Two-dimensional Microwave Tomographic Imaging of Breast Tissues

Despite its recognized value in detecting and characterizing breast disease, X-ray mammography has important limitations that motivate the quest for alternatives to augment the diagnostic tools that are currently available to the radiologist. The rationale for pursuing electromagnetic methods are based on the significant dielectric contrast between normal and cancerous breast tissues, when exposed to microwaves. The present study analyzes two-dimensional microwave tomographic imaging on normal and malignant breast tissue samples extracted by mastectomy, to assess the suitability of the technique for early detection ofbreast cancer. The tissue samples are immersed in matching coupling medium and are illuminated by 3 GHz signal. 2-D tomographic images ofthe breast tissue samples are reconstructed from the collected scattered data using distorted Born iterative method. Variations of dielectric permittivity in breast samples are distinguishable from the obtained permittivity profiles, which is a clear indication of the presence of malignancy. Hence microwave tomographic imaging is proposed as an alternate imaging modality for early detection ofbreast cancer.

“Reconstruction of Gene Regulatory Network from Expression Profile of Plasma RNA Data of Colorectal Cancer Patients using Soft Computing Techniques”

Microarray data analysis is one of data mining tool which is used to extract meaningful information hidden in biological data. One of the major focuses on microarray data analysis is the reconstruction of gene regulatory network that may be used to provide a broader understanding on the functioning of complex cellular systems. Since cancer is a genetic disease arising from the abnormal gene function, the identification of cancerous genes and the regulatory pathways they control will provide a better platform for understanding the tumor formation and development. The major focus of this thesis is to understand the regulation of genes responsible for the development of cancer, particularly colorectal cancer by analyzing the microarray expression data. In this thesis, four computational algorithms namely fuzzy logic algorithm, modified genetic algorithm, dynamic neural fuzzy network and Takagi Sugeno Kang-type recurrent neural fuzzy network are used to extract cancer specific gene regulatory network from plasma RNA dataset of colorectal cancer patients. Plasma RNA is highly attractive for cancer analysis since it requires a collection of small amount of blood and it can be obtained at any time in repetitive fashion allowing the analysis of disease progression and treatment response.

"Effects of some heavy metals copper. zinc and lead on certain tissues of £153 Qarsia (Hamilton and Buchanan) in different environments

The research investigations on pollution, particularly in coastal/ estuarine environments are recent ones and started only in 1970s. Hence the informations available are fragmentary and scattered. They throw some light only on either the concentration of heavy metals in water or in sediment or in organisms. No concerted efforts have been made to consolidate and correlate the results between the environment and biota. Literature on the level of concentration of heavy metals in different tissues of organisms with regard to their availability in the living media, their ratio, their inter—relationship, tolerance limit of organisms, etc. are very few or rather nil. in view of the importance enumerated above, the candidate has selected the topic "Effects of some heavy metals copper, zinc and lead on certain tissues of E E (Hamilton and Buchanan) in different environments" for detailed studies and to understand systematically (i) the source of effluents and wastes, (ii) the concentration of heavy metals copper, zinc and lead in water, in sediments and in tissues of the test animal, (iii) their effects, (iv) capacity of tolerance and accumulation in different tissues of the animal, and (V) the "Bioaccumulation Factor", etc.