Cleavage-stage embryo rotation tracking and automated micropipette control: Towards automated single cell manipulation
Bibliographic record
Abstract
Micromanipulation of individual biological cells, such as embryos during preimplantation genetic diagnosis (PGD), is a delicate and time-consuming task. Two major procedures in PGD include the rotation of the embryo to gain a more favorable position for zona breaching, and the extraction of a blastomere after an opening has been made in the zona pellucida. Rotation tracking of cleavage-stage embryos has not been reported given their lack of distinctive features. In this manuscript, a geometric model for partially determining the three dimensional (3-D) angular position of 2-cell embryos using two dimensional (2-D) microscopic brightfield images was derived and verified using a computer generated model. This model was then applied using computer vision algorithms on a rotating cleavage-stage mouse embryo, demonstrating partial 3-D rotation tracking. Furthermore, embryo micromanipulation tasks are typically performed manually using micropipettes. Technological advances have made automation of these tasks possible. This manuscript also presents computer vision algorithms for the segmentation and calibration of micropipettes. The calibration procedure allowed automated position control of the micropipettes without the need for real-time vision feedback using micropipette recognition algorithms, and effective position control was verified using semi-automated blastomere extraction experiments. This manuscript presents preliminary work towards the automation of cell manipulation procedures.
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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 | 0.000 |
| 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 | 0.000 |
| 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".