Argument from graph
run not observed provisional awaiting approvalRestated from the claim graph alone, what does this paper argue — and where does that part from its abstract?
for iGABASnFR2 is an improved genetically encoded protein sensor of GABA · this layer across all papers · json
Provisional
This layer needs a corpus-scope decision that has not been ruled on yet, so what it produces would change if the decision changed. It waits on claim-format, relation-vocab.
Awaiting approval
Waiting for approval. That is a statement about the record, not about whether anyone has read this: people read the corpus without stamping what they read, and only a stamp leaves a trace. Approval is an operation on a version, not a step of its own — it is recorded against the version it was granted to, so running this layer again does not carry it forward.
What this layer produced
Argument from the graph3
An LLM was given only this paper's enriched claim graph — claims, panel references, roles, and the relations between them — with no access to the abstract, paper prose, or any external context. It was asked to reconstruct the argument. Below: the reconstructed argument, then a comparison to the published abstract above. The two prompts that produced these texts are at the bottom, available for inspection.
Reconstructed argument
The paper advances a two-part thesis: first, that the performance ceiling of iGABASnFR1 is set by suboptimal residues at structurally identifiable positions in and around the GABA-binding pocket and cpGFP-linker interfaces, so that near-saturation mutagenesis at those sites should yield a substantially improved successor; second, that a sensor with sufficiently improved sensitivity, affinity, and kinetics will cross qualitative capability thresholds, enabling measurements that iGABASnFR1 cannot make at all rather than merely improving signal-to-noise on existing ones. The design phase tests the first hypothesis through a screen of 3,947 variants in cultured neurons. This yields iGABASnFR2 with a fourfold gain in sensitivity, a 13-fold increase in expression, and a negative-going variant (iGABASnFR2n) -- outcomes consistent with the prediction that the screen should produce multiple qualitatively distinct improvements rather than marginal single-site gains. The validation phase establishes that these gains reflect independent improvements across multiple biophysical axes. On-cell affinity increases sevenfold (EC50 of 6.4 uM versus 45 uM for v1) while remaining above tonic extracellular GABA. Stopped-flow kinetics shift from biphasic to single-exponential with faster rate constants, and on-cell rise kinetics also improve. Crystal structures (PDB: 9D57) reveal negligible cpGFP conformational change on GABA binding, dissociating the fluorescence mechanism from the large rearrangement seen in GCaMP. Two-photon compatibility and reduced pH dependence are confirmed. Selectivity testing rules out the possibility that the sensitivity gain reflects broader ligand promiscuity. The application phase tests the second hypothesis through three demanding preparations that each dissociate from the others in tissue, circuit, and imaging regime. iGABASnFR2 detects GABA release from individual hippocampal interneuron boutons where iGABASnFR1 produces no detectable signal across 15 trials. In retina, it resolves direction-selective GABA release from starburst amacrine cells on single trials, whereas iGABASnFR1 cannot resolve direction selectivity even after trial-averaging. In vivo, it detects whisker-evoked volume-transmitted GABA in barrel cortex layers 2-3. Each application is independently validated by the selectivity controls and enabled by two-photon compatibility. The convergence of three dissociated preparations on the same conclusion -- that iGABASnFR2 crosses capability thresholds -- confirms the overarching hypothesis. All findings are scoped to mammalian preparations using wet-lab screening, purified-protein biophysics, ex vivo retina and hippocampal slice, and in vivo cranial-window imaging in standard laboratory mouse and rat; the paper does not test iGABASnFR2 in awake behaving animals at fine temporal resolution or in non-mammalian systems.
▸ Show traceback (13 synthesis sentences)
- The paper advances a two-part thesis: first, that the performance ceiling of iGABASnFR1 is set by suboptimal residues at structurally identifiable positions in and around the GABA-binding pocket and cpGFP-linker interfaces, so that near-saturation mutagenesis at those sites should yield a substantially improved successor; second, that a sensor with sufficiently improved sensitivity, affinity, and kinetics will cross qualitative capability thresholds, enabling measurements that iGABASnFR1 cannot make at all rather than merely improving signal-to-noise on existing ones.
