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Yon, M.

Publications and source records attributed to Yon, M..

13 recordsLinked to original sources

Multidimensional diffusion MRI reveals heterogeneous microstructural remodeling associated with amyloid pathology

Alzheimer's disease (AD) pathology involves amyloid deposition, reactive gliosis, and localized tissue alterations that coexist within the same brain regions, creating heterogeneous microstructural environments within individual imaging voxels. Conventional diffusion MRI averages these environments into aggregate measures, potentially obscuring their distinct contributions. Frequency-dependent multidimensional MRI ({omega}MD-MRI) resolves distributions of water components with different diffusion length scales, anisotropies, and relaxation properties, providing sensitivity to microstructural restriction, heterogeneity, and shape-size correlations within a voxel. Whether these measurements reveal microstructural complexity associated with AD pathology remains unclear. Here, we performed {omega}MD-MRI on ex vivo brain specimens from approximately 8-month-old 5xFAD and wild-type mice and interpreted the imaging findings alongside complementary histology. {omega}MD-MRI revealed widespread but spatially nonuniform differences between 5xFAD and wild-type brains. Measurements sensitive to microstructural restriction, heterogeneity, and shape-size correlations consistently indicated greater microstructural heterogeneity in 5xFAD brains, with the most prominent differences in the hippocampal formation and major cerebral white matter tracts. Complementary qualitative histology demonstrated extensive amyloid deposition and glial activation in affected regions, while overall cytoarchitecture and myelin organization remained largely preserved. Thus, the {omega}MD-MRI abnormalities occurred in tissue characterized by multiple coexisting pathological and relatively preserved microstructural environments rather than widespread structural degeneration. These findings demonstrate that {omega}MD-MRI can reveal the spatial and microstructural heterogeneity associated with amyloid pathology and provide a more comprehensive characterization of AD-related tissue alterations.

neuroscience↗

Ultra-high field microstructural MRI of living cortical organoids

Quantitative microstructural magnetic resonance imaging (MRI) can noninvasively characterize tissue configuration at micrometer scales, but clinical uptake is limited by validation and optimization in human-relevant scenarios. Organoids are powerful human-relevant tissue models, yet translation is hampered by lack of non-destructive, longitudinal microstructural assessment. Bridging these gaps, microstructural MRI of living organoids can accelerate MRI biomarker and organoid development and validation. Here, we address key obstacles to enable organoid microstructural MRI. First, we use a unique 28.2 T MRI system to achieve spatial resolution with adequate signal-to-noise ratio and feasible scan times. Second, we implement flexible acquisitions with fast readouts to expand multivariate experimental capacity. Third, we develop a workflow combining 3D MRI and 3D lightsheet microscopy for cross-modality anatomical comparison beyond 2D. Using this platform, we demonstrate microstructural MRI of cortical organoids with resolutions down to (20 {micro}m)3, revealing anisotropy, heterogeneity, maturation-dependent differences, and temporal changes in cortical organoids. Correlative lightsheet microscopy confirms correspondence to axonal and nuclear architecture. This platform enables live-organoid MRI as a complementary tool to human- and animal imaging for robust microstructural assessment.

biophysics↗

Complementary BOLD- and ADC-fMRI explore the role of lateral superior colliculus in flicker fusion frequency

The transition from static to dynamic vision is encoded in the superior colliculus, as recently shown using blood-oxygen-level-dependent functional MRI (BOLD-fMRI) of the rat brain. Visual stimulation at higher frequency than the flicker fusion frequency threshold leads to continuity illusion and is associated with negative BOLD response in the visual cortex, triggered by the superior colliculus. In this paper, we explored this mechanism using fMRI of the rat brain with visual stimulation at low (1Hz) and high (25Hz) frequency. We compared responses between different brain regions (the dorsolateral geniculate nucleus of the thalamus, the medial and lateral parts of the superior colliculus, and the visual cortex), sexes, and field strengths (9.4T and 14T, with varying contributions from large vessels). Results confirmed distinct neural responses to low and high frequency stimulation and highlighted the role of the lateral part of the superior colliculus in the transition from static to dynamic vision. Finally, we evaluated the ability of apparent diffusion coefficient (ADC)-fMRI to detect response to visual stimulation without vascular contribution. We found significant ADC-fMRI response in the medial and lateral parts of the superior colliculus but also in the corpus callosum. Our results highlight the ADC-fMRI high spatial specificity and high sensitivity to white matter.

neuroscience↗

Frequency-dependent diffusion tensor distribution imaging in the evaluation of ischemic stroke

