Microinjection into the <i>Caenorhabditis elegans</i> embryo using an uncoated glass needle enables cell lineage visualization and reveals cell-non-autonomous adhesion control
Bibliographic record
Abstract
Abstract Microinjection is a useful method in cell biology, with which exogenous substances are introduced into a cell in a location- and time-specific manner. The Caenorhabditis elegans embryo is an important model system for cell and developmental biology. Applying microinjection to the C. elegans embryo had been difficult due to the rigid eggshell surrounding the embryo. In 2013, microinjection method using a carbon-coated quartz needle for the C. elegans embryo was reported. To prepare the needle, unfortunately, special equipment is required and thus a limited number of researchers can use this method. In this study, we established a method for the microinjection of drugs, dyes, and microbeads into the C. elegans embryo using an uncoated glass needle that can be produced in a general laboratory. This method enabled us to easily detect cell lineage up to adult stages by injecting a fluorescent dye into a blastomere. We also found a cell-non-autonomous control mechanism of cell adhesion; specifically, the injection of an actin inhibitor into one cell at the 2-cell stage enhanced adhesion between daughter cells of the other cell. Our microinjection method is expected to be used for broad studies and could facilitate various discoveries using C. elegans .
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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) | 0.002 | 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".