Strategic targeting of the PI3K–NFκB axis in cisplatin-resistant NSCLC

Chemoresistance is a major therapeutic challenge to overcome in NSCLC, in order to improve the current survival rates of <15% at 5 years. We and others have shown increased PI3K signaling in NSCLC to be associated with a more aggressive disease, and a poorer prognosis. In this study, targeted inhibition of three strategic points of the PI3K–NFκB axis was performed with the aim of exploiting vulnerabilities in cisplatin-resistant NSCLC cells. Cisplatin-resistant cell lines were previously generated through prolonged exposure to the drug. Expression of PI3K and NFκB pathway-related genes were compared between cisplatin-resistant cells and their matched parent cells using a gene expression array, qRT-PCR, DNA sequencing, western blot, and immunofluorescence. Targeted inhibition was performed using GDC-0980, a dual PI3K–mTOR inhibitor currently in Phase II clinical trials in NSCLC, and DHMEQ, an inhibitor of NFκB translocation which has been used extensively both in vitro and in vivo. Effects of the two inhibitors were assessed by BrdU proliferation assay and multiparameter viability assay. NFKBIA was shown to be 12-fold overexpressed in cisplatin-resistant cells, with no mutations present in exons 3, 4, or 5 of the gene. Corresponding overexpression of IκBα was also observed. Treatment with DHMEQ (but not GDC-0980) led to significantly enhanced effects on viability and proliferation in cisplatin-resistant cells compared with parent cells. We conclude that NFκB inhibition represents a more promising strategy than PI3K–mTOR inhibition for treatment in the chemoresistance setting in NSCLC.

A Tobit model for analyzing speed limit compliance in work zones

Poor compliance with speed limits is a serious safety concern in work zones. Most studies of work zone speeds have focused on descriptive analyses and statistical testing without systematically capturing the effects of vehicle and traffic characteristics. Consequently, little is known about how the characteristics of surrounding traffic and platoons influence speeds. This paper develops a Tobit regression technique for innovatively modeling the probability and the magnitude of non-compliance with speed limits at various locations in work zones. Speed data is transformed into two groups—continuous for non-compliant and left-censored for compliant drivers—to model in a Tobit model framework. The modeling technique is illustrated using speed data from three long-term highway work zones in Queensland, Australia. Consistent and plausible model estimates across the three work zones support the appropriateness and validity of the technique. The results show that the probability and magnitude of speeding was higher for leaders of platoons with larger front gaps, during late afternoon and early morning, when traffic volumes were higher, and when higher proportions of surrounding vehicles were non-compliant. Light vehicles and their followers were also more likely to speed than others. Speeding was more common and greater in magnitude upstream than in the activity area, with higher compliance rates close to the end of the activity area and close to stop/slow traffic controllers. The modeling technique and results have great potential to assist in deployment of appropriate countermeasures by better identifying the traffic characteristics associated with speeding and the locations of lower compliance.

Public sector change, person-organization fit, and work attitudes : a mediation model

Organizational change is a typical phenomenon within public sector agencies in OECD countries. An increasing number of studies in the literature examine the implementation of change and its resulting impact on the work attitudes of public sector employees; however, little is known about the extent to which change management processes impact on employees’ work attitudes. This study aims to address this issue by developing a path model underpinned by change management and public service motivation literature. The path model was tested on a sample of 308 managerial and non-managerial public sector employees from the U.S. The results provide further empirical evidence on the types of change initiatives on nursing work and change management processes being implemented. Public sector agencies in the sample implemented a variety of change initiatives such as downsizing, delayering and empowerment. Employees reported two change management processes: the provision of change-related information and participation in change decision making. While the results indicate that change produces change-induced stressors, change information tends to reduce stressors and, subsequently, role stress. The results also indicate that change management processes are associated with higher levels of public service motivation, which is in turn connected to higher levels of person–organization fit. Person–organization fit was found to partially mediate the relationship between public service motivation and job satisfaction in the context of change.

Transcriptional pathway signatures predict MEK addiction and response to selumetinib (AZD6244)

Selumetinib (AZD6244, ARRY-142886) is a selective, non-ATP-competitive inhibitor of mitogen-activated protein/extracellular signal-regulated kinase kinase (MEK)-1/2. The range of antitumor activity seen preclinically and in patients highlights the importance of identifying determinants of response to this drug. In large tumor cell panels of diverse lineage, we show that MEK inhibitor response does not have an absolute correlation with mutational or phospho-protein markers of BRAF/MEK, RAS, or phosphoinositide 3-kinase (PI3K) activity. We aimed to enhance predictivity by measuring pathway output through coregulated gene networks displaying differential mRNA expression exclusive to resistant cell subsets and correlated to mutational or dynamic pathway activity. We discovered an 18-gene signature enabling measurement of MEK functional output independent of tumor genotype. Where the MEK pathway is activated but the cells remain resistant to selumetinib, we identified a 13-gene signature that implicates the existence of compensatory signaling from RAS effectors other than PI3K. The ability of these signatures to stratify samples according to functional activation of MEK and/or selumetinib sensitivity was shown in multiple independent melanoma, colon, breast, and lung tumor cell lines and in xenograft models. Furthermore, we were able to measure these signatures in fixed archival melanoma tumor samples using a single RT-qPCR-based test and found intergene correlations and associations with genetic markers of pathway activity to be preserved. These signatures offer useful tools for the study of MEK biology and clinical application of MEK inhibitors, and the novel approaches taken may benefit other targeted therapies.

