Biology subjects

Karlas, A.

Publications and source records attributed to Karlas, A..

4 recordsLinked to original sources

bioRxiv2021

Fast Optoacoustic Mesoscopy of Microvascular Endothelial Dysfunction in Cardiovascular Risk and Disease

Microvascular endothelial dysfunction (ED) precedes the ED in larger arteries and is an early marker of cardiovascular disease (CVD). While precise assessment of microvascular ED could thus be used for the early detection and risk stratification of CVD, detailed interrogation of skin microvascular ED is limited by the technology available. Herein, we applied a novel approach for the non-invasive assessment of skin microvascular ED by developing fast plane raster-scan optoacoustic mesoscopy (FP-RSOM) to visualize and quantify skin microvasculature perfusion changes during post-occlusive hyperemia (PORH) tests. We combined static three-dimensional RSOM imaging with fast dynamic FP-RSOM measurements (1 frame / second) in human skin in vivo, which allowed for the first time to fully visualize the cutaneous microvascular response and further quantify changes of individual vessel diameter, total blood volume and vessel density during the PORH process. We further computed biomarkers from FP-RSOM images to quantify skin endothelial function within different skin layers as a function of skin depth, while conventional approaches mainly measure overall changes within sampled tissue volumes. FP-RSOM applied on smokers and patients with CVD showed clear ED in both groups compared to healthy volunteers. Moreover, FP-RSOM imaging showed higher sensitivity in quantifying the effects of smoking and CVD on skin microvascular endothelial function compared to clinically used laser Doppler flowmetry and tissue spectrometry (O2C). Our study introduces FP-RSOM as a novel tool to visualize and quantify skin microvascular ED as an early marker for the diagnostics and monitoring of cardiovascular risk and disease.

bioengineering↗

bioRxiv2020

Multicompartmental Non-invasive Sensing of Postprandial Lipemia in Humans with Multispectral Optoacoustic Tomography

Disturbed blood lipid profiles after food intake have been associated with increased risk for cardiovascular and metabolic disease. Postprandial lipid profiling (PLP) can be used as a risk factor for cardiovascular disease, insulin resistance and other metabolic diseases but is based today on frequent blood sampling over several hours after a meal, an approach that is invasive and inconvenient for patients. Non-invasive PLP may offer a favorable alternative for disseminated monitoring in humans. In this study, we investigate the use of localized lipid sensing guided by Multispectral Optoacoustic Tomography (MSOT) for non-invasive, label-free assessment of postprandial lipemia in human vasculature and in soft tissues. For penetrating deep in human tissue, we utilize measurements at 930 nm, where lipids exhibit strong light absorption in the near-infrared spectral range (NIR). In a pilot study, we longitudinally measured postprandial lipemia in healthy subjects over 6 hours following consumption of a high-fat meal. Localized measurements were obtained from four anatomical structures: the radial artery, the cephalic vein, the brachioradialis muscle and the subcutaneous fat of the forearm. Analysis of optoacoustic signals demonstrated a 63.4% mean lipid increase in intra-arterial lipids at approximately 4 hours postprandially, a 89.7% mean increase in intra-venous lipids at 3-hours, a 120.8% mean increase in intra-muscular lipids at 3-hours and a 30.5% mean increase in subcutaneous fat lipids at 4-hours. We discuss how portable MSOT offers unprecedented potential to study lipid metabolism that could lead to novel diagnostics and prevention strategies by offering label-free and non-invasive detection of tissue biomarkers implicated in cardiometabolic diseases.Competing Interest StatementV. Ntziachristos has stock/stock options in iThera Medical GmbH. All other authors have no competing interests to declare.View Full Text

bioengineering↗

bioRxiv2019

A Sparse Deep Learning Approach for Automatic Segmentation of Human Vasculature in Multispectral Optoacoustic Tomography

Multispectral Optoacoustic Tomography (MSOT) resolves oxy- (HbO2) and deoxy-hemoglobin (Hb) to perform vascular imaging. MSOT suffers from gradual signal attenuation with depth due to light-tissue interactions: an effect that hinders the precise manual segmentation of vessels. Furthermore, vascular assessment requires functional tests, which last several minutes and result in recording thousands of images. Here, we introduce a deep learning approach with a sparse UNET (S-UNET) for automatic vascular segmentation in MSOT images to avoid the rigorous and time-consuming manual segmentation. We evaluated the S-UNET on a test-set of 33 images, achieving a median DICE score of 0.88. Apart from high segmentation performance, our method based its decision on two wavelengths with physical meaning for the task-at-hand: 850 nm (peak absorption of oxy-hemoglobin) and 810 nm (isosbestic point of oxy-and deoxy-hemoglobin). Thus, our approach achieves precise data-driven vascular segmentation for automated vascular assessment and may boost MSOT further towards its clinical translation.

bioengineering↗

bioRxiv2017

Relevance of host cell surface glycan structure for cell specificity of influenza A virus

Influenza A viruses (IAV) initiate infection via binding of the viral hemagglutinin (HA) to sialylated glycan receptors on host cells. HAs receptor specificity towards sialic acid (SA) is well studied and clearly critical for virus infection, but the contribution of the highly complex cellular plasma membrane to the cellular specificity remains elusive. In addition, some studies indicated that other host cell factors such as the epidermal growth factor receptor might contribute to the initial virus-cell contact and further downstream signaling1.\n\nHere we use two complementary methods, glycan arrays and single-virus force spectroscopy (SVFS) to compare influenza virus receptor specificity with actual host cell binding. Unexpectedly, our study reveals that HAs receptor binding preference does not necessarily reflect virus-cell specificity. We propose SVFS as a tool to elucidate the cell binding preference of IAV thereby including the complex environment of sialylated receptors within the plasma membrane of living cells.

microbiology↗