426 research outputs found
Clustering South African households based on their asset status using latent variable models
The Agincourt Health and Demographic Surveillance System has since 2001
conducted a biannual household asset survey in order to quantify household
socio-economic status (SES) in a rural population living in northeast South
Africa. The survey contains binary, ordinal and nominal items. In the absence
of income or expenditure data, the SES landscape in the study population is
explored and described by clustering the households into homogeneous groups
based on their asset status. A model-based approach to clustering the Agincourt
households, based on latent variable models, is proposed. In the case of
modeling binary or ordinal items, item response theory models are employed. For
nominal survey items, a factor analysis model, similar in nature to a
multinomial probit model, is used. Both model types have an underlying latent
variable structure - this similarity is exploited and the models are combined
to produce a hybrid model capable of handling mixed data types. Further, a
mixture of the hybrid models is considered to provide clustering capabilities
within the context of mixed binary, ordinal and nominal response data. The
proposed model is termed a mixture of factor analyzers for mixed data (MFA-MD).
The MFA-MD model is applied to the survey data to cluster the Agincourt
households into homogeneous groups. The model is estimated within the Bayesian
paradigm, using a Markov chain Monte Carlo algorithm. Intuitive groupings
result, providing insight to the different socio-economic strata within the
Agincourt region.Comment: Published in at http://dx.doi.org/10.1214/14-AOAS726 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Catastrophizing mediates the relationship between the personal belief in a just world and pain outcomes among chronic pain support group attendees
Health-related research suggests the belief in a just world can act as a personal resource that protects against the adverse effects of pain and illness. However, currently, little is known about how this belief, particularly in relation to one’s own life, might influence pain. Consistent with the suggestions of previous research, the present study undertook a secondary data analysis to investigate pain catastrophizing as a mediator of the relationship between the personal just world belief and chronic pain outcomes in a sample of chronic pain support group attendees. Partially supporting the hypotheses, catastrophizing was negatively correlated with the personal just world belief and mediated the relationship between this belief and pain and disability, but not distress. Suggestions for future research and intervention development are made
The use of mid-infrared spectrometry to predict body energy status of Holstein cows
Energy balance, especially in early lactation, is known to be associated with subsequent health and fertility in dairy cows. However, its inclusion in routine management decisions or breeding programs is hindered by the lack of quick, easy, and inexpensive measures of energy balance. The objective of this study was to evaluate the potential of mid-infrared (MIR) analysis of milk, routinely available from all milk samples taken as part of large-scale milk recording and milk payment operations, to predict body energy status and related traits in lactating dairy cows. The body energy status traits investigated included energy balance and body energy content. The related traits of body condition score and energy intake were also considered. Measurements on these traits along with milk MIR spectral data were available on 17 different test days from 268 cows (418 lactations) and were used to develop the prediction equations using partial least squares regression. Predictions were externally validated on different independent subsets of the data and the results averaged. The average accuracy of predicting body energy status from MIR spectral data was as high as 75% when energy balance was measured across lactation. These predictions of body energy status were considerably more accurate than predictions obtained from the sometimes proposed fat-to-protein ratio in milk. It is not known whether the prediction generated from MIR data are a better reflection of the true (unknown) energy status than the actual energy status measures used in this study. However, results indicate that the approach described may be a viable method of predicting individual cow energy status for a large scale of application
Prediction of the individual enteric methane emission of dairy cows from milk mid-infrared spectra
peer reviewedThe livestock sector is considered the largest producer of methane (CH4) from anthropogenic sources, world wide contributing 37% of emissions (FAO, 2006). An important step to study and develop mitigation methods for livestock emissions is to be able to measure them on a large scale. However, it is difficult to obtain a large number of individual CH4 measurements with the currently available techniques (chambers or SF6). The aim of this study was to develop a high
throughput tool for determination of CH4 emissions from dairy cows. Anaerobic fermentation of food in the reticulorumen is the basis of enteric CH4 production. End-products of that enteric fermentation can be found in the milk (e.g., volatile fatty acids). Therefore individual enteric CH4 emissions could be quantified from whole milk mid-infrared (MIR) spectra which reflect milk composition and can be obtained at low cost (e.g., national milk recording). Prediction equations of
individual CH4 emissions (determined using the SF6 method) from milk MIR spectra have been established (Dehareng et al., 2012; Soyeurt et al., 2013). The results presented here are the improvement of this methodology by using a multiple breed and country approach
Crystal structure of monomeric human β-2- microglobulin reveals clues to its amyloidogenic properties
Dissociation of human β-2-microglobulin (β(2)m) from the heavy chain of the class I HLA complex is a critical first step in the formation of amyloid fibrils from this protein. As a consequence of renal failure, the concentration of circulating monomeric β(2)m increases, ultimately leading to deposition of the protein into
amyloid fibrils and development of the disorder, dialysis-related amyloidosis. Here we present the crystal structure of a monomeric form of human β(2)m determined at 1.8-Å resolution that reveals remarkable structural changes relative to the HLA-bound protein. These involve the restructuring of a β bulge that separates two
short β strands to form a new six-residue β strand at one edge of this β sandwich protein. These structural changes remove key features proposed to have evolved to protect β sheet proteins from aggregation [Richardson, J.&Richardson, D. (2002) Proc. Natl. Acad.
