Investigations of stress responses in Saccharomyces cerevisiae: Transcriptional control and heat shock protein function

The baker's yeast, Saccharomyces cerevisiae responds to the cytotoxic effects of elevated temperature (37-42°C) by activating transcription of ∼150 genes, termed heat shock genes, collectively required to compensate for the abundance of misfolded and aggregated proteins and various physiological modifications necessary for the cell to survive and grow at heat shock temperatures. An intriguing facet of the yeast heat shock response is the remarkable similarity it shares with the global remodeling that occurs in mammalian cells in response to numerous pathophysiological conditions including cancer and cardiovascular disease and thus provides an ideal model system. I have therefore investigated several novel features of stress signaling, transcriptional regulation, and physiology. Initial work focused on the characterization of SYM1, a novel heat shock gene in yeast which was demonstrated to be required for growth on the nonfermentable carbon source ethanol at elevated temperature, and to be the functional ortholog of the mammalian kidney disease gene, Mpv17. Additional work addressed the role of two proteins, the Akt-related kinase, Sch9, and Sse1, the yeast Hsp110 protein chaperone homolog, in signaling by protein kinase A, establishing Sse1 as a critical negative regulator of this pathway. Furthermore, I have demonstrated a role for Sse1 in biogenesis and stability of the stress-response transcription factor, Msn2; a finding that has been extended to include a select subset of additional high molecular weight proteins, suggesting a more global role for this chaperone in stabilizing the cellular proteome. The final emphasis of my doctoral work has included the finding that celastrol, a compound isolated from the plant family Celasfraceae, a component of traditional Chinese herbal medicine, can activate heat shock transcription factor (Hsf1) in yeast and mammalian cells through an oxidative stress mechanism. Celastrol treatment simultaneously activates both heat shock and oxidative stress response pathways, resulting in increased cytoprotection. ^

Identification and analysis of novel mitotic inhibitors of the Caenorhabditis elegans Aurora B kinase

Proper execution of mitosis requires the accurate segregation of replicated DNA into each daughter cell. The highly conserved mitotic kinase AIR-2/Aurora B is a dynamic protein that interacts with subsets of cofactors and substrates to coordinate chromosome segregation and cytokinesis in Caenorhabdiris elegans. To identify components of the AIR-2 regulatory pathway, a genome-wide RNAi-based screen for suppressors of air-2 temperature-sensitive mutant lethality was conducted. Here, I present evidence that two classes of suppressors identified in this screen are bona fide regulators of the AIR-2 kinase. The strongest suppressor cdc-48.3, encodes an Afg2/Spaf-related Cdc48-like AAA+ ATPase that regulates AIR-2 kinase activity and stability during C. elegans embryogenesis. Loss of CDC-48.3 suppresses the lethality of air-2 mutant embryos, marked by the restoration of the dynamic behavior of AIR-2 and rescue of chromosome segregation and cytokinesis defects. Loss of CDC-48.3 leads to mitotic delays and abnormal accumulation of AIR-2 during late telophase/mitotic exit. In addition, AIR-2 kinase activity is significantly upregulated from metaphase through mitotic exit in CDC-48.3 depleted embryos. Inhibition of the AIR-2 kinase is dependent on (1) a direct physical interaction between CDC-48.3 and AIR-2, and (2) CDC-48.3 ATPase activity. Importantly, the increase in AIR-2 kinase activity does not correlate with the stabilization of AIR-2 in late mitosis. Hence, CDC-48.3 is a bi-functional inhibitor of AIR-2 that is likely to act via distinct mechanisms. The second class of suppressors consists of psy-2/smk-1 and pph-4.1, which encode two components of the conserved PP4 phosphatase complex that is essential for spindle assembly, chromosome segregation, and overall mitotic progression. AIR-2 and its substrates are likely to be targets of this complex since mitotic AIR-2 kinase activity is significantly increased during mitosis when either PSY-2/SMK-1 or PPH-4.l is depleted. Altogether, this study demonstrates that during the C. elegans embryonic cell cycle, regulators including the CDC-48.3 ATPase and PP4 phosphatase complex interact with and control the kinase activity, targeting behavior and protein stability of the Aurora B kinase to ensure accurate and timely progression of mitosis. ^

The association of internet use and depression among spinal cord injury population

