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A framework for designing dynamic lp-ntPET studies to maximize the sensitivity to transient neurotransmitter responses to drugs: Application to dopamine and smoking.

ABSTRACT: The "linear parametric neurotransmitter PET" (lp-ntPET) model was introduced to capture the time course of transient endogenous neurotransmitter response to drug stimulus from dynamic PET data. We previously used this novel analysis tool to probe the short-lived dopamine (DA) response induced by cigarette smoking in the PET scanner. It allowed us to find a sex difference in the DA signature of cigarette smoking. To make best use of this tool to characterize neurotransmitter response to drug stimulus, the sensitivity of lp-ntPET to detect such responses must be maximized. We designed a series of simulation studies to examine the impact of the following factors on the sensitivity of lp-ntPET using smoking-induced DA release as an example application: tracer delivery protocol, pre-processing for image denoising, timing of the smoking task, duration of the PET scan, and dose of the radiotracer. Our results suggest that a Bolus paradigm could replace a more difficult B/I paradigm without sacrificing the sensitivity of the method. Pre-processing the PET data with the de-noising algorithm HYPR could improve the sensitivity. The optimal timing to start the smoking task is 45min in a 90min scan and 35min in a 75min scan. A mild shortening of the scan time from 90mCi to 75min should be acceptable without loss of sensitivity. We suggest a lower dose limit of a bolus injection at 16mCi to limit underestimation of DA activation. This study established the framework to optimize the experimental design for reaching the full potential of lp-ntPET to detect neurotransmitter responses to drugs or even behavioral tasks.

SUBMITTER: Wang S

PROVIDER: S-EPMC5321849 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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A framework for designing dynamic lp-ntPET studies to maximize the sensitivity to transient neurotransmitter responses to drugs: Application to dopamine and smoking.

Wang Shuo S Kim Sujin S Cosgrove Kelly P KP Morris Evan D ED

NeuroImage 20161013

The "linear parametric neurotransmitter PET" (lp-ntPET) model was introduced to capture the time course of transient endogenous neurotransmitter response to drug stimulus from dynamic PET data. We previously used this novel analysis tool to probe the short-lived dopamine (DA) response induced by cigarette smoking in the PET scanner. It allowed us to find a sex difference in the DA signature of cigarette smoking. To make best use of this tool to characterize neurotransmitter response to drug stim ...[more]

PMID: 27743899

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Project description:Microbial communities have become a major research focus due to their importance for biogeochemical cycles, biomedicine and biotechnological applications. While some biotechnological applications, such as anaerobic digestion, make use of naturally arising microbial communities, the rational design of microbial consortia for bio-based production processes has recently gained much interest. One class of synthetic microbial consortia is based on specifically designed strains of one species. A common design principle for these consortia is based on division of labor, where the entire production pathway is divided between the different strains to reduce the metabolic burden caused by product synthesis. We first show that classical division of labor does not automatically reduce the metabolic burden when metabolic flux per biomass is analyzed. We then present ASTHERISC (Algorithmic Search of THERmodynamic advantages in Single-species Communities), a new computational approach for designing multi-strain communities of a single-species with the aim to divide a production pathway between different strains such that the thermodynamic driving force for product synthesis is maximized. ASTHERISC exploits the fact that compartmentalization of segments of a product pathway in different strains can circumvent thermodynamic bottlenecks arising when operation of one reaction requires a metabolite with high and operation of another reaction the same metabolite with low concentration. We implemented the ASTHERISC algorithm in a dedicated program package and applied it on E. coli core and genome-scale models with different settings, for example, regarding number of strains or demanded product yield. These calculations showed that, for each scenario, many target metabolites (products) exist where a multi-strain community can provide a thermodynamic advantage compared to a single strain solution. In some cases, a production with sufficiently high yield is thermodynamically only feasible with a community. In summary, the developed ASTHERISC approach provides a promising new principle for designing microbial communities for the bio-based production of chemicals.

Dataset Information

A framework for designing dynamic lp-ntPET studies to maximize the sensitivity to transient neurotransmitter responses to drugs: Application to dopamine and smoking.

Publications

A framework for designing dynamic lp-ntPET studies to maximize the sensitivity to transient neurotransmitter responses to drugs: Application to dopamine and smoking.

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