Kraruppayne4817

Increases in leaf mass per area (LMA) are commonly observed in response to environmental stresses and are achieved through increases in leaf thickness and/or leaf density. Here, we investigated how the two underlying components of LMA differ in relation to species native climates and phylogeny, across deciduous and evergreen species. Using a phylogenetic approach, we quantified anatomical, compositional and climatic variables from 40 deciduous and 45 evergreen Quercus species from across the Northern Hemisphere growing in a common garden. Deciduous species from shorter growing seasons tended to have leaves with lower LMA and leaf thickness than those from longer growing seasons, while the opposite pattern was found for evergreens. For both habits, LMA and thickness increased in arid environments. However, this shift was associated with increased leaf density in evergreens but reduced density in deciduous species. Deciduous and evergreen oaks showed fundamental leaf morphological differences that revealed a diverse adaptive response. While LMA in deciduous species may have diversified in tight coordination with thickness mainly modulated by aridity, diversification of LMA within evergreens appears to be dependent on the infrageneric group, with diversification in leaf thickness modulated by both aridity and cold, while diversification in leaf density is only modulated by aridity.

Medical note de-identification is critical for the protection of private information and the security of data sharing in collaborative research. The task demands the complete removal of all patient names and other sensitive information such as addresses and phone numbers from medical records. Accomplishing this goal is challenging, with many variations in the medical note formats and string representations. Existing de-identification approaches include pattern matching where extensive dictionary lists are constructed a prior; and entity tagging, which trains on a large word-wise annotated corpus. This motivates us to study an alternative to the existing approaches with a reduced annotation burden.

In this work, we propose a novel approach that implicitly accounts for the language territory of sensitive information. Specifically, our approach incorporates a contextualized word embedding module and a multilayer perceptron to simultaneously infer the similarity of sensitive and non-sensitive vocabularies to ative and quantitative analysis shows that our method achieved better results than the pretrained 3-class Stanford NER toolbox.

To find out whether the diagnostic yield of prenatal array comparative genomic hybridization (aCGH) can be improved by targeting preselected high-risk pregnancies.

All the in-house arrays ordered by the Fetomaternal Medical Center from February 2016 until December 2018 were retrospectively analyzed. The indications for array analysis included fetal structural abnormalities, increased nuchal translucency ≥3.5mm and a chromosomal abnormality in a parent or a sibling. Common aneuploidies were excluded.

Diagnostic yield was 15.1% in the entire patient cohort and as high as 20% in fetuses with multiple structural anomalies. The diagnostic yield was lowest in the group with isolated growth retardation. A total of 76 copy number variants (CNVs) were reported from a total of 65 samples, including 16 CNVs associated with a well-described microdeletion/microduplication syndrome, six autosomal trisomies in mosaic form, and three pathogenic single-gene deletions with dominant inheritance and 12 CNVs known to be risk factors for eg developmental delay.

The diagnostic yield of aCGH was higher than what has previously been reported in less defined patient cohorts. However, the number of CNVs with unclear correlation to the fetal ultrasound findings was still relatively high. The importance of adequate pre- and posttest counseling must therefore be emphasized.

