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Record W2084767196 · doi:10.1097/mnh.0b013e32832c9dba

Glomerular filtration barrier

2009· review· en· W2084767196 on OpenAlexaff
Börje Haraldsson, Marie Jeansson

Bibliographic record

VenueCurrent Opinion in Nephrology & Hypertension · 2009
Typereview
Languageen
FieldMedicine
TopicRenal Diseases and Glomerulopathies
Canadian institutionsMount Sinai HospitalLunenfeld-Tanenbaum Research Institute
Fundersnot available
KeywordsFiltration (mathematics)Renal functionChemistryMedicineInternal medicineMathematics

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: In 2008, more than 376 papers were published on the glomerular barrier. Most of them dealt with the podocyte and its role in kidney disease. RECENT FINDINGS: There is new information on signaling pathways that are utilized in podocytes during proteinuria. Interestingly, the glomerular endothelium, with its fenestrae and glycocalyx, seems to be important for the maintenance of an intact glomerular barrier. All new advances at the molecular level are compatible with a highly size and charge-selective glomerular membrane and refute the concept of a 'leaky' glomerular barrier with tubular retrieval of intact albumin. Still, the hypothesis has its advocates, keeping a stimulating 'charge debate' alive. SUMMARY: Glomerular diseases account for 90% of chronic kidney disease requiring dialysis and transplantation at an annual cost of $20 billion in the USA. In clinical practice, we lack specific treatment of these diseases, giving us plenty of room for improvement. Future research should be directed toward deeper understanding of the signaling pathways involved in different conditions of proteinuria, the cross-talk between cell types in the glomerulus, and the identification of novel targets for treatment of acquired kidney 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 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)0.001
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 score0.019
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0190.012

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 head0.085
GPT teacher head0.369
Teacher spread0.285 · 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

Citations79
Published2009
Admission routes1
Has abstractyes

Explore more

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