TPC2 is a novel NAADP-sensitive Ca2+ release channel, operating as a dual sensor of luminal pH and Ca2+

Nicotinic acid adenine dinucleotide phosphate (NAADP) is a molecule capable of initiating the release of intracellular Ca2+ required for many essential cellular processes. Recent evidence links two-pore channels (TPCs) with NAADP-induced release of Ca2+ from lysosome-like acidic organelles; however, there has been no direct demonstration that TPCs can act as NAADP-sensitive Ca2+-release channels. Controversial evidence also proposes ryanodine receptors as the primary target of NAADP. We show that TPC2, the major lysosomal targeted isoform, is a cation channel with selectivity for Ca2+ that will enable it to act as a Ca2+ release channel in the cellular environment. NAADP opens TPC2 channels in a concentration-dependent manner, binding to high affinity activation and low affinity inhibition sites. At the core of this process is the luminal environment of the channel. The sensitivity of TPC2 to NAADP is steeply dependent on the luminal [Ca2+] allowing extremely low levels of NAADP to open the channel. In parallel, luminal pH controls NAADP affinity for TPC2 by switching from reversible activation of TPC2 at low pH to irreversible activation at neutral pH. Further evidence earmarking TPCs as the likely pathway for NAADP-induced intracellular Ca2+ release is obtained from the use of Ned-19, the selective blocker of cellular NAADP-induced Ca2+ release. Ned-19 antagonizes NAADP-activation of TPC2 in a non-competitive manner at 1 μM but potentiates NAADP activation at nanomolar concentrations. This single-channel study provides a long awaited molecular basis for the peculiar mechanistic features of NAADP signaling and a framework for understanding how NAADP can mediate key physiological events.Publisher PDFPeer reviewe

Deep dyslexia: a case study of connectionist neuropsychology

Deep dyslexia is an acquired reading disorder marked by the occurrence of semantic errors (e.g. reading RIVER as ''ocean''). In addition, patients exhibit a number of other symptoms, including visual and morphological effects in their errors, a part-of-speech effect, and an advantage for concrete over abstract words. Deep dyslexia poses a distinct challenge for cognitive neuropsychology because there is little understanding of why such a variety of symptoms should co-occur in virtually all known patients. Hinton and Shallice (1991) replicated the co-occurrence of visual and semantic errors by lesioning a recurrent connectionist network trained to map from orthography to semantics. Although the success of their simulations is encouraging, there is little understanding of what underlying principles are responsible for them. In this paper we evaluate and, where possible, improve on the most important design decisions made by Hinton and Shallice, relating to the task, the network architecture, the training procedure, and the testing procedure. We identify four properties of networks that underly their ability to reproduce the deep dyslexic symptom-complex: distributed orthographic and semantic representations, gradient descent learning, attractors for word meanings, and greater richness of concrete vs. abstract semantics. The first three of these are general connectionist principles and the last is based on earlier theorising. Taken together, the results demonstrate the usefulness of a connectionist approach to understanding deep dyslexia in particular, and the viability of connectionist neuropsychology in general