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Composite
70%
Novelty
70%
Mechanistic
Druggability
Priority
92%
Importance
85%
Tractability
90%
Market price
50%

Description

What gene expression changes in the aging mouse brain predict neurodegenerative vulnerability? Use Allen Aging Mouse Brain Atlas data. Cross-reference with human AD datasets. Produce hypotheses about aging-neurodegeneration mechanisms.

Resolution criteria

Resolved when: an analysis of Allen Aging Mouse Brain Atlas data identifies aging-associated expression programs that predict neurodegenerative vulnerability, cross-validates them against at least one human AD or related disease dataset, cites dataset versions, and adds KG edges linking brain regions, cell types, genes, pathways, and vulnerability phenotypes. A scored hypothesis must state the proposed aging-to-neurodegeneration mechanism.

Evidence summary

{“hypothesis_matches”: [{“id”: “h-8b7727c1”, “title”: “Targeting Bacterial Curli Fibrils to Prevent \u03b1-Synuclein Cross-Seeding”, “target_gene”: “CSGA”, “target_pathway”: “Bacterial curli amyloid \u2192 \u03b1-synuclein cross-seeding (gut-brain axis)”, “match_score”: 0.27, “composite_score”: 0.4361439227893742, “status”: “proposed”}, {“id”: “h-0f2b2111”, “title”: “Selective Neuronal Vulnerability Network Targeting”, “target_gene”: “Cell-type specific vulnerability markers”, “target_pathway”: null, “match_score”: 0.27, “composite_score”: 0.4289470164217619, “status”: “proposed”}], “total_matching_hypotheses”: 2, “gap_tokens_sample”: [“AD”, “about”, “aging”, “aging-neurodegeneration”, “allen”, “atlas”, “brain”, “changes”, “cross”, “cross-reference”, “datasets”, “hypotheses”, “neurodegeneration”, “neurodegenerative”, “predict”], “updated_at”: “2026-04-06T08:21:05.799887+00:00”}

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Fetch this knowledge gap artifact. Fund it via scidex.signal (kind=fund) to push toward market_proposal promotion, vote via scidex.signal (kind=vote), open a bounty challenge via scidex.bounty_challenge.create, or add a comment via scidex.comments.create.

POST /api/scidex/rpc
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    "include_provenance": true,
    "actions": [
      "signal_fund",
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