Orientador: Elisa Maria Aparecida Giro / Resumo: A clorexidina destaca-se por sua eficácia no combate à diversos micro-organismos de interesse cariogênico. No entanto, sua forma de utilização mais conhecida é o enxaguatório bucal, que não possui aplicação universal para pacientes com necessidades especiais. Desse modo, um desafio para a indústria farmacêutica é o desenvolvimento de um sistema para substituir os enxaguatórios bucais. O objetivo desse estudo foi incorporar digluconato de clorexidina, óleo essencial de Cymbopogon citratus ou a associação dessas substâncias a um sistema precursor de cristal líquido mucoadesivo, realizar a caracterização físico-química desse sistema e avaliar in vitro seu potencial antimicrobiano em biofilmes polimicrobianos. As formulações foram caracterizadas por meio de microscopia de luz polarizada, análises reológicas, mucoadesão e perfil de liberação. Posteriormente, foi avaliada a capacidade de redução da acidogenicidade, composição microbiana e dosagem de polissacarídeos extracelulares insolúveis em água dos biofilmes formados a partir da saliva de um doador. Os dados da seleção do doador de saliva, dos testes de CIM e CBM do óleo essencial de C. citratus e do digluconato de clorexidina, as análises reológicas do sistema e o perfil de liberação in vitro foram analisados descritivamente. Enquanto, para os testes de mucoadesão, contagem de micro-organismos do biofilme, pH, peso seco dos biofilmes e dosagem de polissacarídeos extracelulares insolúveis em água, dependendo da normalidade e ho... (Resumo completo, clicar acesso eletrônico abaixo) / Mestre

In this dissertation, we present a number of studies that primarily focus on data movement challenges among different types of memories (viz., 3D-DRAM, DDRx DRAM and NVM) employed together as a flat-address heterogeneous memory system. We introduce two different hardware-based techniques for prefetching data from slow off-chip phase change memory (PCM) to fast on-chip memories. The prefetching techniques efficiently fetch data from PCM and place that data into processor-resident or 3D-DRAM-resident buffers without putting high demand on bandwidth and provide significant performance improvements. Next, we explore different page migration techniques for flat-address memory systems which differ in when to migrate pages (i.e., periodically or instantaneously) and how to manage the migrations (i.e., OS-based or hardware-based approach). In the first page migration study, we present several epoch-based page migration policies for different organizations of flat-address memories consisting of two (2-level) and three (3-level) types of memory modules. These policies have resulted in significant energy savings. In the next page migration study, we devise an efficient "on-the-fly'" page migration technique which migrates a page from slow PCM to fast 3D-DRAM whenever it receives a certain number of memory accesses without waiting for any specific time interval. Furthermore, we present a light-weight hardware-assisted address reconciliation process for address management of the migrated pages. Such an on-the-fly page migration with hardware-assisted address reconciliation technique provides significant performance improvement over systems using epoch-based page migration and OS-based address management. Finally, we have developed an analytical model, which employs offline analyses of memory access counts per page and recommends whether an application is migration friendly or not. This can be useful in deciding if page migration (either epoch-based or on-the-fly based) should be used or turned off for a given application. Thus, our data management techniques and model enable significant performance improvements for flat-address heterogeneous memory systems involving NVMs.

