Evidence map›Paper›PMID 37164537›Full record

ArticleMethods in cell biology2023

High-SPEED super-resolution SPEED microscopy to study primary cilium signaling in vivo.

Mark Tingey, Andrew Ruba, Weidong Yang

Abstract read
In one paragraph

Article in Methods in cell biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
3.9field-weighted citation impact, top 9% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Review
  2. 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

3 authors at 2 institutions in 1 country.

Mark TingeyDepartment of Biology, Temple University, Philadelphia, PA, United States.
Andrew RubaDepartment of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, United States.
Weidong YangDepartment of Biology, Temple University, Philadelphia, PA, United States. Electronic address: weidong.yang@temple.edu.
Temple University · USUniversity of Pennsylvania · US

Funding

Super-resolution Microscopy Study of Molecular Transport MechanismsR35GM122552 · NIGMS · TEMPLE UNIV OF THE COMMONWEALTH · PI Weidong Yang · 2017 to 2026
$4.5M
NIGMS NIH HHS R35 GM122552
6 · The paper itself

Abstract

The primary cilium is a surface exposed organelle found in eukaryotic cells that functions to decode a variety of intracellular signals with significant implications in human developmental disorders and diseases. It is therefore highly desirable to obtain in vivo information regarding the dynamic processes occurring within the primary cilium. However, current techniques are limited by either the physical limitations of light microscopy or the static nature of electron microscopy. To overcome these limitations, single-point edge-excitation sub-diffraction (SPEED) microscopy was developed to obtain dynamic in vivo information in subcellular organelles such as cilia and nuclear pore complexes using single-molecule super-resolution light microscopy with a spatiotemporal resolution of 10-20nm and 0.4-2ms. Three-dimensional (3D) structural and dynamic information in these organelles can be further obtained through a post-processing 2D-to-3D transformation algorithm. Here we present a modular step-by-step protocol for studying primary cilium signaling dynamics, including Intraflagellar transport (IFT) via IFT20 and somatostatin g-protein-coupled receptor activity via SSTR3.

Indexed as

CiliaMicroscopyBiological TransportHumansSignal TransductionSingle Molecule ImagingPrimary ciliaSuper-resolution light microscopyTransformation algorithm

Identifiers

PMID37164537
PMCPMC13122484
OpenAlexW4318275162

What OpenQuestion holds

Textmetadata
LicenceTDM
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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.