Javier Segura

Bio: Javier Segura is an academic researcher from University of Cantabria. The author has contributed to research in topics: Bessel function & Laguerre polynomials. The author has an hindex of 22, co-authored 168 publications receiving 2114 citations. Previous affiliations of Javier Segura include Universidad Miguel Hernández de Elche & Centrum Wiskunde & Informatica.

Numerical Methods for Special Functions

Abstract: Special functions arise in many problems of pure and applied mathematics, statistics, physics, and engineering. This book provides an up-to-date overview of methods for computing special functions and discusses when to use them in standard parameter domains, as well as in large and complex domains. The first part of the book covers convergent and divergent series, Chebyshev expansions, numerical quadrature, and recurrence relations. Its focus is on the computation of special functions. Pseudoalgorithms are given to help students write their own algorithms. In addition to these basic tools, the authors discuss methods for computing zeros of special functions, uniform asymptotic expansions, Pad approximations, and sequence transformations. The book also provides specific algorithms for computing several special functions (Airy functions and parabolic cylinder functions, among others). Audience: This book is intended for researchers in applied mathematics, scientific computing, physics, engineering, statistics, and other scientific disciplines in which special functions are used as computational tools. Some chapters can be used in general numerical analysis courses. Contents: List of Algorithms; Preface; Chapter 1: Introduction; Part I: Basic Methods. Chapter 2: Convergent and Divergent Series; Chapter 3: Chebyshev Expansions; Chapter 4: Linear Recurrence Relations and Associated Continued Fractions; Chapter 5: Quadrature Methods; Part II: Further Tools and Methods. Chapter 6: Numerical Aspects of Continued Fractions; Chapter 7: Computation of the Zeros of Special Functions; Chapter 8: Uniform Asymptotic Expansions; Chapter 9: Other Methods; Part III: Related Topics and Examples. Chapter 10: Inversion of Cumulative Distribution Functions; Chapter 11: Further Examples; Part IV: Software. Chapter 12: Associated Algorithms; Bibliography; Index.

Engineering pancreatic islets.

Abstract: Pancreatic islets are neuroendocrine organs that control blood glucose homeostasis. The precise interplay of a heterogeneous group of cell populations (β, α, δ and PP cells) results in the fine-tuned release of counterbalanced hormones (insulin, glucagon, somatostatin and pancreatic polypeptide respectively). Under the premises of detailed knowledge of the physiological basis underlying this behaviour, two lines of investigation might be inferred: generating computational and operational models to explain and predict this behaviour and engineering islet cells to reconstruct pancreatic endocrine function. Whilst the former is being fuelled by new computational strategies, giving biophysicists the possibility of modelling a system in which new "emergent" properties appear, the latter is benefiting from the useful tools and strategic knowledge achieved by molecular, cell and developmental biologists. This includes using tumour cell lines, engineering islet cell precursors, knowledge of the mechanisms of differentiation, regeneration and growth and, finally, therapeutic cloning of human tissues. Gaining deep physiological understanding of the basis governing these processes is instrumental for engineering new pancreatic islets.

Insulin production by human embryonic stem cells.

Abstract: Type 1 diabetes generally results from autoimmune destruction of pancreatic islet β-cells, with consequent absolute insulin deficiency and complete dependence on exogenous insulin treatment. The relative paucity of donations for pancreas or islet allograft transplantation has prompted the search for alternative sources for β-cell replacement therapy. In the current study, we used pluripotent undifferentiated human embryonic stem (hES) cells as a model system for lineage-specific differentiation. Using hES cells in both adherent and suspension culture conditions, we observed spontaneous in vitro differentiation that included the generation of cells with characteristics of insulin-producing β-cells. Immunohistochemical staining for insulin was observed in a surprisingly high percentage of cells. Secretion of insulin into the medium was observed in a differentiation-dependent manner and was associated with the appearance of other β-cell markers. These findings validate the hES cell model system as a potential basis for enrichment of human β-cells or their precursors, as a possible future source for cell replacement therapy in diabetes.

Calculation of Gauss quadrature rules.

Abstract: Most numerical integration techniques consist of approximating the integrand by a polynomial in a region or regions and then integrating the polynomial exactly. Often a complicated integrand can be factored into a non-negative ''weight'' function and another function better approximated by a polynomial, thus $\int_{a}^{b} g(t)dt = \int_{a}^{b} \omega (t)f(t)dt \approx \sum_{i=1}^{N} w_i f(t_i)$. Hopefully, the quadrature rule ${\{w_j, t_j\}}_{j=1}^{N}$ corresponding to the weight function $\omega$(t) is available in tabulated form, but more likely it is not. We present here two algorithms for generating the Gaussian quadrature rule defined by the weight function when: a) the three term recurrence relation is known for the orthogonal polynomials generated by $\omega$(t), and b) the moments of the weight function are known or can be calculated.

Secretory Granule Exocytosis

Abstract: Regulated exocytosis of secretory granules or dense-core granules has been examined in many well-characterized cell types including neurons, neuroendocrine, endocrine, exocrine, and hemopoietic cells and also in other less well-studied cell types. Secretory granule exocytosis occurs through mechanisms with many aspects in common with synaptic vesicle exocytosis and most likely uses the same basic protein components. Despite the widespread expression and conservation of a core exocytotic machinery, many variations occur in the control of secretory granule exocytosis that are related to the specialized physiological role of particular cell types. In this review we describe the wide range of cell types in which regulated secretory granule exocytosis occurs and assess the evidence for the expression of the conserved fusion machinery in these cells. The signals that trigger and regulate exocytosis are reviewed. Aspects of the control of exocytosis that are specific for secretory granules compared with synaptic vesicles or for particular cell types are described and compared to define the range of accessory control mechanisms that exert their effects on the core exocytotic machinery.

Tissue engineering and regenerative medicine: history, progress, and challenges.

Abstract: The past three decades have seen the emergence of an endeavor called tissue engineering and regenerative medicine in which scientists, engineers, and physicians apply tools from a variety of fields to construct biological substitutes that can mimic tissues for diagnostic and research purposes and can replace (or help regenerate) diseased and injured tissues. A significant portion of this effort has been translated to actual therapies, especially in the areas of skin replacement and, to a lesser extent, cartilage repair. A good amount of thoughtful work has also yielded prototypes of other tissue substitutes such as nerve conduits, blood vessels, liver, and even heart. Forward movement to clinical product, however, has been slow. Another offshoot of these efforts has been the incorporation of some new exciting technologies (e.g., microfabrication, 3D printing) that may enable future breakthroughs. In this review we highlight the modest beginnings of the field and then describe three application examples that are in various stages of development, ranging from relatively mature (skin) to ongoing proof-of-concept (cartilage) to early stage (liver). We then discuss some of the major issues that limit the development of complex tissues, some of which are fundamentals-based, whereas others stem from the needs of the end users.