Hypothalamic-Pituitary Autoimmunity and Related Impairment of Hormone Secretions in Chronic Fatigue Syndrome
Bibliographic record
Abstract
CONTEXT: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a severe chronic illness that reduces the quality of life. A potential role of neuroendocrine autoimmune dysfunction has been hypothesized. OBJECTIVE: This work aims to investigate the occurrence of antipituitary (APA) and antihypothalamic (AHA) antibodies and possible related hypothalamic/pituitary dysfunctions in ME/CSF patients. METHODS: This is a case-control study conducted in a university hospital setting (Stanford, California, USA; and Naples, Italy). Thirty women with ME/CSF (group 1) diagnosed according to Fukuda, Canadian, and Institute of Medicine criteria, at Stanford University, were enrolled and compared with 25 age-matched healthy controls. APA and AHA were detected by immunofluorescence; moreover, we investigated hormonal secretions of anterior pituitary and respective target glands. APA and AHA titers both were assessed and the prevalence of pituitary hormone deficiencies was also investigated. RESULTS: Patients in group 1 showed a high prevalence of AHA (33%) and APA (56%) and significantly lower levels of adrenocorticotropin (ACTH)/cortisol, and growth hormone (GH) peak/insulin-like growth factor-1 (IGF-1) vs controls (all AHA/APA negative). Patients in group 1A (13 patients positive at high titers, ≥ 1:32) showed ACTH/cortisol and GH peak/IGF-1 levels significantly lower and more severe forms of ME/CFS with respect to patients in group 1B (7 positive at middle/low titers, 1:16-1:8) and 1C (10 antibody-negative patients). CONCLUSION: Both AHA and/or APA at high titers were associated with hypothalamic/pituitary dysfunction, suggesting that hypothalamic/pituitary autoimmunity may play an important role in the manifestations of ME/CFS, especially in its more severe forms.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".