Comments on Methods to Suppress Endogenous β-Galactosidase Activity in Mouse Tissues Expressing the <i>LacZ</i> Reporter Gene
Bibliographic record
Abstract
The Escherichia coli LacZ gene (encoding β-galactosidase) is a widely used reporter for gene regulation analysis in transgenic mice. Determination of β-galactosidase activity is classically performed using 5-bromo-4-chloro-3-indolyl-β-d-galactopyranoside/ferri-/ferrocyanide (X-Gal/FeCN) histochemistry. Uncertainty about the origin of the β-galactosidase signal is encountered in tissues containing high levels of endogenous β-galactosidase. Here, we show that reliable results can nevertheless be obtained in these tissues by performing the histochemical reaction under slightly basic pH conditions (pH 8-9). We further demonstrate that in this context, analysis of tissue sections may be advantageous over that of conventional whole-mount tissues because poor dye penetration and remaining tissue acidity are avoided in tissue sections. We also recommend that bacterial debris should always be carefully removed from the luminal surface of gastrointestinal tract specimens unless staining of resident microflora is deliberately used as an internal positive control in the assay. Finally, we show that 6-chloro-3-indolyl-β-d-galactopyranoside with nitrotetrazolium blue chloride works well as an alternative chromogenic substrate for visualizing LacZ reporter gene expression in cryostat sections. Its use in high endogenous β-galactosidase-expressing organs is superior over the use of X-Gal/FeCN at slightly basic pH conditions.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.099 | 0.106 |
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".