Application of Human Plasma/Serum to Cell Culture In Vitro: A Translational Research Approach to Better Define Disease Mechanisms
Bibliographic record
Abstract
In vitro cell culture experiments play an important role in medical research. Various cellular mechanisms and signaling pathways have been identified with in vitro experimental techniques. Unfortunately, the clinical and translational impact of these studies is often limited due to their inability to closely resemble physiological or pathophysiological milieus in cell culture and the use of unrealistic experimental conditions. Thus, further developments must be made to improve the translation of in vitro cell culture work. The application of human plasma or serum as a stimulus for cells, human or otherwise, is a relatively new approach that ultimately overcomes many of the in vitro limitations and provides a more physiologically relevant model. While this technique has been used for the investigation of various diseases and pharmacological mechanisms, discrepancies remain regarding the appropriate methodologies. This review provides insight into recent findings through the application of human plasma or serum as stimuli, as well as an analysis of methodological considerations and suggestions for future directions.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".