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Record W4220871624 · doi:10.1101/2022.03.23.485486

Filter paper disks as a matrix for manipulation of recombinant proteins

2022· preprint· en· W4220871624 on OpenAlex
Eric H. Ball, Nicoletta T. Basilone

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

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Biosensing Techniques and Applications
Canadian institutionsWestern University
Fundersnot available
KeywordsLinkerFusion proteinElutionRecombinant DNAChromatographyCovalent bondChemistryMatrix (chemical analysis)Binding domainProteaseFilter paperFilter (signal processing)BiochemistryBinding siteComputer scienceGeneEnzymeOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Filter paper provides an excellent matrix for retention of proteins containing a cellulose binding domain. To use this capability for manipulating recombinant fusion proteins, binding and elution parameters were explored and procedures developed for small scale purification, modification and assay. Proteins were tagged with the cellulose binding domain from the C thermocellum CipB gene via a cleavable linker. Filter paper disks of 6mm diameter were able to bind up to 80 μg protein although there was a substantial dependence on molecular size. Different means of introducing fusion proteins to the disks allow either binding within 20 minutes from microliter volumes or slower binding from milliliter volumes. Elution with protease in small volumes yielded greater than 10 μg amounts with concentrations in the 1-2 mg/ml range. To demonstrate their utility, disks were used for small scale protein purification, covalent modification of protein, immunoprecipitation, and in a binding assay. These versatile methods allow parallel processing of multiple samples and may find many uses when only small amounts of protein are needed.

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 categoriesMeta-epidemiology (narrow)
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 score0.116
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 science0.0000.001
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 head0.016
GPT teacher head0.274
Teacher spread0.258 · 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