The Neuroinflammation Perspective of Depression: Reuniting the Outstanding Mechanisms of the Pathophysiology
Bibliographic record
Abstract
Major Depressive Disorder (MDD) is a serious mental health problem that leads to patients’ disability and has huge impact on social and economic burden to society. The current available medications for the treatment of depression are mainly targeted on enhancing monoamine neurotransmission. However, antidepressant treatments are still lacking high efficacy in many cases which is associated with low treatment response and remission rates. However, the latest knowledge regarding the pathophysiology of depression indicates that depression is developed by highly complex and integrated mechanisms in which monoaminergic deficiency could only be part of. The paradigm is now shifting from monoaminergic hypothesis to significance of other novel mechanisms that could possibly play substantial role for the development of depression in a highly inter-related manner. In fact, neuroinflammation, amongst other mechanisms does seem to be a key pathological component by having impact on certain pathway pathologies including glutamatergic neurotransmission, oxidative processes, neurotropic factors, neurotransmitter metabolism, and glucocorticoid functions in the central nervous system (CNS) and in the periphery, thereby triggers the pathological alterations that is thought to contribute to the development of depression. The neuroinflammation comprehends the processes exampled from excessive pro-inflammatory cytokine release to activation of microglia and indolamine 2,3-dioxygenase (IDO) pathway, excessive glutamatergic neurotransmission, hyperactive hypothalamus-pituitary-adrenal (HPA) axis, decreased neurogenesis and synaptic plasticity. In fact, the antidepressant effect of ketamine as a non-competitive N-methyl-D-aspartate (NMDA) receptor antagonist might be at least partially linked to inflammatory modulations. The significance of inflammation in depression is not only mentioned by the literature of basic researches from a mechanistic aspect but also by the possible clinical implications suggested by the clinical reports. Although the exact role of inflammation in depression and its clinical translation have not been determined yet, the inflammationmediated point of view might provide novel insights for improving the diagnosis at clinic (e.g., inflammatory biomarkers), predicting antidepressant treatment response and thereby re-evaluating the treatment strategy. Moreover, with all that, the inflammation aspect raises the question for the possible significance of utilizing anti-inflammatory approaches in the treatment of depression.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".