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The usefulness of statistical clustering algorithms developed for automatic segmentation of lesions and organs in magnetic resonance imaging (MRI) intensity data sets suffers from spatial nonstationarities introduced into the data sets by the acquisition instrumentation. The major intensity inhomogeneity in MRI is caused by variations in the B1-field of the radio frequency (rf) coil. A three-step method was developed to model and then reduce the effect. First, using a least squares formulation, the inhomogeneity is modeled as a maximum variation order two polynomial. Second, in the log domain the polynomial model is subtracted from the actual patient data set resulting in a compensated data set. Lastly, the compensated data set is exponentiated and rescaled. Statistical comparisons indicate volumes of significant corruption undergo a large reduction in the inhomogeneity, whereas volumes of minimal corruption are not significantly changed. As applied to a patient data set the variances of the liver and the subcutaneous fat volumes are reduced 38% and 32%, respectively. The psoas muscle volume, contained in a relatively homogeneous portion of the B1-field, exhibited no significant change in variance. Acting as a preprocessor, the proposed technique can enhance the role of statistical segmentation algorithms in body MRI data sets.

Imaging and characterizing the dynamics of cellular adhesion in blood samples is of fundamental importance in understanding biological function. In vitro microscopy methods are widely used for this task but typically require diluting the blood with a buffer to allow for transmission of light. However, whole blood provides crucial signaling cues that influence adhesion dynamics, which means that conventional approaches lack the full physiological complexity of living microvasculature. We can reliably image cell interactions in microfluidic channels during whole blood flow by motion blur microscopy (MBM) in vitro and automate image analysis using machine learning. MBM provides a low cost, easy to implement alternative to intravital microscopy, for rapid data generation where understanding cell interactions, adhesion, and motility is crucial. MBM is generalizable to studies of various diseases, including cancer, blood disorders, thrombosis, inflammatory and autoimmune diseases, as well as providing rich datasets for theoretical modeling of adhesion dynamics., (© 2024. The Author(s).)

Heavy metal contamination in food and water is a major public health concern because heavy metals are toxic in minute amounts. DNAzyme sensors are emerging as a promising tool for rapid onsite detection of heavy metals, which can aid in minimizing exposure. However, DNAzyme activity toward its target metal is not absolute and has cross-reactivity with similar metals, which is a major challenge in the wide-scale application of DNAzyme sensors for environmental monitoring. To address this, we constructed a four DNAzyme array (17E, GR-5, EtNA, and NaA43) and used a pattern-based readout to improve sensor accuracy. We measured cross-reactivity between three metal cofactors (Pb 2+ , Ca 2+ , and Na + ) and common interferents (Mg 2+ , Zn 2+ , Mn 2+ , UO 2 2+ , Li + , K + , and Ag + ) and then used t-SNE analysis to identify and quantify the metal ion. We further showed that this method can be used for distinguishing mixtures of metals and detecting Pb 2+ in environmental soil samples at micromolar concentrations.

Imaging and characterizing the dynamics of cellular adhesion in blood samples is of fundamental importance in understanding biological function. In vitro microscopy methods are widely used for this task, but typically require diluting the blood with a buffer to allow for transmission of light. However whole blood provides crucial mechanical and chemical signaling cues that influence adhesion dynamics, which means that conventional approaches lack the full physiological complexity of living microvasculature. We propose to overcome this challenge by a new in vitro imaging method which we call motion blur microscopy (MBM). By decreasing the source light intensity and increasing the integration time during imaging, flowing cells are blurred, allowing us to identify adhered cells. Combined with an automated analysis using machine learning, we can for the first time reliably image cell interactions in microfluidic channels during whole blood flow. MBM provides a low cost, easy to implement alternative to intravital microscopy, the in vivo approach for studying how the whole blood environment shapes adhesion dynamics. We demonstrate the method's reproducibility and accuracy in two example systems where understanding cell interactions, adhesion, and motility is crucial-sickle red blood cells adhering to laminin, and CAR-T cells adhering to E-selectin. We illustrate the wide range of data types that can be extracted from this approach, including distributions of cell size and eccentricity, adhesion durations, trajectories and velocities of adhered cells moving on a functionalized surface, as well as correlations among these different features at the single cell level. In all cases MBM allows for rapid collection and processing of large data sets, ranging from thousands to hundreds of thousands of individual adhesion events. The method is generalizable to study adhesion mechanisms in a variety of diseases, including cancer, blood disorders, thrombosis, inflammatory and autoimmune diseases, as well as providing rich datasets for theoretical modeling of adhesion dynamics., Competing Interests: Conflict-of-Interest Disclosure R.A., U.A.G., and Case Western Reserve University have financial interests in Hemex Health Inc. U.A.G., and Case Western Reserve University have financial interests in BioChip Labs Inc. U.A.G. and Case Western Reserve University have financial interests in Xatek Inc. U.A.G. has financial interests in DxNow Inc. Financial interests include licensed intellectual property, stock ownership, research funding, employment, and consulting. Hemex Health Inc. offers point-of-care diagnostics for hemoglobin disorders, anemia, and malaria. BioChip Labs Inc. offers commercial clinical microfluidic biomarker assays for inherited or acquired blood disorders. Xatek Inc. offers point-of-care global assays to evaluate the hemostatic process. DxNow Inc. offers microfluidic and bio-imaging technologies for in vitro fertilization, forensics, and diagnostics. The competing interests of Case Western Reserve University employees are overseen and managed by the Conflict of Interests Committee according to a Conflict-of-Interest Management Plan.