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Record W2040787296 · doi:10.2310/6620.2008.08008

Identification of the Constituents of Balsam of Peru in Tomatoes

2009· article· en· W2040787296 on OpenAlexvenueno aff
Divya Srivastava, David E. Cohen

Bibliographic record

VenueDermatitis · 2009
Typearticle
Languageen
FieldMedicine
TopicContact Dermatitis and Allergies
Canadian institutionsnot available
Fundersnot available
KeywordsIsoeugenolConiferyl alcoholCinnamyl alcoholCinnamic acidChemistryEugenolAlcoholChromatographyLigninOrganic chemistryFood scienceCinnamaldehyde

Abstract

fetched live from OpenAlex

BACKGROUND: Studies show that balsam-restricted diets result in significant improvement of systemic contact dermatitis in patients with contact allergy to balsam of Peru (BOP). While tomatoes have been implicated as a frequent cause of BOP-related dermatitis, the presence of BOP in tomatoes has never been confirmed. OBJECTIVES: High-performance liquid chromatography coupled with mass spectrometry (liquid chromatography [LC]-MS) and UV spectrometry (LC-UV) was used to detect the possible presence of BOP constituents in tomatoes. METHODS: Samples of beefsteak, cherry, and plum tomatoes were extracted in ethyl acetate and analyzed with LC-MS and LC-UV for the presence of the following sensitizing constituents of BOP: benzoic acid, benzyl alcohol, trans-cinnamic acid, cinnamic alcohol, cinnamyl cinnamate, coniferyl alcohol, eugenol, isoeugenol, and methyl cinnamate. RESULTS: The initial LC-MS analysis of each tomato extract showed multiple peaks. Two of these peaks had molecular weights of 134 and 180, which correspond to cinnamic alcohol and coniferyl alcohol, respectively. The analysis did not show peaks corresponding to the molecular weights of the remaining compounds. Cochromatography of tomato extract with cinnamic alcohol and coniferyl alcohol using LC-UV further suggested the presence of these compounds in the tomato extract. CONCLUSION: Coniferyl alcohol and cinnamic alcohol, constituents of BOP, are present in beefsteak, cherry, and plum tomatoes.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.281
Threshold uncertainty score0.153

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 head0.009
GPT teacher head0.253
Teacher spread0.244 · 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 designObservational
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

Citations14
Published2009
Admission routes1
Has abstractyes

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