MétaCan
Menu
Back to cohort
Record W4388598550 · doi:10.1016/j.rpth.2023.100392

OC 37.2 Activated PC Enhances the Renal Tubular Regeneration in Diabetic Kidney Disease

2023· article· en· W4388598550 on OpenAlexaff
Ahmed Elwakiel, Daksh Sanjay Gupta, Kunal Kumar Singh, Sameen Fatima, Saira Ambreen, Ajay Gupta, Shrey Kohli, Khurrum Shahzad, Berend Isermann

Bibliographic record

VenueResearch and Practice in Thrombosis and Haemostasis · 2023
Typearticle
Languageen
FieldMedicine
TopicRenal and Vascular Pathologies
Canadian institutionsMcGill University
Fundersnot available
KeywordsRegeneration (biology)KidneyMedicineDiseaseUrologyArtificial kidneyInternal medicineCell biologyBiology

Abstract

fetched live from OpenAlex

Background: Acute on chronic renal injury (ACRI) is a major health problem.Tubulointerstitial damage in diabetic kidney disease (DKD) impairs the outcome of acute kidney injury (AKI), possibly reflecting exhaustion of the renal regenerative capacity in DKD.The role of activated PC (aPC), which protects against DKD progression and reverses glucose-induced tubular senescence, for renal regeneration after AKI has not been elucidated hitherto.Aims: To delineate the possible role of aPC in controlling renal tubular cell proliferation and repair in DKD after AKI.Methods: A model of ACRI was established in mice with persistent hyperglycemia followed by ischemia-reperfusion injury (IRI).Control mice were compared to mice pre-treated with aPC.Lineage tracing and kidney single-cell RNA sequencing (scRNA-seq) were performed to identify the possible mechanisms of aPC.Ex-vivo analyses of mouse tissues and in vitro work were conducted to gain mechanistic insights.Results: DKD markedly aggravated histopathological changes and functional impairment following IRI.Pre-treatment with aPC conveyed renal protection.Lineage tracing studies revealed increased proliferation and expansion of tubular cell clones upon aPC pre-treatment.scRNA-seq showed marked changes in different cell populations in DKD mice subjected to IRI mainly in the tubular and immune cell clusters.Functional annotations identified activation of senescence pathways and inflammatory pathways in tubular cell and immune cell clusters, respectively.Pretreatment with aPC protected against these changes.Mechanistically, aPC treatment reduced oxidative DNA damage and induction of senescence in renal tubular cells, which was associated with increased proliferation and ex-vivo clonal expansion of tubular cells in DKD mice following IRI.Conclusion(s): aPC improves the outcome of ACRI by enhancing the regenerative capacity of renal tubular cells and reducing the inflammatory response.In DKD, aPC reverses glucose-induced senescence in tubular cells, thus restoring the regenerative capacity.Therefore, aPC-based therapeutics may provide innovative approaches to ACRI in patients with pre-existing DKD.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.177
GPT teacher head0.439
Teacher spread0.262 · 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

Explore more

Same venueResearch and Practice in Thrombosis and HaemostasisSame topicRenal and Vascular PathologiesFrench-language works237,207