Visualization of Sex-Dimorphic Changes in the Intestinal Transcriptome of <b><i>Fabp2</i></b> Gene-Ablated Mice
Bibliographic record
Abstract
<b><i>Background/Aims:</i></b> Sex differences in gene expression program have not been effectively explored at the transcriptome level. We aimed to develop a method for the analysis of transcriptome data to identify sex differences and sex-dimorphic responses to experimental conditions in mice. <b><i>Methods:</i></b> Profiling of the small intestine transcriptome of chow-fed C57BL/6J (wild-type, WT) and <i>Fabp2</i><sup>–/–</sup> mice was carried out by microarray analysis. Sex-specific and androgynous effects of <i>Fabp2</i> gene ablation were examined using FlexArray V1.6 by comparing WT to <i>Fabp2</i><sup>–/–</sup> mice. The data generated were exported into a single spreadsheet, collated and transformed to identify the differentially expressed genes for pathway analysis. <b><i>Results:</i></b> The method revealed enrichment of 17 sex-dimorphic pathways in the small intestine of WT mice compared to only 4 in <i>Fabp2</i><sup>–/–</sup> mice. Comparison of the effects of Fabp2 loss in individual sexes revealed a male-specific upregulation of 5 pathways involved in the production of unsaturated fatty acids, and a female-specific downregulation of pathways involved in xenobiotic metabolism. <b><i>Conclusions:</i></b> Our approach detected the common as well as sex-differential pathways that are modified due to the loss of Fabp2. These findings suggest that the pathways involved in nutrient and xenobiotic metabolism in the intestine are regulated by sex-specific mechanisms.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".