Computational methods for breast cancer diagnosis, prognosis, and treatment prediction

The research presented here develops a robust reliability algorithm for the identification of reliable protein interactions that can be incorporated with a gene expression dataset to improve the algorithm performance, and novel breast cancer based diagnostic, prognostic and treatment prediction algorithms, respectively, which take into account the existing issues in order to provide a fair estimation of their performance.

Cancer risk factors, diagnosis and sexual identity in the Australian longitudinal study of women's health

PURPOSE: We sought to examine cancer diagnosis, cancer treatment, and related risk factors among Australian, middle-aged, exclusively heterosexual women compared with sexual minority women (SMW; mainly heterosexual, bisexual, mainly lesbian, and lesbian). METHODS: Secondary data analysis of the Australian Longitudinal Study of Women's Health for women born in 1946 through 1951 (n = 10,451) included bivariate tests (i.e., contingency table analyses, independent t tests). RESULTS: SMW did not have significantly higher cancer diagnoses compared with exclusively heterosexual women, although they were more likely to report never having had a mammogram or pap smear. SMW were also significantly more likely to be high-risk drinkers (11.1% vs. 6.8%; p < .05), current smokers (15.1% vs. 8.3%; p < .001), report significantly higher rates of depression (mean ± SD; 6.4 ± 5.5 vs. 5.4 ± 5.1; p < .01.), have experienced physical abuse (10.2% vs. 5.1%; p < .001), and been in a violent relationship (27.2% vs. 12.8%; p < .001). CONCLUSION: SMW had higher rates of several known cancer risk factors, ostensibly placing them at higher risk of cancer as well as chronic health conditions. Further research is needed to determine whether increased risk results in increased cancer as these women age, and to inform the development of interventions to reduce the risk of disease for SMW.

Funtionalized gold nanoparticles for retinoblastoma cancer diagnosis and therapy

 The dissertation reports the synthesis of novel self-therapeutic Surface Enhanced Raman (ST-SERs) active gold nanoparticles. The therapeutic response monitored in the retinoblastoma mice model and elucidated the mechanism of the targeted therapy by biomolecule spectral fingerprints.

Brain substrates of social decision-making in dual diagnosis: cocaine dependence and personality disorders

Cocaine dependence frequently co-occurs with personality disorders, leading to increased interpersonal problems and greater burden of disease. Personality disorders are characterised by patterns of thinking and feeling that divert from social expectations. However, the comorbidity between cocaine dependence and personality disorders has not been substantiated by measures of brain activation during social decision-making. We applied functional magnetic resonance imaging to compare brain activations evoked by a social decision-making task-the Ultimatum Game-in 24 cocaine dependents with personality disorders (CDPD), 19 cocaine dependents without comorbidities and 19 healthy controls. In the Ultimatum Game participants had to accept or reject bids made by another player to split monetary stakes. Offers varied in fairness (in fair offers the proposer shares ~50 percent of the money; in unfair offers the proposer shares <30 percent of the money), and participants were told that if they accept both players get the money, and if they reject both players lose it. We contrasted brain activations during unfair versus fair offers and accept versus reject choices. During evaluation of unfair offers CDPD displayed lower activation in the insula and the anterior cingulate cortex and higher activation in the lateral orbitofrontal cortex and superior frontal and temporal gyri. Frontal activations negatively correlated with emotion recognition. During rejection of offers CDPD displayed lower activation in the anterior cingulate cortex, striatum and midbrain. Dual diagnosis is linked to hypo-activation of the insula and anterior cingulate cortex and hyper-activation of frontal-temporal regions during social decision-making, which associates with poorer emotion recognition.

Mass spectrometry-based proteomic data for cancer diagnosis using interval type-2 fuzzy system

An interval type-2 fuzzy logic system is introduced for cancer diagnosis using mass spectrometry-based proteomic data. The fuzzy system is incorporated with a feature extraction procedure that combines wavelet transform and Wilcoxon ranking test. The proposed feature extraction generates feature sets that serve as inputs to the type-2 fuzzy classifier. Uncertainty, noise and outliers that are common in the proteomic data motivate the use of type-2 fuzzy system. Tabu search is applied for structure learning of the fuzzy classifier. Experiments are performed using two benchmark proteomic datasets for the prediction of ovarian and pancreatic cancer. The dominance of the suggested feature extraction as well as type-2 fuzzy classifier against their competing methods is showcased through experimental results. The proposed approach therefore is helpful to clinicians and practitioners as it can be implemented as a medical decision support system in practice.