Non-invasive MRI is widely used to assess and monitor ischemic stroke, yet conventional approaches often lack sensitivity to subtle microstructural changes and struggle to evaluate tissue viability across lesion, penumbra, and distal regions. In this study, frequency dependent diffusion tensor distribution imaging ({omega}DTD) was combined with clustering of diffusion tensor distributions D({omega}) and multivariate regression modeling to characterize ischemic tissue alterations in a whole brain section. Ex vivo {omega}DTD and histology were performed in rats subjected to middle cerebral artery occlusion (MCAO) or sham surgery (P = 17) 24 hours after reperfusion. Lesions showed cell loss and an increased presence of smaller, likely glial, cells. A random forest (RF) model was used to explain and predict histological parameters from diffusion tensor imaging (DTI), manually bin resolved {omega}DTD features, and cluster resolved {omega}DTD parameters. Model performance was evaluated using leave one animal out cross validation (LOO CV). {omega}DTD features better represented cell number than DTI metrics ({omega}DTD R2 = 0.73 vs. DTI R2 = 0.49), with similar advantages for nuclear area and circularity ({omega}DTD R2 = 0.64 and 0.61 vs. DTI R2 = 0.40 and 0.35). The RF model further proved beneficial in capturing complex, nonlinear relationships between MRI parameters and tissue characteristics. Overall, these results indicate that {omega}DTD provides richer microstructural information than standard DTI, and that combining {omega}DTD with advanced machine learning methods enhances interpretation of ischemic tissue damage.

neuroscience↗

Data-driven classification of tissue water populations by massively multidimensional diffusion-relaxation correlation MRI

Massively multidimensional diffusion-relaxation correlation MRI provides detailed information on tissue microstructure by analyzing water populations at a sub-voxel level. This method correlates frequency-dependent tensor-valued diffusion MRI with longitudinal and transverse relaxation rates, generating nonparametric D({omega})-R1-R2 distributions. Traditionally, D({omega})-R1-R2 distributions are separated using manual binning of the diffusivity and anisotropy space to differentiate white matter (WM), gray matter (GM), and free water (FW) in brain tissue. However, while effective, this approach oversimplifies complex tissue fractions and does not fully utilize all available diffusion-relaxation parameters. In this study, we implemented an unsupervised clustering approach to automatically classify WM, GM, and FW and explore additional water populations using all components in the D({omega})-R1-R2 distributions on ex vivo and in vivo rat brain, and in vivo human brain. Results showed that a basic separation of WM, GM, and FW is possible using unsupervised clustering even under different multidimensional diffusion-relaxation protocols of rat brain and human brain. Additionally, when there is high frequency-dependent diffusion range, it is possible to obtain a cluster characterized by restriction localized in specific high cell density regions such as the dentate gyrus and cerebellum of rat brain. These findings were compared with rat histological sections of myelin and Nissl stainings. We demonstrated that unsupervised clustering of diffusion-relaxation MRI data can reveal tissue complexity beyond traditional WM, GM, and FW segmentation in rat and human brain without parameter assumptions. The unsupervised cluster approach could be used in other body parts (e.g., prostate and breast cancer) without requiring pre-defined bin limits. Furthermore, the characterization of the clusters by diffusivities, anisotropy, and relaxation rates can provide a better understanding of the subtle changes in different cellular fractions in tissue-specific pathologies.

neuroscience↗

Ex vivo massively multidimensional diffusion-relaxation correlation MRI: scan-rescan reproducibility and caveats

Massively multidimensional diffusion-relaxation correlation MRI (MMD-MRI) provides information beyond the traditional voxel-averaged metric that may better characterize the microstructural characteristics of biological tissues. MMD-MRI reproducibility has been established in clinical settings, but has yet to be thoroughly evaluated under preclinical conditions, where superior hardware and modulated gradient waveforms enhance its performance. In this study, we investigate the reproducibility of MMD-MRI on a micro-imaging system using ex vivo mouse brains. Notably, the estimated signal fractions of intra-voxel spectral components in the MD-MRI distribution, corresponding to white and gray matter, along with the frequency-dependent parameters, demonstrated high reproducibility. We identified bias between scan and rescan in some of the metrics, which we attribute to the time gap between repeated scans pointing to a long-time progressive fixation effect. We compare our results with in vivo results from clinical scanners and show the reproducibility of diffusion frequency-dependent metrics to benefit from the improved gradient hardware on our preclinical setup. Our results inform future micro-imaging ex vivo MMD-MRI studies of the reproducibility of MMD-MRI metrics and their dependence on fixation time.

biophysics↗

In vivo rat-brain mapping of multiple gray matter water populations using nonparametric D(omega)-R1-R2 distributions MRI

