Partial trisomy 16q and partial monosomy 7p of a fetus derivated from paternal balanced translocation
Bibliographic record
Abstract
INTRODUCTION: Subchromosomal deletions and duplications could currently be detected by noninvasive preliminary screening (NIPS). However, NIPS is a screening test that requires further diagnosis. Here we report a fetus with an autosomal abnormality revealed by NIPS and conventional karyotype combined with copy number variations sequencing (CNV-seq) confirmed the fetus with an unbalanced translocation. PATIENT CONCERN: This was the fourth pregnancy of a 30-year-old woman who underwent 2 spontaneous abortions and gave birth to a child with a normal phenotype. The woman and her husband were healthy and nonconsanguineous. NIPS indicated a repeat of about 19-Mb fragment at the region of 16q22.1-q22.4 at 17-week gestation. DIAGNOSES: The combination of traditional karyotype and CNV-seq could better locate the abnormal chromosomal region and further identify the source of fetal chromosomal abnormalities. Simultaneously, we evaluated the fetal morphology by ultrasound examination. The karyotype of the fetus was 46,XX,der(7)t(7;16)(p22;q23) and CNV-seq results showed an approximately 20.96-Mb duplication in 16q22.1-q24.3 (69200001-90160000) and an approximately 3.86-Mb deletion in 7p22.3-p22.2 (40001-3900000). Prenatal ultrasound revealed the fetal micrognathia. The paternal karyotype was 46,XY, t (7;16) (p22;q23), while the maternal was normal. The fetus inherited an abnormal chromosome 7 from its father. INTERVENTIONS: No treatment for the fetus. OUTCOMES: Pregnancy was terminated. CONCLUSIONS: To our knowledge, the occurrence of de novo partial trisomy 16q (16q22.1-qter) and partial monosomy 7p (7p22.2-pter) has not previously been reported up to now. Here, we present the perinatal findings of such a case and a review of the literatures. CNV-seq combined with karyotype is a useful tool for chromosomal abnormalities indicated by NIPS.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".