66 research outputs found
Computational modelling of the behaviour of biomarker particles of colorectal cancer in fecal matter
Colorectal adenocarcinoma is one of the carcinogenic diseases that is increasing the morbidity and mortality rates worldwide. The disease initially occurs through the segregation of biomarker substances in the human system without manifesting symptoms that affect the health of the carrier. Early detection would allow the application of more effective treatments, less invasive procedures and reduce the development of cancer. The purpose of this investigation was the elaboration of a mathematical model and the development of computational simulations to visualize the behavior of biomarker particles in transit through the colon. The flow conditions, properties of the viscous medium and biological regions of interest were established. Constitutive models, numerical conditions and solution strategies were determined. A numerical grid was used to represent the model of the colon and the human feces that carry the bioparticles (biomarkers). The results indicated the trajectories of the bioparticles in the fecal mass and the interactive movement with the natural contractions of the colon. The analysis of the movement of the biomarker particles can provide future less invasive alternatives for the detection in real time of the cancer by means of the implantation of biosensors in the walls of the colon
A Heterogeneous And Multiscale Modeling Framework To Develop Patient-Specific Pharmacodynamic Systems Models In Cancer
Systems models of key signaling pathways in cancer have been extensively used to under-
stand and explore the mechanisms of action of drugs and growth factors on cancer cell
signaling. In general, such models predict the effect of environmental stimuli (both chemical such as for e.g., growth factor and drugs as well as mechanical such as matrix stiffness)
in terms of activities of proteins such as ERK or AKT which are important regulators of cell
fate decisions. Although such models have helped uncover important emergent properties
of signaling networks such as ultrasensitivity, bistability, and oscillations, they miss many
key features that would make them useful in a clinical setting. 1) The predictions of activity
of proteins such as ERK or AKT cannot be directly translated into a clinically useful parameter such as cell kill rate. 2) They don’t work as well when there are multiple biological
processes operating under different time and length scales such as receptor-based signaling
(4-6 hours) and cell cycle (24-48 hours). 3) The parameter space of such models often exhibits sloppy/stiff character which affects the accuracy of predictions and the robustness of
these models. Apart from single-cell systems models of signaling, pharmacokinetic and cell
population-based pharmacodynamic models are also extensively used to predict the efficacy
of a particular therapy in a clinical setting. However, there are no direct or consistent ways
of incorporating patient-specific gene/protein expression data in these models. This thesis
describes the development and applications of a multiscale and multiparadigm framework
for signaling and pharmacodynamic models that helps us address some of the above short-
comings. First two single scale systems models are described which introduces methods of
exploration of parameter space and their effect on model predictions. Then the multiscale
framework is described and it is applied to two different cancers - Prostate Adenocarcinoma
and Nephroblastoma (Wilm’s Tumor). Special mathematical techniques were used to de-
velop algorithms that can integrate models of disparate time scales and time resolutions
(continuous vs. discrete-time). Such multiscale modeling frameworks have great potential
in the field of personalized medicine and in understanding the physics of cancer taking into
account the biology of the cells
Engineering Novel Detection and Treatment Strategies for Bacterial Therapy of Cancer
Finding and treating cancer is difficult due to limited sensitivity and specificity of current detection and treatment strategies. Many chemotherapeutic drugs are small molecules that are limited by diffusion, making it difficult to reach cancer sites requiring high doses that lead to systemic toxicity and off-target effects. Tomographic detection techniques, like PET, MRI and CT, are good at identifying macroscopic lesions in the body but are limited in their ability to detect microscopic lesions. Biomarker detection strategies are extremely sensitive and able to identify ng/ml concentrations of protein, but are poor at discriminating between healthy and disease state levels due to patient-to-patient variance, often leading to misdiagnosis. Gram negative bacteria, specifically Salmonella typhimurium and Escherichia coli, are potential anticancer agents because of their preferential accumulation and growth within tumors. This tumor specificity allows these bacteria to reduce off-target effects and it enables production of recombinant proteins directly at the tumor site. This thesis presents, three strategies for improving cancer therapy and detection using engineered bacteria
Special oils for halal and safe cosmetics
Three types of non conventional oils were extracted, analyzed and tested for toxicity. Date palm kernel oil (DPKO), mango kernel oil (MKO) and Ramputan seed oil (RSO). Oil content for tow cultivars of dates Deglect Noor and Moshkan was 9.67% and 7.30%, respectively. The three varieties of mango were found to contain about 10% oil in average. The red yellow types of Ramputan were found to have 11 and 14% oil, respectively. The phenolic compounds in DPKO, MKO and RSO were 0.98, 0.88 and 0.78 mg/ml Gallic acid equivalent, respectively. Oils were analyzed for their fatty acid composition and they are rich in oleic acid C18:1 and showed the presence of (dodecanoic acid) lauric acid C12:0, which reported to appear some antimicrobial activities. All extracted oils, DPKO, MKO and RSO showed no toxic effect using prime shrimp bioassay. Since these oils are stable, melt at skin temperature, have good lubricity and are great source of essential fatty acids; they could be used as highly moisturizing, cleansing and nourishing oils because of high oleic acid content. They are ideal for use in such halal cosmetics such as Science, Engineering and Technology 75 skin care and massage, hair-care, soap and shampoo products
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