The potential translational utility of embalmed cadaveric gastrointestinal tract specimens: a proof-of-concept study
Bibliographic record
Abstract
Background in recent decades, fewer autopsies are performed, often replaced by radiological imaging, resulting in abundant imaging data but few complete anatomical examinations. While most surgical specimens are limited to the disease-affected region. Examining the entire gastrointestinal system of anatomical donors and histologically analysing them could enhance research and valorise donation programs, extending medical knowledge. One factor limiting the preservation of the digestive tract in cadavers is the post-mortem interval. Embalming is one of the most widely used methods to preserve donors, but the post-mortem interval affects the gastrointestinal tract in a stable and time-dependent manner, making its histological examination a challenge. Material and Methods this proof-of-concept study assesses the histological potential of gastrointestinal tissues from embalmed bodies used for anatomical education. Digestive tissues from four donors (two embalmed after 12 hours, two after 72 hours postmortem) were histologically processed. A scoring system evaluated histological preservation by assessing seven parameters. Results analysis showed high-quality preservation of embalmed tissues, including intestinal villi, the aorta, and liver sinusoids, highlighting both normal and pathological architecture, such as atherosclerosis, liver fibrosis, and lymphocyte infiltration. Features were identifiable with excellent histological detail in both the 12-hour and 72-hour post-mortem interval groups. Although this is a proof-of-concept study, only a slight difference was found between the two groups, with significant differences only in epithelium and vessel characteristics. Conclusions This study demonstrated that donors’ digestive tissues could be suitable for detailed analyses and insights into chronic diseases and ageing, even in cadavers with a long post-mortem interval.
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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 | 0.003 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".