Macrophage migration inhibitory factor as a potential ‘missing important factor’ driving inflammatory arthritis in adrenocorticotropic hormone deficiency
Bibliographic record
Abstract
To the Editor, With great interest, we read the recent case report published by Yamashita et al. [1]. This report described a patient with isolated adrenocorticotropic hormone (ACTH) deficiency (IAD) who developed inflammatory arthritis (IA) [1]. Although the underlying mechanisms remain unclear, the authors proposed several potential explanations for the relationship between IAD and IA. We concur that the lack of anti-inflammatory effects from cortisol and ACTH may play a major role in promoting IA in IAD patients. However, we believe that macrophage migration inhibitory factor (MIF), a known inflammatory mediator in IA, could also be a critical factor contributing to IA in such cases. MIF is a pleiotropic cytokine secreted not only by corticotropic pituitary cells, which also produce ACTH, but also by various stromal and immune cells [2]. MIF stimulates adrenal glucocorticoid secretion and counter-regulates the glucocorticoid-induced suppression of pro-inflammatory cytokines in activated macrophages in vivo, including tumor necrosis factor (TNF), interleukin (IL)-1, IL-6, and IL-8 [3] (Figure 1(a)). This delicate balance between glucocorticoids and MIF is essential for maintaining immune homeostasis, influencing both innate and adaptive immunity. Therefore, a deficiency in ACTH and cortisol disrupts this balance, potentially allowing pro-inflammatory cytokines, including MIF, to become dysregulated and dominant, thereby promoting the development of IA.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.020 | 0.010 |
| Insufficient payload (model declined to judge) | 0.002 | 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".