Escherichia coli isolates causing asymptomatic bacteriuria in catheterized and noncatheterized individuals possess similar virulence properties

Urinary tract infections (UTIs) are among the most common infectious diseases of humans, with Escherichia coli being responsible for >80% of all cases. Asymptomatic bacteriuria (ABU) occurs when bacteria colonize the urinary tract without causing clinical symptoms and can affect both catheterized patients (catheter-associated ABU [CA-ABU]) and noncatheterized patients. Here, we compared the virulence properties of a collection of ABU and CA-ABU nosocomial E. coli isolates in terms of antibiotic resistance, phylogenetic grouping, specific UTI-associated virulence genes, hemagglutination characteristics, and biofilm formation. CA-ABU isolates were similar to ABU isolates with regard to the majority of these characteristics; exceptions were that CA-ABU isolates had a higher prevalence of the polysaccharide capsule marker genes kpsMT II and kpsMT K1, while more ABU strains were capable of mannose-resistant hemagglutination. To examine biofilm growth in detail, we performed a global gene expression analysis with two CA-ABU strains that formed a strong biofilm and that possessed a limited adhesin repertoire. The gene expression profile of the CA-ABU strains during biofilm growth showed considerable overlap with that previously described for the prototype ABU E. coli strain, 83972. This is the first global gene expression analysis of E. coli CA-ABU strains. Overall, our data suggest that nosocomial ABU and CA-ABU E. coli isolates possess similar virulence profiles.

Effective diffusivity and evaporative cooling in convective drying of food material

This article presents mathematical models to simulate coupled heat and mass transfer during convective drying of food materials using three different effective diffusivities: shrinkage dependent, temperature dependent and average of those two. Engineering simulation software COMSOL Multiphysics was utilized to simulate the model in 2D and 3D. The simulation results were compared with experimental data. It is found that the temperature dependent effective diffusivity model predicts the moisture content more accurately at the initial stage of the drying, whereas, the shrinkage dependent effective diffusivity model is better for the final stage of the drying. The model with shrinkage dependent effective diffusivity shows evaporative cooling phenomena at the initial stage of drying. This phenomenon was investigated and explained. Three dimensional temperature and moisture profiles show that even when the surface is dry, inside of the sample may still contain large amount of moisture. Therefore, drying process should be carefully dealt with otherwise microbial spoilage may start from the centre of the ‘dried’ food. A parametric investigation has been conducted after the validation of the model.

A high and low fear phenotype mouse model

Fear-related illnesses such as post-traumatic stress disorder (PTSD) impose a tremendous burden on individual quality of life, families, and the national economy. In the military population, 17-20% of services members returning from deployment are diagnosed with PTSD. While treatments have improved for PTSD and are helpful for some, many people continue to suffer despite therapy. The aim of this research is to examine fear memory behaviourally and at the cellular level in the amygdala by using a unique inter-cross strain of high and low fear phenotype mice. An extended outcross C57BL/6J x DBA/2J (F8) are selected for high or low Pavlovian fear memory to context and cue. On presentation of either the original learning context or the cue (tone) mice display high or low levels of freezing as a behavioural measure of fear. In order to identify key aspects of the cellular basis of this difference in fear memory behaviour we are making measurements of protein levels and neuron numbers of a known pathway involved in the consolidation of a long term fear memory (pMAPK). Ongoing studies aim to determine if high fear behaviour is associated with differential signalling in the lateral amygdala compared to low fear behaviour. Additionally, by blocking this pathway in the lateral amygdala (LA), we aim to reduce fear behaviour following Pavlovian fear conditioning. This research will help to unravel the cellular mechanisms underlying high fear behaviour and advance the field toward targeted treatment and improved outcomes, ultimately improving human quality of life.

Machine learning for activity recognition : hip versus wrist data

Problem addressed Wrist-worn accelerometers are associated with greater compliance. However, validated algorithms for predicting activity type from wrist-worn accelerometer data are lacking. This study compared the activity recognition rates of an activity classifier trained on acceleration signal collected on the wrist and hip. Methodology 52 children and adolescents (mean age 13.7 +/- 3.1 year) completed 12 activity trials that were categorized into 7 activity classes: lying down, sitting, standing, walking, running, basketball, and dancing. During each trial, participants wore an ActiGraph GT3X+ tri-axial accelerometer on the right hip and the non-dominant wrist. Features were extracted from 10-s windows and inputted into a regularized logistic regression model using R (Glmnet + L1). Results Classification accuracy for the hip and wrist was 91.0% +/- 3.1% and 88.4% +/- 3.0%, respectively. The hip model exhibited excellent classification accuracy for sitting (91.3%), standing (95.8%), walking (95.8%), and running (96.8%); acceptable classification accuracy for lying down (88.3%) and basketball (81.9%); and modest accuracy for dance (64.1%). The wrist model exhibited excellent classification accuracy for sitting (93.0%), standing (91.7%), and walking (95.8%); acceptable classification accuracy for basketball (86.0%); and modest accuracy for running (78.8%), lying down (74.6%) and dance (69.4%). Potential Impact Both the hip and wrist algorithms achieved acceptable classification accuracy, allowing researchers to use either placement for activity recognition.

