Can metal complexes serve as hypoxia activated prodrugs? Investigations of a Co(III) complex of the MMP inhibitor marimastat

For many years proof that the hypoxic nature of malignant tumours can be used to selectively target anticancer drugs has been sought. Several classes of potential redox activated anticancer drugs have been developed to take advantage of the reducing environment resulting from the hypoxia. Drug complexes with redox active metal centres as carriers have been investigated, but have largely been employed with cytotoxic drugs that require release of the drug intracellularly, complicating the design of such complexes. MMP inhibitors, a new class of anticancer drug, conversely act in the extracellular environment and we have investigated inhibitor complexes with several redox active transition metals. Marimastat is an MMP inhibitor with potent in-vitro antimetastatic activity and was recently in Phase III clinical trials for a variety of cancer types. We have synthesised a Co(II1) complex of marimastat incorporating the tetradentate ligand tpa (tris(2-methylpyridyl)amine) as a carrier ligand. The complex was structurally characterised in the solid state by single crystal X-ray diffraction, the first example of a crystal structure containing marimastat. 2D COSY and NOESY NMR spectra showed that the complex exists in two isomeric forms in solution, corresponding to the cis and trans isomers yet only crystallises in one of these forms. Biological testing of the complex in mice with 4T1.2 tumours showed interesting and unexpected outcomes. Initial results of the tumour growth inhibition study showed that a significant inhibition of growth was exhibited by the complex over the free inhibitor and the control. However, the metastatic potential of both free marimastat and the complex were higher than the control indicating likely problems with the experimental protocol. Further experiments are needed to determine the potential of such complexes as hypoxia activated prodrugs but there appears at least to be some promise.

NMR characterization of blends of poly(hydroxybutyrate-co-hydroxyvalerate) with poly(vinyl acetate)

The extent of mixing in blends of poly(hydroxybutyrate-co-hydroxyvalerate) (PHBV) (27% HV) and poly(vinyl acetate) (PVAc) has been measured using a number of different techniques, principally solid-state NMR. Differential scanning calorimetry DSC measurements indicated effective mixing of the polymer chains on a scale of several nanometres. The results of H-1 T-1 and H-1 T-1rho. measurements confirm intimate mixing of the chains. A change on blending in the H-1 T-1rho, and the H-1 NMR line width of the signal from the protons of PVAc was consistent with an increase in the amplitude and frequency of motion of this component. The PVAc chains reside within the inter-lamellar space, as confirmed by spin diffusion measurements after H-1 T-1rho preparation. (C) 2003 Society of Chemical Industry.

Image calibration to like-values in mapping shallow water quality from multitemporal data

The applicability of image calibration to like-values in mapping water quality parameters from multitemporal images is explored, Six sets of water samples were collected at satellite overpasses over Moreton Bay, Brisbane, Australia. Analysis of these samples reveals that waters in this shallow bay are mostly TSS-dominated, even though they are occasionally dominated by chlorophyll as well. Three of the images were calibrated to a reference image based on invariant targets. Predictive models constructed from the reference image were applied to estimating total suspended sediment (TSS) and Secchi depth from another image at a discrepancy of around 35 percent. Application of the predictive model for TSS concentration to another image acquired at a time of different water types resulted in a discrepancy of 152 percent. Therefore, image calibration to like-values could be used to reliably map certain water quality parameters from multitemporal TM images so long as the water type under study remains unchanged. This method is limited in that the mapped results could be rather inaccurate if the water type under study has changed considerably. Thus, the approach needs to be refined in shallow water from multitemporal satellite imagery.

Ecosystem process models at multiple scales for mapping tropical forest productivity

Quantifying mass and energy exchanges within tropical forests is essential for understanding their role in the global carbon budget and how they will respond to perturbations in climate. This study reviews ecosystem process models designed to predict the growth and productivity of temperate and tropical forest ecosystems. Temperate forest models were included because of the minimal number of tropical forest models. The review provides a multiscale assessment enabling potential users to select a model suited to the scale and type of information they require in tropical forests. Process models are reviewed in relation to their input and output parameters, minimum spatial and temporal units of operation, maximum spatial extent and time period of application for each organization level of modelling. Organizational levels included leaf-tree, plot-stand, regional and ecosystem levels, with model complexity decreasing as the time-step and spatial extent of model operation increases. All ecosystem models are simplified versions of reality and are typically aspatial. Remotely sensed data sets and derived products may be used to initialize, drive and validate ecosystem process models. At the simplest level, remotely sensed data are used to delimit location, extent and changes over time of vegetation communities. At a more advanced level, remotely sensed data products have been used to estimate key structural and biophysical properties associated with ecosystem processes in tropical and temperate forests. Combining ecological models and image data enables the development of carbon accounting systems that will contribute to understanding greenhouse gas budgets at biome and global scales.

