Succumbing to the Laws of Attraction: Exploring the Sometimes Pathogenic Versatility of Discrete Immune Logic
Bibliographic record
Abstract
Feedback mechanisms throughout the immune and endocrine systems play a significant role in maintaining physiological homeostasis. Specifically, the hypothalamic-pituitary-adrenal (HPA) and hypothalamic-pituitary-gonadal (HPG) axes contribute important oversight of immune activity and homeostatic regulation. We propose that these components form an overarching regulatory system capable of supporting multiple homeostatic regimes. These emerge as a result of the extensive feedback mechanisms involving cytokine and hormone signaling. Here we explore the possible role of such alternate regulatory programs in perpetuating chronic immune and endocrine dysfunction in males. To do this we represent documented interactions within and between components of the male HPA-HPG-immune system as a set of discrete logic circuits. Analysis of these regulatory circuits indicated that even in the absence of external perturbations this model HPA-HPG-immune network supported three distinct and stable homeostatic regimes. To investigate the relevance of these predicted homeostatic regimes, we compared them to experimental data from male subjects with Gulf War illness (GWI) and chronic fatigue syndrome (CFS), two complex chronic conditions presenting with endocrine and immune dysregulation. Results indicated that molecular profiles observed experimentally in male GWI and CFS were both distinct from the normal resting state. Profile alignments suggests that regulatory circuitry is largely intact in male GWI and that the persistent immune dysfunction in this illness may at least in part be facilitated by the body’s own homeostatic drive. Conversely the profile for male CFS was distant from all three stable states suggesting the continued influence of an exogenous agent or lasting changes to the regulatory circuitry such as epigenetic alterations.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".