From three simple macrophage exposure conditions (P.gingivalis, LPS and FimA) versus control sample, we propose an in vitro model to estimate the combined impact of P. gingivalis and/or its virulence factors (i.e. LPS and FimA) on innate immune response in human macrophages, with analysis at the systems level.
Since plasma PI3 and HNE showed some different correlations between the ARDS samples and the control samples, we proposed to combine two variables by calculating the ratio of HNE/PI3 and included it in the subsequent analyses.
Due to the fact that the current benchmark dataset contains sufficient number of negative samples and a small amount of positive samples, we proposed an improved AdaBoost called Unbalanced-AdaBoost to make the best of the negative samples.
To compromise the two regimes (RW's high-degree dominance vs. MHRW's stratified sampling), we propose an extension to the MHRW algorithm.
To maximize the chances of detecting the drug in serum samples, we propose the use of this specific ELISA test as a high-throughput screening method, combined with a classic isoelectric focusing test as a confirmatory assay.
In cluster randomized designs structured with balanced ranked set sampling, we propose a pooled pivotal test to improve the power of detecting any treatment effect by stabilizing the estimation of variance components when groups are unevenly sized.
According to multiple previous reports, a large amount of different lipid molecules, including cardiolipin, phosphotidylcholine, and phosphotidylethanolamine, should be present in the isolated samples, we propose these lipid molecules may occupy these gaps to further stabilize the respirasome (Gu et al., 2016).
In this respect, to characterize the analyze samples we propose a chemometric representation base on Principal Component Analysis which is compared to the ones based only on the relative amount of the two types of carbonate or on carbonate and collagen.
Furthermore, instead of using the random patches as the negative samples, we propose a reasonable selection criterion, in which both the saliency confidence and similarity are considered with the benefits that confusors in the surrounding background are incorporated into the classifiers update process before the drift occurs.
While it is possible that these species were simply missed, after four years of extensive sampling we propose that this is unlikely.
