Absence-like seizures in adult rats following pilocarpine-induced status epilepticus early in life

Administration of pilocarpine causes epilepsy in rats if status epilepticus (SE) is induced at an early age. To determine in detail the electrophysiological patterns of the epileptogenic activity in these animals, 46 Wistar rats, 7-17 days old, were subjected to SE induced by pilocarpine and electro-oscillograms from the cortex, hippocampus, amygdala, thalamus and hypothalamus, as well as head, rostrum and vibrissa, eye, ear and forelimb movements, were recorded 120 days later. Six control animals of the same age range did not show any signs of epilepsy. In all the rats subjected to SE, iterative spike-wave complexes (8.1 ± 0.5 Hz in frequency, 18.9 ± 9.1 s in duration) were recorded from the frontal cortex during absence fits. However, similar spike-wave discharges were always found also in the hippocampus and, less frequently, in the amygdala and in thalamic nuclei. Repetitive or single spikes were also detected in these same central structures. Clonic movements and single jerks were recorded from all the rats, either concomitantly with or independently of the spike-wave complexes and spikes. We conclude that rats made epileptic with pilocarpine develop absence seizures also occurring during paradoxical sleep, showing the characteristic spike-wave bursts in neocortical areas and also in the hippocampus. This is in contrast to the well-accepted statement that one of the main characteristics of absence-like fits in the rat is that spike-wave discharges are never recorded from the hippocampal fields.

Early detection of metabolic and energy disorders by thermal time series stochastic complexity analysis

Maintenance of thermal homeostasis in rats fed a high-fat diet (HFD) is associated with changes in their thermal balance. The thermodynamic relationship between heat dissipation and energy storage is altered by the ingestion of high-energy diet content. Observation of thermal registers of core temperature behavior, in humans and rodents, permits identification of some characteristics of time series, such as autoreference and stationarity that fit adequately to a stochastic analysis. To identify this change, we used, for the first time, a stochastic autoregressive model, the concepts of which match those associated with physiological systems involved and applied in male HFD rats compared with their appropriate standard food intake age-matched male controls (n=7 per group). By analyzing a recorded temperature time series, we were able to identify when thermal homeostasis would be affected by a new diet. The autoregressive time series model (AR model) was used to predict the occurrence of thermal homeostasis, and this model proved to be very effective in distinguishing such a physiological disorder. Thus, we infer from the results of our study that maximum entropy distribution as a means for stochastic characterization of temperature time series registers may be established as an important and early tool to aid in the diagnosis and prevention of metabolic diseases due to their ability to detect small variations in thermal profile.