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Record W2121439251 · doi:10.1002/rcm.3941

Urea as a protein destabilizing agent in electrospray ionisation

2009· article· en· W2121439251 on OpenAlexafffund
Lynda J. Donald, V.M. Collado, Jamie J. Galka, Joe D. O’Neil, Harry W. Duckworth, P.C. Loewen, Kenneth G. Standing

Bibliographic record

VenueRapid Communications in Mass Spectrometry · 2009
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsChemistryUreaElectrospray ionizationNon-covalent interactionsMass spectrometryElectrosprayChromatographyCrystallographyMoleculeHydrogen bondBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Urea is well known as a denaturant of proteins, but there is also evidence that millimolar amounts of urea may in fact stabilize protein complexes. Advances in mass spectrometric analysis have given us the opportunity to test the effect of urea on several noncovalent complexes in buffered solutions. We expected to see lower charge states if folded proteins were more compact (and therefore more stable), and higher charge states if the proteins were denatured. We have found that mM urea interferes with some noncovalent interactions, and that the extent of interference depends on the specific protein complex. The difference seems to be related to the type of interactions, with weak ones, such as H-bonds, more sensitive to urea. Examples show that a quick check with urea may give some insights into protein stability in the mass spectrometer.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.023
GPT teacher head0.301
Teacher spread0.278 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2009
Admission routes2
Has abstractyes

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