Bibliographic record
Abstract
The current issue of Acta Neuropsychiatrica presents a series of papers which together provide a broad overview relating stress, immunity, cytokine activity and depressive illness, as well as the influence of cytokines on other neurological disorders. This introduction to the issue presents a broad perspective of the impact of stressors on immune functioning in animal studies and in humans, considering the potential effects of acute, subchronic and chronic stressors, as well as the contribution of previous stressor experience in promoting neurochemical and immunological alterations. Given the supposition that cytokines may act as immunotransmitters, and immune challenge may be viewed as a stressor, a brief review is provided concerning the impact of stressors and cytokine challenges on central neurochemical functioning, with particular emphasis on the commonalties between the effects of these treatments. It is suggested that by virtue of the neurochemical changes imparted by cytokines, a depressive affect may be instigated, just as it is in response to psychogenic stressors. To this end, an overview is presented concerning the relationship between cytokines and depression, as well as the influence of cytokine treatments on behavioral changes in animal studies and among patients receiving immunotherapy. Provisionally, the data support the view that activation of the inflammatory response system may contribute to affective illness, and that cytokines may act as signaling molecules to activate central nervous system processes regulating mood states.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".