ArticleACS omega2024
Toward Precise Modeling of Dopamine Release Kinetics: Comparison and Validation of Kinetic Models Using Voltammetry.
Article in ACS omega, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Dopamine (DA) is a neurotransmitter present within the animal brain that is responsible for a wide range of physiologic functions, including motivation, reward, and movement control. Changes or dysfunction in the dynamics of DA release are thought to play a pivotal role in regulating various physiological and behavioral processes, as well as leading to neuropsychiatric diseases. Therefore, it is of fundamental interest to neuroscientists to understand and accurately model the kinetics that govern dopaminergic neurotransmission. In the past several decades, many mathematical models have been proposed to attempt to capture the biologic parameters that govern dopaminergic kinetics, with each model seeking to improve upon a previous model. In this review, each of these models are derived, and the ability of each model to properly fit two fast-scan cyclic voltammetry (FSCV) data sets will be demonstrated and discussed. The dopamine oxidation current in both FSCV data sets exhibits hang-up and overshoot behaviors, which have traditionally been difficult for mathematical models to capture. We show that more recent models are better able to model DA release that exhibits these behaviors but that no single model is clearly the best. Rather, models should be selected based on their mathematical properties to best fit the FSCV data one is trying to model. Developing such differential equation models to describe the kinetics of DA release from the synapse confers significant applications both for advancing scientific understanding of DA neurotransmission and for advancing clinical ability to treat neuropsychiatric diseases.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.