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Record W2056471358 · doi:10.1002/rcm.4340

The use of selected ion flow tube mass spectrometry to detect and quantify polyamines in headspace gas and oral air

2009· article· en· W2056471358 on OpenAlexaff
Brian Ross, Slim Babay, Chelsea Ladouceur

Bibliographic record

VenueRapid Communications in Mass Spectrometry · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPolyamine Metabolism and Applications
Canadian institutionsNOSM UniversityLakehead UniversityScience North
Fundersnot available
KeywordsChemistryMass spectrometryChromatographyTube (container)Ion-mobility spectrometryIonFlow (mathematics)Analytical Chemistry (journal)Organic chemistryMechanicsWaste management

Abstract

fetched live from OpenAlex

Polyamines are a class of aliphatic compounds which include putrescine, cadaverine, spermine and spermidine. They are involved in a variety of cellular processes and have been implicated in a number of different pathophysiological mechanisms. Polyamines are volatile compounds having a distinctive odour normally perceived as being unpleasant. The measurement of their abundance has, however, been restricted to compounds present in the aqueous phase. Using selected ion flow tube mass spectrometry (SIFT-MS) we have shown that the polyamines react with the ions H3O+, NO+ and O2+ to form distinctive product ions allowing their levels to be quantified in the vapour phase. The low volatility of spermine did not allow extensive analysis of this compound by SIFT-MS while the adherent properties of cadaverine and putrescine required the use of PTFE transfer lines and couplers. Our data suggested the presence of cadaverine and putrescine in both oral air and the headspace of putrefying bovine muscle, while product ions corresponding to putrescine and spermidine were found in the headspace of human semen. SIFT-MS therefore appears to be a practical means of measuring vapour-phase polyamine levels, having applications in biology, medicine and dentistry, and food science.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.614
Threshold uncertainty score0.729

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.022
GPT teacher head0.286
Teacher spread0.264 · 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

Citations13
Published2009
Admission routes1
Has abstractyes

Explore more

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