950 resultados para onde, millimetriche, beamforming, indoor, ray, tracing, human, blockage


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The X-ray structure of human phenylethanolamine N-methyltransferase (hPNMT) complexed. with its product, S-adenoSyl-L-homocysteine (4), and the most potent inhibitor reported to date, SK&F 64139 (7), was used to identify the residues involved in inhibitor binding. Four of these residues, Va153, Lys57, Glu219 and Asp267, were replaced, in turn, with alanine. All variants had increased K-m values for phenylethanolamine (10), but only D267A showed a noteworthy (20-fold) decrease in its k(cat) value. Both WT hPNMT and D267A had similar k(cat) values for a rigid analogue, anti-9-amino-6-(trifluoromethyl)benzonorbornene (12), suggesting that Asp267 plays an important role in positioning the substrate but does not participate directly in catalysis. The K-i values for the binding of inhibitors such as 7 to the E219A and D267A variants increased by 2-3 orders of magnitude. Further, the inhibitors were shown to bind up to 50-fold more tightly in the presence of S-adenoSyl-(L)-methionine (3), suggesting that the binding of the latter brings about a conformational change in the enzyme.

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Parasite resistance to antimalarial drugs is a serious threat to human health, and novel agents that act on enzymes essential for parasite metabolism, such as proteases, are attractive targets for drug development. Recent studies have shown that clinically utilized human immunodeficiency virus (HIV) protease inhibitors can inhibit the in vitro growth of Plasmodium falciparum at or below concentrations found in human plasma after oral drug administration. The most potent in vitro antimalarial effects have been obtained for parasites treated with saquinavir, ritonavir, or lopinavir, findings confirmed in this study for a genetically distinct P. falciparum line (3D7). To investigate the potential in vivo activity of antiretroviral protease inhibitors (ARPIs) against malaria, we examined the effect of ARPI combinations in a murine model of malaria. In mice infected with Plasmodium chabaudi AS and treated orally with ritonavir-saquinavir or ritonavir-lopinavir, a delay in patency and a significant attenuation of parasitemia were observed. Using modeling and ligand docking studies we examined putative ligand binding sites of ARPIs in aspartyl proteases of P. falciparum (plasmepsins II and IV) and P. chabaudi (plasmepsin) and found that these in silico analyses support the antimalarial activity hypothesized to be mediated through inhibition of these enzymes. In addition, in vitro enzyme assays demonstrated that P. falciparum plasmepsins II and IV are both inhibited by the ARPIs saquinavir, ritonavir, and lopinavir. The combined results suggest that ARPIs have useful antimalarial activity that may be especially relevant in geographical regions where HIV and P. falciparum infections are both endemic.

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Keyword identification in one of two simultaneous sentences is improved when the sentences differ in F0, particularly when they are almost continuously voiced. Sentences of this kind were recorded, monotonised using PSOLA, and re-synthesised to give a range of harmonic ?F0s (0, 1, 3, and 10 semitones). They were additionally re-synthesised by LPC with the LPC residual frequency shifted by 25% of F0, to give excitation with inharmonic but regularly spaced components. Perceptual identification of frequency-shifted sentences showed a similar large improvement with nominal ?F0 as seen for harmonic sentences, although overall performance was about 10% poorer. We compared performance with that of two autocorrelation-based computational models comprising four stages: (i) peripheral frequency selectivity and half-wave rectification; (ii) within-channel periodicity extraction; (iii) identification of the two major peaks in the summary autocorrelation function (SACF); (iv) a template-based approach to speech recognition using dynamic time warping. One model sampled the correlogram at the target-F0 period and performed spectral matching; the other deselected channels dominated by the interferer and performed matching on the short-lag portion of the residual SACF. Both models reproduced the monotonic increase observed in human performance with increasing ?F0 for the harmonic stimuli, but not for the frequency-shifted stimuli. A revised version of the spectral-matching model, which groups patterns of periodicity that lie on a curve in the frequency-delay plane, showed a closer match to the perceptual data for frequency-shifted sentences. The results extend the range of phenomena originally attributed to harmonic processing to grouping by common spectral pattern.

