E. coli diversity: low in colorectal cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Escherichia coli are mostly commensals but also contain pathogenic lineages. It is largely unclear whether the commensal E. coli as the potential origins of pathogenic lineages may consist of monophyletic or polyphyletic populations, elucidation of which is expected to lead to novel insights into the associations of E. coli diversity with human health and diseases. METHODS: Using genomic sequencing and pulsed field gel electrophoresis (PFGE) techniques, we analyzed E. coli from the intestinal microbiota of three groups of healthy individuals, including preschool children, university students, and seniors of a longevity village, as well as colorectal cancer (CRC) patients, to probe the commensal E. coli populations for their diversity. RESULTS: We delineated the 2280 fresh E. coli isolates from 185 subjects into distinct genome types (genotypes) by PFGE. The genomic diversity of the sampled E. coli populations was so high that a given subject may have multiple genotypes of E. coli, with the general diversity within a host going up from preschool children through university students to seniors. Compared to the healthy subjects, the CRC patients had the lowest diversity level among their E. coli isolates. Notably, E. coli isolates from CRC patients could suppress the growth of E. coli bacteria isolated from healthy controls under nutrient-limited culture conditions. CONCLUSIONS: The coexistence of multiple E. coli lineages in a host may help create and maintain a microbial environment that is beneficial to the host. As such, the low diversity of E. coli bacteria may be associated with unhealthy microenvironment in the intestine and hence facilitate the pathogenesis of diseases such as 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.
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 | 0.000 | 0.001 |
| 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 | 0.001 |
| 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 it