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Zuurbier, C. J.

Publications and source records attributed to Zuurbier, C. J..

2 recordsLinked to original sources
bioRxiv2025

Infarctsize-AI: an efficient infarct size image analysis tool for small rodent myocardial infarction studies

BackgroundMyocardial infarct size (IS) is the gold standard end-point in shorth-term studies on cardioprotection. However, IS quantification in rodent models with standard Evans Blue and 2,3,5-triphenyltetrazolium chloride (TTC) staining is time-consuming and prone to inter-observer variance. Therefore, we aimed to develop an artificial intelligence (AI)-based application to reduce time and inter-observer variability of IS analysis in rodent acute myocardial infarction (MI) models. MethodsWe used TTC/Evans blue-stained heart slice images of independent laboratories from previously published projects. Rat (n = 325 and 248 slices) and mouse (n = 77 slices) datasets were used to train deep learning segmentation models with three different neural network architectures, which were combined into a single AI analysis. AI analysis was compared with manual analysis on rat data from a training laboratory (internal data, n = 496 slices, n = 41 whole-hearts) and data from independent laboratories (external data, n = 60 and 62 slices). Additionally, two independent evaluators performed manual and AI-assisted analysis, consisting of AI-analysis and its manual correction, on internal (n = 36 slices) and external data (n = 37 slices). ResultsLins concordance correlation coefficient (CCC) between IS/AAR values from manual and AI analysis was 0.844 with 95% CI of [0.814; 0.869] for images of internal data heart slices. On external data heart slices, AI accurately annotated slice area and AAR but failed to annotate infarcted area. On internal whole-heart data, CCC between AI and AI-assisted IS/AAR was 0.894 with 95% CI of [0.812; 0.942]. AI-assisted analysis reduced evaluation time on both internal and external datasets and increased region overlap for AAR between the two independent evaluators on dependent data. ConclusionsAI-assisted analysis significantly reduced analysis time and inter-observer variability. For optimal performance, lab-specific AI training is recommended. Infarctsize-AI is available at https://infarctsize.com. Translational perspectiveMyocardial infarct size (IS) is the gold-standard end-point in shorth-term studies to assess potential cardioprotective therapies against acute myocardial infarction (AMI). However, IS quantification in rodent AMI models is time-consuming and prone to inter-observer variance. Therefore, we developed an AI-based software that can reduce analysis time and inter-observer variability and facilitate documentation, which facilitates the clinical translation of potential cardioprotective therapies. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=34 SRC="FIGDIR/small/688527v1_ufig1.gif" ALT="Figure 1"> View larger version (15K): org.highwire.dtl.DTLVardef@187c938org.highwire.dtl.DTLVardef@1ab8bb4org.highwire.dtl.DTLVardef@160dc68org.highwire.dtl.DTLVardef@264617_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗
bioRxiv2023

Sodium myo-inositol cotransporter-1, SMIT1, promotes cardiac hypertrophy and fibrosis in pressure overloaded mouse hearts

AimsRecent clinical studies have reported that myo-inositol is consistently elevated in plasma of patients with heart failure (HF), yet its role in cardiac dysfunction remains poorly understood. Myo-inositol is specifically transported into cells by the sodium-myo-inositol co-transporter-1 (SMIT1), a member of the sodium-glucose co-transporter (SGLT) family expressed in the heart. While myo-inositol is essential for phosphoinositide signaling, osmoregulation, and metabolic homeostasis, dysregulation of SMIT1-mediated myo-inositol transport may contribute to key pathological mechanisms in HF. This study aims to elucidate the role of SMIT1 in the failing heart, especially during left ventricular remodeling that precedes it. Methods and resultsWe used a mouse model of pressure overload induced by transverse aortic constriction in wild-type (WT) mice and mice lacking SMIT1 (Smit1-/-), and primary cultured cardiomyocytes. By combining molecular, structural and functional studies, RNA-sequencing, and calcium measurements, we demonstrate the contribution of myo-inositol and SMIT1 to pathological hypertrophy and the progression towards HF. We found that in comparison to WT controls, Smit1-/- mice were protected against aortic banding induced systolic dysfunction, cardiac fibrosis and hypertrophy. This hypertrophic response was driven by SMIT1 expression in cardiomyocytes, where it favors intracellular myo-inositol and Na+ entry, leading to inositol 1,4,5-trisphosphate (IP3)- and Ca2+-dependent pro-hypertrophic signaling. Following hemodynamic stress, deletion of SMIT1 significantly altered IP3/calcium effectors, including Carabin, which modulates cardiac hypertrophy through inhibition of the calcineurin/NFAT and Ras/ERK1/2 pathways. ConclusionsThis work provides important insights into the role of myo-inositol and SMIT1 in cardiomyocytes. We demonstrate that SMIT1 is a key driver of pathological hypertrophy by inducing an IP3/Ca2+-dependent pro-hypertrophic transcriptional reprogramming in cardiomyocytes. These findings identify SMIT1 as a promising therapeutic target for preventing or treating pathological cardiac hypertrophy and HF.

cell biology↗