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Further findings about plant derived extracellular vesicles (AI assisted research / PathMap.org)

PathMap.org proposes a data model for plant-derived extracellular vesicles (PDEV) that treats the 'periodic table' as a view, not the source of truth, and emphasizes preparation- and evidence-aware tracking. The model would store entities, materials, processes, observations, assertions, and evidence, with a v0.1 prototype to test the structure. The approach cites MISEV2023 guidelines and a 2025 ginger EV comparison showing that isolation methods affect yield, stability, and activity.

read2 min views2 publishedAug 27, 2026

After looking more broadly than I did last time, I think I found quite a lot of existing work that PathMap may be able to borrow from:

I think the PDEV + modifier + target + disease idea is a good direction. The one architectural change I would make early is to treat the “periodic table” / graph as a view, not as the source-of-truth data model.

Underneath it, I would keep something closer to:

Entity
  ↓
Material / Preparation
  ↓
Process
  ↓
Observation
  ↓
Assertion + Evidence
  ↓
CandidateAssembly
  ↓
MissingBridge / CompetingAssembly / NextExperiment

Then the same records can generate the three views you described:

So I would keep one canonical ginger / STAT3 / ovarian-cancer object rather than triplicating entities, and generate different projections from it.

The practical reason is that a “ginger EV” is not necessarily one stable object with one size, charge, cargo profile or activity. MISEV2023 puts substantial emphasis on source material, preprocessing, separation, characterization and storage. A useful 2025 ginger comparison also found that ultracentrifugation, sucrose-gradient UC, membrane filtration and PEG precipitation changed not only yield but stability, metabolomic composition and in-vitro activity (Ming et al., 2025).

So my low-cost default route would be:

That last object may be especially useful for PathMap.

For the datapoints you listed, this is roughly how I would store themA small v0.1 would probably be enough to learn whether this structure is useful:

What is directly known?
What is inferred?
What is challenged?
What exact combination was searched?
What bridge is still missing?
What cheap experiment would resolve the most uncertainty?

That would keep the project very close to the direction you already seem to be exploring rather than turning it into a different system.

The “periodic table” idea can remain the friendly interface. The main change would be to give it a preparation- and evidence-aware source of truth underneath.

And the PathMap-specific design target I would personally explore is this:

a near-complete experimental assembly whose individual commitments, evidence, context, contradictions, prior-art search, missing bridges, competing variants and next discriminating experiment are tracked together.

I would be cautious about claiming that exact combination is unprecedented—the neighboring fields are broad and moving quickly—but it looks like a useful object even if every individual piece has prior art elsewhere.

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