Statistical analysis of spectral data: A methodology for designing an intelligent monitoring system for the diabetic foot

Early detection of (pre-)signs of ulceration on a diabetic foot is valuable for clinical practice. Hyperspectral imaging is a promising technique for detection and classification of such (pre-)signs. However, the number of the spectral bands should be limited to avoid overfitting, which is critical for pixel classification with hyperspectral image data. The goal was to design a detector/classifier based on spectral imaging (SI) with a small number of optical bandpass filters. The performance and stability of the design were also investigated. The selection of the bandpass filters boils down to a feature selection problem. A dataset was built, containing reflectance spectra of 227 skin spots from 64 patients, measured with a spectrometer. Each skin spot was annotated manually by clinicians as "healthy" or a specific (pre-)sign of ulceration. Statistical analysis on the data set showed the number of required filters is between 3 and 7, depending on additional constraints on the filter set. The stability analysis revealed that shot noise was the most critical factor affecting the classification performance. It indicated that this impact could be avoided in future SI systems with a camera sensor whose saturation level is higher than 106, or by postimage processing.

Chemotherapy pretreatment sensitizes solid tumor-derived cell lines to Vα24+ NKT cell-mediated cytotoxicity

There is an increasing awareness of the therapeutic potential for combining immune-based therapies with chemotherapy in the treatment of malignant diseases, but few published studies evaluate possible cytotoxic synergies between chemotherapy and cytotoxic immune cells. Human Vα24 +/Vβ11+ NKT cells are being evaluated for use in cell-based immunotherapy of malignancy because of their immune regulatory functions and potent cytotoxic potential. In this study, we evaluated the cytotoxicity of combinations of chemotherapy and NKT cells to determine whether there is a potential to combine these treatment modalities for human cancer therapy. The cytotoxicity of NKT cells was tested against solid-tumor derived cell lines NCI-H358, DLD-1, HT-29, DU-145, TSU-Pr1 and MDA-MB231, with or without prior treatment of these target cells, with a range of chemotherapy agents. Low concentrations of chemotherapeutic agents led to sensitization of cell lines to NKT-mediated cytotoxicity, with the greatest effect being observed for prostate cancer cells. Synergistic cytotoxicity occurred in an NKT cell in a dose-dependent manner. Chemotherapy agents induced upregulation of cell surface TRAIL-R2 (DR5) and Fas (CD95) expression, increasing the capacity for NKT cells to recognize and kill via TRAIL- and FasL-mediated pathways. We conclude that administration of cytotoxic immune cells after chemotherapy may increase antitumor activities in comparison with the use of either treatment alone.

Spectral Values

This series of drawings takes a diagrammatically creative approach to understanding the economic theories and personalities at the centre of the Global Financial Crisis. Mimicking the form of US currency, the work removes labels from common economic diagrams and portrays financial titans in repose as a way to express a personal and ambivalent experience of contemporary capitalism.

Molecular and biochemical characterisation of transgenic banana lines containing iron uptake and storage enhancing genes

This thesis investigated the basis for availability of iron (Fe) and zinc (Zn) content in different banana fruits grown in Uganda and Australia. Rather than micronutrient content levels in different banana cultivar, genotype and environment interactions explained much of the differences. Such information should provide important insights for future developments in the biofortification of banana. Bananas consumed in Uganda did not contain sufficient levels of Fe and Zn that meet the nutrient requirements for vulnerable groups.

Characterisation of novel primary tumour derived epithelial prostate cancer cell lines

Current translational and basic prostate cancer research is limited by the number of cell lines that truly reflect the spectrum of disease progression, with most commonly used cell lines being derived from metastatic lesions. There are essentially no prostate cancer cell lines derived from primary tumours or localised disease in wide use.

Spectral unmixing with estimated adaptive endmember index using Extended Support Vector Machine

The most difficult operation in the flood inundation mapping using optical flood images is to separate fully inundated areas from the ‘wet’ areas where trees and houses are partly covered by water. This can be referred as a typical problem the presence of mixed pixels in the images. A number of automatic information extraction image classification algorithms have been developed over the years for flood mapping using optical remote sensing images. Most classification algorithms generally, help in selecting a pixel in a particular class label with the greatest likelihood. However, these hard classification methods often fail to generate a reliable flood inundation mapping because the presence of mixed pixels in the images. To solve the mixed pixel problem advanced image processing techniques are adopted and Linear Spectral unmixing method is one of the most popular soft classification technique used for mixed pixel analysis. The good performance of linear spectral unmixing depends on two important issues, those are, the method of selecting endmembers and the method to model the endmembers for unmixing. This paper presents an improvement in the adaptive selection of endmember subset for each pixel in spectral unmixing method for reliable flood mapping. Using a fixed set of endmembers for spectral unmixing all pixels in an entire image might cause over estimation of the endmember spectra residing in a mixed pixel and hence cause reducing the performance level of spectral unmixing. Compared to this, application of estimated adaptive subset of endmembers for each pixel can decrease the residual error in unmixing results and provide a reliable output. In this current paper, it has also been proved that this proposed method can improve the accuracy of conventional linear unmixing methods and also easy to apply. Three different linear spectral unmixing methods were applied to test the improvement in unmixing results. Experiments were conducted in three different sets of Landsat-5 TM images of three different flood events in Australia to examine the method on different flooding conditions and achieved satisfactory outcomes in flood mapping.