODS: Household survey data were collected in villages of rural Muheza district. Children aged between six months and thirteen years were tested for presence of malaria parasites using microscopy. A multivariable logistic regression model was constructed to identify significant risk factors for children. Geographical information systems combined with global positioning data and spatial scan statistic analysis were used to identify clusters of malaria. RESULTS: Using an insecticide-treated mosquito net of any type proved to be highly protective against malaria (OR 0.75, 95% CI 0.59-0.96). Children aged five to thirteen years were at higher risk of having malaria than those aged under five years (OR 1.71, 95% CI 1.01-2.91). The odds of malaria were less for females when compared to males (OR 0.62, 95% CI 0.39-0.98). Two spatial clusters of significantly increased malaria risk were identified in two out of five villages. CONCLUSIONS: This study provides evidence that recent declines in malaria transmission and prevalence may shift the age groups at risk of malaria infection to older children. Risk factor analysis provides support for universal coverage and targeting of long-lasting insecticide-treated nets (LLINs) to all age groups. Clustering of cases indicates heterogeneity of risk. Improved targeting of LLINs or additional supplementary control interventions to high risk clusters may improve outcomes and efficiency as malaria transmission continues to fall under intensified control

The spatial and temporal patterns of falciparum and vivax malaria in Perú: 1994–2006

<p>Abstract</p> <p>Background</p> <p>Malaria is the direct cause of approximately one million deaths worldwide each year, though it is both preventable and curable. Increasing the understanding of the transmission dynamics of falciparum and vivax malaria and their relationship could suggest improvements for malaria control efforts. Here the weekly number of malaria cases due to <it>Plasmodium falciparum </it>(1994–2006) and <it>Plasmodium vivax </it>(1999–2006) in Perú at different spatial scales in conjunction with associated demographic, geographic and climatological data are analysed.</p> <p>Methods</p> <p>Malaria periodicity patterns were analysed through wavelet spectral analysis, studied patterns of persistence as a function of community size and assessed spatial heterogeneity via the Lorenz curve and the summary Gini index.</p> <p>Results</p> <p>Wavelet time series analyses identified annual cycles in the incidence of both malaria species as the dominant pattern. However, significant spatial heterogeneity was observed across jungle, mountain and coastal regions with slightly higher levels of spatial heterogeneity for <it>P. vivax </it>than <it>P. falciparum</it>. While the incidence of <it>P. falciparum </it>has been declining in recent years across geographic regions, <it>P. vivax </it>incidence has remained relatively steady in jungle and mountain regions with a slight decline in coastal regions. Factors that may be contributing to this decline are discussed. The time series of both malaria species were significantly synchronized in coastal (ρ = 0.9, P < 0.0001) and jungle regions (ρ = 0.76, P < 0.0001) but not in mountain regions. Community size was significantly associated with malaria persistence due to both species in jungle regions, but not in coastal and mountain regions.</p> <p>Conclusion</p> <p>Overall, findings highlight the importance of highly refined spatial and temporal data on malaria incidence together with demographic and geographic information in improving the understanding of malaria persistence patterns associated with multiple malaria species in human populations, impact of interventions, detection of heterogeneity and generation of hypotheses.</p

Predicting the impact of Lynch syndrome-causing missense mutations from structural calculations

Accurate methods to assess the pathogenicity of mutations are needed to fully leverage the possibilities of genome sequencing in diagnosis. Current data-driven and bioinformatics approaches are, however, limited by the large number of new variations found in each newly sequenced genome, and often do not provide direct mechanistic insight. Here we demonstrate, for the first time, that saturation mutagenesis, biophysical modeling and co-variation analysis, performed in silico, can predict the abundance, metabolic stability, and function of proteins inside living cells. As a model system, we selected the human mismatch repair protein, MSH2, where missense variants are known to cause the hereditary cancer predisposition disease, known as Lynch syndrome. We show that the majority of disease-causing MSH2 mutations give rise to folding defects and proteasome-dependent degradation rather than inherent loss of function, and accordingly our in silico modeling data accurately identifies disease-causing mutations and outperforms the traditionally used genetic disease predictors. Thus, in conclusion, in silico biophysical modeling should be considered for making genotype-phenotype predictions and for diagnosis of Lynch syndrome, and perhaps other hereditary diseases

Cholesterol treatment with statins: Who is left out and who makes it to goal?

