Inflammation‐driven brain and gut barrier dysfunction in stress and mood disorders
Why this work is in the frame
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Bibliographic record
Abstract
Regulation of emotions is generally associated exclusively with the brain. However, there is evidence that peripheral systems are also involved in mood, stress vulnerability vs. resilience, and emotion-related memory encoding. Prevalence of stress and mood disorders such as major depression, bipolar disorder, and post-traumatic stress disorder is increasing in our modern societies. Unfortunately, 30%-50% of individuals respond poorly to currently available treatments highlighting the need to further investigate emotion-related biology to gain mechanistic insights that could lead to innovative therapies. Here, we provide an overview of inflammation-related mechanisms involved in mood regulation and stress responses discovered using animal models. If clinical studies are available, we discuss translational value of these findings including limitations. Neuroimmune mechanisms of depression and maladaptive stress responses have been receiving increasing attention, and thus, the first part is centered on inflammation and dysregulation of brain and circulating cytokines in stress and mood disorders. Next, recent studies supporting a role for inflammation-driven leakiness of the blood-brain and gut barriers in emotion regulation and mood are highlighted. Stress-induced exacerbated inflammation fragilizes these barriers which become hyperpermeable through loss of integrity and altered biology. At the gut level, this could be associated with dysbiosis, an imbalance in microbial communities, and alteration of the gut-brain axis which is central to production of mood-related neurotransmitter serotonin. Novel therapeutic approaches such as anti-inflammatory drugs, the fast-acting antidepressant ketamine, and probiotics could directly act on the mechanisms described here improving mood disorder-associated symptomatology. Discovery of biomarkers has been a challenging quest in psychiatry, and we end by listing promising targets worth further investigation.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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