Hydrogen Sulfide–Releasing Insulin Polypeptide Mitigates Hyperglycemia-Induced Neurotoxicity and Cognitive Deficits <i>In Vivo</i>
Bibliographic record
Abstract
Hyperglycemia, a characteristic of diabetes, is increasingly associated with an elevated risk of neurodegenerative disorders, such as Parkinson’s disease. Hyperglycemia serves as a comorbidity and hastens neurodegenerative processes in Parkinson’s disease. We report the development of H 2 S-releasing human insulin polypeptide (SHI), which will colocalize metabolic release of H 2 S near insulin action, and a thorough investigation of their combined efficacy in mitigating Parkinson’s disease and hyperglycemia-associated symptoms. SHI demonstrated notable neuroprotective effects in SH-SY5Y human neuroblastoma cells subjected to elevated glucose concentrations and the neurotoxin 6-OHDA. In transgenic Caenorhabditis elegans Parkinson’s disease model, SHI reduced the levels of human α-Synuclein, while increasing the levels of dopamine transporter. Moreover, SHI showed behavioral improvements in both Drosophila and C. elegans, highlighting its potential therapeutic applications. This approach addresses both neurodegenerative and metabolic pathways, providing dual benefits for these interrelated conditions.
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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) | 0.001 | 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".