An efficient injection protocol for <i>Drosophila</i> larvae
Bibliographic record
Abstract
Abstract Intravenous injection provides a direct, rapid, and efficient route for delivering drugs or other substances, particularly for compounds with poor intestinal absorption or molecules (e.g. proteins) that are prone to structural changes and degradation within the digestive system. While Drosophila larvae represent a well-established genetic model for studying developmental and physiological pathways, as well as human diseases, their use in analyzing the molecular effects of substance exposure remains limited. In this study, we present a highly efficient injection method for Drosophila first- and second-instar larvae. Despite causing a slight developmental delay, this method achieves a high survival rate and offers a quick, easily adjustable protocol. The process requires 3–5 h to inject 150–300 larvae, depending on the microcapillary needle, microinjection system, and the compound being administered. As proof of concept, we compared the effects of injecting ferritin protein into Fer1HCH00451 mutant first instar larvae with those of dietary ferritin administration. Our results show that ferritin injection rescues Fer1HCH mutants, a result that cannot be achieved through dietary delivery. This approach is particularly valuable for the delivery of complex compounds in cases where oral administration is impaired or limited by the digestive system.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".