MétaCan
Menu
Back to cohort
Record W4415131557 · doi:10.1002/2211-5463.70141

Diabetes‐induced vascular calcification is associated with low pyrophosphate and its oral supplementation prevents calcification in diabetic mice

2025· article· en· W4415131557 on OpenAlexfundno aff
Krisztina Fülöp, Eszter Kozák, Natália Tőkési, Zsuzsanna Geszti, Adriána Kutás, Mariann Harangi, Ágnes Diószegi, Zsolt Rapi, József Balla, Olivier Le Saux, András Váradi, Viola Pomozi

Bibliographic record

VenueFEBS Open Bio · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDermatological and Skeletal Disorders
Canadian institutionsnot available
FundersNational Research, Development and Innovation OfficeNational Institutes of HealthDebreceni EgyetemHungarian Scientific Research FundMagyar Tudományos AkadémiaNemzeti Kutatási Fejlesztési és Innovációs HivatalQueen's UniversityHungarian Research Network
KeywordsCalcificationPyrophosphateAlkaline phosphataseAortaDiabetes mellitusEctopic calcification

Abstract

fetched live from OpenAlex

The predominant cause of death among diabetic patients comes from cardiovascular complications, including vascular calcification. The objectives of this study were to improve the understanding of the molecular mechanisms involved in diabetes-related calcification and to test potential preventive therapies. We found that levels of plasma pyrophosphate-a potent inhibitor of calcification-were decreased in type 1 and type 2 diabetic patients with cardiovascular symptoms. To further investigate vascular calcification, we developed a diabetic mouse model that showed increased aorta and renal calcification compared to control. Alkaline phosphatase activity was also increased in the circulation of diabetic mice, which resulted in a significant decrease in plasma pyrophosphate. Oral treatment with pyrophosphate prevented diabetes-induced calcification in mice, providing a direct translational value for clinical applications.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.012
GPT teacher head0.274
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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueFEBS Open BioSame topicDermatological and Skeletal DisordersFrench-language works237,207