Chemical Design, Synthesis, and Clinical Exploitation of Promising Ligands Having High Affinity for the TRP-M8 Receptor of Prostate Cancer Cells

Amanda will investigate a novel method of diagnosing, staging, monitoring, and treating prostate cancer. The specific phases of her investigation include optimizing the design and synthesis of N-radiofluoro or N-radioiodo-aryl-cycloalkylcarboxamides, which have high affinity for the TRP (transient receptor potential)-M8 receptor found in prostate cancer cells; and testing the affinity of the designed ligand for the TRP-M8 receptor in vitro and ultimately in vivo. One of the promising medical applications is the visualization of ligand-TRP-M8-receptor complex with PET or SPECT for diagnosis, staging, and monitoring prostate diseases. In contrast, current diagnostic methods are either inconclusive or painful. The ultimate goal is radiotherapy, a less invasive but more effective alternative to radical prostatectomy and brachytherapy. The process of optimizing the design and synthesis of the ligands and the medical exploitation of them will constitute Amanda’s senior honors thesis in MCB.

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Carburetors for the 21st Century: Flow and Temperature Sensor Integration with Enhanced Mixing

Small-scale power generation (10-100W) for electronic devices is currently supplied by batteries. Unfortunately, specific energy [Whr/kg] and power [W/kg] are limited by battery technology. The U.C. Berkeley liquid hydrocarbon fueled, rotary engine power system provides a greener more efficient and higher powered solution. In this work, MEMS-based (Microelectromechanical Systems) carburetion system with integrated air flow and temperature sensing is developed for more efficient engine operation. Chris will use Solidworks, a 3-D modeling program for carburetor design, while Femlab, CFDRC, and ANSYS will be used to predict device behavior and optimize the designed components. Conical venturis, piezoresistive flow sensors, fuel microchannel networks and wheatstone bridge circuitry are the primary design components. The culmination of Chris’ research will result in a semiconductor fabrication process flow for innovative carburetor design.

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Mapping the World's Genome: Global Protein Demographics

As a part of Steven Brenner’s lab, Chris will be analyzing a large set of novel sequences extracted from oceanic and other environmental microbes. Using computational methods such as Hidden Markov Model searches, he will compare novel environmental peptides to currently known peptides that are available in public databases like Ensembl, TIGR, and nr. Chris will help identify protein domains that are over- or under-represented in the ocean relative to the public datasets, as well as identify domains that may have crossed kingdom barriers. He will also investigate how these new data change our perception of protein space by, for example, illuminating biases that exist in currently available sequence datasets.

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