Studies of the heat shock response of the yeast Saccharomyces cerevisiae

Heat shock protein HSP90 has recently been found to be one of the major chaperones of eukaryotic cells. Saccharomyces cerevisiae transformants were constructed with 50-150 copies of the homologous heat-inducible gene for HSP90 (HSP82) present on a high copy number episomal vector. These transformants were then used to demonstrate: (i) that this gene, normally single-copy in the haploid yeast genome, displays almost normal basal and heat shock-induced levels of expression even at 50-150 copies per cell; (ii) that yeast is an expression host suitable for high level synthesis of HSP90 protein (to 30-40% of total cell protein); and (iii) that increasing cellular levels of HSP90 is not protective against heat killing, causing strain-dependent reductions in growth at 37.5°C and in thermotolerance. Heat shock protein induction is only one change elicited in yeast by heat shock. Trehalose is also accumulated, while declining intracellular pH stimulates plasma membrane ATPase activity. Recently the trehalose induction was shown to be regulated by levels of HSP70 and, to a lesser extent, HSP104. Another HSP which might contribute to regulation is HSP90, especially as HSP90 forms complexes with heat shock transcription factor and several of the regulatory proteins of eukaryotic cells. This possibility was investigated using isogenic yeast strains with normal, decreased or elevated HSP90. The results show HSP90 levels having a small negative influence over the heat inductions of trehalose and the heat shock element, a minor effect compared with the major regulation exerted by HSP70. Numerous chemicals are inducers of heat shock proteins, but few agents are known that selectively inhibit expression of these proteins. This thesis provides the first evidence that two widely-used food preservatives (sorbate and benzoate) can act as selective inhibitors of heat shock protein induction in S. cerevisiae. Their effects were strongly dependent on the pH of the culture medium. Below pH5.5 sorbate caused a greatly- increased sensitivity to lethal heat treatment, with strong selection for respiratory- deficient rho- petites amongst the surviving cells. In contrast above pH5.5 sorbate acted as a chemical inducer of thermotolerance. In low pH rho+ cultures sorbate, benzoate, the uncoupler carbonyl cyanide m-chlorophenylhydrazone and the plasma membrane ATPase inhibitor diethylstilboestrol were all shown to act as selective inhibitors of heat shock protein and a heat shock element-lacZ fusion induction by heat shock. In low pH cultures the rho- mutation was found to confer a higher resistance to growth in the presence of sorbate, as well as a partial restoration of the heat inducibility of heat shock proteins and of heat shock element-lacZ fusion in sorbate-treated cultures

Random Sampling of Bandlimited Graph Signals from Local Measurements

The random sampling on graph signals is one of the fundamental topics in graph signal processing. In this letter, we consider the random sampling of k-bandlimited signals from the local measurements and show that no more than O(klogk) measurements with replacement are sufficient for the accurate and stable recovery of any k-bandlimited graph signals. We propose two random sampling strategies based on the minimum measurements, i.e., the optimal sampling and the estimated sampling. The geodesic distance between vertices is introduced to design the sampling probability distribution. Numerical experiments are included to show the effectiveness of the proposed methods

A Simulation-free Group Sequential Design with Max-combo Tests in the Presence of Non-proportional Hazards

Non-proportional hazards (NPH) have been observed recently in many immuno-oncology clinical trials. Weighted log-rank tests (WLRT) with suitably chosen weights can be used to improve the power of detecting the difference of the two survival curves in the presence of NPH. However, it is not easy to choose a proper WLRT in practice when both robustness and efficiency are considered. A versatile maxcombo test was proposed to achieve the balance of robustness and efficiency and has received increasing attentions in both methodology development and application. However, survival trials often warrant interim analyses due to its high cost and long duration. The integration and application of maxcombo tests in interim analyses often require extensive simulation studies. In this paper, we propose a simulation-free approach for group sequential design with maxcombo test in survival trials. The simulation results support that the proposed approaches successfully control both the type I error rate and offer great accuracy and flexibility in estimating sample sizes, at the expense of light computation burden. Notably, our methods display a strong robustness towards various model misspecifications, and have been implemented in an R package for free access online

Enhancing Treatment Effect Estimation: A Model Robust Approach Integrating Randomized Experiments and External Controls using the Double Penalty Integration Estimator

Randomized experiments (REs) are the cornerstone for treatment effect evaluation. However, due to practical considerations, REs may encounter difficulty recruiting sufficient patients. External controls (ECs) can supplement REs to boost estimation efficiency. Yet, there may be incomparability between ECs and concurrent controls (CCs), resulting in misleading treatment effect evaluation. We introduce a novel bias function to measure the difference in the outcome mean functions between ECs and CCs. We show that the ANCOVA model augmented by the bias function for ECs renders a consistent estimator of the average treatment effect, regardless of whether or not the ANCOVA model is correct. To accommodate possibly different structures of the ANCOVA model and the bias function, we propose a double penalty integration estimator (DPIE) with different penalization terms for the two functions. With an appropriate choice of penalty parameters, our DPIE ensures consistency, oracle property, and asymptotic normality even in the presence of model misspecification. DPIE is more efficient than the estimator derived from REs alone, validated through theoretical and experimental results

Why Consumers Buy---and Don\u27t Buy---Your Farm Direct Products

In 2003 we conducted a consumer survey to assess direct marketing opportunities and barriers for farmers in the Maine Highlands region (Piscataquis and Penobscot Counties). The survey addressed five direct marketing methods: farm stand, pick-your-own (PYO), tailgate market, home delivery, and farmers’ market. Our questionnaire was designed to determine whether the current outlets of farm products satisfy consumer needs, and to identify potential areas of direct marketing of farm products that can better serve the needs of consumers.https://digitalcommons.library.umaine.edu/extension_ag/1017/thumbnail.jp

Automatic detection of epileptic slow-waves in EEG based on empirical mode decomposition and wavelet transform

Slow-wave is one of the most typical epileptic activities in EEGs and plays an important role in the diagnosis of disorders related to epilepsy in clinic. However artifacts such as blinking resemble slow-waves in shape and confuse slow-wave detection. Thus, differentiating and removing these artifacts are of great importance in slow-wave detection. In this paper, we propose an improved slow-wave detection algorithm based on discrete wavelet transform (DWT) that specially concerns on removal of blinking artifact (BA). EMD that can break down a complicated signal without a basis function such as sine or wavelet functions is used to decompose EEG. Two intrinsic mode functions (IMFs) which have BA’s characteristic are extracted. Then, we compute the similarity between original EEG and the combination of IMFs for identifying BA. Regression method is used to remove influence of BA from all channels. Finally, improved DWT is employed to detect slow-waves. We employ this method to clinical data and results show that the average false detection rate of the improved method is much lower than that of the traditional DWT method