Lycopene Protects against Hypoxia/Reoxygenation Injury by Alleviating ER Stress Induced Apoptosis in Neonatal Mouse Cardiomyocytes
Bibliographic record
Abstract
Endoplasmic reticulum (ER) stress induced apoptosis plays a pivotal role in myocardial ischemia/reperfusion (I/R)-injury. Inhibiting ER stress is a major therapeutic target/strategy in treating cardiovascular diseases. Our previous studies revealed that lycopene exhibits great pharmacological potential in protecting against the I/R-injury in vitro and vivo, but whether attenuation of ER stress (and) or ER stress-induced apoptosis contributes to the effects remains unclear. In the present study, using neonatal mouse cardiomyocytes to establish an in vitro model of hypoxia/reoxygenation (H/R) to mimic myocardium I/R in vivo, we aimed to explore the hypothesis that lycopene could alleviate the ER stress and ER stress-induced apoptosis in H/R-injury. We observed that lycopene alleviated the H/R injury as revealed by improving cell viability and reducing apoptosis, suppressed reactive oxygen species (ROS) generation and improved the phosphorylated AMPK expression, attenuated ER stress as evidenced by decreasing the expression of GRP78, ATF6 mRNA, sXbp-1 mRNA, eIF2α mRNA and eIF2α phosphorylation, alleviated ER stress-induced apoptosis as manifested by reducing CHOP/GADD153 expression, the ratio of Bax/Bcl-2, caspase-12 and caspase-3 activity in H/R-treated cardiomyocytes. Thapsigargin (TG) is a potent ER stress inducer and used to elicit ER stress of cardiomyocytes. Our results showed that lycopene was able to prevent TG-induced ER stress as reflected by attenuating the protein expression of GRP78 and CHOP/GADD153 compared to TG group, significantly improve TG-caused a loss of cell viability and decrease apoptosis in TG-treated cardiomyocytes. These results suggest that the protective effects of lycopene on H/R-injury are, at least in part, through alleviating ER stress and ER stress-induced apoptosis in neonatal mouse cardiomyocytes.
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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 | 0.000 | 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 | 0.001 |
| 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".