Evidence map›Paper›PMID 36994985›Full record

ArticleeLife2023

Autofluorescence imaging permits label-free cell type assignment and reveals the dynamic formation of airway secretory cell associated antigen passages (SAPs).

Viral S Shah, Jue Hou, Vladimir Vinarsky, Jiajie Xu, Manalee V Surve, Charles P Lin, Jayaraj Rajagopal

Open access · goldAbstract read
In one paragraph

Article in eLife, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.5field-weighted citation impact, top 17% 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

8 citing papers in PubMed, 9 citations in OpenAlex.

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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

7 authors at 2 institutions in 1 country.

Viral S Shah *Department of Internal Medicine, Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, United States.ORCID 0000-0002-3605-8066
Jue Hou *Advanced Microscopy Program, Center for Systems Biology and Wellman Center for Photomedicine, Massachusetts General Hospital, Harvard Medical School, Boston, United States.
Vladimir VinarskyCenter for Regenerative Medicine, Massachusetts General Hospital, Boston, United States.ORCID 0000-0003-1141-6434
Jiajie XuCenter for Regenerative Medicine, Massachusetts General Hospital, Boston, United States.
Manalee V SurveCenter for Regenerative Medicine, Massachusetts General Hospital, Boston, United States.
Charles P LinAdvanced Microscopy Program, Center for Systems Biology and Wellman Center for Photomedicine, Massachusetts General Hospital, Harvard Medical School, Boston, United States.
Jayaraj RajagopalDepartment of Internal Medicine, Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, United States.ORCID 0000-0002-4122-177X
Massachusetts General Hospital · USBroad Institute · US

Funding

Research Training in Pulmonary Immunology and Allergy at MGHT32HL116275 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI David C Christiani, ANDREW D LUSTER · 2013 to 2026
$8.6M
Intercellular communication and cell regulation in airway epithelial ensembles in regeneration and diseaseR01HL118185 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI RAJAGOPAL, JAYARAJ · 2014 to 2021
$4.2M
Live Imaging of Intact AirwayR01HL142559 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI LIN, CHARLES P., RAJAGOPAL, JAYARAJ · 2018 to 2021
$2.2M
Defining the lineage, mechanisms of maintenance, and function of a new injury-resistant airway epithelial structure: the hillockR01HL157221 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI RAJAGOPAL, JAYARAJ · 2022 to 2025
$1.9M
NHLBI NIH HHS R01 HL118185NHLBI NIH HHS R01 HL142559NHLBI NIH HHS R01 HL157221
6 · The paper itself

Abstract

The specific functional properties of a tissue are distributed amongst its component cell types. The various cells act coherently, as an ensemble, in order to execute a physiologic response. Modern approaches for identifying and dissecting novel physiologic mechanisms would benefit from an ability to identify specific cell types in live tissues that could then be imaged in real time. Current techniques require the use of fluorescent genetic reporters that are not only cumbersome, but which only allow the study of three or four cell types at a time. We report a non-invasive imaging modality that capitalizes on the endogenous autofluorescence signatures of the metabolic cofactors NAD(P)H and FAD. By marrying morphological characteristics with autofluorescence signatures, all seven of the airway epithelial cell types can be distinguished simultaneously in mouse tracheal explants in real time. Furthermore, we find that this methodology for direct cell type-specific identification avoids pitfalls associated with the use of ostensibly cell type-specific markers that are, in fact, altered by clinically relevant physiologic stimuli. Finally, we utilize this methodology to interrogate real-time physiology and identify dynamic secretory cell associated antigen passages (SAPs) that form in response to cholinergic stimulus. The identical process has been well documented in the intestine where the dynamic formation of SAPs and goblet cell associated antigen passages (GAPs) enable luminal antigen sampling. Airway secretory cells with SAPs are frequently juxtaposed to antigen presenting cells, suggesting that airway SAPs, like their intestinal counterparts, not only sample antigen but convey their cargo for immune cell processing.

Indexed as

AntigensGoblet CellsAnimalsAntigen-Presenting CellsMiceOptical ImagingPhagocytosisAntigensairway epitheliaautofluorescencecell biologyFADgoblet cell associated antigen passagesmouseNADHsecretory cell associated antigen passages

Identifiers

PMID36994985
PMCPMC10154029
OpenAlexW4361279436

What Socratic 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 Socratic graph.