Biology subjects

Karandikar, S.

Publications and source records attributed to Karandikar, S..

3 recordsLinked to original sources

bioRxiv2026

Charting neuroimaging-based head circumference and cranial shape across development

Quantitative assessment of head growth supports early detection of neurological disease, yet current clinical practice relies on manual measurements that are variable, anatomically limited, and difficult to scale. Here we introduce a fully automated imaging-native framework (CranioTrace) that transforms routine neuroimaging into standardized, population-referenced markers of cranial development. By integrating topology-constrained segmentation, contour regularization, and geometry-based quality control for automated slice selection, CranioTrace robustly extracts head circumference and cranial morphology from heterogeneous MRI and CT data without manual intervention. The framework enabled construction of sex-specific population growth models across pediatric development in a dataset comprising 9,685 scans spanning birth to early adulthood across 25 cohorts. Imaging-derived head circumference shows strong agreement with tape measurements across independent datasets, high reproducibility (intraclass correlation up to 0.99), and consistent performance across modalities. Beyond conventional head circumference, CranioTrace quantifies cranial shape and asymmetry, capturing developmental dynamics that are not accessible through conventional measurements. Population modeling reveals rapid early-life expansion followed by nonlinear deceleration and stable sex differences. Application to neurogenetic cohorts identifies disease-consistent shifts in growth trajectories: head circumference was higher in neurofibromatosis type 1 and 16p11.2 deletion and lower in 22q11.2 deletion and 16p11.2 duplication. By converting clinical imaging archives into scalable cranial phenotypes linked to probabilistic reference models, CranioTrace provides a foundation for imaging-based growth charting, integrated skull-brain phenotyping, and precise assessment of neurodevelopment.

neuroscience↗

bioRxiv2025

LoAR-Exo and HiAR-Exo: One-step label-free isolation of extracellular vesicles using inertial microfluidic devices

Extracellular vesicles (EVs) are lipid membrane-bound nanoscale (20 nm - 1000 nm) objects shed by all cells. As EVs play an important role in intercellular signaling, these have emerged as promising biomarkers for many diseases including cancer and neurodegenerative disorders. A major bottleneck in research into EVs and their smooth translation to clinic as disease biomarkers is a lack of access to affordable and user-friendly technologies to quickly isolate EVs from complex biological and clinical samples with acceptable purity and yield. Here, we report two different designs of inertial microfluidic devices (e.g. LoAR-Exo and HiAR-Exo) that can isolate EVs from different kinds of biological samples in a single label-free step using a spiral microchannel design with different aspect ratios. LoAR-Exo has a height-to-width aspect ratio [~] 1, while HiAR-Exo has a height-to-width aspect ratio of 2.5, optimized by COMSOL simulations. We tested both designs by separating polystyrene particles of size < 1 m from a heterogeneous mixture. We then benchmarked the performance of the microfluidic chips against ultracentrifugation and a precipitation kit by isolating EVs from the cell culture-conditioned media (CCM) of MDA-MB-231 cells. We also compared the microchip with SEC by using the CCM from H1975/OR cells. The size distribution of EVs isolated by the microfluidic chip was comparable with ultracentrifugation, precipitation and SEC. In summary, both devices isolated EVs from as little as 1 mL of sample volume using a label-free technique in a continuous manner and without any user intervention. Both microfluidic platforms offer a simple, efficient, and scalable alternative to conventional methods for EV isolation.

bioengineering↗

bioRxiv2025

Charting structural brain asymmetry across the human lifespan

Lateralization is a fundamental principle of structural brain organization. In vivo imaging of brain asymmetry is essential for deciphering lateralized brain functions and their disruption in neurodevelopmental and neurodegenerative disorders. Here, we present a normative framework for benchmarking brain asymmetry across the lifespan, developed from an aggregated sample of 128 primary neuroimaging studies, including 177,701 scans from 138,231 individuals, jointly spanning the age range from 20 post menstrual weeks to 102 years. This resource includes comprehensive, hemisphere-specific brain growth charts for multiple neuroimaging phenotypes: regional cortical grey matter volume, thickness, surface area, and subcortical volumes. Our findings reveal distinct spatial patterns of asymmetry, with early leftward asymmetry observed in association cortices and late rightward asymmetry in sensory regions. These trajectories support theories of the neuroplasticity of asymmetry and the role of both genetic and environmental factors in shaping brain lateralization. Additionally, we provide tools to generate asymmetry centile scores, which allow the quantification of individual deviations from typical asymmetry throughout the lifespan and can be applied to unseen data or clinical populations. We demonstrate the utility of these models by highlighting group-level differences in asymmetry in autism spectrum disorder, schizophrenia, and Alzheimers disease, and exploring genetic correlations with hemispheric specialization. To facilitate further research, we have made this normative framework freely available as an interactive open-access resource (upon publication), offering an essential tool to advance both basic and clinical neuroscience.

neuroscience↗