Functional polymorphisms of macrophage migration inhibitory factor as predictors of morbidity and mortality of pneumococcal meningitis
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Bibliographic record
Abstract
Pneumococcal meningitis is the most frequent and critical type of bacterial meningitis. Because cytokines play an important role in the pathogenesis of bacterial meningitis, we examined whether functional polymorphisms of the proinflammatory cytokine macrophage migration inhibitory factor (MIF) were associated with morbidity and mortality of pneumococcal meningitis. Two functional MIF promoter polymorphisms, a microsatellite (-794 CATT5-8; rs5844572) and a single-nucleotide polymorphism (-173 G/C; rs755622) were genotyped in a prospective, nationwide cohort of 405 patients with pneumococcal meningitis and in 329 controls matched for age, gender, and ethnicity. Carriages of the CATT7 and -173 C high-expression MIF alleles were associated with unfavorable outcome (P= 0.005 and 0.003) and death (P= 0.03 and 0.01). In a multivariate logistic regression model, shock [odds ratio (OR) 26.0, P= 0.02] and carriage of the CATT7 allele (OR 5.12,P= 0.04) were the main predictors of mortality. MIF levels in the cerebrospinal fluid were associated with systemic complications and death (P= 0.0002). Streptococcus pneumoniae strongly up-regulated MIF production in whole blood and transcription activity of high-expression MIF promoter Luciferase reporter constructs in THP-1 monocytes. Consistent with these findings, treatment with anti-MIF immunoglogulin G (IgG) antibodies reduced bacterial loads and improved survival in a mouse model of pneumococcal pneumonia and sepsis. The present study provides strong evidence that carriage of high-expression MIF alleles is a genetic marker of morbidity and mortality of pneumococcal meningitis and also suggests a potential role for MIF as a target of immune-modulating adjunctive therapy.
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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 | 0.001 | 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 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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