CD38 deficiency prevents diabetic nephropathy by inhibiting lipid accumulation and oxidative stress through activation of the SIRT3 pathway
Bibliographic record
Abstract
Diabetic nephropathy (DN) is one of the most common complications of diabetes. Our previous study showed that CD38 knockout (CD38KO) mice had protective effects on many diseases. However, the roles and mechanisms of CD38 in DN remain unknown. Here, DN mice were generated by high-fat diet (HFD) feeding plus streptozotocin (STZ) injection in male CD38KO and CD38flox mice. Mesangial cells (SV40 MES 13 cells) were used to mimic the injury of DN with palPagination Donemitic acid (PA) treatment in vitro. Our results showed that CD38 expression was significantly increased in kidney of diabetic CD38flox mice and SV40 MES 13 cells treated with PA. CD38KO mice were significantly resistant to diabetes-induced renal injury. Moreover, CD38 deficiency markedly decreased HFD/STZ-induced lipid accumulation, fibrosis, and oxidative stress in kidney tissue. In contrast, overexpression of CD38 aggravated PA-induced lipid accumulation and oxidative stress. CD38 deficiency increased expression of SIRT3, while overexpression of CD38 decreased its expression. More importantly, 3-TYP, an inhibitor of SIRT3, significantly enhanced PA-induced lipid accumulation and oxidative stress in CD38 overexpressing cell lines. In conclusion, our results demonstrated that CD38 deficiency prevented DN by inhibiting lipid accumulation and oxidative stress through activation of the SIRT3 pathway.
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) | 0.000 | 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) | 0.002 | 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".