Volume 74, Issue 6

Many endocrine systems have been found to incorporate some form of cascade mechanism into their operation. Such a mechanism involves an amplification system where an initial reaction gives rise to the generation of multiple second reactions, each of which sets off multiple third reactions, and so on. Examples will be presented, with special attention paid to the hypothalamus­pituitary­testicular axis. The production and secretion of luteinizing hormone (LH) is governed by the medial-basal region of the hypothalamus. It is well known that the release of LH is a highly regulated process determined by negative and positive feedback, as well as neural components. The presence of gonadatropin-releasing hormone (GnRH) on specific adenohypophyseal cell membrane receptors results in the release of LH, which is then transported systemically to the Leydig cells of the testes. All the factors governing the release of these hormones, as well as a biochemical description of their actions, have not been completely elucidated, nor is the mechanism behind the pulsatile fashion in which the decapeptide GnRH and LH are released clearly explained. We describe how such a cascade mechanism in a self-regulatory system may be modeled and analyzed by a singular perturbation approach, identifying conditions that give rise to episodic hormone secretion or activity. Insightful and valuable interpretations can be made from such analysis of the cascade system.

The bioinformatics research area is now faced with a mountain of ever-increasing and distributed information. For example, finding a single gene of the Oryza sativa (rice) genome one must spend weeks, if not months, wandering through approximately 40 million base pairs. These data are scattered in many data repositories. Thus, not only do we need an efficient tool to visualize and analyze DNA data, but the integration and exchange of information on a particular gene or coding regions from different international collaborative databases needs to be done in a careful, but robust manner as well. This research suggests a feasible means to overcome these problems by employing two main technologies. To support the exchange and communication between several sources of data, the grid database technology will be employed on the fast Internet2 backbone. Then, XML-based DNA data will be transported between collaborative sources for further analysis and representation. A preliminary version of our Web-based viewer for the XML data of the Oryza sativa genome is presented to illustrate the idea.

Escherichia coli is a free-living bacterium that condensates a large legacy of knowledge as a result of years of experimental work in molecular biology. It represents a point of departure for analyses and comparisons with the ever-increasing number of finished microbial genomes. For years, we have been gathering knowledge from the literature on transcriptional regulation and operon organization in E. coli K-12, and organizing it in a relational database, RegulonDB. RegulonDB contains information of 20­25 % of the expected total sets of regulatory interactions at the level of transcription initiation. We have used this knowledge to generate computational methods to predict the missing sets in the genome of E. coli, focusing on prediction of promoters, regulatory sites, regulatory proteins, operons, and transcription units. These predictions constitute separate pieces of a single puzzle. By putting them all together, we shall be able to predict the complete set of regulatory interactions and transcription unit organization of E. coli. Orthologous genes in other genomes of known co-regulated sets of genes in E. coli, along with their corresponding predicted operons, and their predicted transcriptional regulators, shall permit the extension of the previous goal to many more microbial genomes.

The ongoing genomics revolution has led to the creation and enumeration of all the genes encoded within several organisms. The next steps are to catalog all proteins, their structures, and their functions in different contexts. At the same time, scientists have been pursuing experimental and theoretical approaches to integrate this information to gain understanding of the behavior of entire systems. In this work, we provide a framework for obtaining structures for all tractable protein sequences encoded by a genome, and using the resulting structures to aid in understanding function. Our aim is to integrate the output produced with other genomic and proteomic data to create a comprehensive picture of systems and organismal biology.

Asymmetric polymerization has been of interest to many academic and industrial polymer scientists, but no reference has been made by IUPAC explicitly to classification and definitions of reactions involving the asymmetric synthesis of polymers. This document presents definitions concerned with asymmetric and related polymerizations, with examples included to clarify the meaning of the definitions. Asymmetric polymerizations embrace two main categories, "asymmetric chirogenic polymerizations" and "asymmetric enantiomer-differentiating polymerizations".

Potentiometric selectivity coefficients, K A,B pot have been collected for ionophore-based ion-selective electrodes (ISEs) for inorganic anions reported during 1988-1998. In addition to the actual numerical values of K A,B pot together with the methods and conditions for their determination, response slopes, linear concentration (activity) ranges, chemical compositions, and ionophore structures for the ISE membranes are tabulated.

Potentiometric selectivity coefficients, K A,B pot , have been collected for ionophore-based ion-selective electrodes (ISEs) for organic ions reported during 1988-1998. In addition to the actual numerical values of K A,B pot together with the methods and conditions for their determination, response slopes, linear ranges, chemical compositions, and ionophore structures for the ISE membranes are tabulated.