Catalyst Program

Overview

Catalyst is an exciting and rigorous science elective that immerses participants in a particular scientific field, giving them new perspectives on the way scientific knowledge is generated. The main goals of the program are to help students discover the nature of science as they increase their abilities to think critically, communicate effectively and learn independently in a research context. Catalyst sets students apart by removing the ceiling of achievement, expanding student comfort zones, and proving student abilities to mentors who can provide impactful college recommendations.

Catalyst requires a high degree of maturity, responsibility and self-motivation. The time and energy commitments are comparable to those of AP science courses and students earn AP weighted grade. For these reasons and because participants represent Gilmour to the scientific community, students must complete an application process and be accepted into the program. Though competence in science is necessary, admittance depends largely on student habits and attitudes.

Catalyst Program Application

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Recent Publications

Ava Thomas ’18
Direct activation of PP2A for the treatment of tyrosine kinase inhibitor–resistant lung adenocarcinoma. JCI Insight, 2019
Although tyrosine kinase inhibitors (TKIs) have demonstrated significant efficacy in advanced lung adenocarcinoma (LUAD) patients with pathogenic alterations in EGFR, most patients develop acquired resistance to these agents via mechanisms enabling the sustained activation of the PI3K and MAPK oncogenic pathways downstream of EGFR. The tumor suppressor protein phosphatase 2A (PP2A) acts as a negative regulator of these pathways. We hypothesize that activation of PP2A simultaneously inhibits the PI3K and MAPK pathways and represents a promising therapeutic strategy for the treatment of TKI-resistant LUAD. After establishing the efficacy of small molecule activators of PP2A (SMAPs) in a transgenic EGFRL858R model and TKI-sensitive cell lines, we evaluated their therapeutic potential in vitro and in vivo in TKI-resistant models. PP2A activation resulted in apoptosis, significant tumor growth inhibition, and downregulation of PI3K and MAPK pathways. Combination of SMAPs and TKI afatinib resulted in an enhanced effect on the downregulation of the PI3K pathway via degradation of the PP2A endogenous inhibitor CIP2A. An improved effect on tumor growth inhibition was observed in a TKI-resistant xenograft mouse model treated with a combination of both agents. These collective data support the development of PP2A activators for the treatment of TKI-resistant LUAD

Olivia A. Robida ’18
Serum biomolecules unable to compete with drug refilling into cyclodextrin polymers regardless of the form. Journal of Materials Chemistry B, 2019
Polymers that are refillable and sustain local release will have a great impact in both preventing and treating local cancer recurrence as well as addressing non-resectable diseases. Polymerized cyclodextrin (pCD) disks, which reload drugs into molecular “pockets” in vivo through affinity interactions, have been previously shown to localize doxorubicin (Dox) to treat glioblastoma multiforme. However, one concern is whether drug refilling is influenced by competition from local biomolecules. In addition the impact of the polymer form on drug refilling is unknown. Herein, different pCD formulations were synthesized from γ-cyclodextrin (γ-CD) and were compared in vitro using competitive drug filling/refilling assays. Data reveal that affinity-based drug refilling occurs as a function of both the polymer form and the sustained release polymeric liquid (SRPL) dilution factor, pointing to the surface/volume ratio, as well as the CD pocket density, and the effects of the distance between pocket. In vitro refilling experiments with cholesterol demonstrated no interference with Dox filling of the CD polymer, while the presence of albumin only slightly reduced Dox filling of pCD-γ-MP (microparticle) and pCD-γ-SRPL forms, but not pCD-γ-disks. Moreover, whole serum competition did not inhibit filling or refilling of pCD-γ-MP with Dox at multiple concentrations and filling times, which indicates that this polymer (re)filling is primarily driven by affinity-based interactions that can overcome the physiological conditions which may limit other drug delivery approaches. This was supplemented by isolating variables through docking simulations and affinity measurements. These results attest to the efficiency of in vivo or in situ polymer filling/refilling in the presence of competitive biological molecules achieved partially through high affinity drug to polymer interactions.

Yihang Zhao ’20
A generalized predictive model for TiO₂–Catalyzed photo-degradation rate constants of water contaminants through artificial neural network. Environmental Research, 2020
Titanium dioxide (TiO₂) is a well-known photocatalyst in the applications of water contaminant treatment. Traditionally, the kinetics of photo-degradation rates are obtained from experiments, which consumes enormous labor and experimental investments. Here, a generalized predictive model was developed for prediction of the photo-degradation rate constants of organic contaminants in the presence of TiO₂ nanoparticles and ultraviolet irradiation in aqueous solution. This model combines an artificial neural network (ANN) with a variety of factors that affect the photo-degradation performance, i.e., ultraviolet intensity, TiO₂ dosage, organic contaminant type and initial concentration in water, and initial pH of the solution. The molecular fingerprints (MF) were used to interpret the organic contaminants as binary vectors, a format that is machine-readable in computational linguistics. A dataset of 446 data points for training and testing was collected from the literature. This predictive model shows a good accuracy with a root mean square error (RMSE) of 0.173.

Jake Robida '18, current student at University of Cincinnati

"Even after three years, Catalyst is still playing an important role in my academic career. For my manufacturing processes course, two other mechanical engineers and I are presenting an informational seminar about Additive Manufacturing for Infrastructure. All my work done in Catalyst is being utilized in front of my professor and peers. The Catalyst program not only introduced me to college-level research, but helped me prepare for the challenging coursework and research that is needed to be a successful engineer. I hope students who are thinking of Catalyst hear my story and accept the challenge."

Outcomes

Upon completion of this externship, students will be able to:

Clearly convey scientific information orally and in writing to multiple audiences.
Analyze scientific processes and data, finding patterns, making connections and identifying inconsistencies or contradictions.
Identify and evaluate assumptions.
Evaluate the reliability of evidence.
Find and synthesize information from a variety of sources (experimental and textual) to propose explanations and draw conclusions.
Provide compelling evidence to support all conclusions and generalizations.
Evaluate own understanding, articulate areas of confusion, and take initiative to acquire needed information.

- Ava Thomas '18, current student at Yale University

“First, Catalyst taught me about the community of research including how to collaborate and work with others, share ideas, give scientific presentations and write research proposals. Second, Catalyst exposed me to real research and the ability to independently conduct experiments using techniques such as Western blotting and gel electrophoresis. These are all methods that are utilized in Yale’s classroom when examining scientific research or reading scientific literature. I am a firm believer in the Catalyst program and would encourage those interested in STEM to be a part of the experience."