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Georgakoudi, I.

Publications and source records attributed to Georgakoudi, I..

9 recordsLinked to original sources

Multi-modal, Label-free, Optical Mapping of Cellular Metabolic Function and Oxidative Stress in 3D Engineered Brain Tissue Models

Brain metabolism is essential for the function of organisms. While established imaging methods provide valuable insights into brain metabolic function, they lack the resolution to capture important metabolic interactions and heterogeneity at the cellular level. Label-free, two-photon excited fluorescence imaging addresses this issue by enabling dynamic metabolic assessments at the single-cell level without manipulations. In this study, we demonstrate the impact of spectral imaging on the development of rigorous intensity and lifetime label-free imaging protocols to assess dynamically metabolic functions over time in 3D engineered brain tissue models comprised of human induced neural stem cells, astrocytes, and microglia. Specifically, we rely on multi-wavelength spectral imaging to identify the excitation/emission profiles of key cellular fluorophores within human brain cells, including NAD(P)H, LipDH, FAD, and lipofuscin. These enable the development of methods to mitigate lipofuscins overlap with NAD(P)H and flavin autofluorescence to extract reliable optical metabolic function metrics from images acquired at two excitation wavelengths over two emission bands. We present fluorescence intensity and lifetime metrics reporting on redox state, mitochondrial fragmentation, and NAD(P)H binding status in neuronal monoculture and the triculture systems to highlight the functional impact of metabolic interactions between different cell types. Our findings reveal significant metabolic differences between neurons and glial cells, shedding light on metabolic pathway utilization, including the glutathione pathway, OXPHOS, glycolysis, and fatty acid oxidation. Collectively, our studies establish a label-free, non-destructive approach to assess the metabolic function and interactions among different brain cell types relying on endogenous fluorescence and illustrate the complementary nature of the information that is gained by combining intensity and lifetime-based images. Such methods can improve understanding of physiological brain function and dysfunction that occurs at the onset of cancers, traumatic injuries and neurodegenerative diseases.

bioengineering↗

Rapid, high-resolution, non-destructive assessments of metabolic and morphological homogeneity uniquely identify high-grade cervical precancerous lesions

PurposeTwo-photon microscopy (2PM) is an emerging clinical imaging modality with the potential to non-invasively assess tissue metabolism and morphology in high-resolution. This study aimed to assess the translational potential of 2PM for improved detection of high-grade cervical precancerous lesions. Experimental Design2P images attributed to reduced nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) and oxidized flavoproteins (FP) were acquired from the full epithelial thickness of freshly excised human cervical tissue biopsies (N = 62). Fifteen biopsies harbored high-grade squamous intraepithelial lesions (HSILs), 14 biopsies harbored low-grade SILs (LSILs), and 33 biopsies were benign. Quadratic discriminant analysis (QDA) leveraged morphological and metabolic functional metrics extracted from these images to predict the presence of HSILs. We performed gene set enrichment analysis (GSEA) using datasets available on the Gene Expression Omnibus (GEO) to validate the presence of metabolic reprogramming in HSILs. ResultsIntegrating metabolic and morphological 2P-derived metrics from finely sampled, full-thickness epithelia achieved a high 90.8 {+/-} 6.1% sensitivity and 72.3 {+/-} 11.3% specificity of HSIL detection. Notably, sensitivity (91.4 {+/-} 12.0%) and specificity (77.5 {+/-} 12.6%) were maintained when utilizing metrics from only two images at 12- and 72-{micro}m from the tissue surface. Upregulation of glycolysis, fatty acid metabolism, and oxidative phosphorylation in HSIL tissues validated the metabolic reprogramming captured by 2P biomarkers. ConclusionLabel-free 2P images from as few as two epithelial depths enable rapid and robust HSIL detection through the quantitative characterization of metabolic and morphological reprogramming, underscoring the potential of this tool for clinical evaluation of cervical precancers. Translational Relevance StatementThe colposcopy and biopsy paradigm for cervical pre-cancer detection leads to an excessive number of unnecessary biopsies, with significant economic and psychological costs. This study highlights the potential of label-free, high-resolution two photon imaging to improve this paradigm by introducing real-time morphofunctional tissue assessments. In an extensive dataset comprising freshly excised high-grade and low-grade cervical intraepithelial lesions, along with benign metaplastic and inflamed human cervical tissue biopsies, we successfully characterize a loss of morphofunctional heterogeneity indicative of high-grade precancerous changes. Leveraging a combination of two-photon imaging-derived quantitative morphofunctional metrics, our findings showcase a substantial improvement in both sensitivity and specificity of high-grade lesion detection compared to the current gold standard of colposcopy followed by a single biopsy. The demonstrated enhancement in sensitivity and specificity highlights the prospect of integrating non-invasive, label-free metabolic imaging into clinical practice, offering a more effective and efficient approach to identify and manage cervical precancerous lesions.

