Bodyweight Perceptions among Texas Women: The Effects of Religion, Race/Ethnicity, and Citizenship Status

Despite previous work exploring linkages between religious participation and health, little research has looked at the role of religion in affecting bodyweight perceptions. Using the theoretical model developed by Levin et al. (Sociol Q 36(1):157–173, 1995) on the multidimensionality of religious participation, we develop several hypotheses and test them by using data from the 2004 Survey of Texas Adults. We estimate multinomial logistic regression models to determine the relative risk of women perceiving themselves as overweight. Results indicate that religious attendance lowers risk of women perceiving themselves as very overweight. Citizenship status was an important factor for Latinas, with noncitizens being less likely to see themselves as overweight. We also test interaction effects between religion and race. Religious attendance and prayer have a moderating effect among Latina non-citizens so that among these women, attendance and prayer intensify perceptions of feeling less overweight when compared to their white counterparts. Among African American women, the effect of increased church attendance leads to perceptions of being overweight. Prayer is also a correlate of overweight perceptions but only among African American women. We close with a discussion that highlights key implications from our findings, note study limitations, and several promising avenues for future research

Spatial abundance and clustering of Culicoides (Diptera: Ceratopogonidae) on a local scale

BACKGROUND: Biting midges, Culicoides, of the Obsoletus group and the Pulicaris group have been involved in recent outbreaks of bluetongue virus and the former was also involved in the Schmallenberg virus outbreak in northern Europe. METHODS: For the first time, here we investigate the local abundance pattern of these two species groups in the field by intensive sampling with a grid of light traps on 16 catch nights. Neighboring trap catches can be spatially dependent on each other, hence we developed a conditional autoregressive (CAR) model framework to test a number of spatial and non-spatial covariates expected to affect Culicoides abundance. RESULTS: The distance to sheep penned in the corner of the study field significantly increased the abundance level up to 200 meters away from the sheep. Spatial clustering was found to be significant but could not be explained by any known factors, and cluster locations shifted between catch nights. No significant temporal autocorrelation was detected. CAR models for both species groups identified a significant positive impact of humidity and significant negative impacts of precipitation and wind turbulence. Temperature was also found to be significant with a peak at just below 16 degrees Celcius. Surprisingly, there was a significant positive impact of wind speed. The CAR model for the Pulicaris group also identified a significant attraction to the smaller groups of sheep placed in the field. Furthermore, a large number of spatial covariates which were incorrectly found to be significant in ordinary regression models were not significant in the CAR models. The 95% C.I. on the prediction estimates ranged from 20.4% to 304.8%, underlining the difficulties of predicting the abundance of Culicoides. CONCLUSIONS: We found that significant spatial clusters of Culicoides moved around in a dynamic pattern varying between catch nights. This conforms with the modeling but was not explained by any of the tested covariates. The mean abundance within these clusters was up to 11 times higher for the Obsoletus group and 4 times higher for the Pulicaris group compared to the rest of the field

Perspectives on utilization of edible coatings and nano-laminate coatings for extension of postharvest storage of fruits and vegetables

