Deep Neural Networks for Automatic Classification of Anesthetic-Induced Unconsciousness

Despite the common use of anesthetics to modulate consciousness in the clinic, brain-based monitoring of consciousness is uncommon. We com-bined electroencephalographic measurement of brain activity with deep neural networks to automatically discriminate anesthetic states induced by propofol. Our results with leave-one-participant-out-cross-validation show that convolutional neural networks significantly outperform multilayer perceptrons in discrimination accuracy when working with raw time series. Perceptrons achieved comparable accuracy when provided with power spec-tral densities. These findings highlight the potential of deep convolutional networks for completely automatic extraction of useful spatio-temporo-spectral features from human EEG

New cytotoxic benzo(b)thiophenilsulfonamide 1,1-dioxide derivatives inhibit a NADH oxidase located in plasma membranes of tumour cells

A series of benzo(b)thiophenesulfonamide 1,1-dioxide derivatives (BTS) have been designed and synthesized as candidate antineoplastic drugs. Several of these compounds have shown in vitro cytotoxic activity on leukaemic CCRF-CEM cells. The cytotoxic BTS, but not the inactive ones, were able to inhibit a tumour cell-specific NADH oxidase activity present in the membrane of CCRF-CEM cells. © 2001 Cancer Research Campaig

Seizure prediction : ready for a new era

Acknowledgements: The authors acknowledge colleagues in the international seizure prediction group for valuable discussions. L.K. acknowledges funding support from the National Health and Medical Research Council (APP1130468) and the James S. McDonnell Foundation (220020419) and acknowledges the contribution of Dean R. Freestone at the University of Melbourne, Australia, to the creation of Fig. 3.Peer reviewedPostprin