The purpose of this study was to exam the relationship between internet use and depression among a population of individuals who have sustained spinal cord injury. This was cross-sectional survey design conducted among spinal cord injury (SCI) patients in the Model Spinal Cord Injury System. We included a total of 1,011 SCI-patients who were interviewed face-to-face or by telephone interview over approximately a three year time period (2004–2006). All data were collected through a telephone survey which included the Patient Health Questionnaire-9 (PHQ-9) to assess depression. We examined various scales of this survey, included a reduced 3-item scale (items 1, 2 and 6) to avoid the presence of somatic symptoms among SCI patients from influencing classification of depression. The frequency of internet usage was grouped as daily/weekly/monthly/non user. Covariates examined as possible confounders included demographic characteristics, occupational status, educational level, injury type, daily function of living, pain level, self-perceived health status and satisfaction with life. We observed a negative association between the frequency of internet use and the level of depression. Daily use of internet was associated with lower PHQ-9 score and depression; however this association did not reach statistical significance after for the mentioned covariates. In conclusion, the factors related to lower depression in SCI patients who use the internet are complicated. Daily internet usage was associated with lower levels of depression. The accuracy of 3-item scale needs further validation and investigation. Further study of internet usage pattern in SCI patient is recommended. ^

Radiomics of NSCLC: Quantitative CT Image Feature Characterization and Tumor Shrinkage Prediction

Radiomics is the high-throughput extraction and analysis of quantitative image features. For non-small cell lung cancer (NSCLC) patients, radiomics can be applied to standard of care computed tomography (CT) images to improve tumor diagnosis, staging, and response assessment. The first objective of this work was to show that CT image features extracted from pre-treatment NSCLC tumors could be used to predict tumor shrinkage in response to therapy. This is important since tumor shrinkage is an important cancer treatment endpoint that is correlated with probability of disease progression and overall survival. Accurate prediction of tumor shrinkage could also lead to individually customized treatment plans. To accomplish this objective, 64 stage NSCLC patients with similar treatments were all imaged using the same CT scanner and protocol. Quantitative image features were extracted and principal component regression with simulated annealing subset selection was used to predict shrinkage. Cross validation and permutation tests were used to validate the results. The optimal model gave a strong correlation between the observed and predicted shrinkages with . The second objective of this work was to identify sets of NSCLC CT image features that are reproducible, non-redundant, and informative across multiple machines. Feature sets with these qualities are needed for NSCLC radiomics models to be robust to machine variation and spurious correlation. To accomplish this objective, test-retest CT image pairs were obtained from 56 NSCLC patients imaged on three CT machines from two institutions. For each machine, quantitative image features with concordance correlation coefficient values greater than 0.90 were considered reproducible. Multi-machine reproducible feature sets were created by taking the intersection of individual machine reproducible feature sets. Redundant features were removed through hierarchical clustering. The findings showed that image feature reproducibility and redundancy depended on both the CT machine and the CT image type (average cine 4D-CT imaging vs. end-exhale cine 4D-CT imaging vs. helical inspiratory breath-hold 3D CT). For each image type, a set of cross-machine reproducible, non-redundant, and informative image features was identified. Compared to end-exhale 4D-CT and breath-hold 3D-CT, average 4D-CT derived image features showed superior multi-machine reproducibility and are the best candidates for clinical correlation.

Comparison of machine learning approaches and statistical methods for estimation of airborne chemical exposures

Accurate quantitative estimation of exposure using retrospective data has been one of the most challenging tasks in the exposure assessment field. To improve these estimates, some models have been developed using published exposure databases with their corresponding exposure determinants. These models are designed to be applied to reported exposure determinants obtained from study subjects or exposure levels assigned by an industrial hygienist, so quantitative exposure estimates can be obtained. ^ In an effort to improve the prediction accuracy and generalizability of these models, and taking into account that the limitations encountered in previous studies might be due to limitations in the applicability of traditional statistical methods and concepts, the use of computer science- derived data analysis methods, predominantly machine learning approaches, were proposed and explored in this study. ^ The goal of this study was to develop a set of models using decision trees/ensemble and neural networks methods to predict occupational outcomes based on literature-derived databases, and compare, using cross-validation and data splitting techniques, the resulting prediction capacity to that of traditional regression models. Two cases were addressed: the categorical case, where the exposure level was measured as an exposure rating following the American Industrial Hygiene Association guidelines and the continuous case, where the result of the exposure is expressed as a concentration value. Previously developed literature-based exposure databases for 1,1,1 trichloroethane, methylene dichloride and, trichloroethylene were used. ^ When compared to regression estimations, results showed better accuracy of decision trees/ensemble techniques for the categorical case while neural networks were better for estimation of continuous exposure values. Overrepresentation of classes and overfitting were the main causes for poor neural network performance and accuracy. Estimations based on literature-based databases using machine learning techniques might provide an advantage when they are applied to other methodologies that combine `expert inputs' with current exposure measurements, like the Bayesian Decision Analysis tool. The use of machine learning techniques to more accurately estimate exposures from literature-based exposure databases might represent the starting point for the independence from the expert judgment.^

