CaM Kinase Kinase Control of Prostate Cancer Cell Survival

Abstract AKT has been implicated in promoting cell survival within certain cells. Current research has shown that hormones that increase the concentration of intracellular calcium can activate AKT that in turn leads to cancer cell survival. Interestingly, LNCaP cells express the M3-subtype of GPCR\u27s that may couple to increases in intracellular calcium and activation of the Ca2+/Calmodulin-dependent Protein Kinases (CaM Ks). Specifically CaM Kinase Kinase (CaM KK) phosphorylates its direct substrates CaM Kinase I, CaM Kinase IV, and AKT. AKT promotes cell survival through phosphorylation of its target BAD that prevents caspase activation. Our goals were to examine the mechanism of carbachol activation of AKT and BAD in LNCaP prostate cancer cells and evaluate whether CaM Ks may be mediating carbachol\u27s activation of AKT and cell survival. The results suggest that both AKT and BAD were phosphorylated in response to a five-minute stimulation with carbachol in LNCaP cells. AKT and BAD phosphorylation were blocked by the selective CaM KK inhibitor, STO-609, suggesting the involvement of CaM KK in the pathway. In addition, BAD phosphorylation was also blocked by treating cells with the AKT inhibitor, AKT-X. Finally, our results suggest that carbachol treatment of LNCaP cells promoted cell survival through CaM KK, AKT, and the anti-apoptotic protein, BAD

Mitigating Cotton Revenue Risk Through Irrigation, Insurance, and Hedging

This study focuses on managing cotton production and marketing risks using combinations of irrigation levels, put options (as price insurance), and crop insurance. Stochastic cotton yields and prices are used to simulate a whole-farm financial statement for a 1,000 acre furrow irrigated cotton farm in the Texas Lower Rio Grande Valley under 16 combinations of risk management strategies. Analyses for risk-averse decision makers indicate that multiple irrigations are preferred. The benefits to purchasing put options increase with yields, as they are more beneficial when higher yields are expected from applying more irrigation applications. Crop insurance is strongly preferred at lower irrigation levels.cotton, crop insurance, irrigation, options, puts, risk, simulation, stochastic efficiency with respect to a function, Farm Management, Risk and Uncertainty, D81, Q12, Q15,

A Practical Model of Student Engagement While Programming

We consider the question of how to predict whether a student is on or off task while working on a computer programming assignment using elapsed time since the last keystroke as the single independent variable. In this paper we report results of an empirical study in which we intermittently prompted CS1 students working on a programming assignment to self-report whether they were engaged in the assignment at that moment. Our regression model derived from the results of the study shows power-law decay in the engagement rate of students with increasing time of keyboard inactivity ranging from a nearly 80% engagement rate after 45 seconds to 30% after 32 minutes of inactivity. We find that students remain engaged in programming for a median of about 8 minutes before going off task, and when they do go off task, they most often return after 1 to 4 minutes of disengagement. Our model has application in estimating the amount of engaged time students take to complete programming assignments, identifying students in need of intervention, and understanding the effects of different engagement behaviors

Plagiarism Deterrence in CS1 Through Keystroke Data

Recent work in computing education has explored the idea of analyzing and grading using the process of writing a computer program rather than just the final submitted code. We build on this idea by investigating the effect on plagiarism when the process of coding, in the form of keystroke logs, is submitted for grading in addition to the final code. We report results from two terms of a university CS1 course in which students submitted keystroke logs. We find that when students are required to submit a log of keystrokes together with their written code they are less likely to plagiarize. In this paper we explore issues of implementation, adoption, deterrence, anxiety, and privacy. Our keystroke logging software is available in the form of an IDE plugin in a public plugin repository

Accurate Estimation of Time-on-Task While Programming

In a recent study, students were periodically prompted to self-report engagement while working on computer programming assignments in a CS1 course. A regression model predicting time-on-task was proposed. While it was a significant improvement over ad-hoc estimation techniques, the study nevertheless suffered from lack of error analysis, lack of comparison with existing methods, subtle complications in prompting students, and small sample size. In this paper we report results from a study with an increased number of student participants and modified prompting scheme intended to better capture natural student behavior. Furthermore, we perform a cross-validation analysis on our refined regression model and present the resulting error bounds. We compare with threshold approaches and find that, in at least one context, a simple 5-minute threshold of inactivity is a reasonable estimate for whether a student is on-task or not. We show that our approach to modeling student engagement while programming is robust and suitable for identification of students in need of intervention, understanding engagement behavior, and estimating time taken on programming assignments

CaM Kinase Control of AKT and LNCaP Cell Survival

AKT and its substrate BAD have been shown to promote prostate cancer cell survival. Agonists, such as carbachol, and hormones that increase intracellular calcium concentration can activate AKT leading to cancer cell survival. The LNCaP prostate cancer cells express the carbacholsensitive M3-subtype of G protein-coupled receptors that cause increases in intracellular calcium and activate the family of Ca2þ/calmodulindependent protein kinases (CaM Ks). One type of CaM Kinase, CaM Kinase Kinase (CaM KK), phosphorylates several substrates including AKT on threonine 308. AKT phosphorylation and activation enhances cell survival through phosphorylation of BAD protein and the subsequent blockade of caspase activation. Our goals were to examine the mechanism of carbachol activation of AKT and BAD in LNCaP prostate cancer cells and evaluate whether CaM KK may be mediating carbachol’s activation of AKT and cell survival. Our results suggest that carbachol treatment of LNCaP cells promoted cell survival through CaM KK and its phosphorylation of AKT. The bacterial toxin anisomycin triggered caspase-3 activation in LNCaP cells that was blocked by carbachol in a CaM KK- and AKT-dependent manner. AKT and BAD phosphorylation were blocked by the selective CaM KK inhibitor, STO-609, as well as siRNA directed against CaM KK. BAD phosphorylation was also blocked by treating cells with the AKT inhibitor, AKT-X, as well as siRNA to AKT. Additionally, epinephrine promoted LNCaP cell survival through activation of AKT that was insensitive to STO-609. Taken together these data suggest a survival role for CaM KK operating through AKT and BAD in LNCaP prostate cancer cells

