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“In the present work an oral solution containing 0.01% alprazolam was developed. Test of effectiveness of antimicrobial preservative and microbial count at the beginning and at the end of the study were carried out. The toxicological study of the medicine was also made, thus guaranteeing its harmlessness and security after its use by oral route. By means of a rheological study made with a rotoviscosimeter, the

solution was characterized as a body with Newtonian flow and with a viscosity of 9.82 +/- 1.4 mPa.s. to 30.0 +/- 0.1 degrees C. Three batches of the medicine were elaborated and the physical-chemistry check details stability was studied, packaged in 120 ml amber glass bottles, SCH727965 stored to room temperature, and the organoleptic characteristics, pH, identification and quantification of the active principle, as well as the presence of degradation products were evaluated. All the results obtained complied with the limits of quality established in the official literature for this type of pharmaceutical form, so we arrive to the conclusion that the medicine developed was correctly formulated from a galenic point of view with a useful life time of 24 months stored under the conditions studied.”
“Background: Structural equation

models (SEMs) provide a general framework for analyzing mediated longitudinal data. However when interest is in the total effect (i.e. direct plus indirect) of a predictor on the binary outcome, alternative statistical techniques such as non-linear mixed models (NLMM) may be preferable, particularly if specific causal pathways are not hypothesized or specialized SEM software is not readily available. The purpose of this paper is to evaluate the performance of the NLMM in a setting where the SEM is presumed optimal.

Methods: We performed a simulation study to assess the performance of NLMMs relative LOXO-101 chemical structure to SEMs with respect to bias, coverage probability, and power in the analysis of mediated binary longitudinal outcomes. Both logistic and probit models were evaluated. Models were also applied to data from a longitudinal study assessing the impact of alcohol

consumption on HIV disease progression.

Results: For the logistic model, the NLMM adequately estimated the total effect of a repeated predictor on the repeated binary outcome and were similar to the SEM across a variety of scenarios evaluating sample size, effect size, and distributions of direct vs. indirect effects. For the probit model, the NLMM adequately estimated the total effect of the repeated predictor, however, the probit SEM overestimated effects.

Conclusions: Both logistic and probit NLMMs performed well relative to corresponding SEMs with respect to bias, coverage probability and power. In addition, in the probit setting, the NLMM may produce better estimates of the total effect than the probit SEM, which appeared to overestimate effects.