4,874 research outputs found
Arm length effect on synthetic chemistry of fullerene-connected urethane-ether star-polymers
No full textSelf-assembly of N, N, N(4-pyridyl)trimesic amide and N, N, N"-tris(3-pyridyl)trimesic amide with Ag-l or Cd-ll ions"
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Mitochondrial Na+ overload is caused by oxidative stress and leads to activation of the caspase 3-dependent apoptotic machinery
No full textUTILIZATION OF POLYHYDROXYLATED C-60 AS A MOLECULAR CORE FOR THE SYNTHESIS OF STAR-SHAPED POLYMERS
No full textYeast metabolism in fresh and frozen dough : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Food Technology at Massey University, Palmerston North, New Zealand
Full text linkAuthor also known as SM LovedayFresh bakery products have a very short shelf life, which limits the extent to which manufacturing can be centralised. Frozen doughs are relatively stable and can be manufactured in large volumes, distributed and baked on-demand at the point of sale or consumption. With appropriate formulation and processing a shelf life of several months can be achieved.Shelf life is limited by a decline in proofing rate after thawing, which is attributed to a) the dough losing its ability to retain gas and b) insufficient gas production, i.e. yeast activity. The loss of shelf life is accelerated by delays between mixing and freezing, which allow yeast cells the chance to ferment carbohydrates.This work examined the reasons for insufficient gas production after thawing frozen dough and the effect of pre-freezing fermentation on shelf life. Literature data on yeast metabolite dynamics in fermenting dough were incomplete. In particular there were few data on the accumulation of ethanol, a major fermentation end product which can be injurious to yeast.Doughs were prepared in a domestic breadmaker using compressed yeast from a local manufacturer and analysed for glucose, fructose, sucrose, maltose and ethanol. Gas production after thawing declined within 48 hours of frozen storage. This was accelerated by 30 or 90 minutes of fermentation at 30;C prior to freezing.Sucrose was rapidly hydrolysed and yeast consumed glucose in preference to fructose. Maltose was not consumed while other sugars remained. Ethanol, accumulated from consumption of glucose and fructose, was produced in approximately equal amounts to CO2, indicating that yeast cells metabolised reductively.Glucose uptake in fermenting dough followed simple hyperbolic kinetics and fructose uptake was competitively inhibited by glucose. Mathematical modelling indicated that diffusion of sugars and ethanol in dough occurred quickly enough to eliminate solute gradients brought about by yeast metabolism
A novel right-angled ligand that forms polymeric metal-organic frameworks with nanometer-sized square cavities
No full textHip fracture risk assessment: Artificial neural network outperforms conditional logistic regression in an age- and sex-matched case control study
Full text linkCopyright @ 2013 Tseng et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly cited.Background - Osteoporotic hip fractures with a significant morbidity and excess mortality among the elderly have imposed huge health and economic burdens on societies worldwide. In this age- and sex-matched case control study, we examined the risk factors of hip fractures and assessed the fracture risk by conditional logistic regression (CLR) and ensemble artificial neural network (ANN). The performances of these two classifiers were compared.
Methods - The study population consisted of 217 pairs (149 women and 68 men) of fractures and controls with an age older than 60 years. All the participants were interviewed with the same standardized questionnaire including questions on 66 risk factors in 12 categories. Univariate CLR analysis was initially conducted to examine the unadjusted odds ratio of all potential risk factors. The significant risk factors were then tested by multivariate analyses. For fracture risk assessment, the participants were randomly divided into modeling and testing datasets for 10-fold cross validation analyses. The predicting models built by CLR and ANN in modeling datasets were applied to testing datasets for generalization study. The performances, including discrimination and calibration, were compared with non-parametric Wilcoxon tests.
Results - In univariate CLR analyses, 16 variables achieved significant level, and six of them remained significant in multivariate analyses, including low T score, low BMI, low MMSE score, milk intake, walking difficulty, and significant fall at home. For discrimination, ANN outperformed CLR in both 16- and 6-variable analyses in modeling and testing datasets (p?<?0.005). For calibration, ANN outperformed CLR only in 16-variable analyses in modeling and testing datasets (p?=?0.013 and 0.047, respectively).
Conclusions - The risk factors of hip fracture are more personal than environmental. With adequate model construction, ANN may outperform CLR in both discrimination and calibration. ANN seems to have not been developed to its full potential and efforts should be made to improve its performance.National Health Research Institutes in Taiwa
Increased expression of the natural killer cell inhibitory receptor CD94/NKG2A and CD158b on circulating and lesional T cells in patients with chronic plaque psoriasis.
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