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Record W4319079753 · doi:10.1038/s41467-023-35894-6

Macromolecular sheets direct the morphology and orientation of plate-like biogenic guanine crystals

2023· article· en· W4319079753 on OpenAlexfundno aff
Avital Wagner, Alexander Upcher, Raquel Maria, Thorolf Magnesen, Einat Zelinger, Graça Raposo, Benjamin A. Palmer

Bibliographic record

VenueNature Communications · 2023
Typearticle
Languageen
FieldMaterials Science
TopicSupramolecular Self-Assembly in Materials
Canadian institutionsnot available
FundersHelmholtz-Zentrum Berlin für Materialien und EnergieAzrieli FoundationHebrew University of Jerusalem
KeywordsGuanineMelanosomeNucleationMorphology (biology)ChromatophoreCrystallizationMaterials scienceBiophysicsCrystal (programming language)StackingMorphogenesisCrystallographyBiomineralizationVesicleNanotechnologyMelaninChemistryBiologyNucleotideBiochemistryMembrane

Abstract

fetched live from OpenAlex

Animals precisely control the morphology and assembly of guanine crystals to produce diverse optical phenomena in coloration and vision. However, little is known about how organisms regulate crystallization to produce optically useful morphologies which express highly reflective crystal faces. Guanine crystals form inside iridosome vesicles within chromatophore cells called iridophores. By following iridosome formation in developing scallop eyes, we show that pre-assembled, fibrillar sheets provide an interface for nucleation and direct the orientation of the guanine crystals. The macromolecular sheets cap the (100) faces of immature guanine crystals, inhibiting growth along the π-stacking growth direction. Crystal growth then occurs preferentially along the sheets to generate highly reflective plates. Despite their different physical properties, the morphogenesis of iridosomes bears a striking resemblance to melanosome morphogenesis in vertebrates, where amyloid sheets template melanin deposition. The common control mechanisms for melanin and guanine formation inspire new approaches for manipulating the morphologies and properties of molecular materials.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.436

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.301
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations37
Published2023
Admission routes1
Has abstractyes

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