Anomalous intraosseous venous drainage: a rare cause of pretibial varicose veins

Valvular incompetence with reflux and postthrombotic syndrome are the most common features of varicose veins, a common disease. More rare etiologies must be evoked when these two main causes have been ruled out. We report herein the case of a 47-year-old man who has been suffering from varicosis and complained with left leg pain since 15?years. He had already been managed by standard stripping, saphenous ligations, phlebectomies but was not completely relieved. X-ray findings of the tibia, doppler ultrasonography and magnetic resonance imaging led us to the diagnosis of tibial intraosseous venous drainage anomaly. We then report diagnosis and therapeutic decisional approach.     

Rapid, local adaptation of zooplankton behavior to changes in predation pressure in the absence of neutral genetic changes

Organisms producing resting stages provide unique opportunities for reconstructing the genetic history of natural populations. Diapausing seeds and eggs often are preserved in large numbers, representing entire populations captured in an evolutionary inert state for decades and even centuries. Starting from a natural resting egg bank of the waterflea Daphnia, we compare the evolutionary rates of change in an adaptive quantitative trait with those in selectively neutral DNA markers, thus effectively testing whether the observed genetic changes in the quantitative trait are driven by natural selection. The population studied experienced variable and well documented levels of fish predation over the past 30 years and shows correlated genetic changes in phototactic behavior, a predator-avoidance trait that is related to diel vertical migration. The changes mainly involve an increased plasticity response upon exposure to predator kairomone, the direction of the changes being in agreement with the hypothesis of adaptive evolution. Genetic differentiation through time was an order of magnitude higher for the studied behavioral trait than for neutral markers (DNA microsatellites), providing strong evidence that natural selection was the driving force behind the observed, rapid, evolutionary changes.     

Neuron Specific Enolase,S100-beta protein and progranulin as diagnostic biomarkers of status epilepticus

Journal of Neurology - Status epilepticus (SE) is a life-threatening prolonged epileptic seizure. A rapid diagnosis is fundamental to initiate antiepileptic treatment and to prevent the development...     

Epilepsy related to focal neuronal lipofuscinosis: extra-frontal localization,EEG signatures and GABA involvement

Journal of Neurology - Focal neuronal lipofuscinosis (FNL) is an uncommon epileptic disorder related to an excess of lipofuscin accumulation within dysmorphic-appearing neurons (DANs), whose...     

Daily resting-state intracranial EEG connectivity for seizure risk forecasts

Forecasting seizure risk aims to detect proictal states in which seizures would be more likely to occur. Classical seizure prediction models are trained over long-term electroencephalographic (EEG) recordings to detect specific preictal changes for each seizure, independently of those induced by shifts in states of vigilance. A daily single measure—during a vigilance-controlled period—to estimate the risk of upcoming seizure(s) would be more convenient. Here, we evaluated whether intracranial EEG connectivity (phase-locking value), estimated from daily vigilance-controlled resting-state recordings, could allow distinguishing interictal (no seizure) from preictal (seizure within the next 24 h) states. We also assessed its relevance for daily forecasts of seizure risk using machine learning models. Connectivity in the theta band was found to provide the best prediction performances (area under the curve ≥ .7 in 80% of patients), with accurate daily and prospective probabilistic forecasts (mean Brier score and Brier skill score of .13 and .72, respectively). More efficient ambulatory clinical application could be considered using mobile EEG or chronic implanted devices.