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Alveolar macrophages undergo METosis in an inflammatory model of neonatal lung injury

2023· article· en· W4378649463 on OpenAlexaffabout
Randa Higazy, Atefeh Mohammadi, Julijana Ivanovska, Harvard Tran, Estelle B. Gauda, Nades Palaniyar

Bibliographic record

VenuePhysiology · 2023
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsBronchoalveolar lavageMyeloperoxidaseInflammationLipopolysaccharideIn vivoNeutrophil extracellular trapsLungImmunologyMacrophageDAPIExtracellularPathologyChemistryBiologyMedicineIn vitroInternal medicineBiochemistry

Abstract

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Background: Activated macrophages can produce macrophage extracellular traps (METs) - DNA strands coated with cytotoxic components that are released to immobilize pathogens and control infection. However, METs can also contribute to the inflammatory process and lead to severe tissue damage. Bronchopulmonary dysplasia (BPD) is a chronic lung disease in premature infants initiated by inflammation and oxidative stress. Gram-negative bacteria and candida increase the risk of developing BPD and are strong inducers of extracellular traps. Macrophages are the most abundant immune cells in the neonatal lung tissue, responsible for controlling the inflammatory process. We aimed to determine whether inflammation triggers METosis in a neonatal model of inflammatory lung injury. Methods: Alveolar macrophages (AMs) from bronchoalveolar lavage fluid (BALF) were isolated from Sprague Dawley rat pups on postnatal day (PND) 8. In vitro - AMs were incubated with METosis agonists (lipopolysaccharide [LPS] and phorbol myristate acetate [PMA]) or control (media) for 4h. Cells were fixed and stained for markers of METosis (myeloperoxidase [MPO] and citrullinated histone H3 [CitH3]) and DNA (DAPI) for immunofluorescence imaging. In vivo - PND6-9 pups were treated with LPS or saline intrapharyngeally and DNase enzyme or saline intraperitoneally. BALF was collected on PND10. BALF was analysed using immunofluoresence imaging and picogreen assay. Results: Immunofluorescence imaging of neonate AMs showed increased expression of METosis markers MPO, CitH3, and DNA strands with in vitro exposure to METosis agonists PMA or LPS compared to control (n =3). In vivo LPS exposure also showed evidence of increased extracellular trap formation in the BALF collected from neonate rat lung compared to control (n=3; p<0.0001); further, rats exposed to both LPS and DNAse enzyme showed decreased extracellular trap formation (p = 0.002) in comparison to the rats exposed to LPS and saline. Conclusions: To the best of our knowledge, this study is first to establish (i) rat AMs undergo METosis, (ii) a plausible role for METosis in lung injury (iii), and the potential relevance of METosis in lung injury during early development. Novel therapies targeting METosis formation may reduce lung inflammation contributing to BPD in premature infants. This work was supported by the Women's Auxiliary Fund, The Hospital for Sick Children, Toronto, Ontario, Canada This is the full abstract presented at the American Physiology Summit 2023 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.053
GPT teacher head0.394
Teacher spread0.341 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

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