Development of a Specific Monoclonal Antibody to Detect Male Cells Expressing the RPS4Y1 Protein
Bibliographic record
Abstract
Hemophilia is an X-linked recessive bleeding disorder. In pregnant women carrier of hemophilia, the fetal sex can be determined by non-invasive analysis of fetal DNA circulating in the maternal blood. However, in case of a male fetus, conventional invasive procedures are required for the diagnosis of hemophilia. Fetal cells, circulating in the maternal bloodstream, are an ideal target for a safe non-invasive prenatal diagnosis. Nevertheless, the small number of cells and the lack of specific fetal markers have been the most limiting factors for their isolation. We aimed to develop monoclonal antibodies (mAbs) against the ribosomal protein RPS4Y1 expressed in male cells. By Western blotting, immunoprecipitation and immunofluorescence analyses performed on cell lysates from male human hepatoma (HepG2) and female human embryonic kidney (HEK293) we developed and characterized a specific monoclonal antibody against the native form of the male RPS4Y1 protein that can distinguish male from female cells. The availability of the RPS4Y1-targeting monoclonal antibody should facilitate the development of novel methods for the reliable isolation of male fetal cells from the maternal blood and their future use for non-invasive prenatal diagnosis of X-linked inherited disease such as hemophilia.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".