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Record W4407058319 · doi:10.1111/jnc.70009

Emerging Roles for MFG‐E8 in Synapse Elimination

2025· review· en· W4407058319 on OpenAlexafffund
Marisa G. Aviani, Fréderic Ménard

Bibliographic record

VenueJournal of Neurochemistry · 2025
Typereview
Languageen
FieldImmunology and Microbiology
TopicPhagocytosis and Immune Regulation
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSynapseNeuroscienceBiologyComputational biologyComputer science

Abstract

fetched live from OpenAlex

Synapse elimination is an essential process in the healthy nervous system and is dysregulated in many neuropathologies. Yet, the underlying molecular mechanisms and under what conditions they occur remain unclear. MFG-E8 is a secreted glycoprotein well known to act as an opsonin, tagging stressed and dying cells for engulfment by phagocytes. Opsonization of cells and debris by MFG-E8 for microglial phagocytosis in the CNS is well established, and its role in astrocytic phagocytosis, and trogocytosis-like engulfment of synapses is beginning to be explored. However, MFG-E8's function in other tissues is highly diverse, and evidence suggests that its role in the nervous system and on synapse elimination in particular may be more complex and varied than opsonization. In this review, we outline the documented direct and indirect effects of MFG-E8 on synapse elimination, while also proposing potential roles to be explored further, in particular, cytoskeletal reorganization of neurites and glia leading to synapse elimination by various mechanisms. Finally, we demonstrate the need for several open questions to be answered-chiefly, under what conditions might MFG-E8-mediated synapse elimination occur in favor of other mechanisms, and when might its activity be dysregulated, increasing unwanted synapse elimination and neurotoxicity?

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
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 head0.021
GPT teacher head0.333
Teacher spread0.312 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations4
Published2025
Admission routes2
Has abstractyes

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