Evidence map›Paper›PMID 34115747›Full record

ArticlePLoS computational biology2021

A physicochemical model of odor sampling.

Mitchell E Gronowitz, Adam Liu, Qiang Qiu, C Ron Yu, Thomas A Cleland

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.6field-weighted citation impact, top 20% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
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  6. Review
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  9. Article
  10. A Systematic Framework for Olfactory Bulb Signal Transformations.Frontiers in computational neuroscience · 2020
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Mitchell E GronowitzDepartment of Psychology, Cornell University, Ithaca, New York, United States of America.
Adam LiuDepartment of Psychology, Cornell University, Ithaca, New York, United States of America.ORCID 0000-0003-1963-4612
Qiang QiuStowers Institute for Medical Research, Kansas City, Missouri, United States of America.ORCID 0000-0002-7280-1005
C Ron YuStowers Institute for Medical Research, Kansas City, Missouri, United States of America.ORCID 0000-0003-1555-8683
Thomas A ClelandDepartment of Psychology, Cornell University, Ithaca, New York, United States of America.ORCID 0000-0001-7506-1201
Cornell University · USStowers Institute for Medical Research · US

Funding

Circuit architecture and dynamics representation in odor perceptionR01DC014701 · NIDCD · STOWERS INSTITUTE FOR MEDICAL RESEARCH · PI Thomas A Cleland, Yingxi Lin · 2015 to 2026
$6.4M
NIDCD NIH HHS R01 DC014701
6 · The paper itself

Abstract

We present a general physicochemical sampling model for olfaction, based on established pharmacological laws, in which arbitrary combinations of odorant ligands and receptors can be generated and their individual and collective effects on odor representations and olfactory performance measured. Individual odor ligands exhibit receptor-specific affinities and efficacies; that is, they may bind strongly or weakly to a given receptor, and can act as strong agonists, weak agonists, partial agonists, or antagonists. Ligands interacting with common receptors compete with one another for dwell time; these competitive interactions appropriately simulate the degeneracy that fundamentally defines the capacities and limitations of odorant sampling. The outcome of these competing ligand-receptor interactions yields a pattern of receptor activation levels, thereafter mapped to glomerular presynaptic activation levels based on the convergence of sensory neuron axons. The metric of greatest interest is the mean discrimination sensitivity, a measure of how effectively the olfactory system at this level is able to recognize a small change in the physicochemical quality of a stimulus. This model presents several significant outcomes, both expected and surprising. First, adding additional receptors reliably improves the system's discrimination sensitivity. Second, in contrast, adding additional ligands to an odorscene initially can improve discrimination sensitivity, but eventually will reduce it as the number of ligands increases. Third, the presence of antagonistic ligand-receptor interactions produced clear benefits for sensory system performance, generating higher absolute discrimination sensitivities and increasing the numbers of competing ligands that could be present before discrimination sensitivity began to be impaired. Finally, the model correctly reflects and explains the modest reduction in odor discrimination sensitivity exhibited by transgenic mice in which the specificity of glomerular targeting by primary olfactory neurons is partially disrupted.

Indexed as

Models, ChemicalAnimalsMiceMice, TransgenicOdorantsPotassium Channels, Inwardly RectifyingReceptors, OdorantKir2.2 channelPotassium Channels, Inwardly RectifyingReceptors, Odorant

Identifiers

PMID34115747
PMCPMC8221795
OpenAlexW3166154083

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.