Evidence map›Paper›PMID 32081933›Full record

ArticleScientific reports2020

Self-organizing pattern of subpleural alveolar ducts.

Wayne Mitzner, Jeffrey Loube, Jarrett Venezia, Alan Scott

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. GM-CSF-dependent CD301bNature communications · 2025
    Article
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  5. Review
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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

4 authors.

Wayne MitznerJohns Hopkins University, Baltimore, Maryland, US. wmitzner@jhu.edu.ORCID http://orcid.org/0000-0003-1615-4090
Jeffrey LoubeJohns Hopkins University, Baltimore, Maryland, US.
Jarrett VeneziaJohns Hopkins University, Baltimore, Maryland, US.
Alan ScottJohns Hopkins University, Baltimore, Maryland, US.

Funding

Training: Molecular & Cellular Bases of Infectious DiseasesT32AI007417 · NIAID · JOHNS HOPKINS UNIVERSITY · PI Arturo Casadevall · 1994 to 2026
$11.9M
Mechanism of pathogenic macrophage activation in emphysemaR01HL140623 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI MITZNER, WAYNE, SCOTT, ALAN L · 2018 to 2021
$2.4M
LSM880 Laser-scanning Microscope with Airyscan ModuleS10OD023548 · OD · JOHNS HOPKINS UNIVERSITY · PI KUO, SCOT CHARLES · 2018 to 2018
$439k
NHLBI NIH HHS R01 HL140623NIAID NIH HHS T32 AI007417NIH HHS S10 OD023548ODCDC CDC HHS S10 OD023548
6 · The paper itself

Abstract

In this study we have utilized an optical clearing method to allow visualization of a heretofore undescribed subpleural acinar structural organization in the mammalian lung. The clearing method enables visualization of the lung structure deep below the visceral pleura in intact inflated lungs. In addition to confirming previous observations that the immediate subpleural alveoli are uniform in appearance, we document for the first time that the subpleural lung parenchyma is much more uniformly organized than the internal parenchyma. Specifically, we report that below the surface layer of alveoli, there is a striking parallel arrangement of alveolar ducts that all run perpendicular to the visceral pleural surface. A three dimensional visualization of alveolar ducts allowed for a calculation of the average inner to outer duct diameter ratio of 0.53 in these subpleural ducts. This unique, self-organizing parallel duct structure likely impacts both elastic recoil and the transmission of tethering forces in healthy and diseased lungs.

Indexed as

AnimalsImage Processing, Computer-AssistedMaleMice, Inbred BALB CPleuraPulmonary Alveoli

Identifiers

PMID32081933
PMCPMC7035422

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.