- The design phase tests the first hypothesis through a screen of 3,947 variants in cultured neurons, yielding iGABASnFR2 with a fourfold gain in sensitivity, a 13-fold increase in expression, and a negative-going variant -- outcomes consistent with the prediction that the screen should produce multiple qualitatively distinct improvements rather than marginal single-site gains.H2.P2.4 · High-throughput mutagenesis screening generated 3,947 total variants from 39 tarH2.P2.2 · iGABASnFR2 exhibits a 4.1-fold improvement in ΔF/F sensitivity compared to iGABAH2.P2.1 · iGABASnFR2 shows a 13.1-fold increase in responsive pixels (expression-weighted H2.P2.3 · A negative-going variant (iGABASnFR2n) achieves -2.2-fold ΔF/F with 10.3-fold inH2.P2 · Saturation mutagenesis should yield multiple variants exceeding iGABASnFR1, at l
- The validation phase establishes that these gains reflect genuinely independent improvements across multiple biophysical axes, not a single underlying change.D8 · iGABASnFR2 expressed on the surface of cultured neurons has an on-cell EC50 of 6D7 · At 10 action potentials (83 Hz), iGABASnFR2 has a rise time constant of 43 ± 9 mD10 · iGABASnFR2 and iGABASnFR2n display single-exponential stopped-flow kinetics, wheH2.P2.2 · iGABASnFR2 exhibits a 4.1-fold improvement in ΔF/F sensitivity compared to iGABA
- On-cell affinity increases sevenfold (EC50 of 6.4 uM versus 45 uM for v1) while remaining above tonic extracellular GABA, and stopped-flow kinetics shift from biphasic to single-exponential with faster observed rate constants.
- Crystal structures reveal that cpGFP and its linkers undergo negligible conformational change on GABA binding (RMSD 0.25 A), dissociating the fluorescence mechanism from the large cpGFP rearrangement seen in GCaMP.
- Two-photon compatibility and reduced pH dependence are confirmed, and selectivity testing rules out the possibility that the sensitivity gain reflects broader ligand promiscuity.
- The application phase tests the second hypothesis through three demanding preparations that each dissociate from the others in tissue, circuit, and imaging regime.
- iGABASnFR2 detects GABA release from individual hippocampal interneuron boutons where iGABASnFR1 produces no detectable signal across 15 trials.
- In retina, it resolves direction-selective GABA release from starburst amacrine cells on single trials, whereas iGABASnFR1 cannot resolve direction selectivity even after trial-averaging.
- In vivo, it detects whisker-evoked volume-transmitted GABA in barrel cortex layers 2-3.
- Each application is independently validated by the selectivity controls and enabled by two-photon compatibility.
- The convergence of three dissociated preparations on the same conclusion confirms the overarching hypothesis that iGABASnFR2 crosses capability thresholds.
- All findings are scoped to mammalian preparations using wet-lab screening, purified-protein biophysics, ex vivo retina and hippocampal slice, and in vivo cranial-window imaging in standard laboratory mouse and rat.
How it is defined
A model answers this layer, so the prompt is the layer. It is reproduced below from the committed file, and it is a declared input — editing it makes every run that used it stale.
The declaration names this path and the repository does not have it. An input that does not exist hashes to nothing, so it cannot make a run stale — the layer is declared to depend on something it is not in fact tracking.
The declaration names this path and the repository does not have it. An input that does not exist hashes to nothing, so it cannot make a run stale — the layer is declared to depend on something it is not in fact tracking.
Artifacts
This layer across the corpus
Across the corpus
9 run not observed · 1 stale·a paper links to its own cell, where this layer's output for it is rendered
Inputs and outputs
- Reads, besides its dependencies
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- extract/prompts/synthesis.md · declared, and not in the repository — it hashes to nothing, so it cannot make a run stale
- extract/prompts/contract/vocabulary.md · declared, and not in the repository — it hashes to nothing, so it cannot make a run stale
- Produces
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- site/src/data/synthesis-v3/{paper}.json
One per paper — the table above links each one that exists.
- Views
-
- document — rendered above, from the artifact itself
- comparison — on the cell page, two versions aligned by the matcher, wherever the ledger holds more than one
Running it
The command comes from the declaration, so this text and what actually runs cannot
diverge. pipeline.py run also runs the unmet dependencies first.
python3 scripts/pipeline.py run <paper> synthesis
Underneath, that runs cd extract && python3 -m claim_graphs.cli synthesis --paper {paper}.