Molecular Profiling of Multiplexed Gene Markers to Assess Viability of <i>Ex Vivo</i> Human Colon Explant Cultures
Bibliographic record
Abstract
Human colon tissue explant culture provides a physiologically relevant model system to study human gut biology. However, the small (20-30 mg) and complex tissue samples used present challenges for monitoring tissue stability, viability, and provision of sufficient tissue for analyses. Combining molecular profiling with explant culture has potential to overcome such limitations, permitting interrogation of complex gene regulation required to maintain gut mucosa in culture, monitor responses to culture environments and interventions. Human ex vivo colon explant gene expression profiles were assayed using an in-house custom-designed hCellMarkerPlex assay at culture time points 0, 1, 2, 4, and 14 h. Characteristic profiles of epithelial cell markers linked to differentiation, cellular polarization, and apoptosis were correlated with visible histochemical changes in explant epithelium during culture and tissue donors. The GenomeLab System provides effective assay of multiple targets not possible from small tissue samples with conventional gene expression technology platforms. This is advantageous to increase the utility of the ex vivo human colon model in applications to interrogate this complex and dynamic tissue environment for use in analytical testing.
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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 | 0.001 | 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 | 0.001 |
| 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".