8th Annual Seminar on Legal Issues for Financial Institutions

Outline of speakers\u27 presentations from the 8th Annual Seminar on Legal Issues for Financial Institutions held by UK/CLE on March 11-12, 1988

Two Factor Reprogramming of Human Neural Stem Cells into Pluripotency

BACKGROUND:Reprogramming human somatic cells to pluripotency represents a valuable resource for the development of in vitro based models for human disease and holds tremendous potential for deriving patient-specific pluripotent stem cells. Recently, mouse neural stem cells (NSCs) have been shown capable of reprogramming into a pluripotent state by forced expression of Oct3/4 and Klf4; however it has been unknown whether this same strategy could apply to human NSCs, which would result in more relevant pluripotent stem cells for modeling human disease. METHODOLOGY AND PRINCIPAL FINDINGS:Here, we show that OCT3/4 and KLF4 are indeed sufficient to induce pluripotency from human NSCs within a two week time frame and are molecularly indistinguishable from human ES cells. Furthermore, human NSC-derived pluripotent stem cells can differentiate into all three germ lineages both in vitro and in vivo. CONCLUSIONS/SIGNIFICANCE:We propose that human NSCs represent an attractive source of cells for producing human iPS cells since they only require two factors, obviating the need for c-MYC, for induction into pluripotency. Thus, in vitro human disease models could be generated from iPS cells derived from human NSCs

18th Annual Conference on Legal Issues for Financial Institutions

Materials from the 18th Annual Conference on Legal Issues for Financial Institutions held by UK/CLE in 1998

Case-Control Cohort Study of Patients' Perceptions of Disability in Mastocytosis

BACKGROUND: Indolent forms of mastocytosis account for more than 90% of all cases, but the types and type and severity of symptoms and their impact on the quality of life have not been well studied. We therefore performed a case-control cohort study to examine self-reported disability and impact of symptoms on the quality of life in patients with mastocytosis. METHODOLOGY/PRINCIPAL FINDINGS: In 2004, 363 mastocytosis patients and 90 controls in France were asked to rate to their overall disability (OPA score) and the severity of 38 individual symptoms. The latter was used to calculate a composite score (AFIRMM score). Of the 363 respondents, 262 were part of an ongoing pathophysiological study so that the following data were available: World Health Organization classification, standard measures of physical and psychological disability, existence of the D816V KIT mutation, and serum tryptase level. The mean OPA and AFIRMM scores and the standard measures of disability indicated that most mastocytosis patients suffer from disabilities due to the disease. Surprisingly, the patient's measurable and perceived disabilities did not differ according to disease classification or presence or absence of the D816V KIT mutation or an elevated (> or = 20 ng/mL) serum tryptase level. Also, 32 of the 38 AFIRMM symptoms were more common in patients than controls, but there were not substantial differences according to disease classification, presence of the D816V mutation, or the serum tryptase level. CONCLUSIONS: On the basis of these results and for the purposes of treatment, we propose that mastocytosis be first classified as aggressive or indolent and that indolent mastocytosis then be categorized according to the severity of patients' perceived symptoms and their impact on the quality of life. In addition, it appears that mastocytosis patients suffer from more symptoms and greater disability than previously thought, that mastocytosis may therefore be under-diagnosed, and that the symptoms of the indolent forms of mastocytosis might be due more to systemic release of mediators than mast cell burden

Single Molecule Conformational Memory Extraction: P5ab RNA Hairpin

Extracting kinetic models from single molecule data is an important route to mechanistic insight in biophysics, chemistry, and biology. Data collected from force spectroscopy can probe discrete hops of a single molecule between different conformational states. Model extraction from such data is a challenging inverse problem because single molecule data are noisy and rich in structure. Standard modeling methods normally assume (i) a prespecified number of discrete states and (ii) that transitions between states are Markovian. The data set is then fit to this predetermined model to find a handful of rates describing the transitions between states. We show that it is unnecessary to assume either (i) or (ii) and focus our analysis on the zipping/unzipping transitions of an RNA hairpin. The key is in starting with a very broad class of non-Markov models in order to let the data guide us toward the best model from this very broad class. Our method suggests that there exists a folding intermediate for the P5ab RNA hairpin whose zipping/unzipping is monitored by force spectroscopy experiments. This intermediate would not have been resolved if a Markov model had been assumed from the onset. We compare the merits of our method with those of others

