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Record W2790726687 · doi:10.1172/jci.insight.90163

Identification of periplakin as a major regulator of lung injury and repair in mice

2018· article· en· W2790726687 on OpenAlexaff
Valérie Besnard, Rania Dagher, Tania Madjer, Audrey Joannes, Madeleine Jaillet, Martin Kolb, Philippe Bonniaud, Lynne A. Murray, Matthew A. Sleeman, Bruno Crestani

Bibliographic record

VenueJCI Insight · 2018
Typearticle
Languageen
FieldMedicine
TopicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Canadian institutionsPopulation Health Research Institute
FundersMedImmuneFondation pour la Recherche MédicaleAgence Nationale de la Recherche
KeywordsBleomycinPulmonary fibrosisLungIdiopathic pulmonary fibrosisFibrosisMedicineAutoimmunityCancer researchImmunologyPathologyImmune systemInternal medicine

Abstract

fetched live from OpenAlex

Periplakin is a component of the desmosomes that acts as a cytolinker between intermediate filament scaffolding and the desmosomal plaque. Periplakin is strongly expressed by epithelial cells in the lung and is a target antigen for autoimmunity in idiopathic pulmonary fibrosis. The aim of this study was to determine the role of periplakin during lung injury and remodeling in a mouse model of lung fibrosis induced by bleomycin. We found that periplakin expression was downregulated in the whole lung and in alveolar epithelial cells following bleomycin-induced injury. Deletion of the Ppl gene in mice improved survival and reduced lung fibrosis development after bleomycin-induced injury. Notably, Ppl deletion promoted an antiinflammatory alveolar environment linked to profound changes in type 2 alveolar epithelial cells, including overexpression of antiinflammatory cytokines, decreased expression of profibrotic mediators, and altered cell signaling with a reduced response to TGF-β1. These results identify periplakin as a previously unidentified regulator of the response to injury in the lung.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.499
Threshold uncertainty score0.274

Codex and Gemma teacher scores by category

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 head0.006
GPT teacher head0.266
Teacher spread0.261 · 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 teacher head, 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

Citations16
Published2018
Admission routes1
Has abstractyes

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