Immune to happiness – inflammatory process indicators and depressive personality traits
Bibliographic record
Abstract
INTRODUCTION: Nowadays, depression is conceptualized as an immune-inflammatory and oxidative stress disorder associated with neuroprogressive changes as a consequence of peripherally activated immune-inflammatory pathways, including peripheral cytokines and immune cells which penetrate into the brain via the blood barrier, as well as nitro-oxidative stress and antioxidant imbalances. The aim of this study was to investigate whether personality traits predisposing to a depressive episode (hypochondria, dysthymic, hysteria) are associated with changes in peripheral gene expression for selected indicators of inflammation and oxidative balance. MATERIAL AND METHODS: One hundred four people meeting the diagnostic criteria specified for a depressive episode took part in the study. Selected scales of the Minnesota Multiphasic Personality Inventory (MMPI-2) were used to measure personality traits. Expression at the mRNA and protein level for manganese superoxide dismutase (MnSOD), myeloperoxidase (MPO), cyclooxygenase 2 (COX-2), inducible nitric oxide synthase (iNOS), and metalloproteinases 2 and 9 (MMP-2, MMP-9) was examined. RESULTS: Scales for the neurotic triad of the MMPI-2 test correlated significantly with the expression at the level of mRNA and protein for MnSOD, MPO and metalloproteinases 2 and 9. CONCLUSIONS: The scales specified for the neurotic triad of the MMPI-2 test correspond substantially with the expression of MnSOD, MPO and metalloproteinases 2 and 9 at the mRNA and protein levels in the group of patients suffering from depression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 |
| 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".