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MHC class II proteins bind oligopeptide fragments derived from proteolysis of pathogen antigens, presenting them at the cell surface for recognition by CD4+ T cells. Human MHC class II alleles are grouped into three loci: HLA-DP, HLA-DQ and HLA-DR. In contrast to HLA-DR and HLA-DQ, HLA-DP proteins have not been studied extensively, as they have been viewed as less important in immune responses than DRs and DQs. However, it is now known that HLA-DP alleles are associated with many autoimmune diseases. Quite recently, the X-ray structure of the HLA-DP2 molecule (DPA*0103, DPB1*0201) in complex with a self-peptide derived from the HLA-DR a-chain has been determined. In the present study, we applied a validated molecular docking protocol to a library of 247 modelled peptide-DP2 complexes, seeking to assess the contribution made by each of the 20 naturally occurred amino acids at each of the nine binding core peptide positions and the four flanking residues (two on both sides).

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This thesis is an exploration of the organisation and functioning of the human visual system using the non-invasive functional imaging modality magnetoencephalography (MEG). Chapters one and two provide an introduction to the ‘human visual system and magnetoencephalographic methodologies. These chapters subsequently describe the methods by which MEG can be used to measure neuronal activity from the visual cortex. Chapter three describes the development and implementation of novel analytical tools; including beamforming based analyses, spectrographic movies and an optimisation of group imaging methods. Chapter four focuses on the use of established and contemporary analytical tools in the investigation of visual function. This is initiated with an investigation of visually evoked and induced responses; covering visual evoked potentials (VEPs) and event related synchronisation/desynchronisation (ERS/ERD). Chapter five describes the employment of novel methods in the investigation of cortical contrast response and demonstrates distinct contrast response functions in striate and extra-striate regions of visual cortex. Chapter six use synthetic aperture magnetometry (SAM) to investigate the phenomena of visual cortical gamma oscillations in response to various visual stimuli; concluding that pattern is central to its generation and that it increases in amplitude linearly as a function of stimulus contrast, consistent with results from invasive electrode studies in the macaque monkey. Chapter seven describes the use of driven visual stimuli and tuned SAM methods in a pilot study of retinotopic mapping using MEG; finding that activity in the primary visual cortex can be distinguished in four quadrants and two eccentricities of the visual field. Chapter eight is a novel implementation of the SAM beamforming method in the investigation of a subject with migraine visual aura; the method reveals desynchronisation of the alpha and gamma frequency bands in occipital and temporal regions contralateral to observed visual abnormalities. The final chapter is a summary of main conclusions and suggested further work.

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The existence of adequate financial capital at start-up as well as during the lifetime of a firm is considered to be vital not only for its survival but also for its effective trading and growth, as it can act as a buffer against unforeseen difficulties (Cooper, Gimeno-Gascon, & Woo, 1994; Chandler & Hanks, 1998; Venkataraman & Van de Ven, 1998; Cassar, 2004). Inadequate or inappropriate capital structure is often the most common reason for a large proportion of small business failures (Chaganti, DeCarolis, & Deeds, 1995).

