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Record W6925239752 · doi:10.17632/f97gr7w6ck.2

Opposite Roles of IL-32α Versus IL-32β/γ Isoforms in Promoting Monocyte-Derived Osteoblast/Osteoclast Differentiation and Vascular Calcification in People with HIV

2025· dataset· en· W6925239752 on OpenAlexaff

Bibliographic record

VenueMendeley Data · 2025
Typedataset
Languageen
FieldPhysics and Astronomy
TopicNonlinear Photonic Systems
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsProinflammatory cytokinePathogenesisCytokineSubclinical infectionGene isoformDownregulation and upregulationBiomarkerDiseasePathophysiologyArterial stiffness

Abstract

fetched live from OpenAlex

People with HIV (PWH) have an increased risk of developing cardiovascular disease (CVD). Our recent data demonstrated that the multi-isoform proinflammatory cytokine IL-32 is upregulated in PWH and is associated with arterial stiffness and subclinical atherosclerosis. However, the mechanisms by which IL-32 contributes to the pathogenesis of these diseases remain unclear. Here, we show that while the less expressed IL-32α isoform induces the differentiation of human classical monocytes into the calcium-resorbing osteoclast cells, the dominantly expressed isoforms IL-32β and IL-32γ suppress this function through the inhibition of TGF-β and induce the differentiation of monocytes into the calcium-depositing osteocalcin+ osteoblasts. These results aligned with the increase in plasma levels of osteoprotegerin, a biomarker of vascular calcification, and its association with the presence of coronary artery subclinical atherosclerosis and calcium score in PWH. These findings support a novel role for the proinflammatory cytokine IL-32 in the pathophysiology of CVD by increasing vascular calcification in PWH.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.187
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.017
GPT teacher head0.259
Teacher spread0.242 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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

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