Dopamine depletion in wistar rats with epilepsy.

The dopamine content in cerebral structures has been related to neuronal excitability and several approaches have been used to study this phenomenon during seizure vulnerability period. In the present work, we describe the effects of dopamine depletion after the administration of 6-hidroxidopamine (6-OHDA) into the substantia nigra pars compacta of male rats submitted to the pilocarpine model of epilepsy. Susceptibility to pilocarpine-induced status epilepticus (SE), as well as spontaneous and recurrent seizures (SRSs) frequency during the chronic period of the model were determined. Since the hippocampus is one of main structures in the development of this experimental model of epilepsy, the dopamine levels in this region were also determined after drug administration. In the first experiment, 62% (15/24) of 6-OHDA pre-treated rats and 45% (11/24) of those receiving ascorbic acid as control solution progressed to motor limbic seizures evolving to SE, after the administration of pilocarpine. Severeness of seizures during the model´s the acute period, was significantly higher in epileptic experimental rats (56.52%), than in controls (4.16%). In the second experiment, the frequency of seizures in the model's chronic phase did not significantly change between groups. Our data show that dopamine may play an important role on seizure severity in the pilo's model acute period, which seems to be due to dopamine inhibitory action on motor expression of seizure.

Hepatitis C virus infection diagnosis using metabonomics.

Metabonomics based on nuclear magnetic resonance (NMR) can reveal the profile of endogenous metabolites of low molecular weight in biofluids related to disease. The profile is identified a 'metabolic fingerprint' like from the pathological process, why this metabonomics has been used as a diagnostic method. The aim of the present study was to apply metabonomics to identify patients infected with the hepatitis C virus (HCV) through an analysis of ¹H NMR spectra of urine samples associated with multivariate statistical methods. A pilot study was carried out for the diagnostic test evaluation, involving two groups: (i) 34 patients positive for anti-HCV and HCV-RNA and negative for anti-HBc (disease group); and (ii) 32 individuals positive for anti-HBc and negative for HBsAg and anti-HCV. The urine samples were analyzed through ¹H NMR, applying principal component analysis and discriminant analysis for classification. The metabonomics model was capable of identifying 32 of the 34 patients in the disease group as positive and 31 of the 32 individuals in the control group as negative, demonstrating 94% sensitivity and specificity of 97% as well as positive and negative predictive values of 97% and 94%, respectively, and 95% accuracy (P < 0.001). In conclusion, the metabonomics model based on ¹H NMR spectra of urine samples in this preliminary study discriminated patients with HCV infection with high sensitivity and specificity, thereby demonstrating this model to be a potential tool for use in medical practice in the near future.