Emotional intelligence and job-demands resources model

Occupational stress research has consistently demonstrated negative effects for employees. Research also describes potential moderators of this relationship. While research has revealed some positive effects of emotional intelligence (EI) on employee adjustment, it has neglected investigation of their potential stress buffering effects. Based on the Job-Demand Resources model, it was predicted that higher trait emotional intelligence would act as a buffer to the potential negative effects of stressors on employee adjustment. Hierarchical multiple regression analyses with a sample of 306 nurses found no main effects of EI but revealed eight moderating effects. While some interactions support the buffering hypothesis, others revealed buffering for those with low EI. Findings are discussed in terms of theoretical and practical implications.

A hybrid quality function deployment and cybernetic analytic network process model for project manager selection

Identifying appropriate decision criteria and making optimal decisions in a structured way is a complex process. This paper presents an approach for doing this in the form of a hybrid Quality Function Deployment (QFD) and Cybernetic Analytic Network Process (CANP) model for project manager selection. This involves the use of QFD to translate the owner's project management expectations into selection criteria and the CANP to weight the expectations and selection criteria. The supermatrix approach then prioritises the candidates with respect to the overall decision-making goal. A case study is used to demonstrate the use of the model in selecting a renovation project manager. This involves the development of 18 selection criteria in response to the owner's three main expectations of time, cost and quality.

Conformational Spread in the Flagellar Motor Switch: A Model Study

The reliable response to weak biological signals requires that they be amplified with fidelity. In E. coli, the flagellar motors that control swimming can switch direction in response to very small changes in the concentration of the signaling protein CheY-P, but how this works is not well understood. A recently proposed allosteric model based on cooperative conformational spread in a ring of identical protomers seems promising as it is able to qualitatively reproduce switching, locked state behavior and Hill coefficient values measured for the rotary motor. In this paper we undertook a comprehensive simulation study to analyze the behavior of this model in detail and made predictions on three experimentally observable quantities: switch time distribution, locked state interval distribution, Hill coefficient of the switch response. We parameterized the model using experimental measurements, finding excellent agreement with published data on motor behavior. Analysis of the simulated switching dynamics revealed a mechanism for chemotactic ultrasensitivity, in which cooperativity is indispensable for realizing both coherent switching and effective amplification. These results showed how cells can combine elements of analog and digital control to produce switches that are simultaneously sensitive and reliable. © 2012 Ma et al.

Memory and Epileptogenesis in Complex Biological and Simulated Systems

Oscillations of neural activity may bind widespread cortical areas into a neural representation that encodes disparate aspects of an event. In order to test this theory we have turned to data collected from complex partial epilepsy (CPE) patients with chronically implanted depth electrodes. Data from regions critical to word and face information processing was analyzed using spectral coherence measurements. Similar analyses of intracranial EEG (iEEG) during seizure episodes display HippoCampal Formation (HCF)—NeoCortical (NC) spectral coherence patterns that are characteristic of specific seizure stages (Klopp et al. 1996). We are now building a computational memory model to examine whether spatio-temporal patterns of human iEEG spectral coherence emerge in a computer simulation of HCF cellular distribution, membrane physiology and synaptic connectivity. Once the model is reasonably scaled it will be used as a tool to explore neural parameters that are critical to memory formation and epileptogenesis.

Stability analysis and implementation of Power-Hardware-in-the-Loop for power system testing

This project develops the required guidelines to assure stable and accurate operation of Power-Hardware-in-the-Loop implementations. The proposals of this research have been theoretically analyzed and practically examined using a Real-Time Digital Simulator. In this research, the interaction between software simulated power network and the physical power system has been studied. The conditions for different operating regimes have been derived and the corresponding analyses have been presented.

The origin of cyclical high- and low-Cr basalts with continental crust trace element signatures in the Kalkarindji Large Igneous Province

The 510 million year old Kalkarindji Large Igneous Province correlates in time with the first major extinction event after the Cambrian explosion of life. Large igneous provinces correlate with all major mass extinction events in the last 500 million years. The genetic link between large igneous provinces and mass extinction remains unclear. My work is a contribution towards understanding magmatic processes involved in the generation of Large Igneous Provinces. I concentrate on the origin of variation in Cr in magmas and have developed a model in which high temperature melts intrude into and assimilate large amounts of upper continental crust.