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Ricklefs, F. L.

Publications and source records attributed to Ricklefs, F. L..

5 recordsLinked to original sources

High-Purity Enrichment of Extracellular Vesicles from Diverse Sources by Conventional and Image-Based Fluorescence Activated Cell Sorters for Robust Downstream Applications

Selective enrichment of extracellular vesicle (EV) subpopulations from the heterogeneous EV pool is essential for understanding their characteristic biological functions and exploiting their potential as diagnostic and prognostic biomarkers. However, isolation of specific EV-subsets remains challenging. Fluorescence-Activated Cell Sorting (FACS) has emerged as promising technique for EV subpopulations enrichment, despite limitations associated to their small size. Although FACS-based EV sorting has been reported, a broadly applicable and systematically validated workflow is still lacking. Here, we describe and validate an optimized workflow for the sorting and analysis of EVs derived from diverse species, tissues, blood and cell culture systems. Using two advanced flow cytometric cell sorters, the BD FACSAria Fusion, and the BD FACSDiscover S8, we systematically evaluated key technical parameters, including nozzle size, sample dilutions, and sorting mode. The optimized workflow enabled efficient enrichment of differently labelled EV populations of interest, achieving near-100% purity, including rare subsets representing less than 10% of the total EV pool, while maintaining compatibility with downstream analyses. Sorted EV populations were characterized by high-sensitivity imaging flow cytometry, transmission electron microscopy, and liquid chromatography-tandem mass spectrometry. This workflow provides a robust framework for EV subset isolation and characterization, supporting both fundamental EV research and translational biomarker applications.

cell biology↗

Voxel-accurate MRI-microscopy correlation enables AI-powered prediction of brain disease states

Magnetic resonance imaging (MRI) is essential for visualizing the healthy and diseased brain, yet the cellular basis of MRI signal and how it changes over time remain poorly understood. Here, we present BRIDGE (Brain Radiological Imaging with Deep-learning based Ground-Truth Exploration), a platform integrating in vivo MRI with in vivo two-photon (2P) and ex vivo super-resolution microscopy using a multi-step, iterative co-registration pipeline. It enables in vivo, longitudinal, and voxel-precise mapping of MRI signals to their cellular origins for the first time. The registered overlay reveals the cellular and anatomical origins of MRI signals and enables training of convolutional neural networks to enhance the effective resolution of MRI. Using BRIDGE, we identified a microenvironmental vessel biomarker for early metastatic colonization in patient-derived xenograft models of brain metastasis. In particular we found that distinct T2*-weighted hypointense lesions correspond to reduced blood flow and erythrostasis in perimetastatic capillaries. In glioma, longitudinal intravital studies further demonstrated direct correlations between non-vasogenic T2-weighted signal changes and patient-dependent tumor growth dynamics. Taken together, BRIDGE advances radiological interpretation by establishing a microscopic ground truth for MRI signatures over time, enabling deep learning-based predictive histology, and providing cellular-level insights into tumor microenvironment features with direct clinical imaging implications. Graphical abstractBRIDGE enables longitudinal voxel-to-voxel correlation and ground truth based automatic segmentation of MR images O_FIG O_LINKSMALLFIG WIDTH=177 HEIGHT=200 SRC="FIGDIR/small/680637v1_ufig1.gif" ALT="Figure 1"> View larger version (73K): org.highwire.dtl.DTLVardef@f1f64eorg.highwire.dtl.DTLVardef@1619e3eorg.highwire.dtl.DTLVardef@1dc2e7forg.highwire.dtl.DTLVardef@7097e1_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

The biomolecular profiles of extracellular vesicles from odontogenic stem cell lines depict donor-dependent differences and emphasize their therapeutic and regenerative potential

BackgroundStem cell-derived extracellular vesicles (EVs) hold great promise in regenerative medicine. However, a comprehensive understanding of the regenerative capabilities of EVs from different stem cell sources remains limited. MethodsThis study systematically compares EVs derived from three odontogenic cell types. Analyses includes EV isolation and characterization, cell viability assays, vasculogenesis experiments, proteomic profiling, and miRNA sequencing. ResultsAll three EV types displayed similar surface marker profiles. Dental pulp stem cell-derived EVs showed superior cellular uptake, promoted higher cell proliferation, and enhanced vasculogenesis compared to periodontal ligament stem cell-derived EVs. Gingival fibroblast-derived EVs performed similarly in functional assays. Principal component analysis of miRNA profiles revealed strong biological heterogeneity among EV sources, with donor-specific factors exerting a greater influence on EV characteristics than cellular origin--an aspect underexplored in prior studies. ConclusionsThese findings underscore the complexity of EV functionality and highlight the regenerative potential of dental stem cell-derived EVs.

cell biology↗

Extracellular vesicles released from cortical neurons influence spontaneous activity of recipient neurons.

Extracellular vesicles (EVs) are membranous structures that cells release into the extracellular space. EVs carry various molecules such as proteins, lipids, and nucleic acids, and serve as specialized transporters to influence other cells. In the central nervous system, EVs have been linked to many important processes, including intercellular communication, but molecular details of their physiological functions are not fully understood. Our study aimed to investigate how EVs are released by neuronal cells, and how they affect the neuronal activity of other recipient neurons. We show that mature primary cortical neurons release EVs from both their soma and dendrites. EVs released from neurons closely resemble non-neuronal EVs regarding size and marker proteins and proteomic analyses showed that neuronally released EVs contain proteins typically acting in pre- and post-synaptic compartments. Interestingly, our analysis revealed that EVs alter spontaneous activity in target neurons by increasing the amplitude of postsynaptic potentials. In summary, our findings elaborates on the role of EVs in synaptic activity modulation in neurons mediated by glutamate receptors.

neuroscience↗

Epigenetic neural glioblastoma enhances synaptic integration and predicts therapeutic vulnerability

Neural-tumor interactions drive glioma growth as evidenced in preclinical models, but clinical validation is nascent. We present an epigenetically defined neural signature of glioblastoma that independently affects patients survival. We use reference signatures of neural cells to deconvolve tumor DNA and classify samples into low- or high-neural tumors. High-neural glioblastomas exhibit hypomethylated CpG sites and upregulation of genes associated with synaptic integration. Single-cell transcriptomic analysis reveals high abundance of stem cell-like malignant cells classified as oligodendrocyte precursor and neural precursor cell-like in high-neural glioblastoma. High-neural glioblastoma cells engender neuron-to-glioma synapse formation in vitro and in vivo and show an unfavorable survival after xenografting. In patients, a high-neural signature associates with decreased survival as well as increased functional connectivity and can be detected via DNA analytes and brain-derived neurotrophic factor in plasma. Our study presents an epigenetically defined malignant neural signature in high-grade gliomas that is prognostically relevant.

neuroscience↗