Search bioRxiv⌕ Search

bioRxiv · 10.64898/2026.07.10.737555

Synthetic Cannabidiol Attenuates Heart Failure Progression with Concomitant and Post Injury Administration Through Modulation of Immune and Endothelial to Mesenchymal Transition Related Remodeling Programs

Abstract

BackgroundCardiac fibrosis is a central driver of adverse remodeling in heart failure with reduced ejection fraction (HFrEF), yet therapies directly targeting these pathways remain less established. We investigated the role of a pharmaceutical-grade synthetic (s) cannabidiol in HFrEF using an invitro and in vivo strategy. MethodsHFrEF was induced in 12-week-old C57BL/6J mice using angiotensin II, L-NAME, and salt exposure. A 5-week (w) s-cannabidiol course was administered either concomitantly (beginning at week 0) during disease induction or after disease induction (beginning at week 4). Echocardiography, cardiac morphological characterization was performed at 5 and 9 weeks of the experiment. Cardiac tissue was processed for RNA extraction. Standard statistical and informatics methodology was used to compare groups. ResultsAt 5 weeks, mice in the concomitant s-cannabidiol group had reduced cardiomyocyte hypertrophy and fibrosis area with better isovolumetric relaxation time, ejection fraction, and fractional shortening compared to HFrEF mice. In the treatment after disease induction model, at 9 weeks, s-cannabidiol treated mice maintained therapeutic effect compared to 5w HFrEF mice but also had enhanced structural and functional recovery compared to mice that recovered naturally. Bulk RNA-sequencing analysis demonstrated a significant transcriptional change in HFrEF compared to controls, with s-cannabidiol partially shifting the cardiac transcriptome away from the failing state and attenuates the HF-enriched transcriptional programs of oxidative stress, inflammatory signaling, hypoxia, apoptosis, p53/MYC/mTORC1/E2F remodeling, and EMT/fibrotic remodeling, while enriching lipid/peroxisomal metabolic pathways. In an invitro HUVEC model of Endothelial to Mesenchymal Transition (EndMT), s-cannabidiol inhibited the transition and also reversed established EndMT, with these effects attenuated by pharmacologic inhibition of CB2 and PPAR{gamma}, but not CB1 receptors. Conclusionss-cannabidiol attenuates adverse remodeling in experimental HFrEF, promotes recovery after injury, and is associated with suppression of EndMT-related programs mediated through CB2/PPAR{gamma}-linked endothelial signaling.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Krishnamoorthi, M. K., Mendez-Fernandez, A., Patel, K., Amirthalingam Thandavarayan, R., Garcia Rivas, G., Lozano Garcia, O., Natarajan, K., Kassi, M., Yousefzai, R., Torre Amione, G., Trevino Alvarado, V. M., Bhimaraj, A.. 2026-07-16. Synthetic Cannabidiol Attenuates Heart Failure Progression with Concomitant and Post Injury Administration Through Modulation of Immune and Endothelial to Mesenchymal Transition Related Remodeling Programs. https://doi.org/10.64898/2026.07.10.737555

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Targeted finetuning enables co-folding models to learn ligand-induced protein conformational states

Advances in protein structure prediction have enabled all-atom protein-ligand co-folding models that predict bound conformations directly from sequence and small-molecule structure. However, these models often fail to generalize to novel binding sites or alternative protein conformational states, limiting their utility for chemical biology and drug discovery. Here we show this limitation reflects training data bias rather than architectural constraints and can be overcome through targeted finetuning. Using ten previously unseen X-ray structures of Werner (WRN) helicase from a drug discovery program, we finetune Boltz-1 to learn both an allosteric binding site and a large conformational change locking the enzyme in an inactive state, while preserving accuracy on the ATP-bound state. The finetuned model generalizes to different chemical series and transfers the conformational logic across RecQ-family helicases in a binding-site sequence-dependent manner. This approach provides a blueprint for adapting foundation models as new structural and mechanistic data emerge, enabling co-folding networks to capture ligand-induced conformational switches and binding poses absent from their training data but central to biological regulation and therapeutic intervention.

bioinformatics↗

Benchmarking single-cell foundation models for aging biology

Single cell foundation models (scFMs) provide representations of cellular states, but their utility across biological questions in aging research remains unclear. We established a benchmark of cellular representations for aging research, evaluating ten general-purpose scFMs, three aging-specific models and conventional methods across five biological questions using more than 2.5 million single cell transcriptomes. Using frozen pretrained representations, Geneformer performed best among scFMs for chronological age prediction and age pseudotime concordance, although 2,000 highly variable genes achieved higher mean performance. Several scFMs captured positive molecular age shifts across three disease contexts, consistent with reported aging-associated changes. SCimilarity performed well for rare cellular state identification across out-of-distribution datasets, exceeding aging specific models and conventional baselines. At the gene level, scGPT showed the highest recovery of reference TF target interactions, including aging-related regulatory hubs. Overall, scFMs supported diverse aging analyses, but performance depended on the biological question, highlighting their utility for rare cellular state identification and regulatory analysis.

bioinformatics↗

CryoMV: Structure-Prior-Guided Modeling and Real-Particle Validation of Continuous Conformational Transitions in Cryo-EM

Continuous protein conformations are essential for understanding fundamental biological processes and supporting drug discovery. Although cryo-EM can resolve individual states at high resolution, recovering continuous heterogeneity from 2D particle images remains challenging. High noise, motion blur, and limited structural priors make it difficult to accurately generate and validate high-resolution continuous conformations using raw particle data. Here, we introduce cryoMV, a framework that integrates structure-prior-guided modeling with real-particle validation for continuous conformational transitions. CryoMV uses reference density maps to establish structural anchors and motion priors, models candidate transition paths between selected conformations, and transfers the learned representation to raw 2D cryo-EM particle images. Each candidate conformation is subsequently evaluated using the estimated particle poses and contrast transfer functions. Supported conformations are reconstructed through raw particle back-projection and assessed using canonical half-maps and Fourier shell correlation. On EMPIAR-10516 and EMPIAR-10345, cryoMV achieves excellent performance in terms of robustness, verifiability, and reconstruction resolution. By incorporating structure-prior modeling and evidence from the raw particles, cryoMV offers an explicit mechanism for assessing whether generated conformations are supported by experimental data and provides a practical approach to reducing model-induced artifacts in continuous cryo-EM heterogeneity analysis.

bioinformatics↗