Efficiency of Co-Expression of Transcription Factors Pdx1, Ngn3, NeuroD and Pax6 with Insulin: A Statistical Approach
Bibliographic record
Abstract
Aim: The objective of this study was to investigate the time related profile and efficiency of co-expression of the homeodomain proteins Pdx1, NeuroD, Ngn3, Pax6 and caspase3 with insulin, and to establish the time periods post PDL optimum for islets transplantation. Study Design/Methods: In this experimental study, immunofluorescent staining procedure was performed on deparaffinized pancreatic duct ligated (PDL) tissues of 78 Sprague–Dawley rats. Quantification of protein coexpression was made using a computerized morphometry. The efficiency of co-expression was arbitrary defined by the value of mean ratio (score without unit) of insulin expression divided by each expression index of the other proteins, occurring within the time interval of 12–24 h post PDL. Statistical tool was used to analyze the efficiency of co-expression of proteins; analysis of variances (one way ANOVA) was used to compare the means of co-expression indexes across the time periods pre- and post PDL. P-values less than 0.05 were considered statistically significant; no post hoc test was done. Results: The curve of insulin expression showed a crossover with that of the co-expression at different time periods pre- and post PDL. The optimal or higher efficiency of co-expression was observed for insulin and Ngn3 co-expression, while a good or medium efficiency was noted for the co-expression of insulin with Pdx1, insulin with NeuroD and insulin with Pax6. Low or weak efficiency was observed for the co-expression of insulin with caspase3. Conclusion: We therefore propose an early islets transplantation using 12–24 h post PDL harvested pancreatic tissues.
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 | 0.019 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".