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Record W2588151809 · doi:10.1093/ndt/gfw178.30

SP671CALCINEURIN INHIBITION WITHOUT THERAPEUTIC DRUG MONITORING?

2016· article· en· W2588151809 on OpenAlexaff
Robert B. Huizinga, Neil Solomons, Mark D. Abel

Bibliographic record

VenueNephrology Dialysis Transplantation · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSignaling Pathways in Disease
Canadian institutionsAurinia (Canada)
Fundersnot available
KeywordsMedicineTherapeutic drug monitoringDrugPharmacologyIntensive care medicine

Abstract

fetched live from OpenAlex

Introduction and Aims: The goal of treatment in lupus nephritis (LN) is to induce remission, preserve native renal function and minimize side effects. Voclosporin (VCS) is a novel calcineurin inhibitor intended for use in the treatment of autoimmune diseases and the prevention of organ graft rejection. Voclosporin was created by adding a single carbon extension to the amino acid-1 (AA1) region of cyclosporine A (CsA). X-Ray crystallography studies have shown that this addition alters cyclophilin-voclosporin complex binding to the catalytic and regulatory subunits in calcineurin. This change in binding has increased the potency of voclosporin relative to CsA and shifted the primary site for voclosporin metabolism to the amino acid-9 position. This leads to lower overall metabolite loads than seen for CsA resulting in less competitive antagonism with voclosporin. The combination of increased potency and a change in metabolite profile for voclosporin allows for administration of lower doses, less pharmacokinetic-pharmacodynamic variability and a potentially improved safety profile compared with other calcineurin inhibitors. Previously published data have demonstrated the strong correlation between VCS concentrations and efficacy which might allow for accurate dosing of patients.

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: Commentary · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.011
GPT teacher head0.253
Teacher spread0.242 · 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
GenreCommentary

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

Citations1
Published2016
Admission routes1
Has abstractyes

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