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Brennan-Minnella A.M.,University of California at San Francisco | Arron S.T.,University of California at San Francisco | Chou K.-M.,Indiana University | Cunningham E.,Torrey Pines High School | Cleaver J.E.,University of California at San Francisco
Environmental and Molecular Mutagenesis | Year: 2016

Cancer and neurodegeneration represent the extreme responses of growing and terminally differentiated cells to cellular and genomic damage. The damage recognition mechanisms of nucleotide excision repair, epitomized by xeroderma pigmentosum (XP), and Cockayne syndrome (CS), lie at these extremes. Patients with mutations in the DDB2 and XPC damage recognition steps of global genome repair exhibit almost exclusively actinic skin cancer. Patients with mutations in the RNA pol II cofactors CSA and CSB, that regulate transcription coupled repair, exhibit developmental and neurological symptoms, but not cancer. The absence of skin cancer despite increased photosensitivity in CS implies that the DNA repair deficiency is not associated with increased ultraviolet (UV)-induced mutagenesis, unlike DNA repair deficiency in XP that leads to high levels of UV-induced mutagenesis. One attempt to explain the pathology of CS is to attribute genomic damage to endogenously generated reactive oxygen species (ROS). We show that inhibition of complex I of the mitochondria generates increased ROS, above an already elevated level in CSB cells, but without nuclear DNA damage. CSB, but not CSA, quenches ROS liberated from complex I by rotenone. Extracellular signaling by N-methyl-D-aspartic acid in neurons, however, generates ROS enzymatically through oxidase that does lead to oxidative damage to nuclear DNA. The pathology of CS may therefore be caused by impaired oxidative phosphorylation or nuclear damage from neurotransmitters, but without damage-specific mutagenesis. Environ. Mol. Mutagen. 57:322–330, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc. Source


Cho M.T.,Korea University | Lee S.H.,Torrey Pines High School
Air and Waste Management Association - International Conference on Thermal Treatment Technologies and Hazardous Waste Combustors 2012 | Year: 2012

The research focuses on the optimum operating condition of a semi dry reactor (SDR) and its design factors that ultimately affect the removal efficiency of acidic gases such as SO2, HCl and dioxin. The Study is conducted based on the analysis of Computational Fluid Dynamics model of SDR. In this study, a modeling of spray dry control system SDR was carried out for application to the municipal solid waste incineration system which is running in South Korea. The capacity of incinerator which used in this model is 200 tons per day. To find the optimum operating condition, variables that affect the removal efficiency were manipulated. The temperature profile, the gas profile and the pH profile of SDR were investigated. As of the parameters, the diameter of SDR was 5 meter and the height of SDR was 15.5 meter. The amount of inlet combustion gas of SDR was 12,000 Nm3/hr and the inlet temperature of SDR was 220°C. The amount of lime injection of SDR was 340 liter/hr. From the research, it was discovered that the change of the stoichiometry ratio of lime affected the temperature profile of the SDR. The gas velocity inside the main body of SDR ranged from 0.52 m/sec to 1.25 m/sec and the outlet gas velocity of SDR ranged from 6.8 to 7.5 m/sec. The average velocity in SDR was 0.65 m/sec, the average outlet gas velocity 7.3 m/sec, and the outlet gas temperature of SDR ranged from 175°C to 200°C. When the stoichiometric ratio was 1.0, 1.2, 1.5, the acidic gas removal was 38%, 45% and 56% respectively. Increasing the inlet gas amount increased the gas velocity and the pressure drop. The most pressure drop took place at the gas outlet duct. Source


Dinsdale E.A.,San Diego State University | Edwards R.A.,San Diego State University | Edwards R.A.,Argonne National Laboratory | Bailey B.A.,San Diego State University | And 16 more authors.
Frontiers in Genetics | Year: 2013

Metagenomics is a primary tool for the description of microbial and viral communities. The sheer magnitude of the data generated in each metagenome makes identifying key differences in the function and taxonomy between communities difficult to elucidate. Here we discuss the application of seven different data mining and statistical analyses by comparing and contrasting the metabolic functions of 212 microbial metagenomes within and between 10 environments. Not all approaches are appropriate for all questions, and researchers should decide which approach addresses their questions.This work demonstrated the use of each approach: for example, random forests provided a robust and enlightening description of both the clustering of metagenomes and the metabolic processes that were important in separating microbial communities from different environments. All analyses identified that the presence of phage genes within the microbial community was a predictor of whether the microbial community was host-associated or free-living. Several analyses identified the subtle differences that occur with environments, such as those seen in different regions of the marine environment. © 2013 Dinsdale, Edwards, Bailey, Tuba, Akhter, McNair, Schmieder, Apkarian, Creek, Guan, Hernandez, Isaacs, Peterson, Reghand Ponomarenko. Source


Krishnan M.,University of California at San Diego | Wu M.,Yale University | Kang Y.H.,Torrey Pines High School | Lee S.,Torrey Pines High School
ARPN Journal of Engineering and Applied Sciences | Year: 2012

This paper proposes a cost-effective approach to map and navigate an area with only the means of a single, lowresolution camera on a "smart robot," avoiding the cost and unreliability of radar/sonar systems. Implementation is divided into three main parts: object detection, autonomous movement, and mapping by spiraling inwards and using A* Pathfinding algorithm. Object detection is obtained by editing Horn-Schunck's optical flow algorithm to track pixel brightness factors to subsequent frames, producing outward vectors. These vectors are then focused on the objects using Sobel edge detection. Autonomous movement is achieved by finding the focus of expansion from those vectors and calculating time to collision which are then used to maneuver. Algorithms are programmed in MATLAB and implemented with LEGO Mindstorm NXT 2.0 robot for real-time testing with a low-resolution video camera. Through numerous trials and diversity of the situations, validity of results is ensured to autonomously navigate and map a room using solely optical inputs. ©2006-2012 Asian Research Publishing Network (ARPN). Source

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