Identification of the E3 Ligase that Directs the Degradation of Proteins that Control Cell Fate Decisions in Yeast

The ubiquitin–proteasome system (UPS) and autophagy pathways are distinct, highly conserved proteolytic systems that play important roles in maintaining cellular homeostasis in response to environmental cues [1]. The goal of this project is to identify the E3 ligase that mediates the degradation of cyclin C following nitrogen starvation in yeast using quantitative Western blot analysis of cyclin C-myc following nitrogen starvation in mutants of known Ubc4/5 interacting E3 ligases. No potential E3 ligases were identified as stable after 4 hours of nitrogen starvation, suggesting redundancy in function

Getting at the Moral Leadership of Education Deans

Vignettes were used to prompt four education deans to think aloud about ways in which they would resolve problems with embedded moral issues. Thematic coding was used to analyze the interview texts that had been tape recorded and transcribed. There was general support for the two moral themes of holding to broad social ideals and negotiating for mutually acceptable outcomes, but individual expressions of specific strategies and actions differed. The results of this study support a multi-dimensional approach to the study of the leadership of deans that simultaneously examines the moral, social, intellectual and emotional aspects of problem solving. The results also suggest a possible shift in the way to advertise and interview for education deans. The advertisement should ask prospective candidates to discuss their list of accomplishments in relation to personal leadership characteristics. The interview should include an administrative colloquium on the order of the pedagogical colloquium suggested by Shulman (1993)

Archeological 3D Mapping: The Structure from Motion Revolution

Mapping is a critical aspect of systematic documentation no matter where archaeologists work. From hand-drawn maps of excavation units to maps created with Total Data Stations or LiDAR scanning, today’s archaeologists have a suite of mapping techniques and technologies to choose from when documenting a site. Typically, spectacular sites often receive high resolution mapping, whereas everyday sites rarely do. Recently, however, a revolutionary technology and technique has been created that can produce highly accurate and precise three-dimensional maps and orthophotos of archaeological sites, features, and profiles at a fraction of the cost and time of LiDAR and intensive TDS mapping: Structure from Motion (SfM). SfM is a new digital photography processing technique for capturing highly detailed, three-dimensional (3D) data from almost any surface using digital cameras. This article introduces the various platforms SfM photographs can be collected from (UAV, kites, balloons, poles, and groundbased) and provides examples of different types of data SfM can provide. The Structure from Motion Revolution is unfolding across the globe at a rapid pace, and we encourage archaeologists to take advantage of this new recording method

Snf1 Dependent Destruction of Med13 is Required for Programmed Cell Death Following Oxidative Stress in Yeast

All eukaryotic cells, when faced with unfavorable environmental conditions, have to decide whether to mount a survival or cell death response. The conserved cyclin C and its kinase partner Cdk8 play a key role in this decision. Both are members of the Cdk8 kinase module that, along with Med12 and Med13, associate with the core mediator complex of RNA polymerase II. In S. cerevisiae, oxidative stress triggers Med13 destruction1, which thereafter releases cyclin Ci nto the cytoplasm. Cytoplasmic cyclin C associates with mitochondria where it induces hyper-fragmentation and programmed cell death2. This suggests a model in which oxidative stress mediated destruction o fMed13 represents a key molecular switch which commits the cell to programmed cell death. Thus it is important to decipher the precise molecular mechanisms that control Med13 destruction following exposure to oxidative stress

Assessing the effect of a treatment when subjects are growing at different rates

The analysis of covariance is often used in the context of premeasure/postmeasure designs to compare treatment and control groups in both randomized [1] and nonrandomized [2] studies. The intent is to adjust the difference between the changes in the 2 groups for any difference which might exist at baseline, i.e., for any difference between the premeasures in the 2 groups. An important assumption underlying the use of the analysis of covariance is that the slopes of the lines for the regression of the postmeasure on the premeasure in the 2 groups are equal. In this paper we describe a program which can be used to test the hypothesis of equal slopes; and performs an alternative analysis which does not depend on this assumption. This is done in the context of comparing treatment and control groups with respect to a measurement subject to natural maturation as in [3]. Equal slopes in this context means equal growth rates; unequal slopes implies that the 2 groups are growing at different rates. The method, known as the Johnson-Neyman procedure [4] is, however, more general than this, and can be used in any two-sample comparison where an alternative to the usual analysis of covariance is deemed appropriate. The procedure identifies a `region of significance' which is especially useful in practice. This region consists of a set of values of the premeasure for which the treatment and the control groups are significantly different with respect to the postmeasure.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/31282/1/0000188.pd

