Microchimerism as a source of information on future pregnancies
Bibliographic record
Abstract
Small numbers of fetal cells cross the placenta during pregnancy turning mothers into microchimeras. Fetal cells from all previous pregnancies accumulate forming the mother's fetal microchiome. What is significant about microchimeric cells is that they have been linked to health problems including reproductive and autoimmune diseases. Three decades after the discovery of fetal microchimerism, the function of these cells remains a mystery. Here, we contend that the role of microchimeric cells is to inform the fetus about the likelihood that its genes are present in future pregnancies. We argue that, when genes are more likely than average to be in future maternal siblings, fetuses will send a fixed number of cells that will not elicit a maternal immune response against them. However, when genes are less likely to be in future maternal siblings, fetuses will send an ever-increasing number of cells that will elicit an ever-stronger maternal immune response. Our work can explain the observed clinical association between microchimeric cells and pre-eclampsia. However, our work predicts that this association should be stronger in women with a genetically diverse microchiome. If supported by medical tests, our work would allow establishing the likelihood of pregnancy or autoimmune problems advising medical interventions.
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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 | 0.004 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".