7, the resulting VIP or qualitative peaks used for such group discrimination were not only “dairy” products
but to a lesser degree also “beans and shellfish”. These were obviously particular deviation characteristics of the limited cohort used here. The great advantage of producing a statistical model is to be able to predict and test outcomes. Using the mathematical model produced by PLS (Fig. 7) the non-milk allergic control patients for instance all have shown a period < 2 years to achieve tolerance, regardless of their actual age. Likewise, the age of milk tolerance predicted for the patients that had achieved milk tolerance is very close to the actual measured age in the cross validation. Ideally, the model should be validated and its prediction error quantified with an external new test set. Due to the difficulty of acquiring suitable datasets and bearing in mind the intrinsic Belinostat cost limitations imposed by a retrospective study as the one presented here, the process of cross validation (for one iteration: leave at random 20% of samples out, predict with the other 80%, repeat until each sample has been left out, repeat for 17 iterations) was used both to estimate the model complexity (7 latent variables) as well as to estimate the error to be expected for new data.
This is still far from ideal but it sets the background for future studies where larger numbers, frequent monitoring, planned and controlled interventions would generate clearer and more accurate mathematical trends. The profiling GW-572016 mw array technique used in this work has shown that IgG and IgA share the same specificity whilst IgM and in particular IgE are distantly related. The correlation between specificity of
IgE and IgA is variable amongst the patients and cannot be used to predict atopy or the onset of tolerance to milk. The profiling technique has corroborated the clinical selection criteria for this cohort albeit it clearly indicated that 4 out of the 41 patients might have allergies other than from milk origin. There was also a good correlation between the array data and ImmunoCAP results. By using multivariate analysis and a particular PLEK2 retrospective cohort of clinically well characterized CMA children collected from patients in multiple visits, it was possible to produce statistical models to predict the onset of the tolerance to milk. These results, still in early stages of development, are encouraging and reinforce the potential use of multivariate models for prognostic analyses of complex profiling data. This work was partially supported by a BBSRC follow-on grant BB/FOF/268. “
“Tumor necrosis factor-alpha (TNF-α) plays a pivotal role in the pathogenesis of inflammatory bowel disease (IBD), rheumatoid arthritis (RA), and other autoimmune disorders (Suryaprasad and Prindiville, 2003, Kopylov et al., 2011 and Sandborn et al., 2010).
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