Endothelial dysfunction in neuroprogressive disorders—causes and suggested treatments
Bibliographic record
Abstract
BACKGROUND: Potential routes whereby systemic inflammation, oxidative stress and mitochondrial dysfunction may drive the development of endothelial dysfunction and atherosclerosis, even in an environment of low cholesterol, are examined. MAIN TEXT: Key molecular players involved in the regulation of endothelial cell function are described, including PECAM-1, VE-cadherin, VEGFRs, SFK, Rho GEF TRIO, RAC-1, ITAM, SHP-2, MAPK/ERK, STAT-3, NF-κB, PI3K/AKT, eNOS, nitric oxide, miRNAs, KLF-4 and KLF-2. The key roles of platelet activation, xanthene oxidase and myeloperoxidase in the genesis of endothelial cell dysfunction and activation are detailed. The following roles of circulating reactive oxygen species (ROS), reactive nitrogen species and pro-inflammatory cytokines in the development of endothelial cell dysfunction are then described: paracrine signalling by circulating hydrogen peroxide, inhibition of eNOS and increased levels of mitochondrial ROS, including compromised mitochondrial dynamics, loss of calcium ion homeostasis and inactivation of SIRT-1-mediated signalling pathways. Next, loss of cellular redox homeostasis is considered, including further aspects of the roles of hydrogen peroxide signalling, the pathological consequences of elevated NF-κB, compromised S-nitrosylation and the development of hypernitrosylation and increased transcription of atherogenic miRNAs. These molecular aspects are then applied to neuroprogressive disorders by considering the following potential generators of endothelial dysfunction and activation in major depressive disorder, bipolar disorder and schizophrenia: NF-κB; platelet activation; atherogenic miRs; myeloperoxidase; xanthene oxidase and uric acid; and inflammation, oxidative stress, nitrosative stress and mitochondrial dysfunction. CONCLUSIONS: Finally, on the basis of the above molecular mechanisms, details are given of potential treatment options for mitigating endothelial cell dysfunction and activation in neuroprogressive disorders.
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How this classification was reachedexpand
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".