Evidence map›Paper›PMID 33393517›Full record

ArticleJournal of visualized experiments : JoVE2020

In vivo Evaluation of Mucociliary Clearance in Mice.

Kyle S Feldman, Maliha Zahid

Abstract readVideo-Audio Media
In one paragraph

Article in Journal of visualized experiments : JoVE, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Review
  2. Stem cells, cell therapies, and bioengineering in lung biology and diseases 2023.American journal of physiology. Lung cellular and molecular physiology · 2024
    Review
  3. 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.

Kyle S FeldmanDepartment of Developmental Biology, University of Pittsburgh School of Medicine.
Maliha ZahidDepartment of Developmental Biology, University of Pittsburgh School of Medicine; maz7@pitt.edu.

Funding

Targeting Underlying Pathophysiological Mechanisms to Develop Novel Therapies for Chronic Obstructive Lung DiseaseR01HL153407 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI ZAHID, MALIHA · 2020 to 2024
$3.0M
NHLBI NIH HHS R01 HL153407
6 · The paper itself

Abstract

Respiratory motile cilia, specialized organelles of the cell, line the apical surface of epithelial cells lining the respiratory tract. By beating in a metachronal, synchronal fashion, these multiple, motile, actin-based organelles generate a cephalad fluid flow clearing the respiratory tract of inhaled pollutants and pathogens. With increasing environmental pollution, novel viral pathogens and emerging multi-drug resistant bacteria, cilia generated mucociliary clearance (MCC) is essential for maintaining lung health. MCC is also depressed in multiple congenital disorders like primary ciliary dyskinesia, cystic fibrosis as well as acquired disorders like chronic obstructive pulmonary disease. All these disorders have established, in some case multiple, mouse models. In this publication, we detail a method using a small amount of radioactivity and dual-modality SPECT/CT imaging to accurately and reproducibly measure MCC in mice in vivo. The method allows for recovery of mice after imaging, making serial measurements possible, and testing potential therapeutics longitudinally over time. The data in wild-type mice demonstrates the reproducibility of the MCC measurement as long as adequate attention to detail is paid, and the protocol strictly adhered to.

Indexed as

AnimalsHumansIntubationLungMiceMucociliary ClearanceRadioisotopesReproducibility of ResultsTomography, Emission-Computed, Single-PhotonTomography, X-Ray ComputedRadioisotopes

Identifiers

PMID33393517
PMCPMC7935021

What OpenQuestion holds

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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.