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Record W4409747298 · doi:10.3389/fcell.2025.1564847

Podocytes in health and glomerular disease

2025· review· en· W4409747298 on OpenAlexafffund
Joanna Cunanan, Dongke Zhang, Anna Julie Peired, Moumita Barua

Bibliographic record

VenueFrontiers in Cell and Developmental Biology · 2025
Typereview
Languageen
FieldMedicine
TopicRenal Diseases and Glomerulopathies
Canadian institutionsToronto General HospitalUniversity of TorontoUniversity Health Network
FundersCanadian Institutes of Health Research
KeywordsPodocyteCell biologyActin cytoskeletonSlit diaphragmBiologyCytoskeletonCellKidneyGenetics

Abstract

fetched live from OpenAlex

Podocytes are highly specialized, terminally differentiated cells in the glomerulus of the kidney and these cells play a central role in blood filtration. In this review, we comprehensively describe the cell biology of podocytes under healthy conditions and in glomerular disorders wherein podocyte injury is a major pathological mechanism. First, the molecular mechanisms that maintain podocyte actin cytoskeleton structure, permanent cell cycle exit, and metabolism under healthy conditions are described. Secondly, the mechanisms of podocyte injury, including genetic alterations and external insults that ultimately disrupt podocyte actin cytoskeleton dynamics or interrupt podocyte quiescence and mitochondrial metabolism are discussed. This understanding forms the basis of described potential therapeutic agents that act by modulating dysregulated podocyte cytoskeleton organization, prevent or reverse cell cycle re-entry, and re-establish normal mitochondrial energy production. Lastly, the application of modern techniques such as single cell RNA sequencing, super resolution microscopy, atomic force microscopy, and glomerular organoids is improving the resolution of mechanistic podocytopathy knowledge. Taken together, our review provides critical insights into the cellular and molecular mechanisms leading to podocyte loss, necessary for the advancement of therapeutic development in glomerular diseases.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.975
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
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 head0.015
GPT teacher head0.297
Teacher spread0.282 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations20
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueFrontiers in Cell and Developmental BiologySame topicRenal Diseases and GlomerulopathiesFrench-language works237,207