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Cleveland, OH, United States

Cleveland Diagnostics | Entity website

Executive LeadershipArnon Chait, PhD, MBA - Chief Executive OfficerDr. Chait has25 years of experience at NASA, Analiza, and three other companies ...


Zaslavsky B.Y.,Cleveland Diagnostics | Uversky V.N.,University of South Florida | Chait A.,Cleveland Diagnostics
Expert Review of Proteomics | Year: 2015

Proteins have several measurable features in biological fluids that may change under pathological conditions. The current disease biomarker discovery is mostly based on protein concentration in the sample as the measurable feature. Changes in protein structures, such as post-translational modifications and in protein–partner interactions are known to accompany pathological processes. Changes in glycosylation profiles are well-established for many plasma proteins in various types of cancer and other diseases. The solvent interaction analysis method is based on protein partitioning in aqueous two-phase systems and is highly sensitive to changes in protein structure and protein–protein- and protein–partner interactions while independent of the protein concentration in the biological sample. It provides quantitative index: partition coefficient representing changes in protein structure and interactions with partners. The fundamentals of the method are presented with multiple examples of applications of the method to discover and monitor structural protein biomarkers as disease-specific diagnostic indicators. © 2015 Taylor & Francis Source


Jones R.N.,45 Beaver Kreek Center | Jones R.N.,Tufts University | Ross J.E.,45 Beaver Kreek Center | Rhomberg P.R.,45 Beaver Kreek Center | And 8 more authors.
Journal of Clinical Microbiology | Year: 2010

The development of diagnostic susceptibility tests for CEM-101, a new fluoroketolide, was addressed by structured studies to determine the optimal disk diffusion test concentration and effects of various testing conditions or supplements and to establish the quality control (QC) ranges for reference broth microdilution tests. The 15-μg CEM-101 disk was selected, and MIC ranges for a total of four QC organisms were proposed, with only three doubling dilutions each that included 95.6 to 99.7% of values reported from the eight-laboratory investigation. Copyright © 2010, American Society for Microbiology. All Rights Reserved. Source


Ferreira L.A.,Cleveland Diagnostics | Breydo L.,University of South Florida | Reichardt C.,University of Marburg | Uversky V.N.,Russian Academy of Sciences | Zaslavsky B.Y.,Cleveland Diagnostics
Journal of Biomolecular Structure and Dynamics | Year: 2016

The solvatochromic solvent features of water (dipolarity/polarizability, π*, hydrogen bond donor acidity, α, and hydrogen bond acceptor basicity, β) of water have been determined in aqueous solutions of erythritol, glucose, inositol, sarcosine, xylitol and urea with concentrations from 0 to ~3 M and higher. The concentration effects of the osmolytes on the solvent features of water were characterized and compared with those reported previously for sorbitol, sucrose, trimethylamine N-oxide (TMAO), and trehalose. The solvent features of water in solutions of all osmolytes except TMAO and sarcosine were established to be linearly interrelated. It is shown that the concentration effects of essentially all nonionic osmolytes depend on osmolytes’ lipophilicity, molecular polarizability, and polar surface area. It is demonstrated that solubility of various compounds in aqueous solutions of glucose, sucrose, sorbitol, and urea of varied concentrations may be described in terms of solvent dipolarity/polarizability of water in these solutions. Surface tension of aqueous solutions of sucrose and sorbitol may also be described in the same terms. The relative permittivity of aqueous solutions of glucose and sucrose may be described in terms of the solvent hydrogen bond donor acidity of water. It is suggested that the effects of nonionic osmolytes on behavior of proteins and nucleic acids in aqueous media may be considered in terms of the altered solvent features of water instead of “nano-molecular crowding” effect. © 2016 Informa UK Limited, trading as Taylor & Francis Group Source


Ferreira L.A.,Cleveland Diagnostics | Madeira P.P.,University of Porto | Breydo L.,University of South Florida | Reichardt C.,University of Marburg | And 3 more authors.
Journal of Biomolecular Structure and Dynamics | Year: 2016

Analysis of the macromolecular crowding effects in polymer solutions show that the excluded volume effect is not the only factor affecting the behavior of biomolecules in a crowded environment. The observed inconsistencies are commonly explained by the so-called soft interactions, such as electrostatic, hydrophobic, and van der Waals interactions, between the crowding agent and the protein, in addition to the hard nonspecific steric interactions. We suggest that the changes in the solvent properties of aqueous media induced by the crowding agents may be the root of these "soft" interactions. To check this hypothesis, the solvatochromic comparison method was used to determine the solvent dipolarity/polarizability, hydrogen-bond donor acidity, and hydrogen-bond acceptor basicity of aqueous solutions of different polymers (dextran, poly(ethylene glycol), Ficoll, Ucon, and polyvinylpyrrolidone) with the polymer concentration up to 40% typically used as crowding agents. Polymer-induced changes in these features were found to be polymer type and concentration specific, and, in case of polyethylene glycol (PEG), molecular mass specific. Similarly sized polymers PEG and Ucon producing different changes in the solvent properties of water in their solutions induced morphologically different α-synuclein aggregates. It is shown that the crowding effects of some polymers on protein refolding and stability reported in the literature can be quantitatively described in terms of the established solvent features of the media in these polymers solutions. These results indicate that the crowding agents do induce changes in solvent properties of aqueous media in crowded environment. Therefore, these changes should be taken into account for crowding effect analysis. © 2015 Taylor and Francis. Source

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