A practical guide to genetic engineering of pancreatic β-cells<i>in vivo</i>: Getting a grip on RIP and MIP
Bibliographic record
Abstract
In vivo gene manipulation is a cornerstone approach in modern physiology. Cre-Lox technology has been extensively used to delete genes and activate reporters in pancreatic β-cells, bringing new insight into the pathophysiology of diabetes. In all cases, it is important to understand the expression domain of the specific reporter-Cre combination in order to correctly interpret the data. In the case of targeted genes with significant expression and function in the brain, the use of Ins2 promoter driven Cre, commonly known as RIP-Cre, has been shown to confound data interpretation when appropriate controls are not present. The recent article from the Philipson group in Islets provides an important characterization of a new Cre-deleter model, referred to as MIP1-CreER, which employs the mouse Ins1 promoter. This Ins1 promoter, recapitulating the expression pattern of the endogenous Ins1 gene, does not drive significant transgene expression in the brain and therefore is highly specific for deleting genes or turning on reporters in the pancreatic β-cell. This model promises to be widely used in the field of islet biology. Here, I review recent developments in the area of in vivo gene modification and predict areas where such tools will be refined further.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".