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Record W3130808652 · doi:10.1111/cge.13941

Novel pathogenic variants in <scp> <i>NLRP7</i> </scp> , <scp> <i>NLRP5</i> , </scp> and <scp> <i>PADI6</i> </scp> in patients with recurrent hydatidiform moles and reproductive failure

2021· article· en· W3130808652 on OpenAlexafffund
Maryam Rezaei, Beena Suresh, Eric Bereke, Zahra Hadipour, Mónica Aguinaga‐Ríos, Jianhua Qian, Rashmi Bagga, Majid Fardaei, Reda Hemida, Sujatha Jagadeesh, Jacek Majewski, Rima Slim

Bibliographic record

VenueClinical Genetics · 2021
Typearticle
Languageen
FieldMedicine
TopicGestational Trophoblastic Disease Studies
Canadian institutionsMcGill University and Génome Québec Innovation CentreMcGill University Health Centre
FundersCanadian Institutes of Health ResearchNational Natural Science Foundation of China
KeywordsBiologyAndrologyMedicineChemistryMicrobiology

Abstract

fetched live from OpenAlex

Recurrent hydatidiform moles (RHMs) are human pregnancies with abnormal embryonic development and hyperproliferating trophoblast. Biallelic mutations in NLRP7 and KHDC3L, members of the subcortical maternal complex (SCMC), explain the etiology of RHMs in only 60% of patients. Here we report the identification of seven functional variants in a recessive state in three SCMC members, five in NLRP7, one in NLRP5, and one in PADI6. In NLRP5, we report the first patient with RHMs and biallelic mutations. In PADI6, the patient had four molar pregnancies, two of which had fetuses with various abnormalities including placental mesenchymal dysplasia and intra-uterine growth restriction, which are features of Beckwith-Wiedemann syndrome and Silver Russell syndrome, respectively. Our findings corroborate recent studies and highlight the common oocyte origin of all these conditions and the continuous spectrum of abnormalities associated with deficiencies in the SCMC genes.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.021
GPT teacher head0.279
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations53
Published2021
Admission routes2
Has abstractyes

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