Polyamines in Parkinson’s Disease: Their Role in Oxidative Stress Induction and Protein Aggregation
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Bibliographic record
Abstract
Parkinson’s disease (PD) is a systemic neurodegenerative disease characterized by tremor, rigidity, bradykinesia, and stooping posture. When more than 60% of dopaminergic neurons in the substantia nigra of the brain have died, motor symptoms manifest in PD. Currently, oxidative stress (OS) is considered to be one of the leading factors provoking death of dopaminergic neurons in PD. This review is concerned with the role of polyamines in PD, especially focusing on their role in OS induction. Polyamines (putrescine, cadaverine, spermidine and spermine) are involved in many molecular mechanisms, including cell proliferation and differentiation, gene transcription and translation, modulation of the functional activity of ion channels and receptors, and other vital processes. It is worth noting that under physiological conditions polyamines are antioxidants. It has been shown that spermine oxidase (SMOX) is up-regulated in PD, activating polyamine breakdown, which leads to excessive formation of toxic aldehydes (such as acrolein), H 2 O 2 (a strong cytostatic) and ammonia (a toxic substance). Polyamines are also involved in the pathogenetic mechanism of α-synuclein modification resulting in the formation of Lewy bodies. This review provides data on the changes in polyamine levels at later stages of the disease. The review also examines the role of polyamines, as gliotransmitters, in regulating neural function and vice versa. The mechanisms of polyamine “pumping” from neurons to glia can be considered factors of OS regulation in neurons. Prolonged accumulation of polyamines in glia can lead to oxidation of polyamines and therefore potentially to gliosis in PD. The exact mechanisms of this process are, however, not clear. Answering the questions regarding the role of polyamines in gliosis development and pathogenesis of PD is necessary for treating cognitive impairment in patients with PD, which is particularly important. J Neurol Res. 2019;9(1-2):1-7 doi: https://doi.org/10.14740/jnr509
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it