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Abstract: Most psychostimulant drugs interfere with the transport proteins that mediate reuptake of the monoamines dopamine, norepinephrine and serotonin into the presynaptic specialization. The majority of these drugs, like cocaine, inhibit monoamine uptake by blocking substrate binding to the cognate transport protein. On the other hand, amphetamines do not simply block reuptake; they directly reverse the transport process and induce non-vesicular monoamine release. Although this has been recognized for several decades, a quantitatively plausible mechanistic explanation has been missing. A central question has been whether the transport reactions met under physiological conditions suffice to account for amphetamine action, or whether additional - amphetamine-specific - transport modes need to be invoked.
Here, recent efforts to solve this problem in the human serotonin transporter will be summarized. The catalytic cycle of the serotonin transport process has been resolved in kinetic detail, which culminated in the formulation of a parsimonious alternating access model of serotonin transport. This model - which obeys a cooperative binding order - is sufficient to account qualitatively and quantitatively for the monoamine-releasing action of amphetamines. Hence, amphetamine-induced monoamine release can be explained without assuming any additional amphetamine-specific transport modes. Moreover, a mechanistic explanation for 'partial release' (i.e. that some amphetamine congeners are less efficacious releasers than others) is a direct consequence of the model. It is hoped that the framework presented here will guide further experiments to delineate the full reaction cycle of amphetamine action.
The presented work can be found in the following articles:
1.) Hasenhuetl PS*, Bhat S*, Mayer FP, Sitte HH, Freissmuth M, Sandtner W (2018) A Kinetic Account for Amphetamine-Induced Monoamine Release. Journal of General Physiology [* shared first author; published online 09. February 2018]
2.) Bhat S, Hasenhuetl PS, Kasture A, El-Kasaby A, Baumann MH, Blough BE, Sucic S, Sandtner W, Freissmuth M (2017) Conformational State Interactions Provide Clues to the Pharmacochaperone Potential of Serotonin Transporter Partial Substrates. Journal of Biological Chemistry 292:16773-16786.
3.) Hasenhuetl PS, Freissmuth M, Sandtner W (2016) Electrogenic Binding of Intracellular Cations Defines a Kinetic Decision-Point in the Transport Cycle of the Human Serotonin Transporter. Journal of Biological Chemistry 291:25864-25876.
Abstract: Neural networks have become an important tool in modern computational analysis. Recent years have seen the successful application of artificial neural networks to hosts of problems in various areas of scientific research, including finance, image and language processing to name a few. Quantum computing has seen an exponential rate of advancement in the past decade, with the majority of big technology corporations starting their own divisions in this field. It is evident that the field of quantum computing is bound to bring a lot of much needed innovation to computer science, including resolutions to long-standing algorithmic and computational problems. In this talk I will review the area of intersection of these two technologies, and will offer an insight into the kind of problems which would become tractable with the application of quantum neural networks. I will also present the roadmap of advancement of quantum computing, and explain the important milestones which need to be met in order to see the mass adoption of this technology.
Learning-related plasticity of dendritic inhibition in neocortical layer 1
Abstract: Transient breaks in the excitation-inhibition ratio termed disinhibition have been shown to contribute to both memory acquisition and expression in a number of recent studies. However, whether disinhibition occurs throughout the somatodendritic domain of pyramidal neurons, or alternatively represents a redistribution of inhibition within the neuron remains little understood. To address this question, here we focus on neocortical layer 1, a key location for processing of top-down information implicated in learning. Using a novel genetic marker for a subpopulation of layer 1 interneurons (Ndnf) in combination with in vivo 2-photon calcium imaging, in vitro electrophysiology, viral tracing and optogenetics, we find that Ndnf positive layer 1 interneurons in auditory cortex provide inhibition widely to interneurons in layer 1 and lower layers, as well as the distal dendrites of pyramidal neurons. These connections recruit a strong component of GabaB receptor signalling, and thereby control the initiation of dendritic spikes in pyramidal cells. To address whether Ndnf positive layer 1 interneurons show learning-related plasticity, we combined in vivo calcium imaging with a form of cortex-dependent auditory fear learning. These experiments reveal that sensory responses of Ndnf positive layer 1 interneurons are potentiated in response to learning in proportionality to the strength of the memory. In contrast, a second source of dendritic inhibition derived from somatostatin-positive Martinotti cells remains unchanged after learning. Together, these results indicate that, in addition to disinhibition, memory retrieval is associated with an increase in a specialized from of dendritic inhibition.