Dielectrophoretic behavior of <i>in vitro</i> -derived bovine metaphase II oocytes and zygotes and its relation to <i>in vitro</i> embryonic developmental competence and mRNA expression pattern
Bibliographic record
Abstract
Selecting developmentally competent oocytes and zygotes based on their morphology is more often influenced by personal judgments and lacks universal standards. Therefore, this experiment was conducted to investigate the rate of development and mRNA level of dielectrophoretically separated oocytes and zygotes to validate dielectrophoresis (DEP) as non-invasive option for selection of oocytes and zygotes. In the first experiment, metaphase II oocytes with (PB(+)) and without (PB(-)) first polar body and zygotes were subjected to DEP at 4 MHz and 450 mum electrode distance and classified into fast, very fast, slow, and very slow depending on the time elapsed to reach one of the electrodes in the electric field. Parthenogenetic activation was employed to monitor the embryonic development of dielectrophoretically classified oocytes. The result revealed that at 6 and 7 days of post-activation, the blastocyst rate of very slow dielectrophoretic PB(+) and PB(-) oocytes was significantly (P < 0.05) lower than other groups. Similarly, in zygotes, the blastocyst rate at 7 days post-insemination was higher (P < 0.05) in the very fast dielectrophoretic categories when compared with the slow and very slow categories. In the second experiment, mRNA level was analyzed in the very fast and very slow dielectrophoretic PB(+) oocytes and zygotes respectively using the bovine cDNA microarray. The result showed that 36 and 42 transcripts were differentially regulated between the very fast and very slow dielectrophoretic categories PB(+) oocytes and zygotes respectively. In conclusion, dielectrophoretically separated oocytes and zygotes showed difference in the rate of blastocyst development accompanied by difference in transcriptional abundances.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".