The Role of MAPK and SCF in the Destruction of Med13 in Cyclin C Mediated Cell Death

In response to stress, the yeast1 and mammalian2 cyclin C translocate from the nucleus to the cytoplasm, where it associates with the GTPase Drp1/Dnm1 to drive mitochondrial fragmentation and apoptosis. Therefore, the decision to release cyclin C represents a key life or death decision. In unstressed cells, the cyclin C‐Cdk8 kinase regulates transcription by associating with the Mediator of RNA polymerase II. We previously reported that the Mediator component Med13 anchors cyclin C in the nucleus3. Loss of Med13 function leads to constitutive cytoplasmic localization of cyclin C, resulting in fragmented mitochondria, hypersensitivity to stress and mitochondrial dysfunction due to loss of mtDNA. Recently we showed that this molecular switch operates in a two-step process

ANCOVA for nonparallel slopes: the Johnson-Neyman technique

The Johnson-Neyman (JN) procedure, as originally formulated (Stat Res Mem, 1 (1936) 57-93), applies to a situation in which measurements on 1 dependent (response) variable, X, and 2 independent (predictor) variables, Z1 and Z2, are available for the members of 2 groups. The expected value of X is assumed to be a linear function of Z1 and Z2, but not necessarily the same function for both groups. The JN technique is used to obtain a set of values for the Z variables for which one would reject, at a specified level of significance [alpha] (e.g., [alpha] = 0.05), the hypothesis that the 2 groups have the same expected X values. This set of values, or `region of significance,' may then be plotted to obtain a convenient description of those values of Z1 and Z2 for which the 2 groups differ. The technique can thus be described as a generalization of the analysis of covariance (ANCOVA) which does not make the assumption that the regression coefficients for the regression of X on the covariates, Z1 and Z2, are equal in the groups being compared. In this paper we describe, illustrate and make available a menu-driven PC program (TXJN2) implementing the JN procedure.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/31210/1/0000112.pd

Regression imputation of missing values in longitudinal data sets

A stand-alone, menu-driven PC program, written in GAUSS, which can be used to estimate missing observations in longitudinal data sets is described and made available to interested readers. The program is limited to the situation in which we have complete data on N cases at each of the planned times of measurement t1, t2,..., tT; and we wish to use this information, together with the non-missing values for n additional cases, to estimate the missing values for those cases. The augmented data matrix may be saved in an ASCII file and subsequently imported into programs requiring complete data. The use of the program is illustrated. Ten percent of the observations in a data set consisting of mandibular ramus height measurements for N = 12 young male rhesus monkeys measured at T = 5 time points are randomly discarded. The augmented data matrix is used to determine the lowest degree polynomial adequate to fit the average growth curve (AGC); the regression coefficients are estimated and confidence intervals for them are determined; and confidence bands for the AGC are constructed. The results are compared with those obtained when the original complete data set is used.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/30933/1/0000603.pd

A PC program for classification into one of several groups on the basis of longitudinal data

A stand-alone, menu-driven PC program, ZCLASS, written in GAUSS386i, for classifying subjects into one of several distinct, existing groups on the basis of longitudinal data is described, illustrated, and made available to interested readers. The program accepts data from studies where common times of measurement are planned, but missing data are accommodated in that one or more measurement sequences may be incomplete.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/31477/1/0000399.pd

Clustering on the basis of longitudinal data

A menu-drive PC program, ZDIST, for computing the distances between the estimated polynomial growth curves of subjects who have been followed longitudinally is described, illustrated, and made available to interested readers. These distances can be computed on the basis of the individual growth curves themselves and/or from estimates of individuals' growth velocity and acceleration curves. The resulting distance matrices can be saved in ASCII format and subsequently imported into any clustering program which accepts this type of input, e.g. SYSTAT.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/30607/1/0000244.pd