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Record W7071865094

UNDERSTANDING HOW ACTIVINS CONTRIBUTE TO TGFß1 PROFIBROTIC SIGNALIING IN CHRONIC KIDNEY DISEASE

2023· dissertation· en· W7071865094 on OpenAlexfundno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2023
Typedissertation
Languageen
FieldComputer Science
TopicQR Code Applications and Technologies
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchUniversity of TorontoChinese Academy of SciencesKidney Foundation of Canada
KeywordsFollistatinKidney diseaseContext (archaeology)FibrosisMediatorTransforming growth factorExtracellular matrixReceptorKidney
DOInot available

Abstract

fetched live from OpenAlex

Chronic kidney disease (CKD) affects around 11% of people in North America and is expected to rise. CKD is characterized by the development of fibrosis requiring kidney transplant or dialysis to survive as a direct result of impaired kidney function. TGFβ1 is a prominent profibrotic mediator in this context and is secreted by mesangial cells, tubular cells and fibroblasts. These cells once activated contribute to excessive production of extracellular matrix (ECM) proteins deteriorating functional renal tissue. The direct inhibition of TGFβ1 has limitations due to adverse effects in humans that alternative methods have gain popularity. Here, we discover activin A (actA), a member of TGFβ1 superfamily, playing a crucial role in sustaining the chronic effects of TGFβ1. Activins are multifunctional secreted cytokines synthesized as homo- or hetero-dimers of inhibin β subunits A, B, C or E. Previously, there have been attempts at blocking actA using various inhibitors such as a naturally occurring antagonist called follistatin (FST), ActRIIA/B trap and antibody. However, there is the risk of uncertain side effects due to their non specificity in blocking other ligands important to various cellular processes. Similarly, other variants of activins such as actAC has been shown to abrogate actA-induced pSmad2/3 signaling however little is known about their long-term effects. It is important to note that actA has been found highly elevated in serum and kidneys from human and mice with CKD. We hypothesize that actA regulates both canonical and noncanonical pathways to control TGFβ1-induced profibrotic responses. In the first study, within mesangial cells (MCs), the profibrotic effects of TGFβ1 are sustained primarily through the secretion of actA as it promotes Smad3 phosphorylation and transcriptional activity when MCs exhibit reduced sensitivity to TGFβ1 but not actA. This in part is facilitated by actA upregulating TGFβ1 receptor type II helping continue downstream signaling. Furthermore, actA enhances transcription through activation of MRTF-A, Smad3 co-activator fibrotic genes. Notably, actA neutralization effectively inhibits fibrosis induced by unilateral ureteral obstruction (UUO) in wildtype mice. Interestingly, TGFβ1-overexpressing mice with CKD (UUO) exhibit worsened fibrosis, accompanied by increased renal expression of actA and that its neutralization mitigated these outcomes. In the second study, we established a novel 5/6 nephrectomy animal model overexpressing TGFβ1 in C57BL/6 background mice resistant to hypertension and fibrosis to directly assess for actA faciliatory role in the maladaptive epithelial-mesenchymal crosstalk from long-term tubulointerstitial fibrosis caused by TGFβ1. TGFβ1 induces secretion of actA from tubular cells and actA neutralization prevents TGFβ1 profibrotic response in renal fibroblasts, interestingly, through Smad3 and YAP. This led us to our third study, which was to investigate TGFβ1’s regulation of the actA gene (INHBA). Results reveal critical transcription factors (Stat5, Foxp1 and Smad3) controlling actA promoter activity within 350 bp region of actA promoter. Targeting actA inhibition shows promise as an antifibrotic approach with potentially better clinical tolerability than direct TGFβ1 inhibition.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.037
GPT teacher head0.232
Teacher spread0.194 · 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 designBench or experimental
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
Published2023
Admission routes1
Has abstractyes

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