The Possible Underworld of Chronic Fatigue Syndrome From Neurotransmitters Polymorphisms to Disease
Bibliographic record
Abstract
Background: Chronic fatigue syndrome is a complex and debilitating disorder. Several clinical studies suggest dysregulation of the hypothalamic-pituitary-adrenal axis and perturbations of the immune and central nervous systems. In this study we esamined the association between serotonin transporter (SERT) and receptor 2A (HTR2A), Glycogen synthase kinase 3 beta (GSK3B) and Brain Derived N eurotrophic Factor (BDNF) genes polymorphisms and CFS, in order to describe genetic associations. Methods: The coding and untranslated regions of each gene examined were amplified by PCR-RFLP. Results: The 44% of the CFS patients presents depressive symptoms: in this subgroup the presence of female sex is significantly higher (88%) than in not depressed patients (35%) (P = 0.0002). The genotypic and allelic frequencies of the HTR2A -1438G / A polymorphism showed a statistically significant difference (P = 0.05): the AA genotype is more present in patients with depressive symptoms. In particular, the frequency of the AA genotype was higher in the depressed patients (48%) compared to the patients without depressive symptoms (21%). The crude odds ratio for the presence of CFS associated with depression in subjects bearing the homozygous AA genotype was 3.56 (95% CI, 1.13 - 11.17). Conclusions: References of increased promoter activity, mRNA, protein levels and receptor binding with this promoter polymorphism and the association of the A allele with CFS sustain a hyperactive serotonergic system in this disease. So we suppose that the neuroendocrine system remains an intriguing field of research in CFS. doi:10.4021/jnr86w
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".