Abstract ↔ claims

run not observed · v1 provisional awaiting approval

Which claims does the abstract carry, and which does it drop?

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

Abstract mapped to claims

The paper's abstract is shown with each sentence linked to the claim(s) it represents in the dependency graph. Hover or click a sentence to highlight the corresponding claim cards. Below: what the graph contains that the abstract leaves out, and vice versa.

Abstract

1Monitoring GABAergic inhibition in the nervous system has been enabled by the development of an intensiometric molecular sensor that directly detects GABA. 2However, the first generation iGABASnFR exhibits low signal-to-noise and suboptimal kinetics, making in vivo experiments challenging. 3To improve sensor performance, we targeted several sites in the protein for near-saturation mutagenesis and evaluated the resulting sensor variants in a high-throughput screening system using evoked synaptic release in primary cultured neurons. 4This identified a sensor variant, iGABASnFR2, with 4.1-fold improved sensitivity and 30% faster rise time, and binding affinity that remained in a range sensitive to changes in GABA concentration at synapses. 5We also identified sensors with an inverted response, decreasing fluorescence intensity upon GABA binding. 6We termed the best such negative-going sensor iGABASnFR2n, which can be used to corroborate observations with the positive-going sensor. 7These improvements yielded a qualitative enhancement of in vivo performance when compared directly to the original sensor. 8iGABASnFR2 enabled the first measurements of direction-selective GABA release in the retina. 9In vivo imaging in somatosensory cortex revealed that iGABASnFR2 can report volume-transmitted GABA release following whisker stimulation. 10Overall, the improved sensitivity and kinetics of iGABASnFR2 make it a more effective tool for imaging GABAergic transmission in intact neural circuits.

[1]
no corresponding claim in the graph
[2]
no corresponding claim in the graph
[3]
no corresponding claim in the graph
[4]
direct map → H2.P2.2 · iGABASnFR2 exhibits a 4.1-fold improvement in ΔF/F sensitivity compared to iGABA, D7 · At 10 action potentials (83 Hz), iGABASnFR2 has a rise time constant of 43 ± 9 m, D8 · iGABASnFR2 expressed on the surface of cultured neurons has an on-cell EC50 of 6
[5]
direct map → H2.P2.3 · A negative-going variant (iGABASnFR2n) achieves -2.2-fold ΔF/F with 10.3-fold in
[6]
direct map → H2.P2.3 · A negative-going variant (iGABASnFR2n) achieves -2.2-fold ΔF/F with 10.3-fold in
[7]
synthesis across claims → H1 · A sufficiently improved GABA sensor will cross qualitative capability thresholds, H1.P1 · iGABASnFR2 should enable single-bouton, single-trial DS, and in vivo whisker-evo
[8]
direct map → H1.P1.2 · iGABASnFR2 directly demonstrates direction-selective GABA release from starburst
[9]
direct map → H1.P1.1 · iGABASnFR2 detects volume-transmitted extracellular GABA signals in vivo in mous
[10]
synthesis across claims → H2 · Targeted saturation mutagenesis of the Pf622 binding pocket and cpGFP linkers ca, H1 · A sufficiently improved GABA sensor will cross qualitative capability thresholds
Claims in the graph not surfaced in the abstract
  • H2.P2.1 igabasnfr2-13fold-expression-increase fig1C
    iGABASnFR2 shows a 13.1-fold increase in responsive pixels (expression-weighted response) compared to iGABASnFR1, indicating both improved sensitivity and membrane trafficking.
  • M1 crystal-structure-pdb-9d57 fig3 (or structural supplement)
    The crystal structure of iGABASnFR2 is deposited at the Protein Data Bank (accession 9D57), providing atomic-resolution structural information on the binding pocket and cpGFP domain arrangement.
  • I1 igabasnfr2-cpgfp-rigid-on-gaba-binding fig3a
    GABA binding to iGABASnFR2 closes the Venus flytrap lobes of the Pf622 domain but produces negligible conformational change in cpGFP and its flanking linkers (RMSD 0.25 Å), contrasting with the large cpGFP interface rearrangement seen in GCaMP upon calcium binding.
  • D10 igabasnfr2-single-exponential-kinetics fig4c, fig4d
    iGABASnFR2 and iGABASnFR2n display single-exponential stopped-flow kinetics, whereas iGABASnFR1 exhibits biphasic kinetics; the observed reaction rate constants (Kobs) are far greater for both v2 sensors than for iGABASnFR1.
  • D2 igabasnfr2-2p-compatible fig4e, fig4f, fig4-supplement3
    iGABASnFR2 has two-photon excitation spectra similar to its one-photon spectra and is compatible with two-photon imaging; both v2 sensors show reduced pH dependence compared to iGABASnFR1.
  • C1 igabasnfr2-gaba-selective-specificity fig4-supplement1, fig4-supplement2
    iGABASnFR2 displays high selectivity for GABA over structurally related compounds, none of which interfere with GABA binding as competitive or non-competitive antagonists at 1 mM concentrations.
  • H1.P1.3 igabasnfr2-single-bouton-hippocampus fig6a, fig6b
    iGABASnFR2 detects GABA release from individual hippocampal interneuron axonal boutons using Tornado scanning two-photon microscopy; iGABASnFR1 failed to produce any detectable spike-evoked fluorescence signal across 15 trials in five separate experiments.

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.

extract/prompts/abstract-map.mdthe prompt it runs undernot in the repository

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

Versions

From the run ledger. There is no changelog beside it to keep in step.

  1. v1 · 2026-04-20 · unrecorded backfilled from the artifact

    backfilled from the artifact on disk

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

PaperStateVersionLast runOutputCell
A three-dimensional immunofluorescence atlas of the …backfilled from the artifact on diskrun not observedv12026-04-20artiushin-2026-spider-atlas.jsonjson
Distinct representational properties of cues and con…backfilled from the artifact on diskrun not observedv12026-04-20bouyeure-2026-fear-rsa.jsonjson
Computational modelling identifies key determinants …backfilled from the artifact on diskrun not observedv12026-04-20ejdrup-2026-dopamine.jsonjson
Contributions of insula and superior temporal sulcus…re-run for the current treestalev52026-09-12gadeke-2026-guilt-insula.jsonjson
Spatially targeted inhibitory rhythms differentially…backfilled from the artifact on diskrun not observedv12026-04-19headley-2026-inhibitory-rhythms.jsonjson
Feedback of peripheral saccade targets to early fove…backfilled from the artifact on diskrun not observedv12026-04-19kammer-2026-foveal-feedback.jsonjson
iGABASnFR2 is an improved genetically encoded protei…backfilled from the artifact on diskrun not observedv12026-04-20kolb-2026-igabasnfr2.jsonjson
A deep learning pipeline for mapping in situ network…backfilled from the artifact on diskrun not observedv12026-04-20rozak-2026-neurovascular-dl.jsonjson
Self-association enhances early attentional selectio…backfilled from the artifact on diskrun not observedv12026-04-20scheller-2026-self-prioritization.jsonjson
Impaired excitability of fast-spiking neurons in a n…backfilled from the artifact on diskrun not observedv12026-04-20wengert-2026-kcnc1.jsonjson

Inputs and outputs

Reads, besides its dependencies
Produces
  • site/src/data/abstract-mapping/{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> abstract-map

Underneath, that runs cd extract && python3 -m claim_graphs.cli abstract-map --paper {paper}.