MétaCan
Menu
Back to cohort
Record W2588339221 · doi:10.1093/ndt/gfv187.24

SP024MURINE RECOMBINANT ACE2 ATTENUATES KIDNEY INJURY IN EXPERIMENTAL ALPORTS SYNDROME (AS)

2015· article· en· W2588339221 on OpenAlexaff
Eun Hui Bae, Ana Konvalinka, Fei Fang, Vanessa Williams, Xuewen Song, Shao‐Ling Zhang, Rohan John, Gavin Y. Oudit, York Pei, James W. Scholey

Bibliographic record

VenueNephrology Dialysis Transplantation · 2015
Typearticle
Languageen
FieldMedicine
TopicNeurological and metabolic disorders
Canadian institutionsUniversity of AlbertaUniversité de MontréalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineRecombinant DNAAcute kidney injuryKidneyInternal medicineBiochemistryGene

Abstract

fetched live from OpenAlex

Introduction and Aims: ACE2 is a monocarboxypeptidase in the renin angiotensin systemthat catalyzes the breakdown of Angiotensin II (AngII) to Ang1-7. We have reported that ACE2 expression and activity in the kidney are reduced in experimental AS but the impact of this finding on kidney disease progression has not been studied. Accordingly, we evaluated the effects of treatment with murine recombinant ACE2 (mrACE2) inCol4A3-/- mice, a model of AS characterized by proteinuria and progressive renal injury. Methods: The mrACE2 was administered from 4 -7 weeks of agevia osmotic mini-pump (0.5mg/kg/day). Results: Treatment with mrACE2 led to an increase in both kidney renal ACE2 expression and the urinary ACE2 excretion rate in 7-week-old Col4A3-/- mice compared to untreated group. Kidney AngII levels declined and kidney Ang1-7 levels increased. These effects were associated with a significant decrease in proteinuria in the treated 7-week-old Col4A3-/- mice compared to the untreated group. The inflammatory cytokine IL-6and F4/80, a macrophage marker,werealso reduced by treatment withmrACE2. Transforming growth factor-β1 (TGF-β1),col1α1, and alpha smooth muscle actinlevels were increased in the kidneys of 7-week-old Col4A3-/- mice and all were reduced by mrACE2.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.292
Threshold uncertainty score0.718

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.278
Teacher spread0.261 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueNephrology Dialysis TransplantationSame topicNeurological and metabolic disordersFrench-language works237,207