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Aims. Long gamma-ray bursts (LGRBs) are associated with the deaths of massive stars and might therefore be a potentially powerful tool for tracing cosmic star formation. However, especially at low redshifts (z< 1.5) LGRBs seem to prefer particular types of environment. Our aim is to study the host galaxies of a complete sample of bright LGRBs to investigate the effect of the environment on GRB formation. Methods. We studied host galaxy spectra of the Swift/BAT6 complete sample of 14 z< 1 bright LGRBs. We used the detected nebular emission lines to measure the dust extinction, star formation rate (SFR), and nebular metallicity (Z) of the hosts and supplemented the data set with previously measured stellar masses M_*. The distributions of the obtained properties and their interrelations (e.g. mass-metallicity and SFR-M_* relations) are compared to samples of field star-forming galaxies. Results. We find that LGRB hosts at z< 1 have on average lower SFRs than if they were direct star formation tracers. By directly comparing metallicity distributions of LGRB hosts and star-forming galaxies, we find a good match between the two populations up to 12 +log (O/H)~8.4−8.5, after which the paucity of metal-rich LGRB hosts becomes apparent. The LGRB host galaxies of our complete sample are consistent with the mass-metallicity relation at similar mean redshift and stellar masses. The cutoff against high metallicities (and high masses) can explain the low SFR values of LGRB hosts. We find a hint of an increased incidence of starburst galaxies in the Swift/BAT6 z< 1 sample with respect to that of a field star-forming population. Given that the SFRs are low on average, the latter is ascribed to low stellar masses. Nevertheless, the limits on the completeness and metallicity availability of current surveys, coupled with the limited number of LGRB host galaxies, prevents us from investigating more quantitatively whether the starburst incidence is such as expected after taking into account the high-metallicity aversion of LGRB host galaxies.

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As the pressure continues to grow on Diamond and the world's synchrotrons for higher throughput of diffraction experiments, new and novel techniques are required for presenting micron dimension crystals to the X ray beam. Currently this task is both labour intensive and primarily a serial process. Diffraction measurements typically take milliseconds but sample preparation and presentation can reduce throughput down to 4 measurements an hour. With beamline waiting times as long as two years it is of key importance for researchers to capitalize on available beam time, generating as much data as possible. Other approaches detailed in the literature [1] [2] [3] are very much skewed towards automating, with robotics, the actions of a human protocols. The work detailed here is the development and discussion of a bottom up approach relying on SSAW self assembly, including material selection, microfluidic integration and tuning of the acoustic cavity to order the protein crystals.

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As the pressure continues to grow on Diamond and the world's synchrotrons for higher throughput of diffraction experiments, new and novel techniques are required for presenting micron dimension crystals to the X ray beam. Currently this task is both labour intensive and primarily a serial process. Diffraction measurements typically take milliseconds but sample preparation and presentation can reduce throughput down to 4 measurements an hour. With beamline waiting times as long as two years it is of key importance for researchers to capitalize on available beam time, generating as much data as possible. Other approaches detailed in the literature [1] [2] [3] are very much skewed towards automating, with robotics, the actions of a human protocols. The work detailed here is the development and discussion of a bottom up approach relying on SSAW self assembly, including material selection, microfluidic integration and tuning of the acoustic cavity to order the protein crystals.

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X-ray computed tomography (CT) imaging constitutes one of the most widely used diagnostic tools in radiology today with nearly 85 million CT examinations performed in the U.S in 2011. CT imparts a relatively high amount of radiation dose to the patient compared to other x-ray imaging modalities and as a result of this fact, coupled with its popularity, CT is currently the single largest source of medical radiation exposure to the U.S. population. For this reason, there is a critical need to optimize CT examinations such that the dose is minimized while the quality of the CT images is not degraded. This optimization can be difficult to achieve due to the relationship between dose and image quality. All things being held equal, reducing the dose degrades image quality and can impact the diagnostic value of the CT examination.

A recent push from the medical and scientific community towards using lower doses has spawned new dose reduction technologies such as automatic exposure control (i.e., tube current modulation) and iterative reconstruction algorithms. In theory, these technologies could allow for scanning at reduced doses while maintaining the image quality of the exam at an acceptable level. Therefore, there is a scientific need to establish the dose reduction potential of these new technologies in an objective and rigorous manner. Establishing these dose reduction potentials requires precise and clinically relevant metrics of CT image quality, as well as practical and efficient methodologies to measure such metrics on real CT systems. The currently established methodologies for assessing CT image quality are not appropriate to assess modern CT scanners that have implemented those aforementioned dose reduction technologies.

Thus the purpose of this doctoral project was to develop, assess, and implement new phantoms, image quality metrics, analysis techniques, and modeling tools that are appropriate for image quality assessment of modern clinical CT systems. The project developed image quality assessment methods in the context of three distinct paradigms, (a) uniform phantoms, (b) textured phantoms, and (c) clinical images.

