Evidence map›Paper›PMID 38019435›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2024

Peptide-Mediated Cyclic Nucleotide Signaling in Plants: Identification and Characterization of Interactor Proteins with Nucleotide Cyclase Activity.

Ilona Turek, Chris Gehring

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.6field-weighted citation impact, top 14% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

2 authors at 2 institutions in 2 countries.

Ilona TurekDepartment of Rural Clinical Sciences, La Trobe Institute for Molecular Science, La Trobe University, Bendigo, VIC, Australia. I.Turek@latrobe.edu.au.
Chris GehringDepartment of Chemistry, Biology and Biotechnology, University of Perugia, Perugia, Italy.
La Trobe University · AUUniversity of Perugia · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

During the last decades, an increasing number of plant signaling peptides have been discovered and it appears that many of them are specific ligands for interacting receptor molecules. These receptors can enable the formation of second messengers which in turn transmit the ligand-induced stimuli into complex and tunable downstream responses. In order to perform such complex tasks, receptor proteins often contain several distinct domains such as a kinase and/or adenylate cyclase (AC) or guanylate cyclase (GC) domains. ACs catalyze the conversion of ATP to 3',5'-cyclic adenosine monophosphate (cAMP) while GCs catalyze the reaction of GTP to 3',5'-cyclic guanosine monophosphate (cGMP). Both cAMP and cGMP are now recognized as essential components of many plant responses, including responses to peptidic hormones. Here we describe the approach that led to the discovery of the Plant Natriuretic Peptide Receptor (PNP receptor), including a protocol for the identification of currently undiscovered peptidic interactions, and the subsequent application of computational methods for the identification of AC and/or GC domains in such interacting receptor candidates.

Indexed as

Nucleotides, CyclicPeptide HormonesAdenylyl CyclasesCyclic AMPCyclic GMPGuanylate CyclaseSignal TransductionAdenylyl CyclasesCyclic AMPCyclic GMPGuanylate CyclaseNucleotides, CyclicPeptide HormonesAdenylate cyclasecAMPcGMPCyclic nucleotidesGuanylate cyclaseNucleotide cyclasesPeptide hormone receptorsPeptide hormones

Identifiers

PMID38019435
OpenAlexW4389146689

What OpenQuestion holds

Textmetadata
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.