Administration of GDF3 Into Septic Mice Improves Survival via Enhancing LXRα-Mediated Macrophage Phagocytosis
Bibliographic record
Abstract
The defective eradication of invading pathogens is a major cause of death in sepsis. As professional phagocytic cells, macrophages actively engulf/kill microorganisms and play essential roles in innate immune response against pathogens. Growth differentiation factor 3 (GDF3) was previously implicated as an important modulator of inflammatory response upon acute sterile injury. In this study, administration of recombinant GDF3 protein (rGDF3) either before or after CLP surgery remarkably improved mouse survival, along with significant reductions in bacterial load, plasma pro-inflammatory cytokine levels, and organ damage. Notably, our in vitro experiments revealed that rGDF3 treatment substantially promoted macrophage phagocytosis and intracellular killing of bacteria in a dose-dependent manner. Mechanistically, RNA-seq analysis results showed that CD5L, known to be regulated by liver X receptor α (LXRα), was the most significantly upregulated gene in rGDF3-treated macrophages. Furthermore, we observed that rGDF3 could promote LXRα nuclear translocation and thereby, augmented phagocytosis activity in macrophages, which was similar as LXRα agonist GW3965 did. By contrast, pre-treating macrophages with LXRα antagonist GSK2033 abolished beneficial effects of rGDF3 in macrophages. In addition, rGDF3 treatment failed to enhance bacteria uptake and killing in LXRα-knockout (KO) macrophages. Taken together, these results uncover that GDF3 may represent a novel mediator for controlling bacterial infection.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".