Student Colloquia
Every week, some of our senior researchers in each department at ASDRP give public seminar presenting the current state of the field, and disseminating how their research at ASDRP fits into the broader context of the frontiers of modern science and engineering. Colloquia are public events, and anyone can join. Simply click the Google Calendar link to add the event to your calendar.
Department of Biological, Human & Life Sciences
Tuesdays @ 8:00 - 9:00 PM PST
Tuesday, February 16, 2021
Evaluating the Effectiveness of Clozapine on Schizophrenic C. elegan Models.
Schizophrenia is a chronic mental illness that is largely defined by an altered awareness of reality. The biological causes of this disorder are largely unknown, which makes it difficult to create a cure for this type of illness, but advances in genetics have revealed factors that increase the risk of developing schizophrenia. Through this study, the efficacy of the second-generation antipsychotic clozapine-- a neuroactive benzodiazepine, which is a class of psychoactive drugs-- will be tested through its ability to treat two defining symptoms of schizophrenia in genetically altered C. elegans: depression and lack of motivation. The efficacy of this drug will be tested on the CB1372 strain-- which exhibits altered aggression and avolition-- and on the CB1370 strain, which exhibits apathy.
Gia O., Granada High School
Truong Research Group
Molecular & Cell Biology
Department of Chemistry, Biochemistry & Physics
Fridays @ 8:00 - 9:00 PM PST
Friday, February 19, 2021
In silico_ screening of a library of carmofur analogs as potential inhibitors of the SARS-CoV-2 main protease and mutational analysis studies of Mpro and HIV-1 reverse transcriptase.
Carmofur is an antineoplastic agent that has been used to treat colorectal cancer. For the past three decades, it has been considered a lipophilic-masked analog of 5-fluorouracil (5-FU). However, recent studies show that it is a human acid ceramidase (ASAH1) inhibitor due to covalent modification of the catalytic cysteine. Carmofur has also been shown to inhibit the SARS-CoV-2 main protease (Mpro) and is a promising lead for a group of antiviral molecules that can be used to treat coronavirus. Density functional theory calculations and docking simulations to Mpro were performed on 39 proposed analogs or carmofur to evaluate their inhibitory potential. Additionally, homology modeling of over 80 clinically-relevant mutations in Mpro in conjunction with molecular dynamics simulations were used to determine whether carmofur and the proposed analogs retain efficacy against these variants. Similarly, homology modeling studies of mutations in HIV-1 reverse transcriptase were conducted on the non-nucleoside reverse transcriptase inhibitor (NNRTI) rilpivirine and a library of 196 novel analogs to determine whether or not these mutants confer resistance. In this discussion, the current progress in synthesizing carmofur monitored by 19F NMR will be presented along with future plans for in vitro testing of the proposed analogs on colorectal cancer cells.
Nickel nanoparticle synthesis for use in catalysts in oxygen reduction reaction.
The oxygen reduction reaction (ORR) is an integral reaction in hydrogen fuel cells, which serve as energy-converting systems that can be used to power a vast array of things. However, one drawback is that it is very slow, and therefore inefficient and unpractical to use in more commercial settings on its own. Catalysts have been developed to speed up the reaction using metals like platinum and palladium, which do increase the rate of the reaction at the cost of being extremely expensive. Therefore, experimenting with nickel has been seen as a potential alternative. Here, an overview of the research performed to create nickel nanoparticles for use in a catalyst will be given, as well as a brief cover of the next steps for these nickel nanoparticles.
Charissa L., Bishop O'Dowd High School
Njoo Research Group
Organic, Medicinal Chemistry
Nikhail J., Fremont High School
Patel Research Group
Inorganic Chemistry & Materials Science
Department of Computer Science & Engineering
Wednesdays @ 8:00 - 9:00 PM PST
Wednesday, February 17, 2021
Predicting the severity of individual coronavirus cases given demographics and pre-existing conditions.
Beginning in early 2020, coronavirus disease (COVID-19) has rapidly spread all over the world. As of now there have been over 108.81 million confirmed cases along with 2.39 million deaths worldwide as of 14 February, 2021. Technology can be used to look at the severity of COVID-19. Our objective is to create an algorithm that will predict the severity of a COVID-19 case for an individual based on demographic data such as race, age, gender, and location. Using international, national and local datasets, we collected the demographic data and organized them into their respective categories, namely age, race, gender, and location of origin. We then inputted this data into an algorithm that works around the principle of probability. Our algorithm uses such trends to develop a risk assessment and create a model. While compiling that data we noted common trends within the three demographics. Specifically, around the age thirty, cases were higher compared to other age ranges. The data collected and trends noted can be used to prioritize and prepare for patients that may be in critical danger, providing a chance for hospitals and vaccine distribution centers to preemptively address higher risk cases early.
Jackie L., BASIS Indepedent High School
McMahan Research Group
Quantum Physics
