Hyperglycemia enhances the generation of ROS and RNS that impair antioxidant power and cause oxidative damage in human erythrocytes
Bibliographic record
Abstract
Hyperglycemia is a state in which excess glucose circulates in blood. Erythrocytes are in direct contact with this high glucose concentration and are greatly affected by it. We have examined the effect of hyperglycemic condition on isolated human erythrocytes under in vitro conditions. Erythrocytes were incubated with different concentrations of glucose (5, 15, 30, 45 mmol/L) for 24 h, and several biochemical parameters were determined. Treatment with high glucose concentrations increased heme degradation and methemoglobin level, while methemoglobin reductase activity was decreased. A significant increase in protein oxidation and lipid hydroperoxides with a decrease in total sulfhydryl content was seen. This suggested the generation of oxidative stress, which was confirmed by an enhanced production of reactive oxygen and nitrogen species. Hyperglycemia led to a significant decline in the antioxidant power of erythrocytes, lowering their ability to quench free radicals and reduce metal ions to lower oxidation states. The plasma membrane redox system was upregulated, while ascorbate free radical reductase activity was lowered. Glucose exposure inhibited the enzymes of glycolysis and hexose monophosphate shunt. Electron microscopy showed morphological changes resulting in the formation of echinocytes. Thus, the hyperglycemic condition generates reactive species that oxidize proteins, hemoglobin, and lipids; impair the total antioxidant capacity; and alter morphology in human erythrocytes.
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 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 | 0.000 |
| 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 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".