Evidence map›Paper›PMID 35836063›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

Quantitative Imaging of Retinoic Acid Activities in Living Mammalian Cells.

Sung-Bae Kim, Rika Fujii, Ramasamy Paulmurugan

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 81% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

3 authors at 2 institutions in 2 countries.

Sung-Bae KimEnvironmental Management Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan. kimu-sb@aist.go.jp.
Rika FujiiEnvironmental Management Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan.
Ramasamy PaulmuruganMolecular Imaging Program at Stanford, Stanford University School of Medicine, Palo Alto, CA, USA.
National Institute of Advanced Industrial Science and Technology · JPStanford University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Retinoic acid (RA) is an intriguing metabolite that is necessary for embryonic development and differentiation in vertebrates. The present protocol demonstrates how to image RA activities indirectly in mammalian cells with ligand-activatable single-chain bioluminescence (BL) probes. We introduce 13 different molecular designs for characterizing an efficient single-chain probe that quantitatively visualizes RA activities with significant sensitivity. The key components included in the probes are (i) the N- and C-terminal fragments of artificial luciferase 16 (ALuc16), (ii) the ligand-binding domain of human retinoic acid receptor α (RAR LBD), and (iii) an LXXLL motif derived from common coactivators of nuclear receptors. The probe is highly selective and sensitive to all-trans-RA (at-RA) in animal cells. This protocol exemplifies quantitative imaging of the RA levels in serum and cerebrospinal fluid with a linear range in two orders. The present protocol is an important addition to conventional techniques on quantitative imaging of endogenous at-RA levels in live mammalian cells.

Indexed as

Receptors, Retinoic AcidTretinoinAnimalsCell DifferentiationHumansLigandsMammalsRetinoic Acid Receptor alphaLigandsReceptors, Retinoic AcidRetinoic Acid Receptor alphaTretinoinArtificial luciferase 16Bioluminescence (BL)Protein–protein interactionsRetinoic acid receptorRetinoic acids (RA)Single-chain probe

Identifiers

PMID35836063
OpenAlexW4285412454

What OpenQuestion holds

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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.