Generation of biological association networks: A novel strategy to detect new targets in cancer therapy

The aim of this work was to design a novel strategy to detect new targets for anticancer treatments. The rationale was to build Biological Association Networks from differentially expressed genes in drug-resistant cells to identify important nodes within the Networks. These nodes may represent putative targets to attack in cancer therapy, as a way to destabilize the gene network developed by the resistant cells to escape from the drug pressure. As a model we used cells resistant to methotrexate (MTX), an inhibitor of DHFR. Selected node-genes were analyzed at the transcriptional level and from a genotypic point of view. In colon cancer cells, DHFR, the AKR1 family, PKC¿, S100A4, DKK1, and CAV1 were overexpressed while E-cadherin was lost. In breast cancer cells, the UGT1A family was overexpressed, whereas EEF1A1 was overexpressed in pancreatic cells. Interference RNAs directed against these targets sensitized cells towards MTX.

2015-2019 Iowa Transportation Improvement Program

This document describes planned investments in Iowa's multimodal transportation system including aviation, transit, railroads, trails, and highways. A large part of funding available for highway programming comes from the federal government. Accurately estimating future federal funding levels is dependent on having a multiyear federal transportation authorization bill in place and having a sustainable and solvent federal Highway Trust Fund. The most recent federal authorization, Moving Ahead for Progress in the 21st Century (MAP-21), will expire September 30, 2014. At the same time that MAP-21 expires and absent Congressional action, the federal Highway Trust Fund will no longer be able to provide funding at current levels resulting in the full elimination of federal highway funding for new projects in federal fiscal year 2015. These two issues provide funding uncertainty with this program in fiscal years 2015 and beyond.

Plastic modifications within inhibitory control networks induced by practicing a stop-signal task: an electrical neuroimaging study.

INTRODUCTION: Inhibitory control refers to our ability to suppress ongoing motor, affective or cognitive processes and mostly depends on a fronto-basal brain network. Inhibitory control deficits participate in the emergence of several prominent psychiatric conditions, including attention deficit/hyperactivity disorder or addiction. The rehabilitation of these pathologies might therefore benefit from training-based behavioral interventions aiming at improving inhibitory control proficiency and normalizing the underlying neurophysiological mechanisms. The development of an efficient inhibitory control training regimen first requires determining the effects of practicing inhibition tasks. METHODS: We addressed this question by contrasting behavioral performance and electrical neuroimaging analyses of event-related potentials (ERPs) recorded from humans at the beginning versus the end of 1 h of practice on a stop-signal task (SST) involving the withholding of responses when a stop signal was presented during a speeded auditory discrimination task. RESULTS: Practicing a short SST improved behavioral performance. Electrophysiologically, ERPs differed topographically at 200 msec post-stimulus onset, indicative of the engagement of distinct brain network with learning. Source estimations localized this effect within the inferior frontal gyrus, the pre-supplementary motor area and the basal ganglia. CONCLUSION: Our collective results indicate that behavioral and brain responses during an inhibitory control task are subject to fast plastic changes and provide evidence that high-order fronto-basal executive networks can be modified by practicing a SST.

Iowa Department of Transportation Major Items - Preliminary Quantity Report, August 19, 2014; With Addendums

Weekly letting report.

The Governor's Blue Ribbon Transportation Task Force: Implementation Report for Maximizing the Efficient Use of Iowa's Road Use Tax Fund, 1998

This report documents the Iowa Department of Transportation's accomplishments and ongoing efforts in response to 39 recommendations proposed by the Governor's Blue Ribbon Transportation Task Force at the end of 1995. Governor Terry Branstad challenged the Task Force to "maximize the benefits of each dollar spent from the Road Use Tax Fund."

Stimulus statistics shape oscillations in nonlinear recurrent neural networks.

Rhythmic activity plays a central role in neural computations and brain functions ranging from homeostasis to attention, as well as in neurological and neuropsychiatric disorders. Despite this pervasiveness, little is known about the mechanisms whereby the frequency and power of oscillatory activity are modulated, and how they reflect the inputs received by neurons. Numerous studies have reported input-dependent fluctuations in peak frequency and power (as well as couplings across these features). However, it remains unresolved what mediates these spectral shifts among neural populations. Extending previous findings regarding stochastic nonlinear systems and experimental observations, we provide analytical insights regarding oscillatory responses of neural populations to stimulation from either endogenous or exogenous origins. Using a deceptively simple yet sparse and randomly connected network of neurons, we show how spiking inputs can reliably modulate the peak frequency and power expressed by synchronous neural populations without any changes in circuitry. Our results reveal that a generic, non-nonlinear and input-induced mechanism can robustly mediate these spectral fluctuations, and thus provide a framework in which inputs to the neurons bidirectionally regulate both the frequency and power expressed by synchronous populations. Theoretical and computational analysis of the ensuing spectral fluctuations was found to reflect the underlying dynamics of the input stimuli driving the neurons. Our results provide insights regarding a generic mechanism supporting spectral transitions observed across cortical networks and spanning multiple frequency bands.

