Biochemical markers for pregnancy in the spent culture medium of in vitro produced bovine embryos
Bibliographic record
Abstract
The present study aimed to identify biomarkers to assess the quality of in vitro produced (IVP) bovine embryos in the culture media. IVP embryos on Day (D) 5 of development were transferred to individual drops, where they were maintained for the last 48 h of culture. Thereafter, the medium was collected and the embryos were transferred to the recipients. After pregnancy diagnosis, the media were grouped into the pregnant and nonpregnant groups. The metabolic profiles of the media were analyzed via electrospray ionization mass spectrometry, and the concentrations of pyruvate, lactate, and glutamate were assessed using fluorimetry. The spectrometric profile revealed that the media from embryos from the pregnant group presented a higher signal intensity compared to that of the nonpregnant group; the ions 156.13 Da [M + H]+, 444.33 Da [M + H]+, and 305.97 Da [M + H]+ were identified as biomarkers. Spent culture medium from expanded blastocysts (Bx) that established pregnancy had a greater concentration of pyruvate (p = 0.0174) and lesser concentration of lactate (p = 0.042) than spent culture medium from Bx that did not establish pregnancy. Moreover, pyruvate in the culture media of Bx can predict pregnancy with 90.9% sensitivity and 75% specificity. In conclusion, we identified markers in the culture media that helped in assessing the most viable IVP embryos with a greater potential to establish pregnancy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".