The work in this dissertation used the “task-based” definition of image quality. That is, image quality was broadly defined as the effectiveness by which an image can be used for its intended task. Under this definition, any assessment of image quality requires three components: (1) A well defined imaging task (e.g., detection of subtle lesions), (2) an “observer” to perform the task (e.g., a radiologists or a detection algorithm), and (3) a way to measure the observer’s performance in completing the task at hand (e.g., detection sensitivity/specificity).

First, this task-based image quality paradigm was implemented using a novel multi-sized phantom platform (with uniform background) developed specifically to assess modern CT systems (Mercury Phantom, v3.0, Duke University). A comprehensive evaluation was performed on a state-of-the-art CT system (SOMATOM Definition Force, Siemens Healthcare) in terms of noise, resolution, and detectability as a function of patient size, dose, tube energy (i.e., kVp), automatic exposure control, and reconstruction algorithm (i.e., Filtered Back-Projection– FPB vs Advanced Modeled Iterative Reconstruction– ADMIRE). A mathematical observer model (i.e., computer detection algorithm) was implemented and used as the basis of image quality comparisons. It was found that image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose (increase in detectability index by up to 163% depending on iterative strength). The use of automatic exposure control resulted in more consistent image quality with changing phantom size.

Based on those results, the dose reduction potential of ADMIRE was further assessed specifically for the task of detecting small (<=6 mm) low-contrast (<=20 HU) lesions. A new low-contrast detectability phantom (with uniform background) was designed and fabricated using a multi-material 3D printer. The phantom was imaged at multiple dose levels and images were reconstructed with FBP and ADMIRE. Human perception experiments were performed to measure the detection accuracy from FBP and ADMIRE images. It was found that ADMIRE had equivalent performance to FBP at 56% less dose.

Using the same image data as the previous study, a number of different mathematical observer models were implemented to assess which models would result in image quality metrics that best correlated with human detection performance. The models included naïve simple metrics of image quality such as contrast-to-noise ratio (CNR) and more sophisticated observer models such as the non-prewhitening matched filter observer model family and the channelized Hotelling observer model family. It was found that non-prewhitening matched filter observers and the channelized Hotelling observers both correlated strongly with human performance. Conversely, CNR was found to not correlate strongly with human performance, especially when comparing different reconstruction algorithms.

The uniform background phantoms used in the previous studies provided a good first-order approximation of image quality. However, due to their simplicity and due to the complexity of iterative reconstruction algorithms, it is possible that such phantoms are not fully adequate to assess the clinical impact of iterative algorithms because patient images obviously do not have smooth uniform backgrounds. To test this hypothesis, two textured phantoms (classified as gross texture and fine texture) and a uniform phantom of similar size were built and imaged on a SOMATOM Flash scanner (Siemens Healthcare). Images were reconstructed using FBP and a Sinogram Affirmed Iterative Reconstruction (SAFIRE). Using an image subtraction technique, quantum noise was measured in all images of each phantom. It was found that in FBP, the noise was independent of the background (textured vs uniform). However, for SAFIRE, noise increased by up to 44% in the textured phantoms compared to the uniform phantom. As a result, the noise reduction from SAFIRE was found to be up to 66% in the uniform phantom but as low as 29% in the textured phantoms. Based on this result, it clear that further investigation was needed into to understand the impact that background texture has on image quality when iterative reconstruction algorithms are used.

To further investigate this phenomenon with more realistic textures, two anthropomorphic textured phantoms were designed to mimic lung vasculature and fatty soft tissue texture. The phantoms (along with a corresponding uniform phantom) were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Scans were repeated a total of 50 times in order to get ensemble statistics of the noise. A novel method of estimating the noise power spectrum (NPS) from irregularly shaped ROIs was developed. It was found that SAFIRE images had highly locally non-stationary noise patterns with pixels near edges having higher noise than pixels in more uniform regions. Compared to FBP, SAFIRE images had 60% less noise on average in uniform regions for edge pixels, noise was between 20% higher and 40% lower. The noise texture (i.e., NPS) was also highly dependent on the background texture for SAFIRE. Therefore, it was concluded that quantum noise properties in the uniform phantoms are not representative of those in patients for iterative reconstruction algorithms and texture should be considered when assessing image quality of iterative algorithms.