It is known that in developing countries, a large quantity of fruit and vegetable losses results at postharvest and processing stages due to poor or scarce storage technology and mishandling during harvest. The use of new and innovative technologies for reducing postharvest losses is a requirement that has not been fully covered. The use of edible coatings (mainly based on biopolymers) as a postharvest technique for agricultural commodities has offered biodegradable alternatives in order to solve problems (e.g., microbiological growth) during produce storage. However, biopolymer-based coatings can present some disadvantages such as: poor mechanical properties (e.g., lipids) or poor water vapor barrier properties (e.g., polysaccharides), thus requiring the development of new alternatives to solve these drawbacks. Recently, nanotechnology has emerged as a promising tool in the food processing industry, providing new insights about postharvest technologies on produce storage. Nanotechnological approaches can contribute through the design of functional packing materials with lower amounts of bioactive ingredients, better gas and mechanical properties and with reduced impact on the sensorial qualities of the fruits and vegetables. This work reviews some of the main factors involved in postharvest losses and new technologies for extension of postharvest storage of fruits and vegetables, focused on perspective uses of edible coatings and nano-laminate coatings.María L. Flores-López thanks Mexican Science and Technology Council (CONACYT, Mexico) for PhD fellowship support (CONACYT Grant Number: 215499/310847). Miguel A. Cerqueira (SFRH/BPD/72753/2010) is recipient of a fellowship from the Fundação para a Ciência e Tecnologia (FCT, POPH-QREN and FSE Portugal). The authors also thank the FCT Strategic Project of UID/ BIO/04469/2013 unit, the project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462) and the project ‘‘BioInd Biotechnology and Bioengineering for improved Industrial and AgroFood processes,’’ REF. NORTE-07-0124-FEDER-000028 Co-funded by the Programa Operacional Regional do Norte (ON.2 – O Novo Norte), QREN, FEDER. Fundação Cearense de Apoio ao Desenvolvimento Científico e Tecnológico – FUNCAP, CE Brazil (CI10080-00055.01.00/13)

A flexible Bayesian hierarchical model of preterm birth risk among US Hispanic subgroups in relation to maternal nativity and education

<p>Abstract</p> <p>Background</p> <p>Previous research has documented heterogeneity in the effects of maternal education on adverse birth outcomes by nativity and Hispanic subgroup in the United States. In this article, we considered the risk of preterm birth (PTB) using 9 years of vital statistics birth data from New York City. We employed finer categorizations of exposure than used previously and estimated the risk dose-response across the range of education by nativity and ethnicity.</p> <p>Methods</p> <p>Using Bayesian random effects logistic regression models with restricted quadratic spline terms for years of completed maternal education, we calculated and plotted the estimated posterior probabilities of PTB (gestational age < 37 weeks) for each year of education by ethnic and nativity subgroups adjusted for only maternal age, as well as with more extensive covariate adjustments. We then estimated the posterior risk difference between native and foreign born mothers by ethnicity over the continuous range of education exposures.</p> <p>Results</p> <p>The risk of PTB varied substantially by education, nativity and ethnicity. Native born groups showed higher absolute risk of PTB and declining risk associated with higher levels of education beyond about 10 years, as did foreign-born Puerto Ricans. For most other foreign born groups, however, risk of PTB was flatter across the education range. For Mexicans, Central Americans, Dominicans, South Americans and "Others", the protective effect of foreign birth diminished progressively across the educational range. Only for Puerto Ricans was there no nativity advantage for the foreign born, although small numbers of foreign born Cubans limited precision of estimates for that group.</p> <p>Conclusions</p> <p>Using flexible Bayesian regression models with random effects allowed us to estimate absolute risks without strong modeling assumptions. Risk comparisons for any sub-groups at any exposure level were simple to calculate. Shrinkage of posterior estimates through the use of random effects allowed for finer categorization of exposures without restricting joint effects to follow a fixed parametric scale. Although foreign born Hispanic women with the least education appeared to generally have low risk, this seems likely to be a marker for unmeasured environmental and behavioral factors, rather than a causally protective effect of low education itself.</p

Histone deacetylases suppress cgg repeat-induced neurodegeneration via transcriptional silencing in models of Fragile X Tremor Ataxia Syndrome

