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We conducted a cross-sectional analysis of the associations between traffic-related pollution and a set of five immune assays using data from the baseline visit of an intervention trial of exercise conducted at the Fred Hutchinson Cancer Research Center FHCRCC) (McTiernan et al. 1999).
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We describe the associations of estradiol, estrone and testosterone with both body mass index and breast cancer risk in postmenopausal women according to assay method, using data from a collaborative pooled analysis of 18 prospective studies.
Because the vast ribozyme excess did not emulate conditions expected for interpretive scenarios, these data were primarily used to establish the best time point to assay the ribozymes for interpretive behaviour using data from the previous section (see Results), and only secondarily to assess interpretive behaviour.
It appears that using data from a diverse set of assays and employing a prediction network to select assays for inclusion in the combined model is a powerful approach.
Results are described from an analysis using data from MLP assays via the BioAssay Research Database (BARD) http://bard.nih.gov.nih.gov
Using data from c-AMP assays in combination with structural analysis of melanocortin receptor/ligand models, we conclude that a lysine residue at the C-terminus of the His-Phe-Arg-Trp core sequence of melanocortin hormone is an important determinant for receptor selectivity in the both cyclic and linear MSH analogues.
Moreover, to decrease technical specific biases, we have used data from chromatin immunoprecipitation assay (ChIP) of RNA pol II inside the genes with specific antibodies (RNA Pol-ChIP-on-chip, RPCC) to detect and correct technical biases specifically associated to the GRO data and not present in the RPCC data.
This article uses data from mosquito feeding assays conducted in Burkina Faso (Ouédraogo et al., 2009, Dryad: Ouédraogo et al., 2013) and Kenya (Schneider et al., 2007, Dryad: Schneider et al., 2013) to estimate the shape of the relationship between gametocyte density and mosquito infection (processed data available at Dryad, Churcher et al., 2013).
It also uses data from the Bureau of Labor Statistics.
We used data from GasBuddy.com.com
We used data from four programs.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com