Two-nested peptides from A1AT (andT1796 A1AT19451945), and peptides COL1A1-1580, and FGB1794 differentiated ND/SAF from all other inflammatory classes (KD/FI/AF) and non-inflammatory classes (QOM/RD/HC), with P values <0.05 or ~0.05.
Of the remaining 13 peptides, COL1A1-11734, COL9A2-1126, FGB1631 and UMOD1755 differentiated ND/SAF from all other inflammatory classes (KD/FI/AF); the other nine peptides did not show an obvious pattern.
The success of compounds under development in this and other anti-inflammatory classes, however, depends as much on the evolution of clinical studies designed to test the "proof of concept" in efficacy through the examination of surrogate markers or physiologic readouts of changes in lung function.
The popular non-steroidal anti-inflammatory class of therapeutics (NSAIDs), which block cyclo-oxygenase (COX), provide symptomatic relief but do not abrogate the underlying disease process [ 3].
Metal and inflammatory compound classes clustered together to form a separate group from other classes.
Most of the compounds in the metals and inflammatory mediators classes, in contrast, down-regulated the 104 transcripts with the exception of zinc.
Interestingly, 104 transcripts were strongly and specifically down-regulated by the metal and inflammatory compound classes, but were up-regulated by anti-microbials, cancer related drugs, pesticides, PXR mediators, and some halogenated contaminants.
Likewise, nonsteroidal anti-inflammatory drugs are not known to lower WBC counts, thus further distinguishing these anti-inflammatory drug classes and potential mechanisms.
The inflammatory mediator class contained compounds such as aspirin, ibuprofen, IL-3, LPS, TNFα, have inflammation regulation function.
She says it was soon found that members of other drug families including the antilipidemic, antidiabetic, antidepressant, beta-blocker, and nonsteroidal anti-inflammatory drug classes also showed potential to induce mitochondrial side effects.
In a decision tree, each node represents an attribute — in our case, the probeset — and the terminal nodes (the 'leaves') represent the attribute producing the best separation between the classes –("inflammatory" and "not inflammatory" in this analysis) of a dataset.
