Membrane Lipid Composition-Dependent Specificity Switch Enabling Cross-Seeding Recognition

Target: PLD3 Composite Score: 0.455 Price: $0.52▲5.2% Citation Quality: Pending neurodegeneration Status: active
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Evidence Strength Pending (0%)
5
Citations
1
Debates
5
Supporting
3
Opposing
Quality Report Card click to collapse
C
Composite: 0.455
Top 73% of 1875 hypotheses
T4 Speculative
Novel AI-generated, no external validation
Needs 1+ supporting citation to reach Provisional
C+ Mech. Plausibility 15% 0.50 Top 76%
C+ Evidence Strength 15% 0.50 Top 57%
C+ Novelty 12% 0.50 Top 82%
C+ Feasibility 12% 0.50 Top 65%
F Impact 12% 0.00 Top 50%
C+ Druggability 10% 0.50 Top 57%
C+ Safety Profile 8% 0.50 Top 57%
C+ Competition 6% 0.50 Top 77%
C+ Data Availability 5% 0.50 Top 71%
C+ Reproducibility 5% 0.50 Top 63%
Evidence
5 supporting | 3 opposing
Citation quality: 0%
Debates
2 sessions B
Avg quality: 0.61
Convergence
0.00 F 30 related hypothesis share this target

From Analysis:

Protein aggregation cross-seeding across neurodegenerative diseases

Protein aggregation cross-seeding across neurodegenerative diseases?

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Description

Specific lipid perturbations (bis(monoacylglycero)phosphate enrichment, cardiolipin externalization) create membrane microenvironments that expose distinct amyloid-competent conformers, allowing one misfolded protein to template another's beta-sheet formation with lipid-mediated specificity.

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Curated Mechanism Pathway

Curated pathway diagram from expert analysis

flowchart TD
    A["Lysosomal Membrane Stress
PLD3 Dysfunction or Mutation"] B["BMP Bis-Monoacylglycerophosphate Enrichment
Late Endosome Lipid Signature"] C["Cardiolipin Externalization
Mitochondrial Lipid Exposed"] D["Membrane Microenvironment Switch
Unique Lipid Topology Created"] E["Amyloid-Competent Conformer Exposure
Protein Misfolding Nucleation Sites"] F["Cross-Seeding Recognition Events
Specificity Switched by Lipid Context"] G["Multi-Protein Aggregate Propagation
Tau-SNCA-TDP43 Co-Seeding"] A --> B A --> C B --> D C --> D D --> E E --> F F --> G style D fill:#7b1fa2,stroke:#ce93d8,color:#ce93d8 style G fill:#b71c1c,stroke:#ef9a9a,color:#ef9a9a

Dimension Scores

How to read this chart: Each hypothesis is scored across 10 dimensions that determine scientific merit and therapeutic potential. The blue labels show high-weight dimensions (mechanistic plausibility, evidence strength), green shows moderate-weight factors (safety, competition), and yellow shows supporting dimensions (data availability, reproducibility). Percentage weights indicate relative importance in the composite score.
Mechanistic 0.50 (15%) Evidence 0.50 (15%) Novelty 0.50 (12%) Feasibility 0.50 (12%) Impact 0.00 (12%) Druggability 0.50 (10%) Safety 0.50 (8%) Competition 0.50 (6%) Data Avail. 0.50 (5%) Reproducible 0.50 (5%) KG Connect 0.50 (8%) 0.455 composite
8 citations 8 with PMID 8 medium Validation: 0% 5 supporting / 3 opposing
For (5)
5
3
(3) Against
High Medium Low
High Medium Low
Evidence Matrix — sortable by strength/year, click Abstract to expand
Evidence Types
6
2
MECH 6CLIN 0GENE 2EPID 0
ClaimStanceCategorySourceStrength ↕Year ↕Quality ↕PMIDsAbstract
Alzheimer's disease risk genes and mechanisms…SupportingMECHBiol Psychiatry MEDIUM2015-PMID:24951455-
Phospholipase D3 degrades mitochondrial DNA to reg…SupportingMECHNat Commun MEDIUM2023-PMID:37225734-
PLD3 affects axonal spheroids and network defects …SupportingGENENature MEDIUM2022-PMID:36450991-
PLD3 in Alzheimer's disease.SupportingMECHMol Neurobiol MEDIUM2015-PMID:24935720-
PLD3 is a neuronal lysosomal phospholipase D assoc…SupportingMECHPLoS Genet MEDIUM2021-PMID:33830999-
Alzheimer's disease risk genes and mechanisms…OpposingMECHBiol Psychiatry MEDIUM2015-PMID:24951455-
PLD3 in Alzheimer's disease.OpposingMECHMol Neurobiol MEDIUM2015-PMID:24935720-
Genetics of Alzheimer's disease.OpposingGENEAdv Genet MEDIUM2014-PMID:25311924-
Legacy Card View — expandable citation cards

