Case Western Reserve University

About: Case Western Reserve University is a education organization based out in Cleveland, Ohio, United States. It is known for research contribution in the topics: Population & Cancer. The organization has 54617 authors who have published 106568 publications receiving 5071613 citations. The organization is also known as: Case & Case Western.

Transfer function synthesis as a ratio of two complex polynomials

Abstract: Experimental frequency response data obtained from a linear dynamic system is processed to obtain the transfer function as a ratio of two frequency-dependent polynomials. The difference between the absolute magnitudes of the actual function and the polynomial ratio is the error considered. The polynomial coefficients are evaluated as the result of minimizing the sum of the squares of the above errors at the experimental points. The polynomial coefficients are computed numerically using an IBM 704 FORTRAN program. The magnitude and phase angle of the transfer function are evaluated at the various frequencies, using the computed polynomial ratio; and are compared with the observed data. The method presented here gives an analytic description of the complex transfer function superior to that given by minimization of the "weighted" sum of the squares of the errors in magnitude.

Artificial intelligence in digital pathology — new tools for diagnosis and precision oncology

Abstract: In the past decade, advances in precision oncology have resulted in an increased demand for predictive assays that enable the selection and stratification of patients for treatment. The enormous divergence of signalling and transcriptional networks mediating the crosstalk between cancer, stromal and immune cells complicates the development of functionally relevant biomarkers based on a single gene or protein. However, the result of these complex processes can be uniquely captured in the morphometric features of stained tissue specimens. The possibility of digitizing whole-slide images of tissue has led to the advent of artificial intelligence (AI) and machine learning tools in digital pathology, which enable mining of subvisual morphometric phenotypes and might, ultimately, improve patient management. In this Perspective, we critically evaluate various AI-based computational approaches for digital pathology, focusing on deep neural networks and 'hand-crafted' feature-based methodologies. We aim to provide a broad framework for incorporating AI and machine learning tools into clinical oncology, with an emphasis on biomarker development. We discuss some of the challenges relating to the use of AI, including the need for well-curated validation datasets, regulatory approval and fair reimbursement strategies. Finally, we present potential future opportunities for precision oncology.

Cytokine expression by human marrow‐derived mesenchymal progenitor cells in vitro: Effects of dexamethasone and IL‐1α

Abstract: We previously reported the purification, culture-expansion, and osteogenic differentiation potential of mesenchymal progenitor cells (MPCs) derived from human bone marrow. As a first step to establishing the phenotypic characteristics of MPCs, we reported on the identification of unique cell surface proteins which were detected with monoclonal antibodies. In this study, the phenotypic characterization of human marrow-derived MPCs is further established through the identification of a cytokine expression profile under standardized growth medium conditions and in the presence of regulators of the osteogenic and stromal cell lineages, dexamethasone and interleukin-1 alpha (IL-1 alpha), respectively. Constitutively expressed cytokines in this growth phase include G-CSF, SCF, LIF, M-CSF, IL-6, and IL-11, while GM-CSF, IL-3, TGF-beta 2 and OSM were not detected in the growth medium. Exposure of cells in growth medium to dexamethasone resulted in a decrease in the expression of LIF, IL-6, and IL-11. These cytokines have been reported to exert influence on the differentiation of cells derived from the bone marrow stroma through target cell receptors that utilize gp130-associated signal transduction pathways. Dexamethasone had no effect on the other cytokines expressed under growth medium conditions and was not observed to increase the expression of any of the cytokines measured in this study. In contrast, IL-1 alpha increased the expression of G-CSF, M-CSF, LIF, IL-6 and IL-11 and induced the expression of GM-CSF. IL-1 alpha had no effect on SCF expression and was not observed to decrease the production of any of the cytokines assayed. These data indicate that MPCs exhibit a distinct cytokine expression profile. We interpret this cytokine profile to suggest that MPCs serve specific supportive functions in the microenvironment of bone marrow. MPCs provide inductive and regulatory information which are consistent with the ability to support hematopoiesis, and also supply autocrine, paracrine, and juxtacrine factors that influence the cells of the marrow microenvironment itself. In addition, the cytokine profiles expressed by MPCs, in response to dexamethasone and IL-1 alpha, identify specific cytokines whose levels of expression change as MPCs differentiate or modulate their phenotype during osteogenic or stromagenic lineage entrance/progression.

Highly efficient drug delivery with gold nanoparticle vectors for in vivo photodynamic therapy of cancer.

Abstract: A highly efficient drug vector for photodynamic therapy (PDT) drug delivery was developed by synthesizing PEGylated gold nanoparticle conjugates, which act as a water-soluble and biocompatible "cage" that allows delivery of a hydrophobic drug to its site of PDT action. The dynamics of drug release in vitro in a two-phase solution system and in vivo in cancer-bearing mice indicates that the process of drug delivery is highly efficient, and passive targeting prefers the tumor site. With the Au NP-Pc 4 conjugates, the drug delivery time required for PDT has been greatly reduced to less than 2 h, compared to 2 days for the free drug.