Prevalence of pks + bacteria and enterotoxigenic Bacteroides fragilis in patients with colorectal cancer
Bibliographic record
Abstract
BACKGROUND: Colorectal cancer (CRC) is the third most diagnosed cancer and the second most common cause of cancer deaths worldwide. CRC patients present with an increase in pathogens in their gut microbiota, such as polyketide synthase-positive bacteria (pks +) and enterotoxigenic Bacteroides fragilis (ETBF). The pks + Escherichia coli promotes carcinogenesis and facilitates CRC progression through the production of colibactin, a genotoxin that induces double-strand DNA breaks (DSBs). ETBF is a procarcinogenic bacterium producing the B. fragilis toxin (bft) that promotes colorectal carcinogenesis by modulating the mucosal immune response and inducing epithelial cell changes. METHODS: Fecal samples were collected from healthy controls (N = 62) and CRC patients (N = 94) from the province of Québec (Canada), and a bacterial DNA extraction was performed. Fecal DNA samples were then examined for the presence of the pks island gene and bft using conventional qualitative PCR. RESULTS: We found that a high proportion of healthy controls are colonized by pks + bacteria (42%) and that these levels were similar in CRC patients (46%). bft was detected in 21% of healthy controls and 32% of CRC patients, while double colonization by both pks + bacteria and ETBF occurred in 8% of the healthy controls and 13% of the CRC patients. Most importantly, we found that early-onset CRC (< 50 years) patients were significantly less colonized with pks + bacteria (20%) compared to late-onset CRC patients (52%). CONCLUSIONS: Healthy controls had similar levels of pks + bacteria and ETBF colonization as CRC patients, and their elevated levels may place both groups at greater risk of developing CRC. Colonization with pks + bacteria was less prevalent in early-compared to late-onset CRC.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".