Massively Multidimensional Diffusion MRI combines tensor-valued encoding, oscillating gradients, and diffusion-relaxation correlation to provide multicomponent sub-voxel parameters depicting the tissue microstructure. This method was successfully implemented ex vivo in micro-imaging systems and in clinical conditions but with a reduced diffusion frequency ({omega}) range due to the use of classical tensor-valued encoding. We demonstrate here its preclinical in vivo implementation with a protocol of 389 contrast images probing a wide diffusion frequency range of 18 to 92 Hz at b-values up to 2.1 ms/{micro}m2 enabled by the use of modulated gradient waveforms and combined with multislice high-resolution and low-distortion EPI acquisition with segmented and full reversed phase-encode acquisition. This framework allows the identification of diffusion{omega} -dependence in the rat cerebellum and olfactory bulb gray matter (GM) and the parameter distributions are shown to resolve two water pools in GM with different diffusion coefficients, shapes,{omega} -dependence, relaxation rates, and spatial repartition whose attribution to specific microstructure could modify the current understanding of the origin of restriction in GM.

biophysics↗

Frequency-dependence in multidimensional diffusion-relaxation correlation MRI of the brain: overfitting or meaningful parameter?

Time- or frequency-dependent ("restricted") diffusion potentially provides useful information about cellular-scale structures in the brain but is challenging to interpret because of the intravoxel tissue heterogeneity. Frequency-dependence was recently incorporated in a multidimensional diffusion-relaxation correlation MRI framework relying on tensor-valued diffusion encoding at multiple frequencies, as well as variable echo and repetition times, to give model-free characterization of intravoxel heterogeneity by Monte Carlo data inversion into nonparametric distributions of frequency-dependent diffusion tensors and nuclear relaxation rates. While microimaging equipment with high-amplitude magnetic field gradients allows exploration of frequencies from tens to hundreds of Hz, clinical scanners with more moderate gradient capabilities are limited to a narrow frequency range, which may be insufficient to observe effects of restricted diffusion for brain tissues. We here investigate the effects of including or omitting frequency-dependence in the data inversion from isotropic and anisotropic liquids, excised tumor tissue, ex vivo mouse brain, and in vivo human brain. For microimaging measurements covering a wide frequency range, from 35 to 320 Hz at b-values over 4{middle dot}109 sm-2, the inclusion of frequency-dependence drastically reduces the fit residuals and avoids bias in the diffusion metrics for tumor and brain voxels with micrometer-scale structures. Conversely, for the case of in vivo human brain investigated in the narrow frequency range from 5 to 11 Hz at b = 3{middle dot}109 sm-2, analyses with and without inclusion of frequency-dependence yield similar fit residuals and diffusion metrics for all voxels. These results indicate that frequency-dependent inversion may be generally applied to diffusion-relaxation correlation MRI data with and without observable effects of restricted diffusion.

biophysics↗

A Wars2 mutant mouse shows a sex and diet specific change in fat distribution, reduced food intake and depot-specific upregulation of WAT browning

1.BackgroundIncreased waist-to-hip ratio (WHR) is associated with increased mortality and risk of type 2 diabetes and cardiovascular disease. The TBX15-WARS2 locus has consistently been associated with increased WHR. Previous study of the hypomorphic Wars2V117L/V117L mouse model found phenotypes including severely reduced fat mass, and white adipose tissue (WAT) browning, suggesting Wars2 could be a potential modulator of fat distribution and WAT browning. MethodsTo test for differences in browning induction across different adipose depots of Wars2V117L/V117L mice, we measured multiple browning markers of a 4-month old chow-fed cohort in subcutaneous and visceral WAT and brown adipose tissue (BAT). To explain previously observed fat mass loss, we also tested for the upregulation of plasma mitokines FGF21 and GDF15 and for differences in food intake in the same cohort. Finally, to test for diet-associated differences in fat distribution, we placed Wars2V117L/V117L mice on low-fat or high-fat diet (LFD, HFD) and assessed their body composition by Echo-MRI and compared terminal adipose depot weights at 6 months of age. ResultsThe chow-fed Wars2V117L/V117L mice showed more changes in WAT browning marker gene expression in the subcutaneous inguinal WAT depot (iWAT) than in the visceral gonadal WAT depot (gWAT). These mice also demonstrated reduced food intake and elevated plasma FGF21 and GDF15, and mRNA from heart and BAT. When exposed to HFD, the Wars2V117L/V117L mice showed resistance to diet-induced obesity and a male and HFD-specific reduction of gWAT : iWAT ratio. ConclusionSevere reduction of Wars2 gene function causes a systemic phenotype which leads to upregulation of FGF21 and GDF15, resulting in reduced food intake and depot-specific changes in browning and fat mass.

