Comparison and culturing different types of cells from fresh breast milk with different culture medium
Bibliographic record
Abstract
Background: To investigate the properties of breast milk cells at different stages and culture different types of cells from fresh breast milk. Methods: Cell concentration and viability were analyzed after being isolated from fresh breast milk. Cell properties were tested by flow cytometry with different cell surface markers. Different types of breast milk cells were cultured with different medium. After being purified, the cells were identified by flow cytometry and immunofluorescence. Results: The concentration of breast milk cells decreased with lactation time. The viability of breast milk cells decreased gradually in both colostrum and transitional milk (C and T milk) group and mature milk group, and there was no significant difference in two groups over time. The expression levels of different cell surface markers were higher in C and T milk than mature milk. Using three different culturing media, we could get different types of cells including immune cells, mammary epithelial cells (MECs), mesenchymal stem cells (MSCs) and breast milk stem cells (BSCs) with different efficiency between C and T milk and mature milk. Conclusions: C and T milk contains more cells than mature milk, especially immunocytes. It is feasible to culture MECs with F medium, MSCs with M medium or F medium, and BSCs with CM medium.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".