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Record W2225086507 · doi:10.1096/fasebj.20.5.a1024-d

Dietary gangliosides modulate lipid composition in young rat testis

2006· article· en· W2225086507 on OpenAlexafffundabout
Miyoung Suh, Eek J. Park, M. T. Clandinin

Bibliographic record

VenueThe FASEB Journal · 2006
Typearticle
Languageen
FieldMedicine
TopicLipid metabolism and disorders
Canadian institutionsUniversity of AlbertaUniversity of Manitoba
FundersUniversity of Manitoba
KeywordsGangliosideWeanlingPhosphatidylcholineEndocrinologyComposition (language)CholesterolInternal medicineChemistryTestosterone (patch)BiologyBiochemistryFood sciencePhospholipidMedicine

Abstract

fetched live from OpenAlex

This study was to investigate if dietary gangliosides alter the lipid‐constituents in rat testis. Weanling male Sprague‐Dawley rats (~37.2g) were fed for 2 weeks diets containing gangliosides (0.1% w/w) and compared animals fed the same diet without gangliosides. Lipids were extracted from whole testis after decapsulation. The level of total and individual gangliosides, cholesterol and fatty acids in phosphatidylcholine (PC) were measured. Rats fed the ganglioside diet exhibited increased total ganglioside content (p<0.02) in testis and a 16% reduction in total cholesterol content (p<0.05) resulting in a decrease in ratio of cholesterol to ganglioside in testis. The major gangliosides in testis were GD1a, GT1b, GM3, and GM1 (30%, 21%, 16% and 14% of total gangliosides, respectively), but no difference in ganglioside composition was observed between dietary treatment. C20:4n‐6 and C22:5n‐6 increased in PC while C18:0 decreased in animals fed the diet containing gangliosides. These results demonstrate that dietary gangliosides may modulate lipid composition in developing rat testis. The influence on production of testosterone is not known. (supported by the University of Manitoba Start‐up Funds).

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 score0.005

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.012
GPT teacher head0.238
Teacher spread0.226 · 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

Citations0
Published2006
Admission routes3
Has abstractyes

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Same venueThe FASEB JournalSame topicLipid metabolism and disordersFrench-language works237,207