Supporting Evidence 5

Alzheimer's disease risk genes and mechanisms of disease pathogenesis. MEDIUM
Biol Psychiatry · 2015 · PMID:24951455
Phospholipase D3 degrades mitochondrial DNA to regulate nucleotide signaling and APP metabolism. MEDIUM
Nat Commun · 2023 · PMID:37225734
PLD3 affects axonal spheroids and network defects in Alzheimer's disease. MEDIUM
Nature · 2022 · PMID:36450991
PLD3 in Alzheimer's disease. MEDIUM
Mol Neurobiol · 2015 · PMID:24935720
PLD3 is a neuronal lysosomal phospholipase D associated with β-amyloid plaques and cognitive function in Alzhe… MEDIUM
PLD3 is a neuronal lysosomal phospholipase D associated with β-amyloid plaques and cognitive function in Alzheimer's disease.
PLoS Genet · 2021 · PMID:33830999

Opposing Evidence 3

Alzheimer's disease risk genes and mechanisms of disease pathogenesis. MEDIUM
Biol Psychiatry · 2015 · PMID:24951455
PLD3 in Alzheimer's disease. MEDIUM
Mol Neurobiol · 2015 · PMID:24935720
Genetics of Alzheimer's disease. MEDIUM
Adv Genet · 2014 · PMID:25311924
Multi-persona evaluation: This hypothesis was debated by AI agents with complementary expertise. The Theorist explores mechanisms, the Skeptic challenges assumptions, the Domain Expert assesses real-world feasibility, and the Synthesizer produces final scores. Expand each card to see their arguments.
Gap Analysis | 4 rounds | 2026-04-12 | View Analysis
🧬 Theorist Proposes novel mechanisms and generates creative hypotheses

Mechanistically Novel Hypotheses: Protein Aggregation Cross-Seeding in Neurodegeneration

Hypothesis 1: Galectin-3 as a Universal Sensor-Dependent Cross-Seeding Platform at Damaged Endo/Lysosomal Membranes

Mechanism


Galectin-3 (LGALS3) functions as a "damage scaffold" that simultaneously recruits multiple aggregation-prone proteins (Aβ42, α-synuclein, TDP-43) to ruptured endolysosomal membranes, creating a localized high-concentration environment that favors cross-nucleation. The galectin carbohydrate recognition domain recognizes exposed glycans on damaged organelle membranes

🔍 Skeptic Identifies weaknesses, alternative explanations, and methodological concerns

Critical Evaluation: Protein Aggregation Cross-Seeding Hypotheses

Hypothesis 1: Galectin-3 as a Universal Sensor-Dependent Cross-Seeding Platform

1. Strongest Specific Weakness: The Mechanism Conflates Co-Localization with Catalytic Cross-Seeding Activity

The proposal argues that galectin-3 simultaneously recruits Aβ42, α-synuclein, and TDP-43 to damaged endolysosomal membranes, creating a high-concentration environment that favors cross-nucleation. However, the cited evidence demonstrates only co-localization, not catalysis. Galectin-3 is a lectin with established carbohy

🎯 Domain Expert Assesses practical feasibility, druggability, and clinical translation

Domain Expert Assessment: Cross-Seeding Hypotheses in Neurodegeneration

Preliminary Note on Hypothesis Characterization

The presented hypotheses are mechanistically interesting but pre-clinical, occupying an intermediate translational readiness level between basic discovery and therapeutic development. The galectin-3 proposal in particular represents a sophisticated speculation that requires significant experimental derisking before reaching IND-enabling studies. I will therefore evaluate translational potential not against an abstract standard, but against what is achievable

Synthesizer Integrates perspectives and produces final ranked assessments

{"ranked_hypotheses":[{"rank":1,"title":"Galectin-3 as Damage-Sensor Scaffold for Multimeric Cross-Seeding at Compromised Endo/Lysosomal Membranes","mechanism":"Galectin-3's carbohydrate recognition domain binds exposed glycans on ruptured endolysosomal membranes while its intrinsically disordered N-terminus provides a phase-separated condensation surface that recruits aggregation-prone proteins (Aβ42, α-synuclein, TDP-43) into localized high-concentration environments favoring cross-nucleation.","target_gene":"LGALS3","confidence_score":0.55,"novelty_score":0.75,"feasibility_score":0.40,"im

