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Record W3033065537 · doi:10.1016/j.bone.2020.115472

Bone morphogenetic protein receptors: Structure, function and targeting by selective small molecule kinase inhibitors

2020· review· en· W3033065537 on OpenAlexfundno aff
Gonzalo Sánchez‐Duffhues, Eleanor Williams, Marie‐José Goumans, Carl‐Henrik Heldin, Peter ten Dijke

Bibliographic record

VenueBone · 2020
Typereview
Languageen
FieldMedicine
TopicHeterotopic Ossification and Related Conditions
Canadian institutionsnot available
FundersEshelman Institute for Innovation, University of North Carolina at Chapel HillJanssen PharmaceuticalsEuropean Research CouncilAFM-TéléthonFrench Muscular Dystrophy AssociationWellcome TrustInnovative Medicines InitiativeHartstichtingMeso Scale DiagnosticsCancer Genomics CentreZonMwBoehringer IngelheimTakeda Pharmaceutical CompanyEuropean Federation of Pharmaceutical Industries and AssociationsMerck KGaANederlandse Federatie van Universitair Medische CentraOntario GenomicsFundação de Amparo à Pesquisa do Estado de São PauloGenome CanadaNovartis PharmaCanada Foundation for InnovationOntario Genomics InstituteNovartisVetenskapsrådetPfizer
KeywordsBMPR2Bone morphogenetic protein receptorBone morphogenetic proteinCell biologySignal transductionKinaseSMADReceptorPhosphorylationActivin receptorBiologyEndoglinCell signalingCancer researchChemistryBiochemistryGene

Abstract

fetched live from OpenAlex

Bone morphogenetic proteins (BMPs) are secreted cytokines that control the fate and function of many different cell types. They exert their cellular responses via heteromeric complexes of specific BMP type I and type II serine/threonine kinase receptors, e.g. BMPRIA and BMPRII. Three type II and four type I receptors, also termed activin receptor-like kinases (ALKs), have been identified. The constitutively active type II kinase phosphorylates the type I receptor, which upon activation initiates intracellular signaling by phosphorylating SMAD effectors. Auxiliary cell surface receptors without intrinsic enzymatic motifs, such as Endoglin and Repulsive guidance molecules (RGM), can fine-tune signaling by regulating the interaction of the BMP ligands with the BMPRs. The functional annotation of the BMPR encoding genes has helped to understand underlying mechanisms of diseases in which these genes are mutated. Loss of function mutations in BMPRII, Endoglin or RGMc are causally linked to pulmonary arterial hypertension, hereditary hemorrhagic telangiectasia and juvenile hemochromatosis, respectively. In contrast, gain of function mutations in ACVR1, encoding ALK2, are linked to Fibrodysplasia ossificans progressiva and diffuse intrinsic pontine glioma. Here, we discuss BMPR identification, structure and function in health and disease. Moreover, we highlight the therapeutic promise of small chemical compounds that act as selective BMPR kinase inhibitors to normalize overactive BMPR signaling.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.018
GPT teacher head0.261
Teacher spread0.243 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations116
Published2020
Admission routes1
Has abstractyes

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