O modelamento estatístico de misturas: experimento tutorial usando voltametria de redissolução anódica

This work illustrates the modeling procedure for a solvent mixture using the simplex- centroid approach. The selected experiment was the optimization of the peak current observed in the direct determination of nickel by anodic stripping voltammetry (ASV) in a solvent mixture composed of N,N-dimethylformamide, ethanol and water. The text is presented in a tutorial way, showing in detail the several steps which must be followed in such a process. Since not all possible mixtures lead to a measurable instrumental response, pseudocomponents had to be used to rescale the experimental design. This also allows to show how to apply this tool, usually troublesome for non-specialists in mixture modeling procedures.

Use Of Experimental Design To Optimize A Triple-potential Waveform To Develop A Method For The Determination Of Streptomycin And Dihydrostreptomycin In Pharmaceutical Veterinary Dosage Forms By Hplc-pad.

An HPLC-PAD method using a gold working electrode and a triple-potential waveform was developed for the simultaneous determination of streptomycin and dihydrostreptomycin in veterinary drugs. Glucose was used as the internal standard, and the triple-potential waveform was optimized using a factorial and a central composite design. The optimum potentials were as follows: amperometric detection, E1=-0.15V; cleaning potential, E2=+0.85V; and reactivation of the electrode surface, E3=-0.65V. For the separation of the aminoglycosides and the internal standard of glucose, a CarboPac™ PA1 anion exchange column was used together with a mobile phase consisting of a 0.070 mol L(-1) sodium hydroxide solution in the isocratic elution mode with a flow rate of 0.8 mL min(-1). The method was validated and applied to the determination of streptomycin and dihydrostreptomycin in veterinary formulations (injection, suspension and ointment) without any previous sample pretreatment, except for the ointments, for which a liquid-liquid extraction was required before HPLC-PAD analysis. The method showed adequate selectivity, with an accuracy of 98-107% and a precision of less than 3.9%.

Behaviour of oligodendrocytes and Schwann cells in an experimental model of toxic demyelination of the central nervous system

Oligodendrocytes and Schwann cells are engaged in myelin production, maintenance and repairing respectively in the central nervous system (CNS) and the peripheral nervous system (PNS). Whereas oligodendrocytes act only within the CNS, Schwann cells are able to invade the CNS in order to make new myelin sheaths around demyelinated axons. Both cells have some limitations in their activities, i.e. oligodendrocytes are post-mitotic cells and Schwann cells only get into the CNS in the absence of astrocytes. Ethidium bromide (EB) is a gliotoxic chemical that when injected locally within the CNS, induce demyelination. In the EB model of demyelination, glial cells are destroyed early after intoxication and Schwann cells are free to approach the naked central axons. In normal Wistar rats, regeneration of lost myelin sheaths can be achieved as early as thirteen days after intoxication; in Wistar rats immunosuppressed with cyclophosphamide the process is delayed and in rats administered cyclosporine it may be accelerated. Aiming the enlightening of those complex processes, all events concerning the myelinating cells in an experimental model are herein presented and discussed.

Experimental determination of benzene uptake rate in Tenax TA diffusive samplers

This paper proposes a methodology to predict benzene uptake rate in ambient air, using passive samplers with Tenax TA. Variations in the uptake rate were found to occur as a function of the sampling time; and were greater at the beginning of sampling. An empirical model was obtained and values for uptake rate agree with literature. Concentration prediction errors can be minimized by using sampling times of 4 to 14 days, thus avoiding the influence of excessive uptake rates in the initial days and the influence of back diffusion at the end of the sampling period.