Neuroprotective properties of levosimendan in an in vitro model of traumatic brain injury

<p>Abstract</p> <p>Background</p> <p>We investigated the neuroprotective properties of levosimendan, a novel inodilator, in an in vitro model of traumatic brain injury.</p> <p>Methods</p> <p>Organotypic hippocampal brain slices from mouse pups were subjected to a focal mechanical trauma. Slices were treated after the injury with three different concentrations of levosimendan (0.001, 0.01 and 0.1 μM) and compared to vehicle-treated slices. After 72 hrs, the trauma was quantified using propidium iodide to mark the injured cells.</p> <p>Results</p> <p>A significant dose-dependent reduction of both total and secondary tissue injury was observed in cells treated with either 0.01 or 0.1 μM levosimendan compared to vehicle-treated slices.</p> <p><b>Conclusion</b></p> <p>Levosimendan represents a promising new pharmacological tool for neuroprotection after brain injury and warrants further investigation in an in vivo model.</p

More space, better mathematics : is space a powerful tool or a cornerstone for understanding arithmetic?

Tight cognitive links between space and number processing exist. Usually, Spatial-Numerical Associations (SNAs) are interpreted causally: spatial capabilities are a cornerstone of math skill. We question this seemingly ubiquitous assumption. After presenting SNA taxonomy, we show that only some SNAs correlate with math skill. These correlations are not conclusive: (1) Their directions vary (stronger SNA relates sometimes to better, sometimes to poorer skill), (2) the correlations might be explained by mediator variables (e.g., SNA tasks involve cognitive control or reasoning), (3) the hypothetical course of causality is not resolved: For instance, contrary to conventional theories, arithmetic skills can underlie performance in some SNA tasks. However, benefits of SNA trainings on math skills seem to reinforce the claim of primary SNA role. Nevertheless, tasks used in such trainings may tap cognitive operations required in arithmetic, but not SNA representations themselves. Therefore, using space is a powerful tool rather than a cornerstone for math