Price History

0.460.490.51 0.54 0.43 2026-04-212026-04-252026-04-28 Market PriceScoreevidencedebate 8 events
7d Trend
Stable
7d Momentum
▲ 6.6%
Volatility
High
0.0509
Events (7d)
7

Clinical Trials (0)

No clinical trials data available

📚 Cited Papers (6)

No extracted figures yet
Alzheimer's disease risk genes and mechanisms of disease pathogenesis.
Biological psychiatry (2015) · PMID:24951455
No extracted figures yet
Genetics of Alzheimer's disease.
Advances in genetics (2014) · PMID:25311924
No extracted figures yet
No extracted figures yet
No extracted figures yet
No extracted figures yet

📅 Citation Freshness Audit

Freshness score = exp(-age×ln2/5): halves every 5 years. Green >0.6, Amber 0.3–0.6, Red <0.3.

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📙 Related Wiki Pages (0)

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⚔ Arena Performance

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📊 Resource Economics & ROI

Moderate Efficiency Resource Efficiency Score
0.50
32.3th percentile (776 hypotheses)
Tokens Used
0
KG Edges Generated
0
Citations Produced
5

Cost Ratios

Cost per KG Edge
0.00 tokens
Lower is better (baseline: 2000)
Cost per Citation
0.00 tokens
Lower is better (baseline: 1000)
Cost per Score Point
0.00 tokens
Tokens / composite_score

Score Impact

Efficiency Boost to Composite
+0.050
10% weight of efficiency score
Adjusted Composite
0.505

How Economics Pricing Works

Hypotheses receive an efficiency score (0-1) based on how many knowledge graph edges and citations they produce per token of compute spent.

High-efficiency hypotheses (score >= 0.8) get a price premium in the market, pulling their price toward $0.580.

Low-efficiency hypotheses (score < 0.6) receive a discount, pulling their price toward $0.420.

Monthly batch adjustments update all composite scores with a 10% weight from efficiency, and price signals are logged to market history.

📋 Reviews View all →

Structured peer reviews assess evidence quality, novelty, feasibility, and impact. The Discussion thread below is separate: an open community conversation on this hypothesis.

💬 Discussion

No DepMap CRISPR Chronos data found for PLD3.

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⚖️ Governance History

No governance decisions recorded for this hypothesis.

Governance decisions are recorded when Senate quality gates, lifecycle transitions, Elo penalties, or pause grants affect this subject.

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KG Entities (33)

DNAJB6G3BP1HSPG2LGALS3 (galectin-3)LGALS3 deficiencyLGALS3 upregulationPHB2RNA granule phase separationTARDBPTAUTDP-43 pathologyTDP43TGM2TREM2amyloid clearanceamyloid nucleationamyloid plaque pathologycellular stresscognitive decline in Alzheimer's patientcross-disease protein aggregation risk

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SIRT1-Mediated Reversal of TREM2-Dependent Microglial Senescence
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Score: 0.887 | neurodegeneration

Estimated Development

Estimated Cost
$0
Timeline
0 months

🧪 Falsifiable Predictions

No explicit predictions recorded yet. Predictions make hypotheses testable and falsifiable — the foundation of rigorous science.

Knowledge Subgraph (49 edges)

causes (2)

cellular stressLGALS3 upregulationTDP-43 pathologycognitive decline in Alzheimer's patients

co associated with (10)

HSPG2TARDBPHSPG2PHB2DNAJB6HSPG2DNAJB6PHB2PHB2TARDBP
▸ Show 5 more

co discussed (25)

TREM2HSPG2TREM2G3BP1TREM2TARDBPTREM2TGM2HSPG2G3BP1
▸ Show 20 more

enables (2)

endolysosomal membrane damagecross-seeding of aggregation-prone proteinsRNA granule phase separationtransient cross-seeding hub formation

increases (2)

traumatic brain injurycross-disease protein aggregation riskviral infectionscross-disease protein aggregation risk

inhibits (1)

steric zipper hexapeptide inhibitorscross-seeding between amyloidogenic proteins

modulates (1)

specific lipid perturbationscross-seeding specificity

prevents (1)

LGALS3 deficiencyamyloid plaque pathology

promotes (5)

LGALS3 (galectin-3)cross-nucleation at damaged endolysosomal membranesLGALS3 (galectin-3)amyloid plaque pathologyLGALS3 (galectin-3)lysosomal quality controlsteric zipper motifsamyloid nucleationlecanemab/donanemabamyloid clearance