<p>Abstract</p> <p>Background</p> <p>Whether patient socio-demographic characteristics (age, sex, race/ethnicity, income, and education) are independently associated with failure to receive indicated statin therapy and/or to achieve low density lipoprotein cholesterol (LDL-C) therapy goals are not known. We examined socio-demographic factors associated with a) eligibility for statin therapy among those not on statins, and b) achievement of statin therapy goals.</p> <p>Methods</p> <p>Adults (21-79 years) participating in the United States (US) National Health and Nutrition Examination Surveys, 1999-2006 were studied. Statin eligibility and achievement of target LDL-C was assessed using the US Third Adult Treatment Panel (ATP III) on Treatment of High Cholesterol guidelines.</p> <p>Results</p> <p>Among 6,043 participants not taking statins, 10.4% were eligible. Adjusted predictors of statin eligibility among statin non-users were being older, male, poorer, and less educated. Hispanics were less likely to be eligible but not using statins, an effect that became non-significant with adjustment for language usually spoken at home. Among 537 persons taking statins, 81% were at LDL-C goal. Adjusted predictors of goal failure among statin users were being male and poorer. These risks were not attenuated by adjustment for healthcare access or utilization.</p> <p>Conclusion</p> <p>Among person's not taking statins, the socio-economically disadvantaged are more likely to be eligible and among those on statins, the socio-economically disadvantaged are less likely to achieve statin treatment goals. Further study is needed to identify specific amenable patient and/or physician factors that contribute to these disparities.</p

Changing Domesticity of Aedes aegypti in Northern Peninsular Malaysia: Reproductive Consequences and Potential Epidemiological Implications

BACKGROUND: The domestic dengue vector Aedes aegypti mosquitoes breed in indoor containers. However, in northern peninsular Malaysia, they show equal preference for breeding in both indoor and outdoor habitats. To evaluate the epidemiological implications of this peridomestic adaptation, we examined whether Ae. aegypti exhibits decreased survival, gonotrophic activity, and fecundity due to lack of host availability and the changing breeding behavior. METHODOLOGY/PRINCIPAL FINDINGS: This yearlong field surveillance identified Ae. aegypti breeding in outdoor containers on an enormous scale. Through a sequence of experiments incorporating outdoors and indoors adapting as well as adapted populations, we observed that indoors provided better environment for the survival of Ae. aegypti and the observed death patterns could be explained on the basis of a difference in body size. The duration of gonotrophic period was much shorter in large-bodied females. Fecundity tended to be greater in indoor acclimated females. We also found increased tendency to multiple feeding in outdoors adapted females, which were smaller in size compared to their outdoors breeding counterparts. CONCLUSION/SIGNIFICANCE: The data presented here suggest that acclimatization of Ae. aegypti to the outdoor environment may not decrease its lifespan or gonotrophic activity but rather increase breeding opportunities (increased number of discarded containers outdoors), the rate of larval development, but small body sizes at emergence. Size is likely to be correlated with disease transmission. In general, small size in Aedes females will favor increased blood-feeding frequency resulting in higher population sizes and disease occurrence

A New Method for Species Identification via Protein-Coding and Non-Coding DNA Barcodes by Combining Machine Learning with Bioinformatic Methods

Species identification via DNA barcodes is contributing greatly to current bioinventory efforts. The initial, and widely accepted, proposal was to use the protein-coding cytochrome c oxidase subunit I (COI) region as the standard barcode for animals, but recently non-coding internal transcribed spacer (ITS) genes have been proposed as candidate barcodes for both animals and plants. However, achieving a robust alignment for non-coding regions can be problematic. Here we propose two new methods (DV-RBF and FJ-RBF) to address this issue for species assignment by both coding and non-coding sequences that take advantage of the power of machine learning and bioinformatics. We demonstrate the value of the new methods with four empirical datasets, two representing typical protein-coding COI barcode datasets (neotropical bats and marine fish) and two representing non-coding ITS barcodes (rust fungi and brown algae). Using two random sub-sampling approaches, we demonstrate that the new methods significantly outperformed existing Neighbor-joining (NJ) and Maximum likelihood (ML) methods for both coding and non-coding barcodes when there was complete species coverage in the reference dataset. The new methods also out-performed NJ and ML methods for non-coding sequences in circumstances of potentially incomplete species coverage, although then the NJ and ML methods performed slightly better than the new methods for protein-coding barcodes. A 100% success rate of species identification was achieved with the two new methods for 4,122 bat queries and 5,134 fish queries using COI barcodes, with 95% confidence intervals (CI) of 99.75–100%. The new methods also obtained a 96.29% success rate (95%CI: 91.62–98.40%) for 484 rust fungi queries and a 98.50% success rate (95%CI: 96.60–99.37%) for 1094 brown algae queries, both using ITS barcodes