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Ohayon, J.

Publications and source records attributed to Ohayon, J..

3 recordsLinked to original sources

Extracellular vesicles from wild-type Epstein-Barr virus-transformed B-cells export host DNA and the viral lncRNA EBER1

Epstein-Barr virus (EBV) infection is nearly ubiquitous and strongly linked to multiple sclerosis (MS), but how EBV-infected B cells communicate with distal tissues remains unclear. We performed an integrated multiomic characterization of small extracellular vesicles (sEVs) released from spontaneous lymphoblastoid cell lines (SLCLs) derived from healthy donors and patients with MS, transformed ex vivo by endogenous wild-type EBV. Proteomics identified over 6,000 shared proteins enriched in nucleic acid-binding and chromatin-associated factors. EV-associated DNA resolved into two structurally distinct compartments: DNase-sensitive, high-molecular weight DNA associated with the vesicle corona and DNase-resistant, nucleosome-sized ([~]130-150 bp) DNA. Both compartments were overwhelmingly host-derived and broadly genomically distributed, whereas EBV DNA was minimal. In contrast, viral RNA cargo was dominated by the EBV noncoding RNA EBER1, which was strikingly enriched across all lines and confirmed within individual vesicles by ddPCR and super-resolution microscopy. EBER1 has previously been detected in MS brain tissue, yet its route to the CNS has remained unexplained. Our findings identify sEVs as a plausible vehicle for disseminating this immunostimulatory viral ncRNA beyond sites of latency, pointing to EV-mediated export of EBER1 as a candidate mechanism linking peripheral EBV infection to distal tissue signaling in MS and beyond.

immunology↗

In-silico heart model phantom to validate cardiac strain imaging

The quantification of cardiac strains as structural indices of cardiac function has a growing prevalence in clinical diagnosis. However, the highly heterogeneous four-dimensional (4D) cardiac motion challenges accurate "regional" strain quantification and leads to sizable differences in the estimated strains depending on the imaging modality and post-processing algorithm, limiting the translational potential of strains as incremental biomarkers of cardiac dysfunction. There remains a crucial need for a feasible benchmark that successfully replicates complex 4D cardiac kinematics to determine the reliability of strain calculation algorithms. In this study, we propose an in-silico heart phantom derived from finite element (FE) simulations to validate the quantification of 4D regional strains. First, as a proof-of-concept exercise, we created synthetic magnetic resonance (MR) images for a hollow thick-walled cylinder under pure torsion with an exact solution and demonstrated that "ground-truth" values can be recovered for the twist angle, which is also a key kinematic index in the heart. Next, we used mouse-specific FE simulations of cardiac kinematics to synthesize dynamic MR images by sampling various sectional planes of the left ventricle (LV). Strains were calculated using our recently developed non-rigid image registration (NRIR) framework in both problems. Moreover, we studied the effects of image quality on distorting regional strain calculations by conducting in-silico experiments for various LV configurations. Our studies offer a rigorous and feasible tool to standardize regional strain calculations to improve their clinical impact as incremental biomarkers.

bioengineering↗

Complete spatiotemporal quantification of cardiac motion in mice through enhanced acquisition and super-resolution reconstruction

The quantification of cardiac motion using cardiac magnetic resonance imaging (CMR) has shown promise as an early-stage marker for cardiovascular diseases. Despite the growing popularity of CMR-based myocardial strain calculations, measures of complete spatiotemporal strains (i.e., three-dimensional strains over the cardiac cycle) remain elusive. Complete spatiotemporal strain calculations are primarily hampered by poor spatial resolution, with the rapid motion of the cardiac wall also challenging the reproducibility of such strains. We hypothesize that a super-resolution reconstruction (SRR) framework that leverages combined image acquisitions at multiple orientations will enhance the reproducibility of complete spatiotemporal strain estimation. Two sets of CMR acquisitions were obtained for five wild-type mice, combining short-axis scans with radial and orthogonal long-axis scans. Super-resolution reconstruction, integrated with tissue classification, was performed to generate full four-dimensional (4D) images. The resulting enhanced and full 4D images enabled complete quantification of the motion in terms of 4D myocardial strains. Additionally, the effects of SRR in improving accurate strain measurements were evaluated using an in-silico heart phantom. The SRR framework revealed near isotropic spatial resolution, high structural similarity, and minimal loss of contrast, which led to overall improvements in strain accuracy. In essence, a comprehensive methodology was generated to quantify complete and reproducible myocardial deformation, aiding in the much-needed standardization of complete spatiotemporal strain calculations.

bioengineering↗