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Record W2993021476 · doi:10.1186/s12974-019-1625-y

IL-33 deficiency causes persistent inflammation and severe neurodegeneration in retinal detachment

2019· article· en· W2993021476 on OpenAlexfundno aff
Josy Augustine, Sofia Pavlou, Imran Ali, Kevin Harkin, Ema Ozaki, Matthew Campbell, Alan W. Stitt, Heping Xu, Mei Chen

Bibliographic record

VenueJournal of Neuroinflammation · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
TopicIL-33, ST2, and ILC Pathways
Canadian institutionsnot available
FundersScience Foundation IrelandQueen's University BelfastDepartment for Education, UK GovernmentQueen's UniversityFight for Sight UKSight Research UKHealth Research Board
KeywordsGlial fibrillary acidic proteinGliosisNeurodegenerationRetinalRetinaInflammationMicrogliaPathologyProinflammatory cytokineNeuroinflammationCytokineMedicineImmunologyBiologyImmunohistochemistryOphthalmologyNeuroscienceDisease

Abstract

fetched live from OpenAlex

Abstract Background Interleukin-33 (IL-33) belongs to the IL-1 cytokine family and resides in the nuclei of various cell types. In the neural retina, IL-33 is predominately expressed in Müller cells although its role in health and disease is ill-defined. Müller cell gliosis is a critical response during the acute phase of retinal detachment (RD), and in this study, we investigated if IL-33 was modulatory in the inflammatory and neurodegenerative pathology which is characteristic of this important clinical condition. Methods RD was induced by subretinal injection of sodium hyaluronate into C57BL/6 J (WT) and IL-33−/− mice and confirmed by fundus imaging and optical coherence tomography (OCT). The expression of inflammatory cytokines, complement components and growth factors was examined by RT-PCR. Retinal neurodegeneration, Müller cell activation and immune cell infiltration were assessed using immunohistochemistry. The expression of inflammatory cytokines in primary Müller cells and bone marrow-derived macrophages (BM-DMs) was assessed by RT-PCR and Cytometric Bead Array. Results RD persisted for at least 28 days after the injection of sodium hyaluronate, accompanied by significant cone photoreceptor degeneration. The mRNA levels of CCL2, C1ra, C1s, IL-18, IL-1β, TNFα, IL-33 and glial fibrillary acidic protein (GFAP) were significantly increased at day 1 post-RD, reduced gradually and, with the exception of GFAP and C1ra, returned to the basal levels by day 28 in WT mice. In IL-33−/− mice, RD induced an exacerbated inflammatory response with significantly higher levels of CCL2, IL-1β and GFAP when compared to WT. Sustained GFAP activation and immune cell infiltration was detected at day 28 post-RD in IL-33−/− mice. Electroretinography revealed a lower A-wave amplitude at day 28 post-RD in IL-33−/− mice compared to that in WT RD mice. IL-33−/− mice subjected to RD also had significantly more severe cone photoreceptor degeneration compared to WT counterparts. Surprisingly, Müller cells from IL-33−/− mice expressed significantly lower levels of CCL2 and IL-6 compared with those from WT mice, particularly under hypoxic conditions, whereas IL-33−/− bone marrow-derived macrophages expressed higher levels of inducible nitric oxide synthase, TNFα, IL-1β and CCL2 after LPS + IFNγ stimulation compared to WT macrophages. Conclusion IL-33 deficiency enhanced retinal degeneration and gliosis following RD which was related to sustained subretinal inflammation from infiltrating macrophages. IL-33 may provide a previously unrecognised protective response by negatively regulating macrophage activation following retinal detachment.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

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)0.0020.000

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 head0.012
GPT teacher head0.213
Teacher spread0.201 · 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 designObservational
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

Citations86
Published2019
Admission routes1
Has abstractyes

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