Expression of Calbindin-D28k in a Pancreatic Islet -Cell Line Protects against Cytokine-Induced Apoptosis and Necrosis
Bibliographic record
Abstract
Cytokines produced by immune system cells that infiltrate pancreatic islets are candidate mediators of islet β-cell destruction in autoimmune (type 1) diabetes mellitus. Because the calcium binding protein, calbindin-D28k, can prevent apoptotic cell death in different cell types, we investigated the possibility that calbindin-D28k may prevent cytokine-mediated islet β-cell destruction. Using the expression vector BSRα, rat calbindin-D28k was stably expressed in the pancreatic isletβ -cell line, βTC-3. Calbindin-D28k expression resulted in increased cell survival in the presence of the cytotoxic combination of the cytokines IL-1β (30 U/ml), TNFα (103 U/ml), and interferon γ (103 U/ml). The greatest protection was observed in the βTC-3 cell clone expressing the highest concentration of calbindin-D28k. Apoptotic cell death was detected by annexin V staining and by the TdT-mediated dUTP-X nick end labeling assay in vector-transfected βTC-3 cells incubated with cytokines (14–15% apoptotic cells). The number of apoptotic cells was significantly decreased in calbindin-D28k-overexpressingβ TC-3 cells incubated with cytokines (5–6% apoptotic cells). To address the mechanism of the antiapoptotic effects of calbindin, studies were done to examine whether calbindin inhibits free radical formation. The stimulatory effects of the cytokines on lipid hydroperoxide, nitric oxide, and peroxynitrite production were significantly decreased in the calbindin-D28k-expressingβ TC-3 cells. Our findings indicate that calbindin-D28k, by inhibiting free radical formation, can protect against cytokine-mediated apoptosis and destruction of β-cells. These findings suggest that calbindin-D28k may be an important regulator of cell death that can protect pancreatic isletβ -cells from autoimmune destruction in type 1 diabetes.
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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".