Process-based modelling of isoprene emission by oak leaves

The emission rate of the volatile reactive compound isoprene, emitted predominantly by trees, must be known before the level of photo-oxidants produced during summer smog can be predicted reliably. The emission is dependent on plant species and local conditions, and these dependencies must be quantified to be included in any empirical algorithm for the calculation of isoprene production. Experimental measurements of isoprene emission rates are expensive, however, and existing data are scarce and fragmentary. To overcome these difficulties, it is promising to develop a numerical model capable of precisely calculating the isoprene emission by trees for diverse ecosystems, even under changing environmental conditions. A basic process-based biochemical isoprene emission model (BIM) has therefore been developed, which describes the enzymatic reactions in leaf chloroplasts leading to the formation of isoprene under varying environmental conditions (e. g. light intensity, temperature). Concentrations of the precursors of isoprene formation, 3-phosphoglyceric acid and glyceraldehyde 3-phosphate, are provided by a published light fleck photosynthesis model. Specific leaf and enzyme parameters were determined for the pedunculate oak (Quercus robur L.), so that the BIM is capable of calculating oak-specific isoprene emission rates as influenced by the leaf temperature and light intensity. High correlation was observed between isoprene emission rates calculated by the BIM and the diurnal isoprene emission rates of leaves measured under controlled environmental conditions. The BIM was even capable of describing changes in isoprene emission caused by midday depression of net photosynthesis

Intelligence quotient improves after antiepileptic drug withdrawal following pediatric epilepsy surgery

ObjectiveAntiepileptic drugs (AEDs) have cognitive side effects that, particularly in children, may affect intellectual functioning. With the TimeToStop (TTS) study, we showed that timing of AED withdrawal does not majorly influence long-term seizure outcomes. We now aimed to evaluate the effect of AED withdrawal on postoperative intelligence quotient (IQ), and change in IQ (delta IQ) following pediatric epilepsy surgery. MethodsWe collected IQ scores of children from the TTS cohort with both pre- and postoperative neuropsychological assessments (NPAs; n=301) and analyzed whether reduction of AEDs prior to the latest NPA was related to postoperative IQ and delta IQ, using linear regression analyses. Factors previously identified as independently relating to (delta) IQ, and currently identified predictors of (delta) IQ, were considered possible confounders and used for adjustment. Additionally, we adjusted for a compound propensity score that contained previously identified determinants of timing of AED withdrawal. ResultsMean interval to the latest NPA was 19.818.9 months. Reduction of AEDs at the latest NPA significantly improved postoperative IQ and delta IQ (adjusted regression coefficient [RC]=3.4, 95% confidence interval [CI]=0.6-6.2, p=0.018 and RC=4.5, 95% CI=1.7-7.4, p=0.002), as did complete withdrawal (RC=4.8, 95% CI=1.4-8.3, p=0.006 and RC=5.1, 95% CI=1.5-8.7, p=0.006). AED reduction also predicted 10-point IQ increase (p=0.019). The higher the number of AEDs reduced, the higher was the IQ (gain) after surgery (RC=2.2, 95% CI=0.6-3.7, p=0.007 and RC=2.6, 95% CI=1.0-4.2, p=0.001, IQ points per AED reduced). InterpretationStart of AED withdrawal, number of AEDs reduced, and complete AED withdrawal were associated with improved postoperative IQ scores and gain in IQ, independent of other determinants of cognitive outcome. Ann Neurol 2015;78:104-11