Sentence examples for hypothesis of excess from inspiring English sources
However, the novel finding of an unexpectedly opposite interaction between smoking and BMI, which had been examined in order to confirm the hypothesis of excess oxidative stress being responsible for the smoking × alcohol interaction, highlights the surprisingly limited understanding of the underlying pathophysiological relationships.
Accumulating body of evidence supports the hypothesis of excess iron as a risk factor for glucose metabolism disorders such as gestational diabetes.
The authors noted that the directions of the two effects are almost universal (with some exceptions), resulting in G and T excess in the leading strands, which was compatible with the hypothesis of excess of cytosine deamination in the single-stranded state during DNA replication [ 11].
The genealogical index of familiality (GIF) is a well-published method to test hypotheses of excess relatedness within sets of individuals selected from the UPDB [ 22, 23].
Conversely, the other alternative hypothesis of heterozygote excess provided no significant outcomes.
The overall GIF statistic, utilizing all pairwise relationships between all cases, allows a test of the alternative hypothesis of no excess clustering over that expected in the Utah population.
Jonkam and colleagues therefore tested the hypothesis of whether excess NO and/or reactive oxygen species production is also responsible for the lung injury induced by MRSA pneumonia [ 83].
The distribution of average relatedness from the 1,000 matched controls sets represents the expected relatedness in the UPDB population and can be compared with the case GIF for an empirical test of the hypothesis of no excess relatedness in the set of cases of interest.
In accordance with this hypothesis, the injection of excess CD4 T cells from NOD mice into pre-diabetic NOD littermates prevented the development of diabetes in the recipients.
We would reject the null hypothesis in favor of excess significant findings if, where P= E/ N is the average probability that a specific trial across the network will find a "positive" result.
Consequently, we would reject the null hypothesis in favor of excess significant findings if, where p= E/ n is the average probability that a specific trial will find a "positive" result and is the binomial distribution function.
