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Record W3080426302 · doi:10.1002/jbmr.4171

Bone Vasculature and Bone Marrow Vascular Niches in Health and Disease

2020· review· en· W3080426302 on OpenAlexfundno aff
Junyu Chen, Michelle Hendriks, Alexandros Chatzis, Saravana K. Ramasamy, Anjali P. Kusumbe

Bibliographic record

VenueJournal of Bone and Mineral Research · 2020
Typereview
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsnot available
FundersH2020 European Research CouncilJohn Fell Fund, University of OxfordMedical Research Council CanadaKennedy Trust for Rheumatology ResearchMedical Research CouncilRoyal SocietyLeukaLeukaemia UKWellcome Trust
KeywordsBone marrowStem cellProgenitor cellHaematopoiesisBiologyHematopoietic stem cellBone cellPathologyCell biologyImmunologyMedicine

Abstract

fetched live from OpenAlex

Bone vasculature and bone marrow vascular niches supply oxygen, nutrients, and secrete angiocrine factors required for the survival, maintenance, and self-renewal of stem and progenitor cells. In the skeletal system, vasculature creates nurturing niches for bone and blood-forming stem cells. Blood vessels regulate hematopoiesis and drive bone formation during development, repair, and regeneration. Dysfunctional vascular niches induce skeletal aging, bone diseases, and hematological disorders. Recent cellular and molecular characterization of the bone marrow microenvironment has provided unprecedented insights into the complexity, heterogeneity, and functions of the bone vasculature and vascular niches. The bone vasculature is composed of distinct vessel subtypes that differentially regulate osteogenesis, hematopoiesis, and disease conditions in bones. Further, bone marrow vascular niches supporting stem cells are often complex microenvironments involving multiple different cell populations and vessel subtypes. This review provides an overview of the emerging vascular cell heterogeneity in bone and the new roles of the bone vasculature and associated vascular niches in health and disease. © 2020 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.120
GPT teacher head0.429
Teacher spread0.309 · 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

Citations168
Published2020
Admission routes1
Has abstractyes

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