NLRP7 and the genetics of post-molar choriocarcinomas in Senegal
Bibliographic record
Abstract
Gestational choriocarcinomas are malignant tumors of trophoblastic cells that affect 5-25% of women with sporadic hydatidiform moles (HMs) depending on countries and studies. Nucleotide binding and oligomerization domain-like receptor protein 7 (NLRP7) is a major gene responsible for recurrent HMs and recently mutations in this gene have also been shown in 13% of women with sporadic, non-recurrent moles. To investigate the role of NLRP7 in the genetic susceptibility for the malignant degeneration of moles, we sequenced its 11 exons in 43 Senegalese patients with post-molar choriocarcinomas. We report the presence of three novel NLRP7 variants that were found only in patients but not in 100 controls from the Senegalese general population, 100 controls from the Tunisian general population, and 100 controls from the Canadian population. In addition, this analysis revealed significant differences in the frequencies of four non-synonymous NLRP7 variants between European and Senegalese controls with the biggest difference being for variant G487E present at a minor allele frequency of 3.5% in Europeans, 18.1% in Tunisians and 45.6% in Senegalese. Comparing human NLRP7 and its paralog, NLRP2, with their mammalian counterparts revealed that allele E at position 487 is most likely the ancestral allele that was acquired in Africa but driven to low frequencies in Europeans and Asians due to migration, population bottlenecks and selective pressures. This study is the first attempt to investigate the role of NLRP7 in choriocarcinomas and highlights the higher frequencies of NLRP7 variants in the general Senegalese and Tunisian populations both known to have higher frequencies of moles and choriocarcinomas.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".