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Record W4408371696 · doi:10.7150/ijms.103806

The Role of Mesenchymal Stem Cells in Treating Diabetic Kidney Disease: Immunomodulatory Effects and Kidney Regeneration

2025· article· en· W4408371696 on OpenAlexaff
Po-Jen Hsiao, W.H. Linda Kao, Li‐Chin Sung, Chia-Yi Lin, Liam Li-An Tsou, Yung-Hsi Kao, Chu‐Lin Chou, Kung-Ta Lee

Bibliographic record

VenueInternational Journal of Medical Sciences · 2025
Typearticle
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsNational Defence Medical Centre
Fundersnot available
KeywordsMesenchymal stem cellRegeneration (biology)Renal stem cellKidneyKidney diseaseStem cellDiseaseMedicineBiologyPathologyCell biologyInternal medicineProgenitor cell

Abstract

fetched live from OpenAlex

hUC-MSCs treatment may present a potential avenue for reversing glomerulosclerosis and mitigating inflammation in DKD mice. The long-term therapeutic benefits of MSCs-based treatments in patients with DKD and other kidney diseases could be further investigated.

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)0.003
metaresearch head score (Gemma)0.003
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 score0.425
Threshold uncertainty score0.334

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.012
GPT teacher head0.323
Teacher spread0.311 · 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

Citations7
Published2025
Admission routes1
Has abstractyes

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