physiology↗

Detection of SARS-CoV-2 Omicron variant (B.1.1.529) infection of white-tailed deer

White-tailed deer (Odocoileus virginianus) are highly susceptible to infection by SARS-CoV-2, with multiple reports of widespread spillover of virus from humans to free-living deer. While the recently emerged SARS-CoV-2 B.1.1.529 Omicron variant of concern (VoC) has been shown to be notably more transmissible amongst humans, its ability to cause infection and spillover to non-human animals remains a challenge of concern. We found that 19 of the 131 (14.5%; 95% CI: 0.10-0.22) white-tailed deer opportunistically sampled on Staten Island, New York, between December 12, 2021, and January 31, 2022, were positive for SARS-CoV-2 specific serum antibodies using a surrogate virus neutralization assay, indicating prior exposure. The results also revealed strong evidence of age-dependence in antibody prevalence. A significantly ({chi}2, p < 0.001) greater proportion of yearling deer possessed neutralizing antibodies as compared with fawns (OR=12.7; 95% CI 4-37.5). Importantly, SARS-CoV-2 nucleic acid was detected in nasal swabs from seven of 68 (10.29%; 95% CI: 0.0-0.20) of the sampled deer, and whole-genome sequencing identified the SARS-CoV-2 Omicron VoC (B.1.1.529) is circulating amongst the white-tailed deer on Staten Island. Phylogenetic analyses revealed the deer Omicron sequences clustered closely with other, recently reported Omicron sequences recovered from infected humans in New York City and elsewhere, consistent with human to deer spillover. Interestingly, one individual deer was positive for viral RNA and had a high level of neutralizing antibodies, suggesting either rapid serological conversion during an ongoing infection or a "breakthrough" infection in a previously exposed animal. Together, our findings show that the SARS-CoV-2 B.1.1.529 Omicron VoC can infect white-tailed deer and highlights an urgent need for comprehensive surveillance of susceptible animal species to identify ecological transmission networks and better assess the potential risks of spillback to humans. Key FindingsThese studies provide strong evidence of infection of free-living white-tailed deer with the SARS-CoV-2 B.1.1.529 Omicron variant of concern on Staten Island, New York, and highlight an urgent need for investigations on human-to-animal-to-human spillovers/spillbacks as well as on better defining the expanding host-range of SARS-CoV-2 in non-human animals and the environment.

microbiology↗

Multiple spillovers and onward transmission of SARS-Cov-2 in free-living and captive White-tailed deer (Odocoileus virginianus)

Many animal species are susceptible to SARS-CoV-2 and could potentially act as reservoirs, yet transmission of the virus in non-human free-living animals has not been documented. White-tailed deer (Odocoileus virginianus), the predominant cervid in North America, are susceptible to SARS-CoV-2 infection, and experimentally infected fawns can transmit the virus. To test the hypothesis that SARS-CoV-2 may be circulating in deer, we tested 283 retropharyngeal lymph node (RPLN) samples collected from 151 free-living and 132 captive deer in Iowa from April 2020 through December of 2020 for the presence of SARS-CoV-2 RNA. Ninety-four of the 283 deer (33.2%; 95% CI: 28, 38.9) samples were positive for SARS-CoV-2 RNA as assessed by RT-PCR. Notably, between November 23, 2020 and January 10, 2021, 80 of 97 (82.5%; 95% CI 73.7, 88.8) RPLN samples had detectable SARS-CoV-2 RNA by RT-PCR. Whole genome sequencing of the 94 positive RPLN samples identified 12 SARS-CoV-2 lineages, with B.1.2 (n = 51; 54.5%), and B.1.311 (n = 19; 20%) accounting for ~75% of all samples. The geographic distribution and nesting of clusters of deer and human lineages strongly suggest multiple zooanthroponotic spillover events and deer-to-deer transmission. The discovery of sylvatic and enzootic SARS-CoV-2 transmission in deer has important implications for the ecology and long-term persistence, as well as the potential for spillover to other animals and spillback into humans. These findings highlight an urgent need for a robust and proactive "One Health" approach to obtaining a better understanding of the ecology and evolution of SARS-CoV-2. One-Sentence SummarySARS-CoV-2 was detected in one-third of sampled white-tailed deer in Iowa between September 2020 and January of 2021 that likely resulted from multiple human-to-deer spillover and deer-to-deer transmission events.