The Impact of Advocacy Organizations on Low-Income Housing Policy in U.S. Cities

Financial support for affordable housing competes with many other municipal priorities. This work seeks to explain the variation in support for affordable housing among U.S. cities with populations of 100,000 or more. Using multivariate statistical analysis, this research investigates political explanations for the level of city expenditures on housing and community with a particular interest in the influence of housing advocacy organizations (AOs). Data for the model were gathered from secondary sources, including the U.S. Census and the National Center for Charitable Statistics. Among other results, the analysis indicates that, on average, the political maturity of AOs has a statistically significant, positive effect on local housing and community development expenditures

Phenotypic Signatures Arising from Unbalanced Bacterial Growth

Fluctuations in the growth rate of a bacterial culture during unbalanced growth are generally considered undesirable in quantitative studies of bacterial physiology. Under well-controlled experimental conditions, however, these fluctuations are not random but instead reflect the interplay between intra-cellular networks underlying bacterial growth and the growth environment. Therefore, these fluctuations could be considered quantitative phenotypes of the bacteria under a specific growth condition. Here, we present a method to identify “phenotypic signatures” by time-frequency analysis of unbalanced growth curves measured with high temporal resolution. The signatures are then applied to differentiate amongst different bacterial strains or the same strain under different growth conditions, and to identify the essential architecture of the gene network underlying the observed growth dynamics. Our method has implications for both basic understanding of bacterial physiology and for the classification of bacterial strains

Three-Dimensional Stochastic Off-Lattice Model of Binding Chemistry in Crowded Environments

Molecular crowding is one of the characteristic features of the intracellular environment, defined by a dense mixture of varying kinds of proteins and other molecules. Interaction with these molecules significantly alters the rates and equilibria of chemical reactions in the crowded environment. Numerous fundamental activities of a living cell are strongly influenced by the crowding effect, such as protein folding, protein assembly and disassembly, enzyme activity, and signal transduction. Quantitatively predicting how crowding will affect any particular process is, however, a very challenging problem because many physical and chemical parameters act synergistically in ways that defy easy analysis. To build a more realistic model for this problem, we extend a prior stochastic off-lattice model from two-dimensional (2D) to three-dimensional (3D) space and examine how the 3D results compare to those found in 2D. We show that both models exhibit qualitatively similar crowding effects and similar parameter dependence, particularly with respect to a set of parameters previously shown to act linearly on total reaction equilibrium. There are quantitative differences between 2D and 3D models, although with a generally gradual nonlinear interpolation as a system is extended from 2D to 3D. However, the additional freedom of movement allowed to particles as thickness of the simulation box increases can produce significant quantitative change as a system moves from 2D to 3D. Simulation results over broader parameter ranges further show that the impact of molecular crowding is highly dependent on the specific reaction system examined

Conceptualizing and measuring distance in international business research:Recurring questions and best practice guidelines

Distance is a central concept in international business research, yet there is debate about the construct as well as its operationalization. In this editorial, we address three of the most important recurring questions posed by authors, editors, and reviewers by examining the theory, methods, and data of distance research. We discuss (1) how to theorize on distance, and (2) what method and (3) what data to use when constructing a distance index. We develop practical recommendations grounded in theory, illustrating and supporting them by calculating cross-country distance indices for all available country pairs and two of the most used distance indices: cultural and institutional. We show that, whereas a specific method to calculate distance may matter to some extent, the choice for a specific cultural or institutional framework to measure cultural or institutional distance has a major impact on country-pair distances. Overall, this editorial highlights the importance of matching data and method to the theoretical argument.</p