Fragile X Tremor Ataxia Syndrome (FXTAS) is a common inherited neurodegenerative disorder caused by expansion of a CGG trinucleotide repeat in the 59UTR of the fragile X syndrome (FXS) gene, FMR1. The expanded CGG repeat is thought to induce toxicity as RNA, and in FXTAS patients mRNA levels for FMR1 are markedly increased. Despite the critical role of FMR1 mRNA in disease pathogenesis, the basis for the increase in FMR1 mRNA expression is unknown. Here we show that overexpressing any of three histone deacetylases (HDACs 3, 6, or 11) suppresses CGG repeat-induced neurodegeneration in a Drosophila model of FXTAS. This suppression results from selective transcriptional repression of the CGG repeat-containing transgene. These findings led us to evaluate the acetylation state of histones at the human FMR1 locus. In patient-derived lymphoblasts and fibroblasts, we determined by chromatin immunoprecipitation that there is increased acetylation of histones at the FMR1 locus in pre-mutation carriers compared to control or FXS derived cell lines. These epigenetic changes correlate with elevated FMR1 mRNA expression in pre-mutation cell lines. Consistent with this finding, histone acetyltransferase (HAT) inhibitors repress FMR1 mRNA expression to control levels in pre-mutation carrier cell lines and extend lifespan in CGG repeat-expressing Drosophila. These findings support a disease model whereby the CGG repeat expansion in FXTAS promotes chromatin remodeling in cis, which in turn increases expression of the toxic FMR1 mRNA. Moreover, these results provide proof of principle that HAT inhibitors or HDAC activators might be used to selectively repress transcription at the FMR1 locus.open293

Density functional theory based screening of ternary alkali-transition metal borohydrides: A computational material design project

The dissociation of molecules, even the most simple hydrogen molecule, cannot be described accurately within density functional theory because none of the currently available functionals accounts for strong on-site correlation. This problem led to a discussion of properties that the local Kohn-Sham potential has to satisfy in order to correctly describe strongly correlated systems. We derive an analytic expression for the nontrivial form of the Kohn-Sham potential in between the two fragments for the dissociation of a single bond. We show that the numerical calculations for a one-dimensional two-electron model system indeed approach and reach this limit. It is shown that the functional form of the potential is universal, i.e., independent of the details of the two fragments.We acknowledge funding by the Spanish MEC (Grant No. FIS2007-65702-C02-01), “Grupos Consolidados UPV/EHU del Gobierno Vasco” (Grant No. IT-319-07), and the European Community through e-I3 ETSF project (Grant Agreement No. 211956).Peer reviewe

Antiinflammatory Therapy with Canakinumab for Atherosclerotic Disease

Background: Experimental and clinical data suggest that reducing inflammation without affecting lipid levels may reduce the risk of cardiovascular disease. Yet, the inflammatory hypothesis of atherothrombosis has remained unproved. Methods: We conducted a randomized, double-blind trial of canakinumab, a therapeutic monoclonal antibody targeting interleukin-1β, involving 10,061 patients with previous myocardial infarction and a high-sensitivity C-reactive protein level of 2 mg or more per liter. The trial compared three doses of canakinumab (50 mg, 150 mg, and 300 mg, administered subcutaneously every 3 months) with placebo. The primary efficacy end point was nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death. RESULTS: At 48 months, the median reduction from baseline in the high-sensitivity C-reactive protein level was 26 percentage points greater in the group that received the 50-mg dose of canakinumab, 37 percentage points greater in the 150-mg group, and 41 percentage points greater in the 300-mg group than in the placebo group. Canakinumab did not reduce lipid levels from baseline. At a median follow-up of 3.7 years, the incidence rate for the primary end point was 4.50 events per 100 person-years in the placebo group, 4.11 events per 100 person-years in the 50-mg group, 3.86 events per 100 person-years in the 150-mg group, and 3.90 events per 100 person-years in the 300-mg group. The hazard ratios as compared with placebo were as follows: in the 50-mg group, 0.93 (95% confidence interval [CI], 0.80 to 1.07; P = 0.30); in the 150-mg group, 0.85 (95% CI, 0.74 to 0.98; P = 0.021); and in the 300-mg group, 0.86 (95% CI, 0.75 to 0.99; P = 0.031). The 150-mg dose, but not the other doses, met the prespecified multiplicity-adjusted threshold for statistical significance for the primary end point and the secondary end point that additionally included hospitalization for unstable angina that led to urgent revascularization (hazard ratio vs. placebo, 0.83; 95% CI, 0.73 to 0.95; P = 0.005). Canakinumab was associated with a higher incidence of fatal infection than was placebo. There was no significant difference in all-cause mortality (hazard ratio for all canakinumab doses vs. placebo, 0.94; 95% CI, 0.83 to 1.06; P = 0.31). Conclusions: Antiinflammatory therapy targeting the interleukin-1β innate immunity pathway with canakinumab at a dose of 150 mg every 3 months led to a significantly lower rate of recurrent cardiovascular events than placebo, independent of lipid-level lowering. (Funded by Novartis; CANTOS ClinicalTrials.gov number, NCT01327846.

