Browsing by Author "Patel, Meera"

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    Assessment of Early Clinical Experiences for Predoctoral Students in North American Dental Schools
    (American Dental Education Association Annual Session and Exhibition, 0022-03) Patel, Meera; Treat, Timothy
    Objectives: To assess the current status of Early Clinical Experiences at North American dental schools. Methods: An IRB-exempt (#10350) survey was distributed to each ADEA chapter president at North American dental schools using the survey instrument, RedCap. Aggregated data was analyzed by the investigators for trends and significant findings were noted. Results: Amongst 19 respondents enrolled in North American dental schools, 1 identified as a D2 student, 12 were D3 students, and 6 were D4 students. When asked if D1 students participated in clinical activity, 9 respondents answered no and 10 respondents answered yes. Of the 10, a majority stated that students spent 0-49 hours participating in procedures such as comprehensive exams, screening exams, taking radiographs and non-surgical periodontal procedures in clinic but did not serve as the primary provider. Of the 19 respondents, when asked if D2’s participated in any clinical activity, 3 answered no and 16 answered yes. Most respondents indicated that D2s spend 50 or more hours in clinic participating in procedures such as comprehensive exams, screening exams, taking radiographs, non-surgical periodontal procedures, direct restorations, single tooth indirect restorations, fixed prosthodontics, and removable prosthodontics in clinic and the majority indicated that D2s can serve as the primary provider for their patients. In addition, most respondents felt that students should serve as primary providers during the D2 year. Conclusions: Early patient care experiences can form an integral part of the pre-clinical experience. At North American dental schools, D1s typically participate in patient care between 0-49 hours but rarely serve as primary provider. D2s often serve as primary provider for many different dental procedures and are typically in clinic 50 hours or more per year. Respondents indicated that an overwhelming majority of North American Dental schools include early patient care experiences as part of their curriculum.
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    A Computational Statistics Approach to Evaluate Blood Biomarkers for Breast Cancer Risk Stratification
    (Springer, 2020) Oktay, Kaan; Santaliz-Casiano, Ashlie; Patel, Meera; Marino, Natascia; Stomiolo, Anna Maria V.; Torun, Hamdi; Acar, Burak; Madak Erdogan, Zeynep; Medicine, School of Medicine
    Breast cancer is the second leading cause of cancer mortality among women. Mammography and tumor biopsy followed by histopathological analysis are the current methods to diagnose breast cancer. Mammography does not detect all breast tumor subtypes, especially those that arise in younger women or women with dense breast tissue, and are more aggressive. There is an urgent need to find circulating prognostic molecules and liquid biopsy methods for breast cancer diagnosis and reducing the mortality rate. In this study, we systematically evaluated metabolites and proteins in blood to develop a pipeline to identify potential circulating biomarkers for breast cancer risk. Our aim is to identify a group of molecules to be used in the design of portable and low-cost biomarker detection devices. We obtained plasma samples from women who are cancer free (healthy) and women who were cancer free at the time of blood collection but developed breast cancer later (susceptible). We extracted potential prognostic biomarkers for breast cancer risk from plasma metabolomics and proteomics data using statistical and discriminative power analyses. We pre-processed the data to ensure the quality of subsequent analyses, and used two main feature selection methods to determine the importance of each molecule. After further feature elimination based on pairwise dependencies, we measured the performance of logistic regression classifier on the remaining molecules and compared their biological relevance. We identified six signatures that predicted breast cancer risk with different specificity and selectivity. The best performing signature had 13 factors. We validated the difference in level of one of the biomarkers, SCF/KITLG, in plasma from healthy and susceptible individuals. These biomarkers will be used to develop low-cost liquid biopsy methods toward early identification of breast cancer risk and hence decreased mortality. Our findings provide the knowledge basis needed to proceed in this direction.
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    Free Fatty Acids Rewire Cancer Metabolism in Obesity-Associated Breast Cancer via Estrogen Receptor and mTOR Signaling
    (AACR, 2019-05) Madak-Erdogan, Zeynep; Band, Shoham; Zhao, Yiru C.; Smith, Brandi P.; Kulkoyluoglu-Cotul, Eylem; Zuo, Qianying; Casiano, Ashlie Santaliz; Wrobel, Kinga; Rossi, Gianluigi; Smith, Rebecca L.; Kim, Sung Hoon; Katzenellenbogen, John A.; Johnson, Mariah L.; Patel, Meera; Marino, Natascia; Storniolo, Anna Maria V.; Flaws, Jodi A.; Medicine, School of Medicine
    Obesity is a risk factor for postmenopausal estrogen receptor alpha (ERα)-positive (ER+) breast cancer. Molecular mechanisms underlying factors from plasma that contribute to this risk and how these mechanisms affect ERα signaling have yet to be elucidated. To identify such mechanisms, we performed whole metabolite and protein profiling in plasma samples from women at high risk for breast cancer, which led us to focus on factors that were differentially present in plasma of obese versus nonobese postmenopausal women. These studies, combined with in vitro assays, identified free fatty acids (FFA) as circulating plasma factors that correlated with increased proliferation and aggressiveness in ER+ breast cancer cells. FFAs activated both the ERα and mTOR pathways and rewired metabolism in breast cancer cells. Pathway preferential estrogen-1 (PaPE-1), which targets ERα and mTOR signaling, was able to block changes induced by FFA and was more effective in the presence of FFA. Collectively, these data suggest a role for obesity-associated gene and metabolic rewiring in providing new targetable vulnerabilities for ER+ breast cancer in postmenopausal women. Furthermore, they provide a basis for preclinical and clinical trials where the impact of agents that target ERα and mTOR signaling cross-talk would be tested to prevent ER+ breast cancers in obese postmenopausal women.