Quantification of donor microchimerism in sex-mismatched porcine allotransplantation by competitive PCR
Bibliographic record
Abstract
The persistence of donor cells in recipient circulation and peripheral tissues post-transplantation has been demonstrated in solid organ allotransplantation and xenotransplantation models. Although this state of microchimerism has been postulated as the basis for graft acceptance, chimerism has not been directly linked to the maintenance of peripheral tolerance or prevention of rejection. Studies have demonstrated that the qualitative presence or absence of donor microchimerism bears no association with graft acceptance. Our preliminary work suggests that there is a threshold chimerism necessary for the induction of donor-specific hyporesponsiveness. Because the kinetics of donor cell accumulation and distribution in allograft recipients are largely unknown, quantitative analyses are needed to evaluate chimerism's significance to donor-specific tolerance. We developed a quantitative, competitive PCR assay to precisely measure the amount of chimerism in male to female transplant pairs by targeting the sex-determining region of the Y chromosome (SRY gene). Traditionally, this technique requires that serial known amounts of an SRY-specific competitive template (CT) be coamplified with a constant amount of sample DNA to determine the equivalence point of the relative band intensities of the PCR products. However running a panel of PCRs with CT amounts above and below the equivalence point to generate a standard curve for ever' sample is laborious. Here we describe the generation of a single standard curve that permits the rapid and reliable quantification of microchimerism after coamplification of sample DNA with a single amount of CT.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".