Multi-level modeling of social factors and preterm delivery in Santiago de Chile

<p>Abstract</p> <p>Background</p> <p>Birth before the 37th week of gestation (preterm birth) is an important cause of infant and neonatal mortality, but has been little studied outside of wealthy nations. Chile is an urbanized Latin American nation classified as "middle-income" based on its annual income per capita of about $6000.</p> <p>Methods</p> <p>We studied the relations between maternal social status and neighborhood social status on risk of preterm delivery in this setting using multilevel regression analyses of vital statistics data linked to geocoded decennial census data. The analytic data set included 56,970 births from 2004 in the metropolitan region of Santiago, which constitutes about 70% of all births in the study area and about 25% of all births in Chile that year. Dimensionality of census data was reduced using principal components analysis, with regression scoring to create a single index of community socioeconomic advantage. This was modeled along with years of maternal education in order to predict preterm birth and preterm low birthweight.</p> <p>Results</p> <p>Births in Santiago displayed an advantaged pattern of preterm risk, with only 6.4% of births delivering before 37 weeks. Associations were observed between risk of outcomes and individual and neighborhood factors, but the magnitudes of these associations were much more modest than reported in North America.</p> <p>Conclusion</p> <p>While several potential explanations for this relatively flat social gradient might be considered, one possibility is that Chile's egalitarian approach to universal prenatal care may have reduced social inequalities in these reproductive outcomes.</p

Development and validation of a prognostic model for the early identification of COVID-19 patients at risk of developing common long COVID symptoms

Background: The coronavirus disease 2019 (COVID-19) pandemic demands reliable prognostic models for estimating the risk of long COVID. We developed and validated a prediction model to estimate the probability of known common long COVID symptoms at least 60 days after acute COVID-19. Methods: The prognostic model was built based on data from a multicentre prospective Swiss cohort study. Included were adult patients diagnosed with COVID-19 between February and December 2020 and treated as outpatients, at ward or intensive/intermediate care unit. Perceived long-term health impairments, including reduced exercise tolerance/reduced resilience, shortness of breath and/or tiredness (REST), were assessed after a follow-up time between 60 and 425 days. The data set was split into a derivation and a geographical validation cohort. Predictors were selected out of twelve candidate predictors based on three methods, namely the augmented backward elimination (ABE) method, the adaptive best-subset selection (ABESS) method and model-based recursive partitioning (MBRP) approach. Model performance was assessed with the scaled Brier score, concordance c statistic and calibration plot. The final prognostic model was determined based on best model performance. Results: In total, 2799 patients were included in the analysis, of which 1588 patients were in the derivation cohort and 1211 patients in the validation cohort. The REST prevalence was similar between the cohorts with 21.6% (n = 343) in the derivation cohort and 22.1% (n = 268) in the validation cohort. The same predictors were selected with the ABE and ABESS approach. The final prognostic model was based on the ABE and ABESS selected predictors. The corresponding scaled Brier score in the validation cohort was 18.74%, model discrimination was 0.78 (95% CI: 0.75 to 0.81), calibration slope was 0.92 (95% CI: 0.78 to 1.06) and calibration intercept was -0.06 (95% CI: -0.22 to 0.09). Conclusion: The proposed model was validated to identify COVID-19-infected patients at high risk for REST symptoms. Before implementing the prognostic model in daily clinical practice, the conduct of an impact study is recommended. Keywords: Clinical prediction model; Long COVID; Prognostic factors; Stratified medicin