The move beyond just assessing noise properties in textured phantoms towards assessing detectability, a series of new phantoms were designed specifically to measure low-contrast detectability in the presence of background texture. The textures used were optimized to match the texture in the liver regions actual patient CT images using a genetic algorithm. The so called “Clustured Lumpy Background” texture synthesis framework was used to generate the modeled texture. Three textured phantoms and a corresponding uniform phantom were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Images were reconstructed with FBP and SAFIRE and analyzed using a multi-slice channelized Hotelling observer to measure detectability and the dose reduction potential of SAFIRE based on the uniform and textured phantoms. It was found that at the same dose, the improvement in detectability from SAFIRE (compared to FBP) was higher when measured in a uniform phantom compared to textured phantoms.

The final trajectory of this project aimed at developing methods to mathematically model lesions, as a means to help assess image quality directly from patient images. The mathematical modeling framework is first presented. The models describe a lesion’s morphology in terms of size, shape, contrast, and edge profile as an analytical equation. The models can be voxelized and inserted into patient images to create so-called “hybrid” images. These hybrid images can then be used to assess detectability or estimability with the advantage that the ground truth of the lesion morphology and location is known exactly. Based on this framework, a series of liver lesions, lung nodules, and kidney stones were modeled based on images of real lesions. The lesion models were virtually inserted into patient images to create a database of hybrid images to go along with the original database of real lesion images. ROI images from each database were assessed by radiologists in a blinded fashion to determine the realism of the hybrid images. It was found that the radiologists could not readily distinguish between real and virtual lesion images (area under the ROC curve was 0.55). This study provided evidence that the proposed mathematical lesion modeling framework could produce reasonably realistic lesion images.

Based on that result, two studies were conducted which demonstrated the utility of the lesion models. The first study used the modeling framework as a measurement tool to determine how dose and reconstruction algorithm affected the quantitative analysis of liver lesions, lung nodules, and renal stones in terms of their size, shape, attenuation, edge profile, and texture features. The same database of real lesion images used in the previous study was used for this study. That database contained images of the same patient at 2 dose levels (50% and 100%) along with 3 reconstruction algorithms from a GE 750HD CT system (GE Healthcare). The algorithms in question were FBP, Adaptive Statistical Iterative Reconstruction (ASiR), and Model-Based Iterative Reconstruction (MBIR). A total of 23 quantitative features were extracted from the lesions under each condition. It was found that both dose and reconstruction algorithm had a statistically significant effect on the feature measurements. In particular, radiation dose affected five, three, and four of the 23 features (related to lesion size, conspicuity, and pixel-value distribution) for liver lesions, lung nodules, and renal stones, respectively. MBIR significantly affected 9, 11, and 15 of the 23 features (including size, attenuation, and texture features) for liver lesions, lung nodules, and renal stones, respectively. Lesion texture was not significantly affected by radiation dose.

The second study demonstrating the utility of the lesion modeling framework focused on assessing detectability of very low-contrast liver lesions in abdominal imaging. Specifically, detectability was assessed as a function of dose and reconstruction algorithm. As part of a parallel clinical trial, images from 21 patients were collected at 6 dose levels per patient on a SOMATOM Flash scanner. Subtle liver lesion models (contrast = -15 HU) were inserted into the raw projection data from the patient scans. The projections were then reconstructed with FBP and SAFIRE (strength 5). Also, lesion-less images were reconstructed. Noise, contrast, CNR, and detectability index of an observer model (non-prewhitening matched filter) were assessed. It was found that SAFIRE reduced noise by 52%, reduced contrast by 12%, increased CNR by 87%. and increased detectability index by 65% compared to FBP. Further, a 2AFC human perception experiment was performed to assess the dose reduction potential of SAFIRE, which was found to be 22% compared to the standard of care dose.