Sci. USA 99, 2754–2759] and replaces them with an aggregationcompetent surface. In combination with solution studies using (1)H NMR, we show that the crystal structure presented here represents a rare species in solution that could provide important clues about the mechanism of amyloid formation from the normally highly
soluble native protein
Application of InSAR to the Analysis of Ground Deformation in ChangYun Area of Taiwan
Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchive
Bacterial metabolites and cardiovascular risk in children with chronic kidney disease
Cardiovascular complications are the major cause of the marked morbidity and mortality associated with chronic kidney disease (CKD). The classical cardiovascular risk factors such as diabetes and hypertension undoubtedly play a role in the development of cardiovascular disease (CVD) in adult CKD patients; however, CVD is just as prominent in children with CKD who do not have these risk factors. Hence, the CKD-specific pathophysiology of CVD remains incompletely understood. In light of this, studying children with CKD presents a unique opportunity to analyze CKD-associated mechanisms of CVD more specifically and could help to unveil novel therapeutic targets.Here, we comprehensively review the interaction of the human gut microbiome and the microbial metabolism of nutrients with host immunity and cardiovascular end-organ damage. The human gut microbiome is evolutionary conditioned and modified throughout life by endogenous factors as well as environmental factors. Chronic diseases, such as CKD, cause significant disruption to the composition and function of the gut microbiome and lead to disease-associated dysbiosis. This dysbiosis and the accompanying loss of biochemical homeostasis in the epithelial cells of the colon can be the result of poor diet (e.g., low-fiber intake), medications, and underlying disease. As a result of dysbiosis, bacteria promoting proteolytic fermentation increase and those for saccharolytic fermentation decrease and the integrity of the gut barrier is perturbed (leaky gut). These changes disrupt local metabolite homeostasis in the gut and decrease productions of the beneficial short-chain fatty acids (SCFAs). Moreover, the enhanced proteolytic fermentation generates unhealthy levels of microbially derived toxic metabolites, which further accumulate in the systemic circulation as a consequence of impaired kidney function. We describe possible mechanisms involved in the increased systemic inflammation in CKD that is associated with the combined effect of SCFA deficiency and accumulation of uremic toxins. In the future, a more comprehensive and mechanistic understanding of the gut-kidney-heart interaction, mediated largely by immune dysregulation and inflammation, might allow us to target the gut microbiome more specifically in order to attenuate CKD-associated comorbidities
Radial Flow in Au+Au Collisions at E=0.25-1.15 A GeV
A systematic study of energy spectra for light particles emitted at
midrapidity from Au+Au collisions at E=0.25-1.15 A GeV reveals a significant
non-thermal component consistent with a collective radial flow. This component
is evaluated as a function of bombarding energy and event centrality.
Comparisons to Quantum Molecular Dynamics (QMD) and Boltzmann-Uehling-Uhlenbeck
(BUU) models are made for different equations of state.Comment: 10 pages of text and 4 figures (all ps files in a uuencoded package)
The energy dependence of flow in Ni induced collisions from 400 to 1970A MeV
We study the energy dependence of collective (hydrodynamic-like) nuclear
matter flow in 400-1970 A MeV Ni+Au and 1000-1970 A MeV Ni+Cu reactions. The
flow increases with energy, reaches a maximum, and then gradually decreases at
higher energies. A way of comparing the energy dependence of flow values for
different projectile-target mass combinations is introduced, which demonstrates
a common scaling behaviour among flow values from different systems.Comment: 12 pages, 3 figures. Submitted to Physical Review Letter
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