Infection With Escherichia Coli Pathotypes Is Associated With Biomarkers of Gut Enteropathy and Nutritional Status Among Malnourished Children in Bangladesh
Bibliographic record
Abstract
Escherichia coli (E. coli) pathotypes are the most common cause of diarrhea, especially in developing countries. Environmental Enteric Dysfunction (EED) is presumed to be the result of infection with one or more pathotypes and can affect intestinal health and childhood growth. We sought to investigate the association of E. coli pathotypes infection with biomarkers of EED and nutritional status among slum-dwelling malnourished children in Bangladesh. This study comprised a total of 1050 stunted and at risk of stunting children. TaqMan Array Card assays were used to determine the presence of E. coli pathotypes in feces. Prevalence of infection with EAEC was highest (68.8%) in this cohort of children, followed by EPEC (55.9%), ETEC (44%), Shigella/EIEC (19.4%) and STEC (3.2%). The levels of myeloperoxidase and calprotectin were significantly higher in EAEC (P=0.02 and P=0.04), EPEC (P=0.02 and P=0.03) and Shigella/EIEC (P=0.05 and P=0.02) positive participants while, only calprotectin was significantly higher in ETEC (P=0.01) positive participants. Reg1B was significantly higher in participants with EAEC (P=0.004) while, neopterin levels were significantly lower in ETEC (P=0.003) and Shigella/EIEC (P=0.003) positive cases. A significant positive relationship was observed between EAEC and fecal levels of Reg1B (β = 0.28; 95% CI = 0.12, 0.43; p-value<0.001). Besides, ETEC was found to be positively and significantly associated with the levels of calprotectin (β = 0.14; 95 percent CI = 0.01, 0.26; p-value=0.037) and negatively with neopterin (β = -0.16; 95% CI = -0.30, -0.02; p-value=0.021). On the other hand, infection with EPEC was found to be negatively associated with length-for-age (β = -0.12; 95% CI = -0.22, -0.03; p-value=0.011) and weight-for-age (β = -0.11; 95% CI = -0.22, -0.01; p-value=0.037). The study findings suggest that infection with certain E. coli pathotypes (EAEC and ETEC) influences gut health and EPEC is associated with linear growth and underweight in Bangladeshi children.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".