This study was to explore the relationships between personal exposure to 10 volatile organic compounds (VOCs) and biochemical liver tests with the application of canonical correlation analysis. Data from a subsample of the 1999-2000 National Health and Nutrition Examination Survey were used. Serum albumin, total bilirubin (TB), alanine aminotransferase (ALT), aspartate aminotransferase (AST), lactate dehydrogenase (LDH), alkaline phosphatase (ALP), and γ-glutamyl transferase (GGT) served as the outcome variables. Personal exposures to benzene, chloroform, ethylbenzene, tetrachloroethene, toluene, trichloroethene, o-xylene, m-,p-xylene, 1,4-dichlorobenzene, and methyl tert-butyl ether (MTBE) were assessed through the use of passive exposure monitors worn by study participants. The first two canonical correlations were 0.3218 and 0.2575, suggesting a positive correlation mainly between the six VOCs (benzene, ethylbenzene, toluene, o-xylene, m-,p-xylene, and MTBE) and the three biochemical liver tests (albumin, ALP, and GGT) and a positive correlation mainly between the two VOCs (1,4-dichlorobenzene and tetrachloroethene) and the two biochemical liver tests (LDH and TB). Subsequent multiple linear regressions show that exposure to benzene, toluene, or MTBE was associated with serum albumin, while exposure to tetrachloroethene was associated with LDH and total bilirubin. In conclusion, exposure to certain VOCs as a group or individually may influence certain biochemical liver test results in the general population.

Indiana University-Purdue University Indianapolis (IUPUI) / The aim of this study is to identify metabolic transformations in breast cancer through urinary volatile organic compounds in mammary pad or bone tumor mice models. Subsequently, it focuses on investigating the efficacy of therapeutic intervention through identified potential biomarkers. Methods for monitoring tumor development and treatment responses have technologically advanced over the years leading to significant increase in percent survival rates. Although these modalities are reliable, it would be beneficial to observe disease progression from a new perspective to gain greater understanding of cancer pathogenesis. Analysis of cellular energetics affected by cancer using bio-fluids can non-invasively help in prognosis and selection of treatment regimens. The hypothesis is altered profiles of urinary volatile metabolites is directly related to disrupted metabolic pathways. Additionally, effectiveness of treatments can be indicated through changes in concentration of metabolites. In this ancillary experiment, mouse urine specimens were analyzed using gas chromatography-mass spectrometry, an analytical chemistry tool in identifying volatile organic compounds. Female BALB/c mice were injected with 4T1.2 murine breast tumor cells in the mammary fat pad. Consecutively, 4T1.2 cells were injected in the right iliac artery of BALB/c mice and E0771 tumor cells injected in the tibia of C57BL/6 mice to model bone tumor. The effect of two different modes of treatment: chemical drug and mechanical stimulation was investigated through changes in compound profiles. Chemical drug therapy was conducted with dopamine agents, Triuoperazine, Fluphenazine and a statin, Pitavastatin. Mechanical stimulation included tibia and knee loading at the site of tumor cell injection were given to mice. A biological treatment mode included administration of A5 osteocyte cell line. A set of potential volatile organic compounds biomarkers differentiating mammary pad or bone confined tumors from healthy controls was identified using forward feature selection. Effect of treatments was demonstrated through hierarchical heat maps and multivariate data analysis. Compounds identified in series of experiments belonged to the class of terpenoids, precursors of cholesterol molecules. Terpene synthesis is a descending step of mevalonate pathway suggesting its potential role in cancer pathogenesis. This thesis demonstrates the ability of urine volatilomics to indicate signaling pathways inflicted in tumors. It proposes a concept of using urine to detect tumor developments at two distinct locations as well as to monitor treatment efficacy.

Corpus Christi among of the largest industrialized coastal urban areas in Texas. The strategic location of the city along the Gulf of Mexico allows for many important industries and an international business to be located. The cluster of industries and businesses in the region contribute to the air pollution from emissions that are harmful to the environment and to the people living in and visiting the area. Volatile organic compounds (VOC) constitute an important class of pollutants measured in the area. The automated gas chromatography (Auto GC) data was collected from Texas Commission of Environmental Quality (TCEQ) and source apportionment analysis was conducted on this data to identify key sources of VOC affecting this study region. EPA PMF 3.0 was employed in this sources apportionment study of measured VOC concentration during 2005 - 2012 in Corpus Christi, Texas. The study identified nine optimal factors (Source) that could explain the concentration of VOC at two urbane monitoring sites in the study region. Natural gas was found to be the largest contributor of VOC in the area, followed by gasoline and vehicular exhaust. Diesel was the third highest contributor with emissions from manufacturing and combustion processes. Refineries gases and evaporative fugitive emissions were other major contributors in the area; Flaring operations, solvents, and petrochemicals also impacted the measured VOC in the urban area. It was noted that he measured VOC concentrations were significantly influenced by the economic downturn in the region and this was highlighted in the annual trends of the apportioned VOC.

