Berberine Inhibits Oxygen Consumption Rate Independent of Alteration in Cardiolipin Levels in H9c2 Cells
Bibliographic record
Abstract
Abstract Small clinical studies have shown that oral treatment with the plant alkaloid berberine (BBR) reduces blood glucose levels similar to that of metformin and have promoted its use as a novel anti‐diabetic therapy. However, in vitro studies have shown that high concentrations of BBR potently inhibit cell proliferation through inhibition of mitochondrial function. Cardiolipin (Ptd2Gro) is a key phospholipid required for regulating mitochondrial bioenergetic function. We examined if BBR inhibited oxygen consumption rate in H9c2 cardiac myocytes through alteration in Ptd2Gro metabolism. Treatment of H9c2 cells with BBR resulted in a rapid (within minutes) concentration‐dependent decrease in the oxygen consumption rate (OCR) as determined using a Seahorse XF24 analyzer. Concentrations of BBR as low as 1 µM were effective in inhibiting OCR. In addition, all concentrations of BBR inhibited the fatty acid‐mediated increase in OCR that was observed in untreated cells. Treatment of H9c2 cells with up to 25 µM BBR for 24 h markedly reduced [3H]thymidine incorporation into cells but did not alter the pool size of Ptd2Gro. In contrast, 12.5 µM BBR increased [1‐14C]palmitate incorporation into Ptd2Gro and 12.5 µM and 25 µM BBR reduced [1‐14C]oleate incorporation into Ptd2Gro. Protein kinase C delta (PKCδ) activation through its increased membrane association is known to alter Ptd2Gro distribution within mitochondria. BBR treatment resulted in a decrease in membrane‐associated PKCδ and attenuated the palmitate‐mediated increase in PKCδ membrane‐association. Thus, BBR treatment of H9c2 cardiac myocytes inhibits cellular OCR independent of alteration in Ptd2Gro levels.
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) | 0.001 | 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) | 0.002 | 0.001 |
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".