microbiology↗

A groupwise registration and tractography framework for cardiac myofiber architecture description by diffusion MRI : an application to the ventriclar junctions

BackgroundKnowledge of the normal myocardial-myocyte orientation could theoretically allow the definition of relevant quantitative biomarkers in clinical routine to diagnose heart pathologies. A whole heart diffusion tensor template representative of the global myofiber organization over species is therefore crucial for comparisons across populations. In this study, we developed a groupwise registration and tractography framework to resolve the global myofiber arrangement of large mammalian sheep hearts. To demonstrate the potential application of the proposed method, a novel description of sub-regions in the intraventricular septum is presented. MethodsThree explanted sheep (ovine) hearts (size ~12x8x6 cm3, heart weight ~ 150 g) were perfused with contrast agent and fixative and imaged in a 9.4T magnet. A group-wise registration of high-resolution anatomical and diffusion-weighted images were performed to generate anatomical and diffusion tensor templates. Diffusion tensor metrics (eigenvalues, eigenvectors, fractional anisotropy ...) were computed to provide a quantitative and spatially-resolved analysis of cardiac microstructure. Then tractography was performed using deterministic and probabilistic algorithms and used for different purposes: i) Visualization of myofiber architecture, ii) Segmentation of sub-area depicting the same fiber organization, iii) Seeding and Tract Editing. Finally, dissection was performed to confirm the existence of macroscopic structures identified in the diffusion tensor template. ResultsThe template creation takes advantage of high-resolution anatomical and diffusion-weighted images obtained at an isotropic resolution of 150 m and 600 m respectively, covering ventricles and atria and providing information on the normal myocardial architecture. The diffusion metric distributions from the template were found close to the one of the individual samples validating the registration procedure. Small new sub-regions exhibiting spatially sharp variations in fiber orientation close to the junctions of the septum and ventricles were identified. Each substructure was defined and represented using streamlines. The existence of a fiber-bundles in the posterior junction was validated by anatomical dissection. A complex structural organization of the anterior junction in comparison to the posterior junction was evidenced by the high-resolution acquisition. ConclusionsA new framework combining cardiac template generation and tractography was applied on the whole sheep heart. The framework can be used for anatomical investigation, characterization of microstructure and visualization of myofiber orientation across samples. Finally, a novel description of the ventricular junction in large mammalian sheep hearts was proposed.

biophysics↗

Phenotyping of Klf14 mouse white adipose tissue enabled by whole slide segmentation with deep neural networks

White adipose tissue (WAT) plays a central role in metabolism, with multiple diseases and genetic mutations causing its remodeling. Quantitative analysis of white adipocyte size is of great interest to understand physiology and disease, but previous studies of H&E histology have been limited to a subsample of whole depot cross-sections. In this paper, we present the deep learning pipeline DeepCytometer, that can segment mouse and human whole slides ([~=]40,000 cells per mouse slide on average) using an adaptive tiling method, correct for cell overlap and reject non-white adipocytes from the segmentation. Using quantile colour maps we show intra- and inter-depot cell size heterogeneity with local correlation; quantile estimates also suggest significant differences in population estimates from 75 whole slides compared to smaller data sets. We propose three linked levels (body weight BW, depot weight DW and cell area quartiles) for exploratory analysis of mouse Klf14 phenotypes in gonadal and subcutaneous depots. We find a rich set of phenotypes when stratifying by sex, depot and three genotype strata: (1) WTs/Hets with a Het father (Controls), (2) WTs with a Het mother, and (3) Hets with a Het mother (functional KOs or FKOs). Namely, at BW level, mean difference testing suggests that female FKOs are similar to Controls, but WTs with a Het mother are significantly larger. At DW and cell levels, linear models with interaction terms and BW or DW covariates, respectively, reveal phenotypes not shown by difference of means tests. For example, at DW level, gonadal and subcutaneous models are similar, and female FKOs have lower fat percentage than Controls due to both an offset and the DW/BW slope in the linear model. Meanwhile, female WTs with a Het mother have on average similar fat percentage to Controls, but as their slopes are close to zero, their DWs are uncorrelated to BW, suggesting that larger female WTs with a Het mother have lower fat percentage than smaller ones. In contrast to depot level, at cell level female gonadal phenotypes diverge from subcutaneous ones. Furthermore, male Controls and FKOs have similar average area values in subcutaneous depots, but area~DW slope flattening in FKOs suggests that larger DWs could be caused by cell size increase in Controls and by cell count increase in FKOs. Thus, DeepCytometer and associated exploratory analysis reveal new insights into adipocyte heterogeneity and phenotyping.

bioinformatics↗