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Record W4415984869 · doi:10.1186/s12920-025-02252-y

Identification of a VHL germline deletion in a family with Von Hippel-Lindau syndrome using MLPA-NGS

2025· article· en· W4415984869 on OpenAlexaff
Yongchen Yang, Xiaolan Ren, Chaoran Xia, Ying Zhang, Xiaozhen Song, Xiaojun Tang, Chengkan Du, Wuhen Xu, Wenhao Weng

Bibliographic record

VenueBMC Medical Genomics · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsSanger sequencingExonProbandGermlineExome sequencingBreakpointDNA sequencingHuman geneticsMultiplex ligation-dependent probe amplificationExome

Abstract

fetched live from OpenAlex

Von Hippel-Lindau syndrome (VHL) is an autosomal dominant disorder characterized by the development of tumors and cysts in multiple organs. Pathogenic variants in VHL are known to be associated with the development of this syndrome. Therefore, the present study aimed to investigate VHL rearrangements in a family with VHL syndrome. In the proband, who presented with retinal hemangioma, whole exome sequencing (WES) revealed significant genetic variation. However, WES did not detect germline deletion in VHL in the proband's son. Furthermore, multiplex ligation-dependent probe amplification (MLPA)-next-generation sequencing (NGS) analysis showed that the genomes of the proband and her son encompassed a deletion in VHL, extending from exon 2 to exon 3. Via increasing the probe density to gradually approach the breakpoint and following Sanger sequencing analysis, it was verified that an intermediate fragment of 6,662 bp was lost, with a reconnection occurring between chromosome 3:10145434 and 10,152,097 (GRCh38/hg38). Overall, the present study demonstrated that the application of MLPA-NGS technology combined with Sanger sequencing could be employed to precisely locate deleted DNA ‌fragments.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.492
Threshold uncertainty score0.448

Codex and Gemma teacher scores by category

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

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 head0.011
GPT teacher head0.266
Teacher spread0.254 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2025
Admission routes1
Has abstractyes

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