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Vascular Growth Factors and Glomerular Disease

2016· review· en· W1894886495 on OpenAlexfundno aff
Christina S. Bartlett, Marie Jeansson, Susan E. Quaggin

Bibliographic record

VenueAnnual Review of Physiology · 2016
Typereview
Languageen
FieldMedicine
TopicRenal Diseases and Glomerulopathies
Canadian institutionsnot available
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Heart, Lung, and Blood InstituteCanadian Institutes of Health Research
KeywordsGlomerulusPodocyteMesangiumCell biologyGlomerular mesangiumParacrine signallingEndotheliumKidney GlomerulusBiologyPathologyMedicineGlomerulonephritisEndocrinologyInternal medicineKidneyReceptor

Abstract

fetched live from OpenAlex

The glomerulus is a highly specialized microvascular bed that filters blood to form primary urinary filtrate. It contains four cell types: fenestrated endothelial cells, specialized vascular support cells termed podocytes, perivascular mesangial cells, and parietal epithelial cells. Glomerular cell-cell communication is critical for the development and maintenance of the glomerular filtration barrier. VEGF, ANGPT, EGF, SEMA3A, TGF-β, and CXCL12 signal in paracrine fashions between the podocytes, endothelium, and mesangium associated with the glomerular capillary bed to maintain filtration barrier function. In this review, we summarize the current understanding of these signaling pathways in the development and maintenance of the glomerulus and the progression of disease.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.720
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.002
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 head0.017
GPT teacher head0.324
Teacher spread0.308 · 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.

Study designSystematic review
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
Published2016
Admission routes1
Has abstractyes

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