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Full-Text Articles in Physical Sciences and Mathematics

Cancer Incidence And Stage At Diagnosis Among People With Psychotic Disorders: Systematic Review And Meta-Analysis., Jared C Wootten, Joshua C Wiener, Phillip S Blanchette, Kelly K. Anderson Oct 2022

Cancer Incidence And Stage At Diagnosis Among People With Psychotic Disorders: Systematic Review And Meta-Analysis., Jared C Wootten, Joshua C Wiener, Phillip S Blanchette, Kelly K. Anderson

Epidemiology and Biostatistics Publications

Research regarding the incidence of cancer among people with psychotic disorders relative to the general population is equivocal, although the evidence suggests that they have more advanced stage cancer at diagnosis. We conducted a systematic review and meta-analysis to examine the incidence and stage at diagnosis of cancer among people with, relative to those without, psychotic disorders. We searched the MEDLINE, EMBASE, PsycINFO, and CINAHL databases. Articles were included if they reported the incidence and/or stage at diagnosis of cancer in people with psychotic disorders. Random effects meta-analyses were used to determine risk of cancer and odds of advanced stage …


Cancer Incidence And Stage At Diagnosis Among People With Recent-Onset Psychotic Disorders: A Retrospective Cohort Study Using Health Administrative Data From Ontario, Canada., Jared C Wootten, Lucie Richard, Phillip S Blanchette, Joshua C. Wiener, Kelly K. Anderson Sep 2022

Cancer Incidence And Stage At Diagnosis Among People With Recent-Onset Psychotic Disorders: A Retrospective Cohort Study Using Health Administrative Data From Ontario, Canada., Jared C Wootten, Lucie Richard, Phillip S Blanchette, Joshua C. Wiener, Kelly K. Anderson

Epidemiology and Biostatistics Publications

OBJECTIVE: Prior evidence on the relative risk of cancer among people with psychotic disorders is equivocal. The objective of this study was to compare incidence and stage at diagnosis of cancer for people with psychotic disorders relative to the general population.

METHOD: We constructed a retrospective cohort of people with a first diagnosis of non-affective psychotic disorder and a comparison group from the general population using linked health administrative databases in Ontario, Canada. The cohort was followed for incident diagnoses of cancer over a 25-year period. We used Poisson and logistic regression models to compare cancer incidence and stage at …


Design And Synthesis Of Hyaluronan:Rhamm Interaction Inhibitors, Emily Rodrigues Aug 2017

Design And Synthesis Of Hyaluronan:Rhamm Interaction Inhibitors, Emily Rodrigues

Electronic Thesis and Dissertation Repository

A major component of the extracellular matrix is hyaluronan, a regulator of cell migration/survival and differentiation during response-to-injury processes. The receptor for hyaluronan-mediated motility (RHAMM) binds to HA and has limited constitutive expression but is upregulated during tissue injury. Blocking HA fragment:RHAMM interactions has therapeutic potential for treating cancer but truncation of RHAMM into peptides mimicking only the HA binding domains is predicted to lose their natural α-helical structure. The goal of this project is to explore the effects cyclizing each binding domain has on helicity and its biological effect. Eighteen peptides were synthesized and cyclized using lactam bridges. The …


Using Machine Learning To Predict Chemotherapy Response In Cell Lines And Patients Based On Genetic Expression, Dimo Angelov Mar 2017

Using Machine Learning To Predict Chemotherapy Response In Cell Lines And Patients Based On Genetic Expression, Dimo Angelov

Electronic Thesis and Dissertation Repository

The goal of this thesis was to examine different machine learning techniques for predicting chemotherapy response in cell lines and patients based on genetic expression. After trying regression, multi-class classification techniques and binary classification it was concluded that binary classification was the best method for training models due to the limited size of available cell line data. We found support vector machine classifiers trained on cell line data were easier to use and produced better results compared to neural networks. Sequential backward feature selection was able to select genes for the models that produced good results, however the greedy algorithm …