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Record W4403543621 · doi:10.1111/liv.16131

Osteopontin Promotes Cholangiocyte Secretion of Chemokines to Support Macrophage Recruitment and Fibrosis in <scp>MASH</scp>

2024· article· en· W4403543621 on OpenAlexafffund
Jason D. Coombes, Paul Manka, Marzena Swiderska‐Syn, Danielle T. Vannan, Antonio Riva, Lee C. Claridge, Cynthia A. Moylan, Ayako Suzuki, Marco A. Briones‐Orta, Rasha Younis, Naoto Kitamura, Svenja Sydor, Shanna Bittencourt, Zhiyong Mi, Paul C. Kuo, Anna Mae Diehl, Leo A. van Grunsven, Shilpa Chokshi, Ali Canbay, Manal F. Abdelmalek, Patricia Aspichueta, Salvatore Papa, Bertus Eksteen, Wing‐Kin Syn

Bibliographic record

VenueLiver International · 2024
Typearticle
Languageen
FieldMedicine
TopicLiver physiology and pathology
Canadian institutionsUniversity of Calgary
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNatural Sciences and Engineering Research Council of CanadaAlberta InnovatesUniversity of BirminghamNational Institutes of HealthBardham Research and Education TrustBelgian Federal Science Policy OfficeDeutsche ForschungsgemeinschaftGuts UKRégion de Bruxelles-CapitaleEuropean Association for the Study of the LiverRosetrees TrustFoundation for Liver Research
KeywordsChemokineOsteopontinCCR2CCL5CXCL2BiologyChemokine receptorCancer researchImmunologyInflammationT cellImmune systemIL-2 receptor

Abstract

fetched live from OpenAlex

ABSTRACT Background and Aims Osteopontin (OPN) promotes the ductular reaction and is a major driver of chronic liver disease (CLD) progression. Although CLD is characterised by the accumulation of inflammatory cells including macrophages around the peri‐portal regions, the influence of OPN on recruitment is unclear. We investigated the role of OPN in cholangiocyte chemokine production and macrophage recruitment by combining in vivo, in vitro, and in silico approaches. Methods The effects of OPN on cholangiocyte chemokine production and macrophage migration were assessed in culture, alongside RNA‐sequencing to identify genes and pathways affected by OPN depletion. Murine liver injury models were used to assess liver chemokine expression and liver macrophage/monocyte recruitment. OPN and chemokine expression were analysed in liver tissue and plasma from biopsy‐proven metabolic dysfunction‐associated alcoholic steatohepatitis (MASH) patients. Results OPN‐knockdown in cholangiocytes reduced chemokine secretion. RNA‐sequencing showed OPN‐related effects clustered around immunity, chemotaxis and chemokine production. Macrophage exposure to cholangiocyte‐conditioned media showed OPN‐supported migration via chemokines chemokine (C‐C motif) ligand (CCL)2, CCL5 and chemokine (C‐X‐C motif) ligand (CXCL)1. These effects were related to NF‐κB signalling. Murine liver fibrosis was accompanied by upregulated liver OPN, CCL2, CCL5 and CXCL1 mRNA, and accumulation of liver cluster of differentiation (CD)11b/F4/80 + CC chemokine receptors (CCR2) high macrophages but treatment with OPN‐specific neutralising aptamers reduced fibrosis, chemokine mRNAs and accumulation of liver CD11b/F4/80 + CCR2 high /lymphocyte antigen 6 complex high inflammatory monocytes. In human MASH, liver OPN correlated with chemokines CCL2 and IL8 in association with portal injury and fibrosis. Plasma OPN, serum CCL2 and IL8 also increased with fibrosis stage. Conclusions OPN promotes cholangiocyte chemokine secretion and the accumulation of pro‐inflammatory monocytes. These data support neutralisation of OPN as an anti‐inflammatory and anti‐fibrotic strategy.

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 score0.650
Threshold uncertainty score0.315

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 head0.034
GPT teacher head0.311
Teacher spread0.277 · 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

Citations10
Published2024
Admission routes2
Has abstractyes

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