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Record W2917246659 · doi:10.1002/ajmg.a.61071

Disruption of the PTHLH regulatory landscape results in features consistent with hyperparathyroid disease

2019· article· en· W2917246659 on OpenAlexaff
Ashish R. Deshwar, Malte Spielmann, Lisa Vi, Roberto Mendoza‐Londono, Lucie Dupuis, Jennifer Stimec, Andrew Howard, Jennifer Harrington, Pekka Kannus

Bibliographic record

VenueAmerican Journal of Medical Genetics Part A · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Syndromes and Imprinting
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersScience and Engineering Research Board
KeywordsEnhancerRegulatory sequenceParathyroid hormoneCoding regionCancer researchBiologyTranscription factorMedicineEndocrinologyInternal medicineGeneticsGene

Abstract

fetched live from OpenAlex

Parathyroid hormone like hormone (PTHLH) signaling is essential for the proper formation of bone and its elevation or disruption has been directly implicated in several different skeletal dysplasias. We report a patient with a 2.802 Mb deletion upstream of the PTHLH coding sequence who presents with multiple fractures, metaphyseal changes, and overall features consistent with hyperparathyroid like disease. Analysis of the deleted region revealed the loss of putative regulatory regions adjacent to PTHLH and the possible gain of a limb enhancer. Furthermore, PTHLH expression appeared to be mis-regulated in fibroblasts derived from the patient. Altogether, we find that the disruption of the regulatory landscape of PTHLH likely results in its inappropriate expression and this novel clinical presentation.

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)0.000
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0020.000

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 head0.005
GPT teacher head0.237
Teacher spread0.231 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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Same venueAmerican Journal of Medical Genetics Part ASame topicGenetic Syndromes and ImprintingFrench-language works237,207