Growth hormone-mediated reprogramming of macrophage transcriptome and effector functions
Bibliographic record
Abstract
Macrophages are an important component of the innate immune response. Priming and activation of macrophages is stimulated by cytokines (i.e IFNγ). However, growth hormone (GH) can also stimulate macrophage activation. Based on these observations, the goal of this work was to 1) to compare the transcriptome profile of macrophages activated in vitro with GH and IFNγ, and 2) to assess the impact of GH on key macrophage functional properties like reactive oxygen species (ROS) production and phagosomal proteolysis. To assess the global transcriptional and functional impact of GH on macrophage programming, bone marrow derived macrophages were treated with GH or IFNγ. Our data strongly support a potential link between GH, which wanes with age, and impaired macrophage function. The notable overlap of GH with IFNγ-induced pathways involved in innate immune sensing of pathogens and antimicrobial responses argue for an important role for GH in macrophage priming and maturation. By using functional assays that report on biochemical activities within the lumen of phagosomes, we have also shown that GH alters physiologically relevant processes such as ROS production and proteolysis. These changes could have far reaching impacts on antimicrobial capacity, signaling, and antigen presentation.
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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) | 0.000 | 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 | 0.000 |
| 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".