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Record W4317877776 · doi:10.1165/rcmb.2022-0269oc

Hedgehog and Platelet-derived Growth Factor Signaling Intersect during Postnatal Lung Development

2023· article· en· W4317877776 on OpenAlexfundno aff
Ting-An Yie, Cynthia A. Loomis, Johannes Nowatzky, Alireza Khodadadi‐Jamayran, Ziyan Lin, Michael Cammer, C.R. Barnett, Valeria Mezzano, Mark Alu, Jackson A. Novick, John S. Munger, Matthias C. Kugler

Bibliographic record

VenueAmerican Journal of Respiratory Cell and Molecular Biology · 2023
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsnot available
FundersNational Institute of Environmental Health SciencesNational Heart, Lung, and Blood InstituteNational Cancer InstituteStony Wold-Herbert FundSchool of Medicine, New York UniversityNational Eye InstituteYork UniversityMemorial Sloan-Kettering Cancer Center
KeywordsPDGFRAPlatelet-derived growth factor receptorMyofibroblastHedgehogBiologyPlatelet-derived growth factorCell biologyHedgehog signaling pathwayGrowth factorMesenchymal stem cellSignal transductionCancer researchInternal medicineReceptorStromal cellGeneticsMedicineFibrosis

Abstract

fetched live from OpenAlex

Abstract Normal lung development critically depends on HH (Hedgehog) and PDGF (platelet-derived growth factor) signaling, which coordinate mesenchymal differentiation and proliferation. PDGF signaling is required for postnatal alveolar septum formation by myofibroblasts. Recently, we demonstrated a requirement for HH in postnatal lung development involving alveolar myofibroblast differentiation. Given shared features of HH signaling and PDGF signaling and their impact on this key cell type, we sought to clarify their relationship during murine postnatal lung development. Timed experiments revealed that HH inhibition phenocopies the key lung myofibroblast phenotypes of Pdgfa (platelet-derived growth factor subunit A) and Pdgfra (platelet-derived growth factor receptor alpha) knockouts during secondary alveolar septation. Using a dual signaling reporter, Gli1lZ;PdgfraEGFP, we show that HH and PDGF pathway intermediates are concurrently expressed during alveolar septal myofibroblast accumulation, suggesting pathway convergence in the generation of lung myofibroblasts. Consistent with this hypothesis, HH inhibition reduces Pdgfra expression and diminishes the number of Pdgfra-positive and Pdgfra-lineage cells in postnatal lungs. Bulk RNA sequencing data of Pdgfra-expressing cells from Postnatal Day 8 (P8) lungs show that HH inhibition alters the expression not only of well-established HH targets but also of several putative PDGF target genes. This, together with the presence of Gli-binding sites in PDGF target genes, suggests HH input into PDGF signaling. We identified these HH/PDGF targets in several postnatal lung mesenchymal cell populations, including myofibroblasts, using single-cell transcriptomic analysis. Collectively, our data indicate that HH signaling and PDGF signaling intersect to support myofibroblast/fibroblast function during secondary alveolar septum formation. Moreover, they provide a molecular foundation relevant to perinatal lung diseases associated with impaired alveolarization.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.321
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations19
Published2023
Admission routes1
Has abstractyes

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