Indiana University-Purdue University Indianapolis (IUPUI) / Volatile organic compounds (VOCs) are endogenous byproducts of metabolic pathways that can be altered by a disease or condition, leading to an associated and unique VOC profile or signature. Current methodologies for VOC detection include canines, gas chromatography-mass spectrometry (GC-MS), and electronic nose (eNose). Some of the challenges for canines and GC-MS are cost-effectiveness, extensive training, expensive instrumentation. On the other hand, a significant downfall of the eNose is low selectivity. This thesis proposes to design a breathalyzer using chemiresistive gas sensors that detects VOCs from human breath, and subsequently create an interface to process and deliver the results via Bluetooth Low Energy (BLE). Breath samples were collected from patients with hypoglycemia, COVID-19, and healthy controls for both. Samples were processed, analyzed using GC-MS, and probed through statistical analysis. A panel of 6 VOC biomarkers distinguished between hypoglycemia (HYPO) and Normal samples with a training AUC of 0.98 and a testing AUC of 0.93. For COVID-19, a panel of 3 VOC biomarkers distinguished between COVID-19 positive symptomatic (COVID-19) and healthy Control samples with a training area under the curve (AUC) of receiver operating characteristic (ROC) of 1.0 and cross-validation (CV) AUC of 0.99. The model was validated with COVID-19 Recovery samples. The discovery of these biomarkers enables the development of selective gas sensors to detect the VOCs. Polyethylenimine-ether functionalized gold nanoparticle (PEI-EGNP) gas sensors were designed and fabricated in the lab and metal oxide (MOX) semiconductor gas sensors were obtained from Nanoz (Chip 1: SnO2 and Chip 2: WO3). These sensors were tested at different relative humidity (RH) levels and VOC concentrations. The contact angle which measures hydrophobicity was 84° and the thickness of the PEI-EGNP coating was 11 µ m. The PEI-EGNP sensor response at RH 85% had a signal 10x higher than at RH 0%. Optimization of the MOX sensor was performed by changing the heater voltage and concentration of VOCs. At RH 85% and heater voltage of 2500 mV, the performance of the sensors increased. Chip 2 had higher sensitivity towards VOCs especially for one of the VOC biomarkers identified for COVID-19. PCA distinguished VOC biomarkers of HYPO, COVID-19, and healthy human breath using the Nanoz. A sensor interface was created to integrate the PEI-EGNP sensors with the printed circuit board (PCB) and Bluno Nano to perform machine learning. The sensor interface can currently process and make decisions from the data whether the breath is HYPO (-) or Normal (+). This data is then sent via BLE to the Hypo Alert app to display the decision.

京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第18802号 / 理博第4060号 / 新制||理||1584(附属図書館) / 31753 / 京都大学大学院理学研究科地球惑星科学専攻 / (主査)教授 竹村 惠二, 教授 平原 和朗, 教授 大沢 信二 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DGAM

京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第19534号 / 理博第4194号 / 新制||理||1602(附属図書館) / 32570 / 京都大学大学院理学研究科生物科学専攻 / (主査)教授 髙林 純示, 教授 永益 英敏, 教授 石田 厚 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DGAM

京都大学 / 0048 / 新制・論文博士 / 博士(農学) / 乙第13034号 / 論農博第2835号 / 新制||農||1044(附属図書館) / 学位論文||H28||N5007(農学部図書室) / 32992 / 京都大学大学院農学研究科農学専攻 / (主査)教授 坪山 直生, 教授 黒木 裕士, 教授 妻木 範行 / 学位規則第4条第2項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

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