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Record W3126536341

Identification of Novel Therapeutic Approaches to the Progression of Chronic Kidney Disease

2020· dissertation· W3126536341 on OpenAlexafffund
Vanessa Williams

Bibliographic record

VenueTSpace · 2020
Typedissertation
Language
FieldArts and Humanities
TopicHermeneutics and Narrative Identity
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health ResearchKidney Foundation of CanadaUniversity of TorontoAlport Syndrome FoundationChonnam National UniversityAmgen
KeywordsIdentification (biology)Kidney diseaseMedicineDiseaseComputational biologyIntensive care medicineData scienceBiologyComputer scienceInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Progression of chronic kidney disease (CKD) to renal failure is a substantial international public health problem. Existing treatments have limited effectiveness as they slow, but do not prevent, progression. This is particularly true for rare forms of CKD. Accordingly, we sought to identify and test new therapeutic approaches to Alport syndrome (AS), a rare genetic condition characterized by progressive CKD. AS is caused by mutations in the genes encoding collagen, type IV, alpha (COL4A) chains present in the glomerular basement membrane. Mutations interfere with normal assembly of the COL4A network necessary for maintenance of the glomerular filtration barrier, leading to glomerular injury, proteinuria, and interstitial fibrosis. We studied Col4a3–/– mice, an experimental model displaying these hallmarks of AS. We have reported that intrarenal expression of angiotensin-converting enzyme 2 (ACE2), a peptidase that catalyzes conversion of angiotensin (Ang) II to Ang-(1–7), is decreased in Col4a3–/– mice. We therefore examined effects of recombinant ACE2 (rACE2) administration on kidney injury in Col4a3–/– mice. Treatment with rACE2 affected turnover of renal ACE2 likely through suppression of tumor necrosis factor alpha-converting enzyme. rACE2 also mitigated kidney mitogen-activated protein kinase (MAPK) activation, fibrosis, and oxidative stress. Utilizing an unbiased approach, we defined a disease progression signature reflecting transcript-level expression patterns detected in Col4a3–/– kidneys during development of CKD. We performed computational drug repurposing by querying the Connectivity Map for potential compounds to reverse signature gene expression. Vorinostat, a lysine deacetylase (KDAC) inhibitor emerged as a potential treatment. Vorinostat reduced tubulointerstitial fibrosis and prolonged survival of Col4a3–/– mice. In tubular epithelial cells, vorinostat prevented Ang II- and albumin-induced MAPK phosphorylation and activator protein 1 activation. Taken together, this work identified two novel treatment approaches to AS: rACE2 delivery and KDAC inhibition. These studies also demonstrated that regulation of Ang peptide metabolism and lysine acetylation via ACE2 and KDACs, respectively, are important determinants of disease progression in experimental CKD, at least in part, due to their impact on MAPK signaling and evolution of interstitial fibrosis. This dissertation provides a rationale for rACE2 therapy and KDAC blockade in humans with CKD.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.118
GPT teacher head0.335
Teacher spread0.218 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2020
Admission routes2
Has abstractyes

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