In conclusion, this dissertation provides to the scientific community a series of new methodologies, phantoms, analysis techniques, and modeling tools that can be used to rigorously assess image quality from modern CT systems. Specifically, methods to properly evaluate iterative reconstruction have been developed and are expected to aid in the safe clinical implementation of dose reduction technologies.

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Polybrominated diphenyl ethers (PBDEs) are a class of brominated flame retardants (BFRs) that have been heavily used in consumer products such as furniture foams, plastics, and textiles since the mid-1970’s. BFRs are added to products in order to meet state flammability standards intended to increase indoor safety in the event of a fire. The three commercial PBDE mixtures, Penta-, Octa-, and DecaBDE, have all been banned in the United States, however, limited use of DecaBDE is still permitted. PBDEs were phased out of production and added to the Stockholm Convention due to concerns over their environmental persistence and toxicity. Human exposure to PBDEs occurs primarily through the inadvertent ingestion of contaminated house dust, as well as though dietary sources. Despite the phase-out and discontinued use of PBDEs, human exposure to this class of chemicals is likely to continue for decades due to the continued use of treated products and existing environmental reservoirs of PBDEs. Extensive research over the years has shown that PBDEs disrupt thyroid hormone (TH) levels and neurodevelopmental endpoints in rodent and fish models. Additionally, there is growing epidemiological evidence linking PBDE exposure in humans to altered TH homeostasis and neurodevelopmental impairments in children. Due to the importance of THs throughout gestation, there is a great need to understand the effects of BFRs on the developing fetus. Specifically, the placenta plays a critical role in the transport, metabolism, and delivery of THs to the fetal compartment during pregnancy and is a likely target for BFR bioaccumulation and endocrine disruption. The central hypothesis of this dissertation research is that BFRs disrupt the activity of TH sulfotransferase (SULT) enzymes, thereby altering TH concentrations in the placenta.

In the first aim of this dissertation research, the concentrations of PBDEs and 2,4,6-TBP were measured in a cohort of 102 placenta tissue samples from an ongoing pregnancy cohort in Durham, NC. Methods were developed for the extraction and analysis of the BFR analytes. It was found that 2,4,6-TBP was significantly correlated with all PBDE analytes, indicating that 2,4,6-TBP may share common product applications with PBDEs or that 2,4,6-TBP is a metabolite of PBDE compounds. Additionally, this was the first study to measure 2,4,6-TBP in human placenta tissues.

In the second aim of this dissertation research, the placenta tissue concentrations of THs, as well as the endogenous activity of deiodinase (DI) and TH SULT enzymes were quantified using the same cohort of 102 placenta tissue samples. Enzyme activity was detected in all samples and this was the first study to measure TH DI and SULT activity in human placenta tissues. Enzyme activities and TH concentrations were compared with BFR concentrations measured in Aim 1. There were few statistically significant associations observed for the combined data, however, upon stratifying the data set based on infant sex, additional significant associations were observed. For example, among males, those with the highest concentrations of BDE-99 in placenta had T3 levels 0.80 times those with the lowest concentration of BDE-99 (95% confidence interval (CI): 0.59, 1.07). Whereas females with the highest concentrations of BDE-99 in placenta had T3 levels 1.50 times those with the lowest concentration of BDE-99 (95% CI: 1.10, 2.04). Additionally, all BFR analyte concentrations were higher in the placenta of males versus females and they were significantly higher for 2,4,6-TBP and BDE-209. 3,3’-T2 SULT activity was significantly higher in female placenta tissues, while type 3 DI activity was significantly higher in male placenta tissues. This research is the first to show sex-specific differences in the bioaccumulation of BFRs in human placenta tissue, as well as differences in TH concentrations and endogenous DI and SULT activity. The underlying mechanisms of these observed sex differences warrant further investigation.

