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Record W2325165981 · doi:10.1021/bc300551j

<i>In Vivo</i> Self-Assembly of Fluorescent Protein Microparticles Displaying Specific Binding Domains

2013· article· en· W2325165981 on OpenAlexfundno aff
Anika C. Jahns, Yogananda Maspolim, Shuxiong Chen, Jenness M. Guthrie, L. F. Blackwell, Bernd H. A. Rehm

Bibliographic record

VenueBioconjugate Chemistry · 2013
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Surface Interaction Studies
Canadian institutionsnot available
FundersPublic Health Agency of Canada
KeywordsChemistryFluorescenceIn vivoFluorescent proteinBiophysicsCell biologyNanotechnologyGreen fluorescent proteinBiochemistryBiotechnology

Abstract

fetched live from OpenAlex

In this study, fluorescent proteins (FPs) were engineered to self-assemble into protein particles inside recombinant Escherichia coli while mediating the display of various protein functionalities such as maltose binding protein or IgG binding domains of Protein A or G, respectively. Escherichia coli produced functional FP particles of up to 30% of cellular dry weight. The use of respective FP particles displaying certain binding domains in diagnostics and as bioseparation resins was demonstrated by direct comparison to commercial offerings. It was demonstrated that variable extensions (AVTS, FHKP, LAVG, or TS) of the N-terminus of FPs (GFP, YFP, CFP, HcRed) in combination with large C-terminal extensions such as translational fusion of the polyester synthase from Ralstonia eutropha or an aldolase from Escherichia coli led to extensive intracellular self-assembly of strongly fluorescent fusion protein particles of oval shape (0.5×1 μm). The strong fluorescent label of these bioparticles in combination with covalent display of protein functions provides a molecular toolbox for the design of self-assembled microparticles suitable for antibody-capture or ligand binding based diagnostic assays as well as the high affinity purification of target compounds such as antibodies.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.001
Threshold uncertainty score1.000

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)0.0010.000

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 head0.010
GPT teacher head0.232
Teacher spread0.222 · 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.

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

Citations17
Published2013
Admission routes1
Has abstractyes

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