Mechanisms of human complement factor B induction in sepsis and inhibition by activated protein C
Bibliographic record
Abstract
To investigate the potential role of the local expression of alternative complement factor B (hBf) in human sepsis, we examined the induction of Bf gene expression in human peripheral blood monocytes (PBMCs) from patients with septic shock and the mechanisms of hBf gene regulation by tumor necrosis factor (TNF)-alpha, interferon (IFN)-gamma, and lipopolysaccharide (LPS) in human monocytes. PBMCs from septic shock patients showed increased hBf mRNA expression when compared with control patients. Costimulation with TNF-alpha and IFN-gamma or stimulation with LPS demonstrated a time- and dose-dependent induction of hBf mRNA expression in human PBMCs. A region of the hBf promoter between -735 and +128 bp was found to mediate IFN-gamma, TNF-alpha, and LPS responsiveness as well as the synergistic effect of IFN-gamma/TNF-alpha on hBf promoter activity. Site-directed mutagenesis of a IFN-gamma-activation site (GAS) cis element (-90 to -82 bp) abrogated IFN-gamma responsiveness. Mutagenesis of a nuclear factor (NF)-kappaB cis element at -466 to -456 bp abrogated TNF-alpha and LPS responsiveness of the Bf promoter. Thus hBf gene expression is induced in PBMCs from septic shock patients, and the induction of hBf by IFN-gamma, TNF-alpha, and LPS is through GAS and NF-kappaB cis-binding sites on the hBf promoter. Furthermore, activated protein C (APC) inhibited LPS-stimulated hBf promoter activity and protein expression in human monocytes suggesting that the beneficial effect of APC therapy in sepsis may in part be due to inhibition of complement induction and/or activation via the alternative pathway.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| Research integrity | 0.000 | 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".