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Record W1967027418 · doi:10.1159/000220659

Benzylpenicillin Toxicity in Albino Rats Fed Synthetic High Starch Versus High Sugar Diets

2009· article· en· W1967027418 on OpenAlexaff
Eldon M. Boyd, Ilona Dobos, Frank Taylor

Bibliographic record

VenueChemotherapy · 2009
Typearticle
Languageen
FieldMedicine
TopicDiet, Metabolism, and Disease
Canadian institutionsQueen's University
Fundersnot available
KeywordsBenzylpenicillinToxicityStarchSugarFood scienceChemistryBiologyTraditional medicineAntibioticsMedicineBiochemistryPenicillinOrganic chemistry

Abstract

fetched live from OpenAlex

The studies reported in this paper were undertaken to investigate the hypothesis of Boyd, Covert and Pitman (Chemotherapia 11: 320, 1966) that the augmented toxicity of benzylpenicillin given orally to albino rates fed a synthetic pyridoxine-deficient diet was due to the presence of large amounts of sucrose in that diet. Benzylpenicillin potassium was given orally in a dose of 5.34 g/kg/day to young adult albino rats fed (a) a diet containing 22 % of casein, 69.4 % of sucrose, 4.0 % of salt mix, 2 % of hydrogenated vegetable oil, 2 % of cod liver oil, 0.5 % of wheat germ oil and adequate vitamin supplements (except pyridoxine) or (b) the same diet but with 69.4 % of cornstarch in place of the 69.4 % sucrose. The death rate and clinicopathologic signs of toxicity to benzylpenicillin were significantly greater in rats fed diet (a) than in those fed diet (b). It was concluded that the fulminating toxicity syndrome seen in animals fed diet (a) was due to a combination of the toxicity of subtoxic amounts of dietary sucrose and sublethal amounts of administered benzylpenicillin over the interval studied.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.286
Teacher spread0.268 · 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

Citations9
Published2009
Admission routes1
Has abstractyes

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