Attenuation of Oxidative Stress by Cannabinoids and Cannabis Extracts in Differentiated Neuronal Cells
Bibliographic record
Abstract
In this proof-of-concept study, the antioxidant activity of phytocannabinoids, namely cannabidiol (CBD) and Δ9- tetrahydrocannabinol (THC), were investigated using an in vitro system of differentiated human neuronal SY-SH5Y cells. The oxidative stress was induced by hydrogen peroxide, as reactive oxygen species (ROS). Alzheimer’s disease (AD)-like pathological conditions were mimicked in vitro by treating the differentiated neuronal cells with amyloid-β1–42 (Aβ1–42) in the presence of Cu(II). We showed that THC had a high potency to combat oxidative stress in both in vitro models, while CBD did not show a remarkable antioxidant activity. The cannabis extracts also exhibited a significant antioxidant activity, which depended on the ratio of the THC and CBD. However, our results did not suggest any antagonist effect of the CBD on the antioxidant activity of THC. The effect of cannabis extracts on the cell viability of differentiated human neuronal SY-SH5Y cells was also investigated, which emphasized the differences between the bioactivity of cannabis extracts due to their composition. Our preliminary results demonstrated that cannabis extracts and phytocannabinoids have a promising potential as antioxidants, which can be further investigated to develop novel pharmaceuticals targeting oxidative stress therapy.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".