The representation of three-way proximity data by single and multiple tree structure models

Models for the representation of proximity data (similarities/dissimilarities) can be categorized into one of three groups of models: continuous spatial models, discrete nonspatial models, and hybrid models (which combine aspects of both spatial and discrete models). Multidimensional scaling models and associated methods, used for thespatial representation of such proximity data, have been devised to accommodate two, three, and higher-way arrays. At least one model/method for overlapping (but generally non-hierarchical) clustering called INDCLUS (Carroll and Arabie 1983) has been devised for the case of three-way arrays of proximity data. Tree-fitting methods, used for thediscrete network representation of such proximity data, have only thus far been devised to handle two-way arrays. This paper develops a new methodology called INDTREES (for INdividual Differences in TREE Structures) for fitting various(discrete) tree structures to three-way proximity data. This individual differences generalization is one in which different individuals, for example, are assumed to base their judgments on the same family of trees, but are allowed to have different node heights and/or branch lengths.We initially present an introductory overview focussing on existing two-way models. The INDTREES model and algorithm are then described in detail. Monte Carlo results for the INDTREES fitting of four different three-way data sets are presented. In the application, a single ultrametric tree is fitted to three-way proximity data derived from intention-to-buy-data for various brands of over-the-counter pain relievers for relieving three common types of maladies. Finally, we briefly describe how the INDTREES procedure can be extended to accommodate hybrid modelling, as well as to handle other types of applications.     

A new semisynthetic ergot peptide alkaloid: DCN 203-922

We report the synthesis, stereochemistry and preliminary pharmacological evaluation of DCN 203-922, a novel ergot alkaloid of the cyclol type, which contains in its peptide moiety the uncommon amino acid L-allo-isoleucine.     

Regulation of B and T cell development by anterior pituitary hormones

Hormones produced by the anterior pituitary gland have been implicated in the regulation of primary lymphocyte development. In order to identify endocrine factors involved in that process, several strains of mice with genetic defects resulting in a selective impairment in the production of one or more anterior pituitary-derived hormones have been analysed. This study has resulted in the classification of endocrine hormones into the following four categories (i) hormones such as prolactin with no apparent effects on primary lymphopoiesis; (ii) anabolic hormones such as growth hormone and insulin-like growth factor-I whose stimulatory effects on primary lymphopoiesis are non-lineage-specific and related to their actions as systemic mediators of growth and/or differentiation; (iii) hormones such as thyroid hormones that have an obligate role in primary B lymphopoiesis; and (iv) hormones such as oestrogens that act as negative regulators of lymphopoiesis.     

Planetary science: bedrock formation at Meridiani Planum

The Mars Exploration Rover Opportunity discovered sulphate-rich sedimentary rocks at Meridiani Planum on Mars, which are interpreted by McCollom and Hynek as altered volcanic rocks. However, their conclusions are derived from an incorrect representation of our depositional model, which is upheld by more recent Rover data. We contend that all the available data still support an aeolian and aqueous sedimentary origin for Meridiani bedrock.     

Interactive memory systems in the human brain.

Learning and memory in humans rely upon several memory systems, which appear to have dissociable brain substrates. A fundamental question concerns whether, and how, these memory systems interact. Here we show using functional magnetic resonance imaging (FMRI) that these memory systems may compete with each other during classification learning in humans. The medial temporal lobe and basal ganglia were differently engaged across subjects during classification learning depending upon whether the task emphasized declarative or nondeclarative memory, even when the to-be-learned material and the level of performance did not differ. Consistent with competition between memory systems suggested by animal studies and neuroimaging, activity in these regions was negatively correlated across individuals. Further examination of classification learning using event-related FMRI showed rapid modulation of activity in these regions at the beginning of learning, suggesting that subjects relied upon the medial temporal lobe early in learning. However, this dependence rapidly declined with training, as predicted by previous computational models of associative learning.