Search

Understanding biological systems at the level of their relational (emergent) molecular properties in functional protein networks relies on imaging methods, able to spatially resolve a tissue or a cell as a giant, non-random, topologically defined collection of interacting supermolecules executing myriads of subcellular mechanisms. Here, the development and findings of parameter-unlimited functional super-resolution microscopy are described—a technology based on the fluorescence imaging cycler (IC) principle capable of co-mapping thousands of distinct biomolecular assemblies at high spatial resolution and differentiation (

A discount for the lack of marketability is the implicit cost of quickly monetizing a non-marketable asset at its current value. These discounts are used in many venues to determine the fair market value of a non-marketable asset such as a privately-held business. There has been much written on the quantification of the discount for the lack of the marketability which is briefly summarized in this article. Marketability refers to monetizing the non-marketable asset at its cash equivalent current value. Current practice often uses the cost of a put option as a proxy for the discount. A put option insures that the investor will receive no less than the current value of the underlying asset. However, the use of a put also allows the investor to maintain the asset's upside potential. Therefore, the cost of a put overstates the discount for the lack of marketability. We show that the cost of monetizing a non-marketable asset at its current value through a loan, secured by an at-the-money equity collar, more effectively captures the true cost of marketability. When puts and calls cannot be employed to secure the current value on the underlying asset, a portfolio consisting of the non-marketable asset and a stock index, where puts and calls can be written on the index can be constructed. The effectiveness of the portfolio in creating a risk free outcome depends upon the correlation and volatility of the stock index and the non-marketable asset. We demonstrate that, relative to current practice, the use of an equity collar with a loan greatly reduces the implied discount for the lack of marketability.

To enable high-throughput screening of molecular phenotypes, multi-parameter fluorescence microscopy is applied. Object of our study is lymphocytes which invade human tissue. One important basis for our collaborative project is the development of methods for automatic and accurate evaluation of fluorescence micrographs. As a part of this, we focus on the question of how to measure the accuracy of microscope image interpretation, by human experts or a computer system. Following standard practice we use methods motivated by receiver operator characteristics to discuss the accuracies of human experts and of neural network-based algorithms. For images of good quality the algorithms achieve the accuracy of the medium-skilled experts. In images with increased noise, the classifiers are outperformed by some of the experts. Furthermore, the neural network-based cell detection is much faster than the human experts.

A neural cell detection system (NCDS) for the automatic quantitation of fluorescent lymphocytes in tissue sections was used to analyze CD26 expression in muscle-invasive T-cells. CD26 is a cell surface dipeptidyl-peptidase IV (DPP IV) involved in co-stimulatory activation of T-cells and also in adhesive events. The NCDS system acquires visual knowledge from a set of training cell image patches selected by a user. The trained system evaluates an image in 2 min calculating (i) the number, (ii) the positions and (iii) the phenotypes of the fluorescent cells. In the present study we have used the NCDS to identity DPP IV (CD26) expressing invasive lymphocytes in sarcoid myopathy and to analyze the associated cell surface phenotypes. We find highly unusual phenotypes characterized by differential combination of seven cell surface receptors usually involved in co-stimulatory events in T-lymphocytes. The data support a differential adhesive rather than a co-stimulatory role of CD26 in muscle-invasive cells. The adaptability of the NCDS algorithm to diverse types of cells should enable us to approach any invasion process, including invasion of malignant cells.

A neural cell detection system (NCDS) for the automatic quantitation of fluorescent lymphocytes in tissue sections is presented in this paper. The system acquires visual knowledge from a set of training cell-image patches selected by a user. The trained system evaluates an image in 2 min calculating: the number, the positions, and the phenotypes of the fluorescent cells. For validation, the NCDS learning performance was tested by cross validation on digitized images of tissue sections obtained from inherently different types of tissue: diagnostic tissue sections across the human tonsil and across an inflammatory lymphocyte infiltrate of the human skeletal muscle. The NCDS detection results were compared with detection results from biomedical experts and were visually evaluated by our most experienced biomedical expert. Although the micrographs were noisy and the fluorescent cells varied in shape and size, the NCDS detected a minimum of 95% of the cells. In contrast, the cellular counts based on visual cell recognition of the experts were inconsistent and largely unreproducible for approximately 80% of the lymphocytes present in a visual field. The data indicate that the NCDS is rapid and delivers highly reproducible results and, therefore, enables high-throughput topological screening of lymphocytes in many types of tissue, e.g., as obtained by routine diagnostic biopsy procedures. High-throughput screening with the NCDS provides the platform for the quantitative analysis of the interrelationship between tissue environment, cellular phenotype, and cellular topology.