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Inhibition of Bacterial Mutagenesis through Polyubiquitination
Inhibition of Bacterial Mutagenesis through Polyubiquitination
Bacterial cells can have DNA damage due to transcriptional error, or through the effect of an antibiotic. The SOS response is a bacterial cell program for coping with DNA damage, in which the cell cycle is arrested, and DNA repair is induced. The repairs have high probability in leading to mutagenesis in the bacteria, which can lead to antibiotic resistance. The RecA protein in bacteria is responsible for the activation of the SOS response; therefore, making it a target for inhibition. I elected to use the ubiquitination system, natively used for apoptosis, as a means of targeted degradation of the RecA protein in bacteria prone to mutations. Polyubiquitination of misfolded proteins leads to the breaking down of the protein with the aid of proteasomes, which break down unnecessary proteins through a chemical reaction known as proteolysis. Using random forest-predictors, I determined a statistically high likelihood of ubiquitination of the RecA protein in MRSA, Tuberculosis, and other high risk bacterial infections. I hypothesized that I could foster ubiquitin-tagging on RecA by forcing the protein to misfold. Chaperones are proteins which interact with each other to prevent specific sets of proteins from misfolding. CHIP (C terminus of HSC70-Interacting Protein) is a biomolecule that inhibits interactions between the chaperones of RecA. Adding CHIP, ubiquitin, and 26s proteasomes into the bacterial system, should theoretically lead to the degradation of the RecA protein inside the bacteria. I tested my hypothesis by conducting an assay for monitoring CHIP-mediated ubiquitination, and conducted analysis on the assay using SDS- Page gel electrophoresis, and Western-blotting. The resulting data showed signs of polyubiquitination on the RecA protein, with chains of five or more ubiquitin, showing high drug potential. Adding an antibody drug conjugate, containing all the necessary components of a CHIP-mediated ubiquitination reaction, to common antibiotics can lead to the inhibition of bacterial mutagenesis, and higher antibiotic drug potency.
Abheer Singh
CSE8803 Project: Mortality Prediction in ICU patients
CSE8803 Project: Mortality Prediction in ICU patients
Accurate prognosis and prediction of a patient's current disease state is critical in an ICU. The use of vast amounts of digital medical information can help in predicting the best course of action for the diagnosis and treatment of patients. The proposed technique investigates the strength of using a combination of latent variable models (latent dirichlet allocation) and structured data to transform the information streams into potentially actionable knowledge. In this project, I use Apache Spark to predict mortality among ICU patients so that it can be used as an acuity surrogate to help physicians identify the patients in need of immediate care.
Pradeep Vairamani
Cryptology and Combinatorics
Cryptology and Combinatorics
Math 299S Final Project
Thomas Lenell
Identifying Sunspots.
Identifying Sunspots.
Our project titled "Identifying Sunspots," involved the observation and the attempt to collect extensive data on sunspots. In our project, we created a detailed summary of what sun spots are, how they form, how to identify them, and why they are important to us. The in-class presentation served as an opportunity for us to collaborate as a group to learn something on our own, collect data, and to share what we discovered with our classmates.
David
Applications of Compressive Sensing in Communications and Signal Processing
Applications of Compressive Sensing in Communications and Signal Processing
Compressive Sensing is a Signal Processing technique, which gave a break through in 2004. The main idea of CS is, by exploiting the sparsity nature of the signal (in any domain), we can reconstruct the signal from very fewer samples than required by Shannon-Nyquist sampling theorem. Reconstructing a sparse signal from fewer samples is equivalent to solving a under-determined system with sparsity constraints. Least square solution to such a problem yield poor `results because sparse signals cannot be well approximated to a least norm solution. Instead we use l1 norm(convex) to solve this problem which is the best approximation to the exact solution given by l0 norm(non-convex). In this paper we plan to discuss three applications of CS in estimation theory. They are, CS based reliable Channel estimation assuming sparsity in the channel is known for TDS-OFDM systems[1]. Indoor location estimation from received signal strength (RSS) where CS is used to reconstruct the radio map from RSS measurements[2]. Identifying that subspace in which the signal of interest lies using ML estimation, assuming signal lies in a union of subspaces which is a standard sparsity assumption according to CS theory[3]. Index terms : Compressive Sensing, Indoor positioning, fingerprinting, radio map, Maximum likelihood estimation, union of linear subspaces, subspace recovery.
mohangiridhar
PRACTICA 1: Seguridad en el laboratorio.
PRACTICA 1: Seguridad en el laboratorio.
Se realizaron las correspondientes mediciones según lo que se pedía en la práctica, esto para comprobar la resistencia en un circuito paralelo de manera calculada y otra midiéndola en un circuito real. Se midió el valor de diversas resistencias observando el código de color y después de esto se midieron 10 resistencias iguales con un óhmetro para comprobar sus valores y de todos los procedimientos se saco el error absoluto, relativo y su porcentaje.
Pedro Mendoza
University College Cork - MA Module Assignment
University College Cork - MA Module Assignment
Template source: Short Sectioned Assignment LaTeX Template Version 1.0 (5/5/12) This template has been downloaded from: http://www.LaTeXTemplates.com Original author: Frits Wenneker (http://www.howtotex.com) License: CC BY-NC-SA 3.0 (http://creativecommons.org/licenses/by-nc-sa/3.0/)
Brian Sheridan