Seasonal dynamics of a drosophilid (Diptera) assemblage and its potencial as bioindicator in open environments

Drosophila Fallen, 1823 (Diptera, Drosophilidae) is for long a well-established model organism for genetics and evolutionary research. The ecology of these flies, however, has only recently been better studied. Recent papers show that Drosophila assemblies can be used as bioindicators of forested environment degradation. In this work the bioindicator potential of drosophilids was evaluated in a naturally opened environment, a coastal strand-forest (restinga). Data from nine consecutive seasonal collections revealed strong temporal fluctuation pattern of the majority of Drosophila species groups. Drosophila willistoni group was more abundant at autumns, whereas D. cardini and D. tripunctata groups were, respectively, expressive at winters and springs, and D. repleta group at both seasons. The exotic species D. simulans Sturtevant, 1919 (from D. melanogaster group) and Zaprionus indianus Gupta, 1970 were most abundant at summers. Overall, the assemblage structure did not show the same characteristics of forested or urban environments, but was similar to the forests at winters and to cities at summers. This raises the question that this locality may already been under urbanization impact. Also, this can be interpreted as an easily invaded site for exotic species, what might lead to biotic homogenization and therefore can put in check the usage of drosophilid assemblages as bioindicators at open environments.

Geospatial clustering in data-rich environments: Features and issues

Geospatial clustering must be designed in such a way that it takes into account the special features of geoinformation and the peculiar nature of geographical environments in order to successfully derive geospatially interesting global concentrations and localized excesses. This paper examines families of geospaital clustering recently proposed in the data mining community and identifies several features and issues especially important to geospatial clustering in data-rich environments.

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.

The assessment of oral cytology utilizing ploidy analysis and virtual microscopy for the early detection of epithelial dysplasia and neoplasia in oral mucosal lesions

Oral squamous cell carcinoma (OSCC) is associated with high morbidity and mortality which is due, at least in part, to late detection. Precancerous and cancerous oral lesions may mimic any number of benign oral lesions, and as such may be left without investigation and treatment until they are well advanced. Over the past several years there has been renewed interest in oral cytology as an adjuvant clinical tool in the investigation of oral mucosal lesions. The purpose of the present study was to compare the usefulness of ploidy analysis after Feulgen stained cytological thin-prep specimens with traditional incisional biopsy and routine histopathological examination for the assessment of the pre-malignant potential of oral mucosal lesions. An analysis of the cytological specimens was undertaken with virtual microscopy which allowed for rapid and thorough analysis of the complete cytological specimen. 100 healthy individuals between 30 and 70 years of age, who were non-smokers, non-drinkers and not taking any medication, had cytological specimens collected from both the buccal mucosa and lateral margin of tongue to establish normal cytology parameters within a control population. Patients with a presumptive clinical diagnosis of lichen planus, leukoplakia or OSCC had lesional cytological samples taken prior to their diagnostic biopsy. Standardised thin preparations were prepared and each specimen stained by both Feuglen and Papanicolau methods. High speed scanning of the complete slide at 40X magnification was undertaken using the Aperio Scanscope TM and the green channel of the resultant image was analysed after threshold segmentation to isolate only nuclei and the integrated optical density of each nucleus taken as a gross measure of the DNA content (ploidy). Preliminary results reveal that ploidy assessment of oral cytology holds great promise as an adjunctive prognostic factor in the analysis of the malignant potential of oral mucosal lesions.

Virtual plants - integrating architectural and physiological models

Recent advances in computer technology have made it possible to create virtual plants by simulating the details of structural development of individual plants. Software has been developed that processes plant models expressed in a special purpose mini-language based on the Lindenmayer system formalism. These models can be extended from their architectural basis to capture plant physiology by integrating them with crop models, which estimate biomass production as a consequence of environmental inputs. Through this process, virtual plants will gain the ability to react to broad environmental conditions, while crop models will gain a visualisation component. This integration requires the resolution of the fundamentally different time scales underlying the approaches. Architectural models are usually based on physiological time; each time step encompasses the same amount of development in the plant, without regard to the passage of real time. In contrast, physiological models are based in real time; the amount of development in a time step is dependent on environmental conditions during the period. This paper provides a background on the plant modelling language, then describes how widely-used concepts of thermal time can be implemented to resolve these time scale differences. The process is illustrated using a case study. (C) 1997 Elsevier Science Ltd.