Size and Shape Determination of Riprap and Large-sized Aggregates Using Field Imaging

Riprap rock and large-sized aggregates are extensively used in transportation, geotechnical, and hydraulic engineering applications. Traditional methods for assessing riprap categories based on particle weight may involve subjective visual inspection and time-consuming manual measurements. Aggregate imaging and segmentation techniques can efficiently characterize riprap particles for their size and morphological/shape properties to estimate particle weights. Particle size and morphological/shape characterization ensure the reliable and sustainable use of all aggregate skeleton materials at quarry production lines and construction sites. Aggregate imaging systems developed to date for size and shape characterization, however, have primarily focused on measurement of separated or non-overlapping aggregate particles. This research study presents an innovative approach for automated segmentation and morphological analyses of stockpile aggregate images based on deep-learning techniques. As a project outcome, a portable, deployable, and affordable field-imaging system is envisioned to estimate volumes of individual riprap rocks for field evaluation. A state-of-the-art object detection and segmentation framework is used to train an image-segmentation kernel from manually labeled 2D riprap images in order to facilitate automatic and user-independent segmentation of stockpile aggregate images. The segmentation results show good agreement with ground-truth validation, which entailed comparing the manual labeling to the automatically segmented images. A significant improvement to the efficiency of size and morphological analyses conducted on densely stacked and overlapping particle images is achieved. The algorithms are integrated into a software application with a user-friendly Graphical User Interface (GUI) for ease of operation. Based on the findings of this study, this stockpile aggregate image analysis program promises to become an efficient and innovative application for field-scale and in-place evaluations of aggregate materials. The innovative imaging-based system is envisioned to provide convenient, reliable, and sustainable solutions for the on-site quality assurance/quality control (QA/QC) tasks related to riprap rock and large-sized aggregate material characterization and classification.IDOT-R27-182Ope

Community assembly and stability in the root microbiota during early plant development

Little is known about how community composition in the plant microbiome is affected by events in the life of a plant. For example, when the plant is exposed to soil, microbial communities may be an important factor in root community assembly. We conducted two experiments asking whether the composition of the root microbiota in mature plants could be determined by either the timing of root exposure to microbial communities or priority effects by early colonizing microbes. Timing of microbial exposure was manipulated through an inoculation experiment, where plants of different ages were exposed to a common soil inoculum. Priority effects were manipulated by challenging roots with established microbiota with an exogenous microbial community. Results show that even plants with existing microbial root communities were able to acquire new microbial associates, but that timing of soil exposure affected root microbiota composition for both bacterial and fungal communities in mature plants. Plants already colonized were only receptive to colonizers at 1 week post-germination. Our study shows that the timing of soil exposure in the early life stages of a plant is important for the development of the root microbiota in mature plants

Novel reductive-reductive mode electrochemical detection of Rohypnol following liquid chromatography and its determination in coffee

© 2014 Elsevier B.V. Rohypnol (flunitrazepam) has been successfully determined in coffee by high performance liquid chromatography dual electrode detection (LC-DED) in the dual reductive mode. Initial studies were performed to optimise the chromatographic conditions and these were found to be 50% acetonitrile, 50% 50mM pH 2.0 phosphate buffer at a flow rate of 0.75mLmin-1, employing a Hypersil C18, 5μm, 250mm×4.6mm column. Cyclic voltammetric studies were made to ascertain the redox behaviour of Rohypnol at a glassy carbon electrode over the pH range 2-12. Hydrodynamic voltammetry was used to optimise the applied potential at the generator and detector cells; these were identified to be -2.4V and +0.8V for the redox mode and -2.4V and -0.1V for the dual reductive mode respectively. A linear range of 0.5-100μgmL-1, with a detection limit of 20ngmL-1 was obtained for the dual reductive mode. Further studies were then performed to identify the optimum conditions required for the LC-DED determination of Rohypnol in beverage samples. A convenient and rapid method for the determination of Rohypnol in beverage samples was developed using a simple sample pre-treatment procedure. A recovery of 95.5% was achieved for a sample of white coffee fortified at 9.6μgmL-1 Rohypnol

Transcriptomic profiling of 39 commonly-used neuroblastoma cell lines

Neuroblastoma cell lines are an important and cost-effective model used to study oncogenic drivers of the disease. While many of these cell lines have been previously characterized with SNP, methylation, and/or mRNA expression microarrays, there has not been an effort to comprehensively sequence these cell lines. Here, we present raw whole transcriptome data generated by RNA sequencing of 39 commonly-used neuroblastoma cell lines. These data can be used to perform differential expression analysis based on a genetic aberration or phenotype in neuroblastoma (e.g., MYCN amplification status, ALK mutation status, chromosome arm 1p, 11q and/or 17q status, sensitivity to pharmacologic perturbation). Additionally, we designed this experiment to enable structural variant and/or long-noncoding RNA analysis across these cell lines. Finally, as more DNase/ATAC and histone/transcription factor ChIP sequencing is performed in these cell lines, our RNA-Seq data will be an important complement to inform transcriptional targets as well as regulatory (enhancer or repressor) elements in neuroblastoma