Iowa Department of Transportation Major Items - Preliminary Quantity Report, August 19, 2014; With Addendums

Weekly letting report.

Iowa Department of Transportation Major Items - Preliminary Quantity Report, October 21, 2014; With Addendums

Weekly letting report.

2012 Emergency Response Guidebook: A Guidebook for First Responders During the Initial Phase of a Dangerous Goods/ Hazardous Materials Transportation Incident,

A Guidebook for First Responders During the Initial Phase of a Dangerous Goods/Hazardous Materials Transportation Incident.

Iowa Department of Transportation Major Items - Preliminary Quantity Report, September 16, 2014; With Addendums

Weekly letting report.

Use of Reversions, Iowa Department of Transportation, 2014

The Iowa Department of Transportation spent $406,240 of the Fiscal year 2013 RUTF/PRF budget reversion in FY 2014 for desktop and server software, information technology professional services, training and computer equipment.

Report on the Iowa Department of Transportation for the year ended June 30, 2013

Report on the Iowa Department of Transportation for the year ended June 30, 2013

Development of Asphalt Dynamic Modulus Master Curve Using Falling Weight Deflectometer Measurements, TR-659

The asphalt concrete (AC) dynamic modulus (|E*|) is a key design parameter in mechanistic-based pavement design methodologies such as the American Association of State Highway and Transportation Officials (AASHTO) MEPDG/Pavement-ME Design. The objective of this feasibility study was to develop frameworks for predicting the AC |E*| master curve from falling weight deflectometer (FWD) deflection-time history data collected by the Iowa Department of Transportation (Iowa DOT). A neural networks (NN) methodology was developed based on a synthetically generated viscoelastic forward solutions database to predict AC relaxation modulus (E(t)) master curve coefficients from FWD deflection-time history data. According to the theory of viscoelasticity, if AC relaxation modulus, E(t), is known, |E*| can be calculated (and vice versa) through numerical inter-conversion procedures. Several case studies focusing on full-depth AC pavements were conducted to isolate potential backcalculation issues that are only related to the modulus master curve of the AC layer. For the proof-of-concept demonstration, a comprehensive full-depth AC analysis was carried out through 10,000 batch simulations using a viscoelastic forward analysis program. Anomalies were detected in the comprehensive raw synthetic database and were eliminated through imposition of certain constraints involving the sigmoid master curve coefficients. The surrogate forward modeling results showed that NNs are able to predict deflection-time histories from E(t) master curve coefficients and other layer properties very well. The NN inverse modeling results demonstrated the potential of NNs to backcalculate the E(t) master curve coefficients from single-drop FWD deflection-time history data, although the current prediction accuracies are not sufficient to recommend these models for practical implementation. Considering the complex nature of the problem investigated with many uncertainties involved, including the possible presence of dynamics during FWD testing (related to the presence and depth of stiff layer, inertial and wave propagation effects, etc.), the limitations of current FWD technology (integration errors, truncation issues, etc.), and the need for a rapid and simplified approach for routine implementation, future research recommendations have been provided making a strong case for an expanded research study.

Iowa Department of Transportation Major Items - Preliminary Quantity Report, November 18, 2014; With Addendums

Weekly letting report.

Coworker networks in the labour market

This paper studies the role coworker-based networks play for individual labour marketoutcomes. I analyse how the provision of labour market relevant information by formercoworkers affects the employment probabilities and, if hired, the wages of male workerswho have previously become unemployed as the result of an establishment closure. Toidentify the causal effect of an individual worker's network on labour market outcomes, Iexploit exogenous variation in the strength of these networks that is due to the occurrenceof mass-layoffs in the establishments of former coworkers. The empirical analysis is basedon administrative data that comprise the universe of workers employed in Germany between1980 and 2001. The results suggest a strong positive effect of a higher employmentrate in a worker's network of former coworkers on his re-employment probability afterdisplacement: a 10 percentage point increase in the prevailing employment rate in thenetwork increases the re-employment probability by 7.5 percentage points. In contrast,there is no evidence of a statistically significant effect on wages.