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Record W1974335872 · doi:10.1159/000244273

Peroxisomes and Peroxisomal Enzymes in the Human Fetal Small Intestine

2009· article· en· W1974335872 on OpenAlexaff
Michel Dauça, Sylvie Cablé, R. Calvert, Suzanne Colin, J. Schilt, Bruno Leheup, Jean Marie Keller, Daniel Ménard

Bibliographic record

VenueBiology of the Neonate · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPeroxisome Proliferator-Activated Receptors
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPeroxisomeBiologyFetusOxidase testCytochemistryCatalaseMicrobodyEnzymeBiochemistryPeroxisomal disorderInternal medicineEndocrinologyAndrologyPregnancyMedicineReceptor

Abstract

fetched live from OpenAlex

The appearance and development of peroxisomes and the expression of their enzymes in the human fetal intestine have been investigated between 11 and 22 weeks of gestation. In the youngest samples (11-16 weeks of age), cytochemistry at the ultrastructural level revealed the presence of rare, mostly circular peroxisomes. From 16 weeks of gestation onwards, an increase was noted in the number of peroxisomes. Two peroxisomal types were distinguished: round to oval forms and elongated and/or tailed organelles. Biochemical assays revealed that total and specific intestinal catalase activities increased gradually between 11 and 20 weeks of gestation. The activity of fatty acylCoA oxidase, the first enzyme of the peroxisomal beta-oxidation system, was detectable as early as 11 weeks of gestation. Thereafter, total and specific activities of the enzyme increased steadily. Activities of other peroxisomal oxidases (D-amino acid oxidase, L-alpha-hydroxyacid oxidase) appeared more slowly in the fetal intestine during the period studied. This investigation establishes the presence and the morphological changes that occur in intestinal peroxisomes during human fetal development as well as the developmental patterns of associated enzymes.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.409

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 head0.012
GPT teacher head0.253
Teacher spread0.240 · 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

Citations10
Published2009
Admission routes1
Has abstractyes

Explore more

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