Mapping cortical change in Alzheimer's disease, brain development, and schizophrenia

This paper describes algorithms that can identify patterns of brain structure and function associated with Alzheimer's disease, schizophrenia, normal aging, and abnormal brain development based on imaging data collected in large human populations. Extraordinary information can be discovered with these techniques: dynamic brain maps reveal how the brain grows in childhood, how it changes in disease, and how it responds to medication. Genetic brain maps can reveal genetic influences on brain structure, shedding light on the nature-nurture debate, and the mechanisms underlying inherited neurobehavioral disorders. Recently, we created time-lapse movies of brain structure for a variety of diseases. These identify complex, shifting patterns of brain structural deficits, revealing where, and at what rate, the path of brain deterioration in illness deviates from normal. Statistical criteria can then identify situations in which these changes are abnormally accelerated, or when medication or other interventions slow them. In this paper, we focus on describing our approaches to map structural changes in the cortex. These methods have already been used to reveal the profile of brain anomalies in studies of dementia, epilepsy, depression, childhood and adult-onset schizophrenia, bipolar disorder, attention-deficit/ hyperactivity disorder, fetal alcohol syndrome, Tourette syndrome, Williams syndrome, and in methamphetamine abusers. Specifically, we describe an image analysis pipeline known as cortical pattern matching that helps compare and pool cortical data over time and across subjects. Statistics are then defined to identify brain structural differences between groups, including localized alterations in cortical thickness, gray matter density (GMD), and asymmetries in cortical organization. Subtle features, not seen in individual brain scans, often emerge when population-based brain data are averaged in this way. Illustrative examples are presented to show the profound effects of development and various diseases on the human cortex. Dynamically spreading waves of gray matter loss are tracked in dementia and schizophrenia, and these sequences are related to normally occurring changes in healthy subjects of various ages. (C) 2004 Published by Elsevier Inc.

A new clinical and molecular form of Unverricht-Lundborg disease localized by homozygosity mapping

Progressive myoclonus epilepsy (PME) has a number of causes, of which Unverricht-Lundborg disease (ULD) is the most common. ULD has previously been mapped to a locus on chromosome 21 (EPM1). Subsequently, mutations in the cystatin B gene have been found in most cases. In the present work we identified an inbred Arab family with a clinical pattern compatible with ULD, but mutations in the cystatin B gene were absent. We sought to characterize the clinical and molecular features of the disorder. The family was studied by multiple field trips to their town to clarify details of the complex consanguineous relationships and to personally examine the family. DNA was collected for subsequent molecular analyses from 21 individuals. A genome-wide screen was performed using 811 microsatellite markers. Homozygosity mapping was used to identify loci of interest. There were eight affected individuals. Clinical onset was at 7.3 +/- 1.5 years with myoclonic or tonic-clonic seizures. All had myoclonus that progressed in severity over time and seven had tonic-clonic seizures. Ataxia, in addition to myoclonus, occurred in all. Detailed cognitive assessment was not possible, but there was no significant progressive dementia. There was intrafamily variation in severity; three required wheelchairs in adult life; the others could walk unaided. MRI, muscle and skin biopsies on one individual were unremarkable. We mapped the family to a 15-megabase region at the pericentromeric region of chromosome 12 with a maximum lod score of 6.32. Although the phenotype of individual subjects was typical of ULD, the mean age of onset (7.3 years versus 11 years for ULD) was younger. The locus on chromosome 12 does not contain genes for any other form of PME, nor does it have genes known to be related to cystatin B. This represents a new form of PME and we have designated the locus as EPM1B.

Application of biotechnology in breeding lentil for resistance to biotic and abiotic stress

Lentil is a self-pollinating diploid (2n = 14 chromosomes) annual cool season legume crop that is produced throughout the world and is highly valued as a high protein food. Several abiotic stresses are important to lentil yields world wide and include drought, heat, salt susceptibility and iron deficiency. The biotic stresses are numerous and include: susceptibility to Ascochyta blight, caused by Ascochyta lentis; Anthracnose, caused by Colletotrichum truncatum; Fusarium wilt, caused by Fusarium oxysporum; Sclerotinia white mold, caused by Sclerotinia sclerotiorum; rust, caused by Uromyces fabae; and numerous aphid transmitted viruses. Lentil is also highly susceptible to several species of Orabanche prevalent in the Mediterranean region, for which there does not appear to be much resistance in the germplasm. Plant breeders and geneticists have addressed these stresses by identifying resistant/tolerant germplasm, determining the genetics involved and the genetic map positions of the resistant genes. To this end progress has been made in mapping the lentil genome and several genetic maps are available that eventually will lead to the development of a consensus map for lentil. Marker density has been limited in the published genetic maps and there is a distinct lack of co-dominant markers that would facilitate comparisons of the available genetic maps and efficient identification of markers closely linked to genes of interest. Molecular breeding of lentil for disease resistance genes using marker assisted selection, particularly for resistance to Ascochyta blight and Anthracnose, is underway in Australia and Canada and promising results have been obtained. Comparative genomics and synteny analyses with closely related legumes promises to further advance the knowledge of the lentil genome and provide lentil breeders with additional genes and selectable markers for use in marker assisted selection. Genomic tools such as macro and micro arrays, reverse genetics and genetic transformation are emerging technologies that may eventually be available for use in lentil crop improvement.

Nmr imaging of the diffusion of water into poly(tetrahydrofurfuryl methacrylate-co-hydroxyethyl methacrylate)

0Nuclear magnetic resonance (n.m.r.) imaging was used to study the ingress of water into poly(tetrahydrofurfuryl methacrylate-co-hydroxyethyl methacrylate). The study offers strong evidence that the diffusion is Fickian in nature. The diffusion coefficient, D, obtained by fitting the underlying diffusion profile, attainable from the images, according to the equation for Fickian diffusion, is 1.5 x 10(-11) m(2) s(-1), which is in good correlation with the value of 2.1 x 10(-11) m(2) s(-1), obtained from mass uptake measurements. Additionally, from the T-2-weighted images, Superimposed features observed in addition to the underlying Fickian diffusion profiles were shown to have a longer spin-spin relaxation time, T-2. This Suggests the presence of two types of water within the polymer matrix; a less mobile phase of absorbed water that is interacting strongly with the polymer matrix and a more mobile phase of absorbed water residing within the cracks observed in the environmental scanning electron micrograph. (C) 1997 Elsevier Science Ltd.