64 research outputs found
Human genetic selection on the MTHFR 677C>T polymorphism
<p>Abstract</p> <p>Background</p> <p>The prevalence of genotypes of the 677C>T polymorphism for the MTHFR gene varies among humans. In previous studies, we found changes in the genotypic frequencies of this polymorphism in populations of different ages, suggesting that this could be caused by an increase in the intake of folate and multivitamins by women during the periconceptional period. The aim was to analyze changes in the allelic frequencies of this polymorphism in a Spanish population, including samples from spontaneous abortions (SA).</p> <p>Methods</p> <p>A total of 1305 subjects born in the 20th century were genotyped for the 677C>T polymorphism using allele specific real-time PCR with Taqman<sup>® </sup>probes. A section of our population (n = 276) born in 1980–1989 was compared with fetal samples (n = 344) from SA of unknown etiology from the same period.</p> <p>Results</p> <p>An increase in the frequency of the T allele (0.38 vs 0.47; p < 0.001) and of the TT genotype (0.14 vs 0.24; p < 0.001) in subjects born in the last quarter of the century was observed. In the 1980–1989 period, the results show that the frequency of the wild type genotype (CC) is about tenfold lower in the SA samples than in the controls (0.03 vs 0.33; p < 0.001) and that the frequency of the TT genotype increases in the controls (0.19 to 0.27) and in the SA samples (0.20 to 0.33 (p < 0.01)); r = 0.98.</p> <p>Conclusion</p> <p>Selection in favor of the T allele has been detected. This selection could be due to the increased fetal viability in early stages of embryonic development, as is deduced by the increase of mutants in both living and SA populations.</p
Multi-criteria ranking of corporate distress prediction models: empirical evaluation and methodological contributions
YesAlthough many modelling and prediction frameworks for corporate bankruptcy
and distress have been proposed, the relative performance evaluation of prediction models
is criticised due to the assessment exercise using a single measure of one criterion at
a time, which leads to reporting conflicting results. Mousavi et al. (Int Rev Financ Anal
42:64–75, 2015) proposed an orientation-free super-efficiency DEA-based framework to
overcome this methodological issue. However, within a super-efficiency DEA framework,
the reference benchmark changes from one prediction model evaluation to another, which
in some contexts might be viewed as “unfair” benchmarking. In this paper, we overcome
this issue by proposing a slacks-based context-dependent DEA (SBM-CDEA) framework
to evaluate competing distress prediction models. In addition, we propose a hybrid crossbenchmarking-
cross-efficiency framework as an alternative methodology for ranking DMUs
that are heterogeneous. Furthermore, using data on UK firms listed on London Stock
Exchange, we perform a comprehensive comparative analysis of the most popular corporate
distress prediction models; namely, statistical models, under both mono criterion and
multiple criteria frameworks considering several performance measures. Also, we propose
new statistical models using macroeconomic indicators as drivers of distress
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