IDDF2022-ABS-0219 Recovery of the gut microbiota under oral iron supplementation is deleterious and promotes colorectal carcinogenesis in <i> APC <sup>Min/+</sup> </i> mice
Bibliographic record
Abstract
Background Colorectal cancer (CRC) induces anemia in a large proportion of patients and is usually treated with oral iron supplementation. Surgery, the main treatment for CRC, is routinely accompanied by prophylactic antibiotics to avoid infection. However, the combined effect of antibiotics and luminal iron in the gut on the microbiota and intestinal homeostasis remains unknown. Methods Wild-type (WT) mice were subjected to antibiotic treatment followed by oral iron supplementation at different concentrations. The composition of the gut microbiota and its recovery were assessed by 16S rRNA sequencing of the stool. Short-chain fatty acid (SCFA) concentrations were also assessed in the stool. In addition, APCMin/+ mice (a CRC mouse model) received fecal microbiota transplantation (FMT) using samples from anemic CRC patients, followed by oral iron supplementation at different concentrations. Tumor burden and Ki-67-positive colonic cells were quantified, and gut microbiota composition was assessed by 16S rRNA sequencing. Results In WT mice, recovery from antibiotics under high luminal iron concentration shifted the gut microbiota toward a Bacteroidetes phylum-dominant composition. Three bacterial species characterized as CRC markers and/or CRC initiators were more abundant under oral iron supplementation and showed a lack of recovery of fecal concentrations of butyrate, an SCFA that inhibits cancer cell proliferation. APCMin/+ mice that received FMT from anemic CRC patients under oral iron supplementation developed more colonic tumors and had a higher proportion of Ki-67-positive cells compared to APCMin/+fed an iron sufficient diet. Conclusions Gut microbiota recovery from antibiotic exposure under oral iron supplementation is frequent in CRC patients but is also common in the general population. This study identifies possible deleterious effects of the concomitance of these two disruptive agents of the gut microbiota and may lead to modifications in the management of anemia in patients with CRC.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.037 | 0.014 |
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".