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Ulutas, E. Z.

Publications and source records attributed to Ulutas, E. Z..

2 recordsLinked to original sources

High-resolution in vivo kinematic tracking with injectable fluorescent nanoparticles

Behavioral quantification is a cornerstone of many neuroscience experiments. Recent advances in motion tracking have streamlined the study of behavior in small laboratory animals and enabled precise movement quantification on fast (millisecond) timescales. This includes markerless keypoint trackers, which utilize deep network systems to label positions of interest on the surface of an animal (e.g., paws, snout, tail, etc.). These approaches mark a major technological achievement. However, they have a high error rate relative to motion capture in humans and are yet to be benchmarked against ground truth datasets in mice. Moreover, the extent to which they can be used to track joint or skeletal kinematics remains unclear. As the primary output of the motor system is the activation of muscles that, in turn, exert forces on the skeleton rather than the skin, it is important to establish potential limitations of techniques that rely on surface imaging. This can be accomplished by imaging implanted fiducial markers in freely moving mice. Here, we present a novel tracking method called QD-Pi (Quantum Dot-based Pose estimation in vivo), which employs injectable near-infrared fluorescent nanoparticles (quantum dots, QDs) immobilized on microbeads. We demonstrate that the resulting tags are biocompatible and can be imaged non-invasively using commercially available camera systems when injected into fatty tissue beneath the skin or directly into joints. Using this technique, we accurately capture 3D trajectories of up to ten independent internal positions in freely moving mice over multiple weeks. Finally, we leverage this technique to create a large-scale ground truth dataset for benchmarking and training the next generation of markerless keypoint tracker systems.

neuroscience↗

Understanding Lesion Progression in a Chronic Model of Cerebral Cavernous Malformations through Combined MRI and Histology

Cerebral cavernous malformations (CCM), also known as cavernous angiomas, are blood vessel abnormalities comprised of clusters of grossly enlarged and hemorrhage-prone capillaries. The prevalence in the general population, including asymptomatic cases, is estimated to be 0.5%. Some patients develop severe symptoms, including seizures and focal neurologic deficits, while others have no symptoms. The causes of this remarkable presentation heterogeneity within a primarily monogenic disease remain poorly understood. To address this problem, we have established a chronic mouse model of CCM, induced by postnatal ablation of Krit1 with Pdgfb-CreERT. These mice develop CCM lesions gradually over 4-6 months of age throughout of the brain. We examined lesion progression in these mice with T2-weighted 7T MRI protocols. Precise volumetric analysis of individual lesions revealed non-monotonous behavior, with some lesions temporarily growing smaller. However, the cumulative lesional volume invariably increased over time and accelerated after about 3 months. Next, we established a modified protocol for dynamic contrast enhanced (DCE) MR imaging and produced quantitative maps of gadolinium tracer MultiHance in the lesions, indicating a high degree of heterogeneity in lesional permeability. Multivariate comparisons of MRI properties of the lesions with cellular markers for endothelial cells, astrocytes, and microglia revealed that increased cell density surrounding lesions correlates with stability, while increased vasculature within and surrounding lesions may correlate with instability. Our results lay a foundation for better understanding individual lesion properties and provide a comprehensive pre-clinical platform for testing new drug and gene therapies for controlling CCM.

neuroscience↗