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Record W4415530071 · doi:10.1101/2025.10.23.684000

Levosimendan Ameliorates Adverse Pulmonary Vascular Remodeling in Group-2 Pulmonary Hypertension

2025· preprint· W4415530071 on OpenAlexaff
Antonella abi sleimen, Ruaa Al Qazazi, Yann Grobs, Yahe Xu, Tsukasa Shimauchi, Ashley Martin, Danchen Wu, Reem El-Kabbout, Manon Mougin, Charlie Théberge, Steeve Provencher, Olivier Boucherat, Sébastien Bonnet, Stephen L. Archer, François Potus

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Language
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsQueen's University
Fundersnot available
KeywordsLevosimendanPulmonary hypertensionHemodynamicsInotropeVasodilationHeart failureCardiac function curveAdverse effect

Abstract

fetched live from OpenAlex

Abstract Aims Pulmonary hypertension (PH) due to left heart disease (Group-2PH) is the most common form of PH and comprises two distinct subtypes: isolated post-capillary-PH (IpcPH) and combined post-and pre-capillary-PH (CpcPH). Despite its high prevalence and poor prognosis, no targeted therapies are currently approved, largely due to the absence of reliable preclinical models that recapitulate these human hemodynamic phenotypes. Levosimendan, a calcium sensitizer with inotropic and vasodilatory properties, has shown promise in early clinical trials for Group-2PH, but its mechanisms of action remain unclear. This study aimed to develop and validate experimental models of IpcPH and CpcPH and to assess the therapeutic effects of levosimendan on pulmonary vascular remodeling, inflammation, and cardiac function to support ongoing clinical translation. Methods and Results In a multicentre preclinical study, we established two rodent models that faithfully replicate the human IpcPH and CpcPH hemodynamic profiles. CpcPH animals exhibited severe pulmonary vascular remodeling, inflammatory cell infiltration, and a distinct pro-proliferative transcriptomic signature, whereas IpcPH animals showed minimal pulmonary vascular involvement. Levosimendan (3 mg/kg/day, 3 weeks) improved biventricular function and pulmonary hemodynamics in both models. In CpcPH, levosimendan additionally reduced pulmonary vascular remodeling, attenuated inflammation, and partially reversed disease-associated transcriptomic reprogramming. Transcription factor enrichment analysis identified NF-κB as a key upstream regulator inhibited by treatment. In a translational extension, nine circulating inflammation-related-proteins differentiated CpcPH from IpcPH patients; among them, TNF, IL-12B, 4E-BP1, NT-3, NGF, FGF21, and FGF23 predicted poor survival. IL-18 and 4E-BP1 were elevated in CpcPH lungs and decreased following levosimendan treatment. Conclusions Inflammation is a major contributor to adverse pulmonary vascular remodeling in CpcPH. Levosimendan improves cardiac performance and mitigates pulmonary vascular inflammation and remodeling, supporting its potential as a dual-action therapeutic agent in Group-2PH. These findings validate novel preclinical models and provide mechanistic evidence reinforcing ongoing clinical evaluation of levosimendan in this condition. Translational perspective Group-2 PH lacks targeted therapies, partly due to the absence of validated preclinical models. We validated models recapitulating human IpcPH and CpcPH and identified inflammation as a key driver of pulmonary vascular remodeling in CpcPH. Levosimendan improved biventricular function and reduced vascular remodeling and inflammation through NF-κB inhibition. Circulating IL-18 and 4E-BP1 reflected disease severity and treatment response. These findings establish robust translational models, reveal inflammatory mechanisms underlying CpcPH, and provide mechanistic evidence supporting ongoing clinical trials of levosimendan as a dual-action therapeutic strategy in Group-2 PH.

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: Observational · Consensus signal: none
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)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0020.000

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 head0.023
GPT teacher head0.247
Teacher spread0.225 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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