The diagnostic yield of aCGH was higher than what has previously been reported in less defined patient cohorts. However, the number of CNVs with unclear correlation to the fetal ultrasound findings was still relatively high. The importance of adequate pre- and posttest counseling must therefore be emphasized.Brown adipose tissue (BAT) is an endocrine organ that contributes to thermogenesis and energy consumption. We investigated the effects of salt loading and surgical removal of whitened interscapular BAT (iBAT) on cardiac and adipose tissue pathology in DahlS.Z-Leprfa /Leprfa (DS/obese) rats, an animal model of metabolic syndrome (MetS). DS/obese rats were subjected to surgical removal of iBAT or sham surgery at 8 weeks of age and were provided with drinking water containing or not containing 0.3% NaCl for 4 weeks beginning at 9 weeks of age. Removal of iBAT suppressed the salt-induced exacerbation of left ventricular inflammation, fibrosis, and diastolic dysfunction, but not that of hypertension development, in DS/obese rats. Salt loading attenuated adipocyte hypertrophy but enhanced inflammation in both visceral white adipose tissue (WAT) and iBAT. Although iBAT removal did not affect visceral WAT pathology in salt-loaded DS/obese rats, it attenuated the elevation of circulating interleukin-6 levels in these animals. Downregulation of uncoupling protein-1 expression in iBAT of DS/obese rats was not affected by salt loading. Our results suggest that the conversion of iBAT to WAT-like tissue contributes to a salt-induced elevation of circulating proinflammatory cytokine levels that leads to exacerbation of cardiac pathology in this model of MetS.Brewing is the final and key step in the production of the coffee beverage. Extraction related metrics such as the total dissolved solids (TDS), percentage extraction yield (PE) of solutes, and brew temperature (BT) are widely believed to govern the flavor and corresponding consumer acceptance of the resulting brew, as summarized in the industry standard "Coffee Brewing Control Chart." In this study, we investigated how the three factors of TDS, PE, and BT affected consumer acceptance of a medium roast, single-origin coffee and whether consumer preference segmentation would be observed based on these variables. A cohort of 118 mostly college-age, self-reported consumers of black coffee tasted coffees that varied in BT, TDS, and PE. For each coffee, consumers rated overall acceptance on the 9-point hedonic scale; the adequacy of serving temperature, flavor intensity, acidity, and mouthfeel using 5-point just-about-right (JAR) scales; and described the flavor using a check-all-that-apply list of 17 attributes. Cluster analysis revealed two consumer segments whose preferences varied most strongly with TDS. Response surface methodology relating liking to TDS and PE produced dome- and saddle-shaped surfaces for the two segments, respectively. External preference mapping and penalty analysis indicated that overall flavor intensity as well as acidity heavily influenced the preferences of the two clusters. The Coffee Brewing Control Chart's "ideal" coffee should therefore be reconsidered to reflect consumer preference segmentation. PRACTICAL APPLICATION This research informs the way coffee brewers manipulate brew strength and extraction of drip brew coffee for optimal consumer acceptance; and justifies a reform of the standard "Coffee Brewing Control Chart" in its representation of an "ideal" coffee as we uncovered two consumer preference segments with different positive and negative sensory drivers of liking.Multivariate spatial data, where multiple responses are simultaneously recorded across spatially indexed observational units, are routinely collected in a wide variety of disciplines. For example, the Southern Ocean Continuous Plankton Recorder survey collects records of zooplankton communities in the Indian sector of the Southern Ocean, with the aim of identifying and quantifying spatial patterns in biodiversity in response to environmental change. One increasingly popular method for modeling such data is spatial generalized linear latent variable models (GLLVMs), where the correlation across sites is captured by a spatial covariance function in the latent variables. However, little is known about the impact of misspecifying the latent variable correlation structure on inference of various parameters in such models. To address this gap in the literature, we investigate how misspecifying and assuming independence for the latent variables' correlation structure impacts estimation and inference in spatial GLLVMs. Through both theory and numerical studies, we show that performance of maximum likelihood estimation and inference on regression coefficients under misspecification depends on a combination of the response type, the magnitude of true regression coefficient, and the corresponding loadings, and, most importantly, whether the corresponding covariate is (also) spatially correlated. On the other hand, estimation and inference of truly nonzero loadings and prediction of latent variables is consistently not robust to misspecification of the latent variable correlation structure.Parental care, such as nest or offspring defence, is crucial for offspring survival in many species. Yet, despite its obvious fitness benefits, the level of defence can consistently vary between individuals of the same species. One prominent adaptive explanation for consistent individual differences in behaviours involves state dependency relatively stable differences in individual state should lead to the emergence of repeatable behavioural variation whereas changes in state should lead to a readjustment of behaviour. Therefore, empirical testing of adaptive state dependence requires longitudinal data where behaviour and state of individuals of the same population are repeatedly measured. Here, we test if variation in states predicts nest defence behaviour (a 'risky' behaviour) in a long-lived species, the barnacle goose Branta leucopsis. Adaptive models have predicted that an individual's residual reproductive value or 'asset' is an important state variable underlying variation in risk-taking behaviour. Hence, we investigate how nest defence varies as a function of time of the season and individual age, two state variables that can vary between and within individuals and determine asset. Repeated measures of nest defence towards a human intruder (flight initiation distance or FID) of females of known age were collected during 15 breeding seasons. Increasing values of FID represent increasing shyness. Ganetespib in vitro We found that females strongly and consistently differed in FID within- and between-years. As predicted by theory, females adjusted their behaviour to state by decreasing their FID with season and age. Decomposing these population patterns into within- and between-individual effects showed that the state-dependent change in FID was driven by individual plasticity in FID and that bolder females were more plastic than shyer females. This study shows that nest defence behaviour differs consistently among individuals and is adjusted to individual state in a direction predicted by adaptive personality theory.This study investigates whether facets of rumination statistically mediate the relationships between Big Five personality traits and depressive symptoms. Self-reported personality traits and rumination were investigated as predictors of depressive symptoms in a cross-sectional sample of 3043 participants aged 18-60 years (68.8% female). Multiple regression analysis investigated which personality traits and rumination facets best explained variance in depressive symptoms. Structural equation modelling was used to determine whether facets of rumination mediated the relationships between personality traits and depressive symptoms. Multiple regression analysis found that variance in depressive symptoms was best explained by the personality traits neuroticism, extroversion, conscientiousness; and both facets of rumination, brooding and reflection. Structural equation modelling added that the effects of neuroticism, extroversion, conscientiousness and openness on depressive symptoms were statistically mediated by brooding; the effects of neuroticism, extroversion and openness to depressive symptoms were statistically mediated by reflection.