Mannan-binding lectin in children with <i>Escherichia coli</i> O157:H7 haemmorrhagic colitis and haemolytic uraemic syndrome
Bibliographic record
Abstract
Mannan-binding lectin (MBL) triggers complement activation upon binding to microbial surfaces. MBL deficiency has been associated with increased susceptibility to severe bacterial infections. We hypothesized that MBL deficiency may predispose children to Shiga toxin-producing Escherichia coli (STEC) O157:H7 infections and the associated haemolytic uraemic syndrome (HUS). We compared circulating levels of MBL among children with uncomplicated O157:H7 haemorrhagic colitis (HC), patients with O157:H7 HUS, normal and diseases control groups. Circulating MBL concentrations on admission were as follows: 3.22 +/- 2.43 micro g/ml among normal controls (n = 23); 2.90 +/- 2.44 micro g/ml in patients with rotavirus enteritis (n = 10); 2.78 +/- 1.65 micro g/ml in children with HC due to non-STEC bacterial pathogen (n = 15); 2.67 +/- 2.44 micro g/ml in patients with uncomplicated O157:H7 HC (n = 27); 2.80 +/- 2.97 micro g/ml in children with O157:H7 HUS (n = 15); 6.70 +/- 4.49 micro g/ml in patients with chronic renal failure unrelated to O157:H7 infection (n = 6). Higher MBL levels were found in patients with chronic renal failure compared to O157:H7 HC (P < 0.047). However, MBL concentrations <0.5 micro g/ml, which have been associated with MBL deficiency in relation to increased susceptibility to infections, were noted at comparable rates between the different groups (P = NS). Our data does not support that MBL deficiency may predispose to O157:H7 infections nor than the development of diarrhoea associated HUS.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".