Grain-size analysis and geochemistry of sediment core GeoB13602-1

Grain-size, terrigenous element and rock magnetic remanence data of Quaternary marine sediments retrieved at the NW African continental margin off Gambia (gravity core GeoB 13602-1, 13°32.71' N, 17°50.96'W) were jointly analyzed by end-member (EM) unmixing methods to distinguish and budget past terrigenous fluxes. We compare and cross-validate the identified single-parameter EM systems and develop a numerical strategy to calculate associated multi-parameter EM properties. One aeolian and two fluvial EMs were found. The aeolian EM is much coarser than the fluvial EMs and is associated with a lower goethite/hematite ratio, a higher relative concentration of magnetite and lower Al/Si and Fe/K ratios. Accumulation rates and grain sizes of the fluvial sediment appear to be primarily constrained by shore distance (i.e., sea-level fluctuations) and to a lesser extent by changes in hinterland precipitation. High dust fluxes occurred during the Last Glacial Maximum (LGM) and during Heinrich Stadials (HS) while the fluvial input remained unchanged. Our approach reveals that the LGM dust fluxes were ~7 times higher than today's. However, by far the highest dust accumulation occurred during HS 1 (~300 g m**-2 yr** -1), when dust fluxes were ~80 fold higher than today. Such numbers have not yet been reported for NW Africa, and emphasize strikingly different environmental conditions during HSs. They suggest that deflation rate and areal extent of HSs dust sources were much larger due to retreating vegetation covers. Beyond its regional and temporal scope, this study develops new, in principle, generally applicable strategies for multi-method end-member interpretation, validation and flux budgeting calibration.

Physical, chemical and biological characteristics of disturbed and undisturbed Arctic lakes, Northwest Territories

1. Global warming is predicted to cause changes in permafrost cover and stability in the Arctic. Zones of high ion concentration in regions of ice-rich permafrost are a reservoir of chemicals that can potentially be transferred to fresh waters during thawing. Consequently, input of enriched runoff from the thaw and sediment and vegetation from the landscape could alter lakes by affecting their geochemistry and biological production. 2. Three undisturbed lakes and five lakes disturbed by retrogressive permafrost thaw slumps were sampled during late summer of 2006 to assess the potential effects of thermokarst shoreline slumping on water and sediment chemistry, the underwater light regime, and benthic macrophyte biomass and community structure. 3. Undisturbed lakes had sediments rich in organic material and selected micronutrients, while disturbed lakes had sediments richer in calcium, magnesium and strontium, greater transparency of the water column, and a well-developed submerged macrophyte community. 4. It is postulated that enriched runoff chemistry may alter nutrient availability at the sediment-water interface and also the degradation of organic material, thus affecting lake transparency and submerged macrophytes. The results suggest that retrogressive permafrost slumping can significantly affect food webs in arctic tundra lakes through an increase in macrophyte biomass and development of a more complex benthic habitat.

Methanol and ethanol analysis in marine sediment pore water

Low-molecular-weight (LMW) alcohols are produced during the microbial degradation of organic matter from precursors such as lignin, pectin, and carbohydrates. The biogeochemical behavior of these alcohols in marine sediment is poorly constrained but potentially central to carbon cycling. Little is known about LMW alcohols in sediment pore waters because of their low concentrations and high water miscibility, both of which pose substantial analytical challenges. In this study, three alternative methods were adapted for the analysis of trace amounts of methanol and ethanol in small volumes of saline pore waters: direct aqueous injection (DAI), solid-phase microextraction (SPME), and purge and trap (P&T) in combination with gas chromatography (GC) coupled to either a flame ionization detector (FID) or a mass spectrometer (MS). Key modifications included the desalination of samples prior to DAI, the use of a threaded midget bubbler to purge small-volume samples under heated conditions and the addition of salt during P&T. All three methods were validated for LMW alcohol analysis, and the lowest detection limit (60 nM and 40 nM for methanol and ethanol, respectively) was achieved with the P&T technique. With these methods, ambient concentrations of volatile alcohols were determined for the first time in marine sediment pore waters of the Black Sea and the Gulf of Mexico. A strong correlation between the two compounds was observed and tentatively interpreted as being controlled by similar sources and sinks at the examined stations.