bioengineering↗

Non-invasive Imaging Techniques for Monitoring Cellular Response to Treatment in Stable Vitiligo

Punch grafting procedures, where small pieces of normal skin are transplanted into stable vitiligo patches, results in repigmentation in only half of patients treated, yet the factors that determine whether a patient responds to treatment or not are still unknown. Reflectance confocal microscopy (RCM) is adept at visualizing melanocyte migration and epidermal changes over large areas while multiphoton microscopy (MPM) can capture metabolic changes in keratinocytes. With the overall goal of identifying optical biomarkers for early treatment response, we followed 12 vitiligo lesions undergoing punch grafting. Dendritic melanocytes adjacent to the graft site were observed before clinical evidence of repigmentation in treatment responsive patients but not in treatment non-responsive patients, suggesting that the early visualization of melanocytes is indicative of a therapeutic response. Keratinocyte metabolic changes in vitiligo skin adjacent to the graft site also correlated with treatment response, indicating that a keratinocyte microenvironment that more closely resembles normal skin is more hospitable for migrating melanocytes. Taken together, these studies suggest that successful melanocyte transplantation requires both the introduction of new melanocytes and modulation of the local tissue microenvironment.

bioengineering↗

Deep Learning-Enabled, Detection of Rare Circulating Tumor Cell Clusters in Whole Blood Using Label-free, Flow Cytometry

Metastatic tumors have poor prognoses for progression-free and overall survival for all cancer patients. Rare circulating tumor cells (CTCs) and rarer circulating tumor cell clusters (CTCCs) are potential biomarkers of metastatic growth, with CTCCs representing an increased risk factor for metastasis. Current detection platforms are optimized for ex vivo detection of CTCs only. Microfluidic chips and size exclusion methods have been proposed for CTCC detection; however, they lack in vivo utility and real-time monitoring capability. Confocal backscatter and fluorescence flow cytometry (BSFC) has been used for label-free detection of CTCCs in whole blood based on machine learning (ML) enabled peak classification. Here, we expand to a deep-learning (DL) -based, peak detection and classification model to detect CTCCs in whole blood data. We demonstrate that DL-based BSFC has a low false alarm rate of 0.78 events/min with a high Pearson correlation coefficient of 0.943 between detected events and expected events. DL-based BSFC of whole blood maintains a detection purity of 72% and a sensitivity of 35.3% for both homotypic and heterotypic CTCCs starting at a minimum size of two cells. We also demonstrate through artificial spiking studies that DL-based BSFC is sensitive to changes in the number of CTCCs present in the samples and does not add variability in detection beyond the expected variability from Poisson statistics. The performance established by DL-based BSFC motivates its use for in vivo detection of CTCCs. Further developments of label-free BSFC to enhance throughput could lead to critical applications in the clinical detection of CTCCs and ex vivo isolation of CTCC from whole blood with minimal disruption and processing steps.

bioengineering↗

Formalin fixation and paraffin embedding interfere with preservation of optical metabolic assessments based on endogenous NAD(P)H and FAD two photon excited fluorescence

Endogenous NAD(P)H and FAD two-photon excited fluorescence (TPEF) images provide functional metabolic information with high spatial resolution for a wide range of living specimens. Preservation of metabolic function optical metrics upon fixation would facilitate studies which assess the impact of metabolic changes in the context of numerous diseases. However, robust assessments of the impact of formalin fixation, paraffin embedding, and sectioning on the preservation of optical metabolic readouts are lacking. Here, we evaluate intensity and lifetime images at excitation/emission settings optimized for NAD(P)H and FAD TPEF detection from freshly excised murine oral epithelia and corresponding bulk and sectioned fixed tissues. We find that fixation impacts the overall intensity as well as the intensity fluctuations of the images acquired. Accordingly, the depth-dependent variations of the optical redox ratio (defined as FAD/(NAD(P)H + FAD)) across squamous epithelia are not preserved following fixation. This is consistent with significant changes in the 755 nm excited spectra, which reveal broadening upon fixation and additional distortions upon paraffin embedding and sectioning. Analysis of fluorescence lifetime images acquired for excitation/emission settings optimized for NAD(P)H TPEF detection indicate that fixation alters the long lifetime of the observed fluorescence and the long lifetime intensity fraction. These parameters as well as the short TPEF lifetime are significantly modified upon embedding and sectioning. Thus, our studies highlight that the autofluorescence products formed during formalin fixation, paraffin embedding and sectioning overlap highly with NAD(P)H and FAD emission and limit the potential to utilize such tissues to assess metabolic activity.

bioengineering↗

Restoration of metabolic functional metrics from label-free, two-photon cervical tissue images using multiscale deep-learning-based denoising algorithms

