Proapoptotic bax is hyperexpressed in isolated human islets compared with antiapoptotic bcl-21
Bibliographic record
Abstract
BACKGROUND: Apoptosis is a well-documented pathway for islet cell death. One potential mechanism is overexpression of death-promoting Bax compared with antiapoptotic Bcl-2 in islets. METHODS: We isolated islets from 10 human pancreata and measured the expression of Bax mRNA and Bcl-2 mRNA by real-time quantitative polymerase chain reaction; islet and pancreas expression of Bax, Bcl-2, activated caspase-3, and cleaved poly (ADP-ribose) polymerase were also assessed by immunohistochemistry. Islet cell apoptosis was evaluated by terminal deoxynucleotide transferase-mediated dUTP nick-end labeling (TUNEL) assay and by flow cytometry. RESULTS: The mean (+/-SE) level of Bax mRNA was 336+/-79 copies per nanogram of total RNA, and the level of Bcl-2 mRNA was 36+/-10 (P=0.001). A positive correlation existed between islet expression of Bax mRNA and Bcl-2 mRNA (P=0.001). The islet Bax to Bcl-2 ratio was 10.8+/-1.3 and 1.71+/-0.3 for the spleens (P=0.0001). Bax mRNA (P=0.04), but not Bcl-2 mRNA, was expressed at a higher level in islets compared with spleens. Human islets contained large numbers of cells expressing Bax protein, whereas only infrequent islet cells expressed Bcl-2 protein, activated caspase-3, and poly (ADP-ribose) polymerase. The apoptotic index was 5% by TUNEL assay, and the percentage of apoptotic islet cells was 9.7+/-2.5% by flow cytometry. Sections of human pancreas before islet isolation showed islet staining for Bax but not Bcl-2. CONCLUSIONS: Our finding that isolated human islets express Bax at a higher level compared with Bcl-2 suggests a molecular mechanism for islet cell death by apoptosis. We hypothesize that reducing islet expression of Bax, or regulating its activation, will help preserve islet cell mass after islet transplantation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".