Documentation, profile descriptions and analytical results of loes profiles from Bavaria, southern Germany

This study investigates the landscape evolution and soil development in the loess area near Regensburg between approximately 6000-2000 yr BP (radiocarbon years), Eastern Bavaria. The focus is on the question how man and climate influenced landscape evolution and what their relative significance was. The theoretical background concerning the factors that controlled prehistoric soil erosion in Middle Europe is summarized with respect to rainfall intensity and distribution, pedogenesis, Pleistocene relief, and prehistoric farming. Colluvial deposits , flood loams, and soils were studied at ten different and representative sites that served as archives of their respective palaeoenvironments. Geomorphological, sedimentological, and pedological methods were applied. According to the findings presented here, there was a high asynchronity of landscape evolution in the investigation area, which was due to prehistoric land-use patterns. Prehistoric land use and settlement caused highly difIerenciated phases of morphodynamic activity and stability in time and space. These are documented at the single catenas ofeach site. In general, Pleistocene relief was substantially lowered. At the same time smaller landforms such as dells and minor asymmetric valleys filled up and strongly transformed. However, there were short phases at many sites, forming short lived linear erosion features ('Runsen'), resulting from exceptional rainfalls. These forms are results of single events without showing regional trends. Generally, the onset of the sedimentation of colluvial deposits took place much earlier (usually 3500 yr BP (radiocarbon) and younger) than the formation of flood loams. Thus, the deposition of flood loams in the Kleine Laaber river valley started mainly as a consequence of iron age farming only at around 2500 yr BP (radiocarbon). A cascade system explains the different ages of colluvial deposits and flood loams: as a result of prehistoric land use, dells and other minor Pleistocene landforms were filled with colluvial sediments. After the filling of these primary sediment traps , eroded material was transported into flood plains, thus forming flood loams. But at the moment we cannot quantify the extent ofprehistoric soil erosion in the investigation area. The three factors that controlled the prehistoric Iandscapc evolution in the Ioess area near Regensburg are as follows: 1. The transformation from a natural to a prehistoric cultural landscape was the most important factor: A landscape with stable relief was changed into a highly morphodynamic one with soil erosion as the dominant process of this change. 2. The sediment traps of the pre-anthropogenic relief determined where the material originated from soil erosion was deposited: either sedimentation took place on the slopes or the filled sediment traps of the slopes rendered flood loam formation possible. Climatic influence of any importance can only be documented as the result of land use in connection with singular and/or statistic events of heavy rainfalls. Without human impact, no significant change in the Holocene landscape would have been possible.

Global LAI uncertainty and relative uncertainty datasets derived from a Triple Collocation Error Model (TCEM)

Uncertainty information for global leaf area index (LAI) products is important for global modeling studies but usually difficult to systematically obtain at a global scale. Here, we present a new method that cross-validates existing global LAI products and produces consistent uncertainty information. The method is based on a triple collocation error model (TCEM) that assumes errors among LAI products are not correlated. Global monthly absolute and relative uncertainties, in 0.05° spatial resolutions, were generated for MODIS, CYCLOPES, and GLOBCARBON LAI products, with reasonable agreement in terms of spatial patterns and biome types. CYCLOPES shows the lowest absolute and relative uncertainties, followed by GLOBCARBON and MODIS. Grasses, crops, shrubs, and savannas usually have lower uncertainties than forests in association with the relatively larger forest LAI. With their densely vegetated canopies, tropical regions exhibit the highest absolute uncertainties but the lowest relative uncertainties, the latter of which tend to increase with higher latitudes. The estimated uncertainties of CYCLOPES generally meet the quality requirements (± 0.5) proposed by the Global Climate Observing System (GCOS), whereas for MODIS and GLOBCARBON only non-forest biome types have met the requirement. Nevertheless, none of the products seems to be within a relative uncertainty requirements of 20%. Further independent validation and comparative studies are expected to provide a fair assessment of uncertainties derived from TCEM. Overall, the proposed TCEM is straightforward and could be automated for the systematic processing of real time remote sensing observations to provide theoretical uncertainty information for a wider range of land products.

