Influence of CTG repeats from the human DM1 locus on murine gut microbiota
Bibliographic record
Abstract
Myotonic Dystrophy type 1 (DM1) is caused by a CTG repeat expansion in the 3' untranslated region of the DMPK gene. This expansion leads to the production of toxic RNA transcripts, which accumulate in the nucleus and interfere with normal RNA processing. DM1 affects a broad range of tissues and systems such as the skeletal muscle, the central nervous system, cardiac, visual, reproductive, and gastrointestinal (GI) system. GI dysfunction is a significant but poorly understood aspect of DM1. Particularly, it is unknown if there are alterations in the intestinal microbiome in DM1. Here, we used a transgenic humanized mouse model (DMSXL) to explore how the gut microbiome may be linked to GI issues in DM1. For this purpose, 68 stool samples from Homozygous, Heterozygous, and Wild-Type (WT) mice were collected. These samples were sequenced by MiSeq and analyzed with DADA2 to generate taxonomic profiles. Our analysis indicated that the overexpression of CTG repeats significantly influences the bacterial structure of the gut microbiome in Homozygous mice samples, especially in terms of the relative abundance of the Patescibacteria and Defferibacterota Phyla. These results provide valuable information about the gut microbiota structure thus improving the understanding of the role of these changes in the pathogenicity as well as GI problems of DM1 patients.
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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 | 0.000 | 0.000 |
| 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".