Apollo-NADP+ in 3D: Investigating In Vivo NADPH/NADP+ Redox Dynamics in Zebrafish Pancreatic β Cells
Bibliographic record
Abstract
The insulin-secreting β cells of the pancreas show low pentose phosphate pathway (PPP) activity, which is the main source of NADP+ reduction for NADPH generation in many other cell types. NADPH is required for reactive oxygen species scavenging and anabolic metabolism, thus it is unclear how β cells compensate for this limited PPP activity to avoid dysfunction and diabetes pathogenesis. To measure the dynamics of NADPH/NADP+ metabolism, our lab developed Apollo-NADP+, a genetically-encoded anisotropy sensor for NADPH/NADP+ based on NADP+-dependent homo-dimerization of enzymatically inactive glucose-6-phosphate dehydrogenase (G6PD). Anisotropy-based sensors provide ratiometric measurements with high spatial-temporal resolution and occupy low consumption of the spectral bandwidth. My goal was to translate the Apollo-NADP+ sensor in vivo to measure live cell dynamics and track endogenous cellular events. We show that two major challenges associated with in vivo translation of anisotropy sensors, light scattering and interactions with endogenous proteins, do not prevent the use of Apollo-NADP+ in vivo. We then generated transgenic zebrafish with β cell expression of Apollo-NADP+ and developed an in vivo assay using microfluidic devices to measure the endogenous β cell NADPH/NADP+ redox dynamics of zebrafish larvae. Using this assay, we show that pyruvate cycling is the main source of NADP+ reduction in β cells, with contributions from folate cycling after acute electrical activation. Finally, we evaluated a variety of image analysis and machine learning tools for segmenting and tracking individual cells in order to identify β cell subpopulations within the larval zebrafish pancreatic islet based on heterogeneity in NADPH/NADP+ redox dynamics. Overall, this thesis demonstrates the feasibility and utility of using anisotropy sensors such as Apollo-NADP+ in vivo, furthers our understanding of β cells redox biology, and makes progress towards automated single-cell image analysis.
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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".