Measurement of the muon beam direction and muon flux for the T2K neutrino experiment

The Tokai-to-Kamioka (T2K) neutrino experiment measures neutrino oscillations by using an almost pure muon neutrino beam produced at the J-PARC accelerator facility. The T2K muon monitor was installed to measure the direction and stability of the muon beam which is produced together with the muon neutrino beam. The systematic error in the muon beam direction measurement was estimated, using data and MC simulation, to be 0.28 mrad. During beam operation, the proton beam has been controlled using measurements from the muon monitor and the direction of the neutrino beam has been tuned to within 0.3 mrad with respect to the designed beam-axis. In order to understand the muon beam properties, measurement of the absolute muon yield at the muon monitor was conducted with an emulsion detector. The number of muon tracks was measured to be (4.06 ± 0.05) × 10⁴ cm⁻² normalized with 4 × 10¹¹protons on target with 250 kA horn operation. The result is in agreement with the prediction which is corrected based on hadron production data.

Agglomeration and directional imbalance of freight rates : the role of density economies in the transport sector

This paper examines the conventional assumption that bilateral transport costs are symmetric. We develop an economic geography model with transport sector in which asymmetric freight rates can occur as a result of density economies. Comparing this to models without density economies, we show that agglomeration of economic activities is more likely to emerge and that multiple equilibria can emerge for some parameters. Then we show the change in its bifurcation and stability of equilibrium and conclude that economies of density in transport flows can act as an agglomeration force.

Integrated program debugging, verification, and optimization using abstract interpretation (and the Ciao system preprocessor)

The technique of Abstract Interpretation has allowed the development of very sophisticated global program analyses which are at the same time provably correct and practical. We present in a tutorial fashion a novel program development framework which uses abstract interpretation as a fundamental tool. The framework uses modular, incremental abstract interpretation to obtain information about the program. This information is used to validate programs, to detect bugs with respect to partial specifications written using assertions (in the program itself and/or in system libraries), to generate and simplify run-time tests, and to perform high-level program transformations such as multiple abstract specialization, parallelization, and resource usage control, all in a provably correct way. In the case of validation and debugging, the assertions can refer to a variety of program points such as procedure entry, procedure exit, points within procedures, or global computations. The system can reason with much richer information than, for example, traditional types. This includes data structure shape (including pointer sharing), bounds on data structure sizes, and other operational variable instantiation properties, as well as procedure-level properties such as determinacy, termination, nonfailure, and bounds on resource consumption (time or space cost). CiaoPP, the preprocessor of the Ciao multi-paradigm programming system, which implements the described functionality, will be used to illustrate the fundamental ideas.

Program development using abstract interpretation (and the ciao system preprocessor)

The technique of Abstract Interpretation has allowed the development of very sophisticated global program analyses which are at the same time provably correct and practical. We present in a tutorial fashion a novel program development framework which uses abstract interpretation as a fundamental tool. The framework uses modular, incremental abstract interpretation to obtain information about the program. This information is used to validate programs, to detect bugs with respect to partial specifications written using assertions (in the program itself and/or in system librarles), to genérate and simplify run-time tests, and to perform high-level program transformations such as múltiple abstract specialization, parallelization, and resource usage control, all in a provably correct way. In the case of validation and debugging, the assertions can refer to a variety of program points such as procedure entry, procedure exit, points within procedures, or global computations. The system can reason with much richer information than, for example, traditional types. This includes data structure shape (including pointer sharing), bounds on data structure sizes, and other operational variable instantiation properties, as well as procedure-level properties such as determinacy, termination, non-failure, and bounds on resource consumption (time or space cost). CiaoPP, the preprocessor of the Ciao multi-paradigm programming system, which implements the described functionality, will be used to illustrate the fundamental ideas.

A tutorial on program development and optimization using the Ciao preprocessor

We present in a tutorial fashion CiaoPP, the preprocessor of the Ciao multi-paradigm programming system, which implements a novel program development framework which uses abstract interpretation as a fundamental tool. The framework uses modular, incremental abstract interpretation to obtain information about the program. This information is used to validate programs, to detect bugs with respect to partial specifications written using assertions (in the program itself and/or in system libraries), to generate and simplify run-time tests, and to perform high-level program transformations such as multiple abstract specialization, parallelization, and resource usage control, all in a provably correct way. In the case of validation and debugging, the assertions can refer to a variety of program points such as procedure entry, procedure exit, points within procedures, or global computations. The system can reason with much richer information than, for example, traditional types. This includes data structure shape (including pointer sharing), bounds on data structure sizes, and other operational variable instantiation properties, as well as procedure-level properties such as determinacy, termination, non-failure, and bounds on resource consumption (time or space cost).