Label-free, two-photon imaging captures morphological and functional metabolic tissue changes and enables enhanced understanding of numerous diseases. However, this modality suffers from low signal arising from limitations imposed by the maximum permissible dose of illumination and the need for rapid image acquisition to avoid motion artifacts. Recently, deep learning methods have been developed to facilitate the extraction of quantitative information from such images. Here, we employ deep neural architectures in the synthesis of a multiscale denoising algorithm optimized for restoring metrics of metabolic activity from low-SNR, two-photon images. Two-photon excited fluorescence (TPEF) images of reduced nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) and flavoproteins (FAD) from freshly excised human cervical tissues are used. We assess the impact of the specific denoising model, loss function, data transformation, and training dataset on established metrics of image restoration when comparing denoised single frame images with corresponding six frame averages, considered as the ground truth. We further assess the restoration accuracy of six metrics of metabolic function from the denoised images relative to ground truth images. Using a novel algorithm based on deep denoising in the wavelet transform domain, we demonstrate optimal recovery of metabolic function metrics. Our results highlight the promise of denoising algorithms to recover diagnostically useful information from low SNR label-free two-photon images and their potential importance in the clinical translation of such imaging.

bioengineering↗

Mitochondria dysregulation contributes to secondary neurodegeneration progression post-contusion injury in human 3D in vitro triculture brain tissue model.

Traumatic Brain injury-induced disturbances in mitochondrial fission-and-fusion dynamics have been linked to the onset and propagation of neuroinflammation and neurodegeneration. However, cell-type-specific contributions and crosstalk between neurons, microglia, and astrocytes in mitochondria-driven neurodegeneration after brain injury remain undefined. We developed a human three-dimensional in vitro triculture tissue model of a contusion injury, composed of neurons, microglia, and astrocytes, and examined the contributions of mitochondrial dysregulation to neuroinflammation and progression of injury-induced neurodegeneration. Pharmacological studies presented here suggest that fragmented mitochondria released by microglia are a key contributor to secondary neuronal damage progression after contusion injury, a pathway that requires astrocyte-microglia crosstalk. Controlling mitochondrial dysfunction thus offers an exciting option for the development of therapies for TBI patients.

neuroscience↗

Riboflavin Depletion Promotes Longevity and Metabolic Hormesis in Caenorhabditis elegans

Riboflavin is an essential cofactor in many enzymatic processes and in the production of flavin adenine dinucleotide (FAD). Here we report that the partial depletion of riboflavin through knockdown of the C. elegans riboflavin transporter 1 (rft-1) promotes metabolic health by reducing intracellular flavin concentrations. Knockdown of rft-1 significantly increases lifespan in a manner dependent on FOXO/daf-16, AMP-activated protein kinase (AMPK)/aak-2, the mitochondrial unfolded protein response, and mTOR complex 2 (mTORC2). Riboflavin depletion promotes altered energetic and redox states and increases adiposity, independent of lifespan genetic dependencies. Riboflavin depleted animals also exhibit activation of caloric restriction reporters without a reduction in TORC1 signaling. Our findings indicate that riboflavin depletion activates an integrated, hormetic response that promotes lifespan and healthspan in C. elegans.

genetics↗

Multimodal Analyses of Stable Vitiligo Skin Identify Tissue Interactions That Control Disease Persistence

Vitiligo is an autoimmune skin disease that is characterized by the progressive destruction of melanocytes by autoreactive CD8+ T cells. Melanocyte destruction in active vitiligo is mediated by CD8+ T cells but why white patches in stable disease persist is poorly understood. The interaction between immune cells, melanocytes, and keratinocytes in situ in human skin has been difficult to study due to the lack of proper tools. Here, we combine non-invasive multiphoton microscopy (MPM) imaging and single-cell RNA sequencing (scRNA-seq) to identify distinct subpopulations of keratinocytes in lesional skin of stable vitiligo patients. We show that these keratinocytes are enriched in lesional vitiligo skin and differ in metabolism, an observation corroborated by both MPM and scRNA-seq. Systematic investigation of cell-cell communication show that CXCL is the prominent signaling change in this small population of keratinocytes, which secrete CXCL9 and CXCL10 to create local inflammatory cytokine loops with T cells to drive stable vitiligo persistence. Pseudotemporal dynamics analyses predict an alternative keratinocyte differentiation trajectory that generates this new population of keratinocytes in vitiligo skin. In summary, we couple advanced imaging with transcriptomics and bioinformatics to discover cellcell communication networks and keratinocyte cell states that perpetuate inflammation and prevent repigmentation. One Sentence SummaryCommunication between keratinocytes, immune cells, and melanocytes maintain depigmented patches in stable vitiligo.

molecular biology↗