Determination of fungal activity in modified wood by means of micro-calorimetry and determination of total esterase activity

Beech and pine wood blocks were treated with 1,3-dimethylol-4,5-dihydroxyethylen urea (DMDHEU) to increasing weight percent gains (WPG). The resistance of the treated specimens against Trametes versicolor and Coniophora puteana, determined as mass loss, increased with increasing WPG of DMDHEU. Metabolic activity of the fungi in the wood blocks was assessed as total esterase activity (TEA) based on the hydrolysis of fluorescein diacetate and as heat or energy production determined by isothermal micro-calorimetry. Both methods revealed that the fungal activity was related with the WPG and the mass loss caused by the fungi. Still, fungal activity was detected even in wood blocks of the highest WPG and showed that the treatment was not toxic to the fungi. Energy production showed a higher consistency with the mass loss after decay than TEA; higher mass loss was more stringently reflected by higher heat production rate. Heat production did not proceed linearly, possibly due to the inhibition of fungal activity by an excess of carbon dioxide

Characterization of K-Complexes and Slow Wave Activity in a Neural Mass Model

NREM sleep is characterized by two hallmarks, namely K-complexes (KCs) during sleep stage N2 and cortical slow oscillations (SOs) during sleep stage N3. While the underlying dynamics on the neuronal level is well known and can be easily measured, the resulting behavior on the macroscopic population level remains unclear. On the basis of an extended neural mass model of the cortex, we suggest a new interpretation of the mechanisms responsible for the generation of KCs and SOs. As the cortex transitions from wake to deep sleep, in our model it approaches an oscillatory regime via a Hopf bifurcation. Importantly, there is a canard phenomenon arising from a homoclinic bifurcation, whose orbit determines the shape of large amplitude SOs. A KC corresponds to a single excursion along the homoclinic orbit, while SOs are noise-driven oscillations around a stable focus. The model generates both time series and spectra that strikingly resemble real electroencephalogram data and points out possible differences between the different stages of natural sleep