Use of Two-Part Regression Calibration Model to Correct for Measurement Error in Episodically Consumed Foods in a Single-Replicate Study Design: EPIC Case Study.

In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model.

An in vitro iron superoxide dismutase inhibitor decreases the parasitemia levels of Trypanosoma cruzi in BALB/c mouse model during acute phase.

In order to identify new compounds to treat Chagas disease during the acute phase with higher activity and lower toxicity than the reference drug benznidazole (Bz), two hydroxyphthalazine derivative compounds were prepared and their trypanocidal effects against Trypanosoma cruzi were evaluated by light microscopy through the determination of IC50 values. Cytotoxicity was determined by flow cytometry assays against Vero cells. In vivo assays were performed in BALB/c mice, in which the parasitemia levels were quantified by fresh blood examination; the assignment of a cure was determined by reactivation of blood parasitemia levels after immunosuppression. The mechanism of action was elucidated at metabolic and ultra-structural levels, by (1)H NMR and TEM studies. Finally, as these compounds are potentially capable of causing oxidative damage in the parasites, the study was completed, by assessing their activity as potential iron superoxide dismutase (Fe-SOD) inhibitors. High-selectivity indices observed in vitro were the basis of promoting one of the tested compounds to in vivo assays. The tests on the murine model for the acute phase of Chagas disease showed better parasitemia inhibition values than those found for Bz. Compound 2 induced a remarkable decrease in the reactivation of parasitemia after immunosuppression. Compound 2 turned out to be a great inhibitor of Fe-SOD. The high antiparasitic activity and low toxicity together with the modest costs for the starting materials render this compound an appropriate molecule for the development of an affordable anti-Chagas agent.