Acylated Ghrelin Directly Modulates In Vitro Cytokine Secretion in Lipopolysaccharide-Stimulated Bone Marrow-Derived Macrophages from Male C57BL/6J Mice
Bibliographic record
Abstract
Macrophages are the sentinels of the mammalian body and are involved in both inflammatory and reparative functions.Upon activation, macrophages reprogram to bias energy production and the availability of precursor molecules used to kill invading pathogens.Interrupting reprogramming has direct effects on macrophage physiology and host immunity.Macrophages express receptors for the orexigenic peptide ghrelin, and recently this stomach-derived hormone has been shown to influence inflammatory signaling.However, the underlying mechanisms are poorly understood and data available on sex differences is scarce.The objective of the current thesis is to evaluate if ghrelin pre-treatment can directly augment cytokine responses from lipopolysaccharide stimulated bone marrow-derived macrophages from male and female C57BL/6J mice in vitro.We show that pre-treating male macrophages for 4 hours with ghrelin ( 250nM) prior to 24-hour stimulation with lipopolysaccharide (100 ng/mL) significantly reduces IL-1β, IL-10, and TNF-α secretion.This effect was absent in macrophages derived from females.I would like to recognize the work of two former graduate students, Alex Edwards and Allison Jaworski -they completed the original study from which the femurs used in the generation of BMDMs for the current thesis were obtained.As well, without the gracious guidance and mentorship of Duale Ahmed, this project would not have been possible.I had the pleasure of working with a couple skilled and intelligent undergraduate students: Maria Papoulias and Sam Tate, who completed their theses alongside me, and contributed many hours and thought-provoking questions that ultimately helped shape this current document.To my supervisors, Dr. Alfonso Abizaid and Dr. Edana Cassol -your guidance, support, and patience with me during this process is unlike any I have ever received.I cannot thank you both enough for your roles in my graduate school experience.To the entire Abizaid Lab, sharing a workplace with you has been a pleasure and a privilege, I have met many intelligent and compassionate people who made tedious lab days much more enjoyable.And lastly, I have family and friends to thank for their generosity and continual support; this work was not just about fulfilling degree
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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 | 0.001 |
| 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) | 0.003 | 0.001 |
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".