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Record W1965257810 · doi:10.1021/bm201037j

Three-Dimensional Spatial Patterning of Proteins in Hydrogels

2011· article· en· W1965257810 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBiomacromolecules · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Fluorescence Microscopy Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAgaroseSelf-healing hydrogelsChemistryHuman serum albuminFusion proteinMaleimideBiophysicsSerum albuminCombinatorial chemistryBiochemistryPolymer chemistryRecombinant DNA

Abstract

fetched live from OpenAlex

The ability to create three-dimensional biochemical environments that mimic those in vivo is valuable for the elucidation of fundamental biological phenomena and pathways. To this end, we designed a system in which proteins can be photochemically patterned in three dimensions within hydrogels under physiological conditions. Fibroblast growth factor-2 (FGF2) was immobilized within agarose hydrogels that were modified with two-photon labile 6-bromo-7-hydroxycoumarin-protected thiols. Two different methods were developed for FGF2 immobilization. The first procedure relies on the protein containing free cysteines for the formation of disulfide bonds with photoexposed agarose thiols. The second procedure takes advantage of the femtomolar binding partners, human serum albumin (HSA) and albumin binding domain (ABD), which have K(D) values of ~10(-14) M. Here HSA-maleimide was chemically bound to photoexposed agarose thiols, and then the FGF2-ABD fusion protein was added to form a stable complex with the immobilized HSA. The use of orthogonal, physical binding pairs allows protein immobilization under mild conditions and can be broadly applied to any protein expressed as an ABD fusion.

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.

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)0.000
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 score0.037
Threshold uncertainty score0.583

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.016
GPT teacher head0.254
Teacher spread0.238 · 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