The Growth Medium Affects the Viability of IPEC-J2 Animal Cell Line in the Presence of Probiotic Bacteria
Bibliographic record
Abstract
Background: The IPEC-J2 cell line is frequently used as an in vitro model to study the bioactivity of live probiotics. However, lactic acid bacteria (LB) acidify the medium, and the impact of pH and lactic acid accumulation on cell viability seem to be underestimated. Methods: IPEC-J2 viability was assessed by neutral red and flow cytometry in the presence of eight probiotics at concentrations between 106 and 109 bacteria/mL in maintenance and buffered media. Results: It was shown that a high inoculation level led to higher cytotoxic effects on IPEC-J2 cells after 22 h of incubation and that viability losses were more related to a combination of low pH and lactic acid than to the probiotics themselves. Furthermore, with LB at 106 and 107 bacteria/mL, the addition of phosphates to the media significantly reduced the drop in the pH and preserved the IPEC-J2 viability between 100% and 69%, compared to a highly variable viability between 100% and 17.5% in the unbuffered media. Conclusions: Under certain in vitro conditions, probiotics can lead to the deterioration of animal cells, and pH neutralization is an essential parameter in the cell–probiotic system in order to preserve cell viability and to better evaluate the bioactive properties of live probiotics.
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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 | 0.000 |
| 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 | 0.001 |
| 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".