Cytokines as a stressor: implications for depressive illness
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Stressful events have been implicated in the provocation of depressive illness. Inasmuch as immunological challenge, and particularly cytokine administration, engender neuroendocrine and central neurochemical changes reminiscent of those provoked by psychogenic stressors, it was suggested that immune activation may also contribute to affective illness. The present report provides a brief overview of the neurochemical sequelae of acute and repeated interleukin-1beta (IL-1beta), tumour necrosis factor-alpha (TNF-alpha) and IL-2 treatment, describes some of the synergisms associated with these treatments, as well as their potential interactions with psychogenic stressors. In addition, a discussion is provided concerning the fact that cytokines, like stressors, may have time-dependent proactive effects, so that re-exposure to the treatments provoke greatly augmented neurochemical changes (sensitization). Given that the effects of cytokines are evident within hypothalamic, as well as extrahypothalamic sites, including various limbic regions, it is suggested that cytokines may impact on emotional changes, including 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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it