In the third aim of this dissertation research, the effects of BFRs were examined in a human choriocarcinoma placenta cell line, BeWo. Michaelis-Menten parameters and inhibition curves were calculated for 2,4,6-TBP, 3-OH BDE-47, and 6-OH BDE-47. 2,4,6-TBP was shown to be the most potent inhibitor of 3,3’-T2 SULT activity with a calculated IC50 value of 11.6 nM. It was also shown that 2,4,6-TBP and 3-OH BDE-47 exhibit mixed inhibition of 3,3’-T2 sulfation in BeWo cell homogenates. Next, a series of cell culture exposure experiments were performed using 1, 6, 12, and 24 hour exposure durations. Once again, 2,4,6-TBP was shown to be the most potent inhibitor of basal 3,3’-T2 SULT activity by significantly decreasing activity at the high and medium dose (1 M and 0.5 M, respectively) at all measured time points. Interestingly, BDE-99 was also shown to inhibit basal 3,3’-T2 SULT activity in BeWo cells following the 24 hour exposure, despite exhibiting no inhibitory effects in the BeWo cell homogenate experiments. This indicates that BDE-99 must act through a pathway other than direct enzyme inhibition. Following exposures, the TH concentrations in the cell culture growth media and mRNA expression of TH-related genes were also examined. There was no observed effect of BFR treatment on these endpoints. Future work should focus on determining the downstream biological effects of TH SULT disruption in placental cells, as well as the underlying mechanisms of action responsible for reductions in basal TH SULT activity following BFR exposure.

This was one of the first studies to measure BFRs in a cohort of placenta tissue samples from the United States and the first study to measure THs, DI activity, and SULT activity in human placenta tissues. This research provides a novel contribution to our growing understanding of the effects of BFRs on TH homeostasis within the human placenta, and provides further evidence for sex-specific differences within this important organ. Future research should continue to investigate the effects of environmental contaminants on TH homeostasis within the placenta, as this represents the most critical and vulnerable stage of human development.

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Human Exonuclease 1 (Exo1) plays important roles in numerous DNA metabolic/repair pathways including DNA mismatch repair, DNA double strand break repair, Okazaki fragment maturation etc. The nuclease activity of Exo1 is tightly regulated in vivo. The regulation of Exo1 in different pathways is achieved by interactions with different protein partners. The focus of this dissertation will be on characterization of Exo1 interactions with traditional protein partners and providing experimental evidences for new Exo1 interactions.

Molecular cloning, biochemical assays, collaborative nuclear magnetic resonance and X-ray crystallography have been employed to study Exo1 interactions with protein partners. This work contains: (i) the experimental evidence for new Exo1 interactions, and (ii) the detailed characterization of Exo1 interactions with PCNA, MLH1 and MutSα/β.

Taken together, the research progress presented in this dissertation further advances our understanding of traditional Exo1 interaction network and probably provides new insights to new functions and new regulations of Exo1.

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I distinguish two ways that philosophers have approached and explained the reality and status of human social institutions. I call these approaches “naturalist” and “post-naturalist”. Common to both approaches is an understanding that the status of mind and its relation to the world or “nature” has implications on a conception of the status of institutional reality. Naturalists hold that mind is explicable within a scientific frame that conceives of mind as a fundamentally material process. By proxy, social reality is also materially explicable. Post-naturalists critique this view, holding instead that naturalism is parasitic on contemporary science—it therefore is non-compulsory and distorts how we ought to understand mind and social reality. A comparison of naturalism and post-naturalism will comprise the content of the first chapter. The second chapter turns to tracing out the dimensions of a post-naturalist narrative of mind and social reality. Post-naturalists conceive of mind and its activity of thought as sui generis, and it transpires from this that social institutions are better understood as a rational mind’s mode of the expression in the world. Post-naturalism conceives of social reality as a necessary dimension of thought. Thought requires a second person and thereby a tradition or context of norms that come to both structure its expression and become the products of expression. This is in contrast to the idea that social reality is a production of minds, and thereby derivative. Social reality, self-conscious thought, and thought of the second person are therefore three dimensions of a greater unity.