Fluoxetine, an antidepressant that is used clinically in the treatment of mood disorders, is a selective serotonin reuptake inhibitor. In the present study we investigated the effects of fluoxetine on 4-aminopyridine (4AP)-evoked glutamate release in cerebrocortical nerve terminals (synaptosomes). Fluoxetine suppressed the release of glutamate evoked by 4AP in a concentration-dependent manner. This effect was associated with a reduction in the depolarization-evoked increase in cytosolic free calcium levels in the absence of significant effect on the synaptosomal membrane potential. In addition, both ionomycin- and sucrose-evoked glutamate releases were not affected by fluoxetine, indicating that fluoxetine-mediated inhibition of glutamate release is not a direct effect on the exocytotic machinery. Furthermore, the inhibitory action of fluoxetine was completely abolished in synaptosomes pretreated with P/Q type Ca(2+) channel blocker omega-agatoxin IVA (omega-AgTX IVA) or protein kinase C (PKC) stimulator 4beta-phorbol 12, 13-dibutyrate (PDBu). These results suggest that, in cerebrocortical nerve terminals, fluoxetine inhibits glutamate release through the suppression of P/Q type Ca(2+) channel activity. The presynaptic action of fluoxetine is mediated by a PKC-sensitive signaling pathway. Synapse 48:170-177, 2003.

In this paper the main wave height characteristics in the Mediterranean Sea are studied from both observational and numerical perspectives. The numerical wave model WAM is employed on a high spatial resolution mode and in two different versions, one of which incorporates information for sea surface currents. Altimeter data obtained from all available satellite missions over the area are also utilized. The data sets are analyzed both by conventional statistical measures as well as by advanced techniques provided by a relatively new branch of mathematics, information geometry, in the framework of which the data under study and the distributions that they form are treated as elements of non Euclidean spaces. In this framework, novel ideas for the estimation of the deviations between the observed and modeled values are proposed.

The analysis of remotely sensed altimeter data and in situ measurements shows that ERS 2 radar can monitor the ocean permanent thermocline from space. The remotely sensed sea level anomaly data account for ∼2/3 of the temperature variance or vertical displacement of isotherms at a depth of ∼550 m in the Subtropical North Atlantic Ocean near 32·5°N. This depth corresponds closely to the region of maximum temperature gradient in the permanent thermocline where near semi-annual internal vertical displacements reach 200 to 300 m. The gradient of the altimeter sea level anomaly data correlates well with measured ocean currents to a depth of 750 m. It is shown that observations from space can account for ∼3/4 of the variance of ocean currents measured in situ in the permanent thermocline over a 2-y period. The magnification of the permanent thermocline displacement with respect to the displacement of the sea surface was determined as −×650 and gives a measure of the ratio of barotropic to baroclinic decay scale of geostrophic current with depth. The overall results are used to interpret an eight year altimeter data time series in the Subtropical North Atlantic at 32·5°N which shows a dominant wave or eddy period near 200 days, rather than semi-annual and increases in energy propagating westward in 1995 (west of 25°W). The effects of rapid North Atlantic Oscillation climate change on ocean circulation are discussed. The altimeter data for the Atlantic were Fourier analysed. It is shown how the annual and semi-annual components relate to the seasonal maximum cholorophyll-a SeaWiFS signal in tropical and equatorial regions due to the lifting of the thermocline caused by seasonally varying ocean currents forced by wind stress.

The main characteristics of the significant wave height in an area of increased interest, the north Atlantic ocean, are studied based on satellite records and corresponding simulations obtained from the numerical wave prediction model WAM. The two data sets are analyzed by means of a variety of statistical measures mainly focusing on the distributions that they form. Moreover, new techniques for the estimation and minimization of the discrepancies between the observed and modeled values are proposed based on ideas and methodologies from a relatively new branch of mathematics, information geometry. The results obtained prove that the modeled values overestimate the corresponding observations through the whole study period. On the other hand, 2-parameter Weibull distributions fit well the data in the study. However, one cannot use the same probability density function for describing the whole study area since the corresponding scale and shape parameters deviate significantly for points belonging to different regions. This variation should be taken into account in optimization or assimilation procedures, which is possible by means of information geometry techniques.

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