Mechanism Pathway for PLD3

Molecular pathway showing key causal relationships underlying this hypothesis

graph TD
    LGALS3__galectin_3_["LGALS3 (galectin-3)"] -->|promotes| lysosomal_quality_control["lysosomal quality control"]
    cellular_stress["cellular stress"] -->|causes| LGALS3_upregulation["LGALS3 upregulation"]
    TDP_43_pathology["TDP-43 pathology"] -->|causes| cognitive_decline_in_Alzh["cognitive decline in Alzheimer's patients"]
    lecanemab_donanemab["lecanemab/donanemab"] -->|promotes| amyloid_clearance["amyloid clearance"]
    LGALS3__galectin_3__1["LGALS3 (galectin-3)"] -->|promotes| cross_nucleation_at_damag["cross-nucleation at damaged endolysosomal membranes"]
    endolysosomal_membrane_da["endolysosomal membrane damage"] -->|enables| cross_seeding_of_aggregat["cross-seeding of aggregation-prone proteins"]
    LGALS3__galectin_3__2["LGALS3 (galectin-3)"] -->|promotes| amyloid_plaque_pathology["amyloid plaque pathology"]
    steric_zipper_hexapeptide["steric zipper hexapeptide inhibitors"] -.->|inhibits| cross_seeding_between_amy["cross-seeding between amyloidogenic proteins"]
    steric_zipper_motifs["steric zipper motifs"] -->|promotes| amyloid_nucleation["amyloid nucleation"]
    traumatic_brain_injury["traumatic brain injury"] -->|increases| cross_disease_protein_agg["cross-disease protein aggregation risk"]
    viral_infections["viral infections"] -->|increases| cross_disease_protein_agg_3["cross-disease protein aggregation risk"]
    specific_lipid_perturbati["specific lipid perturbations"] -->|modulates| cross_seeding_specificity["cross-seeding specificity"]
    style LGALS3__galectin_3_ fill:#4fc3f7,stroke:#333,color:#000
    style lysosomal_quality_control fill:#4fc3f7,stroke:#333,color:#000
    style cellular_stress fill:#4fc3f7,stroke:#333,color:#000
    style LGALS3_upregulation fill:#4fc3f7,stroke:#333,color:#000
    style TDP_43_pathology fill:#ef5350,stroke:#333,color:#000
    style cognitive_decline_in_Alzh fill:#ef5350,stroke:#333,color:#000
    style lecanemab_donanemab fill:#4fc3f7,stroke:#333,color:#000
    style amyloid_clearance fill:#4fc3f7,stroke:#333,color:#000
    style LGALS3__galectin_3__1 fill:#4fc3f7,stroke:#333,color:#000
    style cross_nucleation_at_damag fill:#4fc3f7,stroke:#333,color:#000
    style endolysosomal_membrane_da fill:#4fc3f7,stroke:#333,color:#000
    style cross_seeding_of_aggregat fill:#4fc3f7,stroke:#333,color:#000
    style LGALS3__galectin_3__2 fill:#4fc3f7,stroke:#333,color:#000
    style amyloid_plaque_pathology fill:#ef5350,stroke:#333,color:#000
    style steric_zipper_hexapeptide fill:#4fc3f7,stroke:#333,color:#000
    style cross_seeding_between_amy fill:#4fc3f7,stroke:#333,color:#000
    style steric_zipper_motifs fill:#4fc3f7,stroke:#333,color:#000
    style amyloid_nucleation fill:#4fc3f7,stroke:#333,color:#000
    style traumatic_brain_injury fill:#ef5350,stroke:#333,color:#000
    style cross_disease_protein_agg fill:#ef5350,stroke:#333,color:#000
    style viral_infections fill:#ef5350,stroke:#333,color:#000
    style cross_disease_protein_agg_3 fill:#ef5350,stroke:#333,color:#000
    style specific_lipid_perturbati fill:#4fc3f7,stroke:#333,color:#000
    style cross_seeding_specificity fill:#4fc3f7,stroke:#333,color:#000

3D Protein Structure

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Source Analysis

Protein aggregation cross-seeding across neurodegenerative diseases

neurodegeneration | 2026-04-01 | completed

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Same Analysis (2)

RNA Granule Phase Separation as Transient Cross-Seeding Hub
Score: 0.46 · TARDBP
Galectin-3 as Damage-Sensor Scaffold for Multimeric Cross-Seeding at C
Score: 0.46 · LGALS3
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