Gene‐expression Profile Analysis in the Mid‐gestation Human Intestine Discloses Greater Functional Immaturity of the Colon as Compared With the Ileum
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The occurrence of many neonatal inflammatory intestinal diseases in preterm infants highlights the susceptibility of the immature intestine to responding inadequately to nutrients and microbes. A better understanding of functional intestinal development is essential for the design of optimal treatments ensuring survival and growth of premature infants. The purpose of this study was to evaluate the gene expression profiles of the human ileum and colon at mid-gestation because these 2 segments are considered to be similar at this stage and are the sites of the most frequent pathologies in preterm infants. SUBJECTS AND METHODS: We compared the gene-expression profiles of human fetal small and large intestines using a cDNA microarray and analyzed the data with Ingenuity Pathway Analysis software. RESULTS: We found that a significant proportion of the genes was differentially expressed in the 2 segments. Gene cluster analysis revealed an even higher level of transcriptional dissimilarity at the functional level. For instance, segment-specific/overexpressed gene clusters in the ileum included genes involved with amino acid, vitamin, and mineral metabolism, reflecting the higher level of maturity of the small intestine as compared with the colon in which genes involved with cell cycle, cell death, and cell signaling were the predominant clusters of genes expressed. CONCLUSIONS: Functional clustering analysis of the differentially expressed genes revealed important functional differences between the 2 segments and a relative immaturity of the colon, suggesting that already at mid-gestation, the 2 intestinal segments should be considered as 2 distinct organs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".