Evaluation of a Low-Cost, PC-Based Driving Simulator to Assess Persons with Cognitive Impairments Due to Brain Injury

Brain injury due to accident or stroke frequently results in cognitive impairment, reducing an individual’s ability to judge driving situations accurately. Rehabilitation professionals typically use a combination of clinical and on-road tests to determine whether an individual is safe to drive. Weighing the safety of the community, the candidate, and the driving evaluator, these on-road tests are often conducted under road, traffic and weather conditions less demanding than those that a driver might face in the “real world,” and thus may offer less than complete information regarding the candidate’s responses to such real-world driving challenges. Indeed, individuals with mild cognitive deficits may perform adequately under such testing conditions but unsafely when driving challenges increase. Complicating this situation further, those with mild to moderate acquired cognitive impairments may be largely unaware of their own limitations, and thus more intolerant of perceived delays or challenges to their desire to drive again. Although continuing advances have improved performance and fidelity while significantly reducing costs, most interactive driving simulators remain too expensive for widespread clinical application. In a project funded by the National Center for Medical Rehabilitation Research, National Institutes of Health, we sought to determine, on a pilot basis, whether a low-cost, PC-based driving simulator could provide clinicians with information useful to their efforts to assess the safe ability to drive of individuals with cognitive impairments. We developed two comprehensive simulator-based driving scenarios, one quite basic and one more challenging, and pilot-tested them on ten subjects – five with moderate cognitive impairments, and five age and sex matched-controls without impairment. The “simple” scenario was developed to match the essential demands of the first half of an existing on-road driving evaluation; the “complex” scenario was based on the second half of the on-road evaluation into which more demanding, but still common, driving challenges were integrated. Road types, lane widths, pavement markings, traffic signals, horizontal and vertical curvature, and the proximal built environment were all created in simulation to provide a convincing generic representation of the on-road test. Challenges incorporated into the “complex” phase of the scenario, which were absent from the “simple” phase, included traffic events such as: cross-traffic failing to stop at a STOP sign; pedestrians crossing the driver’s path; vehicles suddenly pulling out in front of the subject from the road shoulder; opposing thru traffic appearing suddenly from behind slower moving vehicles as the subject attempted to turn left; slower moving lead vehicles causing passing decisions; traffic streams forcing gap acceptance decisions; etc. Results from the simulator were compared to results from the on-road evaluation. In addition, data gathered from subject exit interviews was used to judge simulator verisimilitude and efficacy in changing self-awareness of deficit. Because the cognitive impairments associated with brain injury often reduce the individual’s awareness of his or her own limitations, we looked at evidence that performance on the simulator could contribute to an individual’s own understanding of his or her driving strengths and weaknesses. The results of the pilot study will lead to an enhancement of simulator capabilities, and to a comprehensive clinical trial at multiple sites. This paper will present the findings of this pilot investigation and an overview of the expanded clinical study

An analysis of Australia's carbon pollution reduction scheme

The authors review the decision-making since the Labour Government came into office (November 2007). The Australian Government’s ‘Carbon Pollution Reduction Scheme’ White Paper (15 December 2008) proposes that an Australian Emissions Trading Scheme (AETS) be implemented in mid-2010. Acknowledging that the scheme is comprehensive, the paper finds that in many cases, Australia will take a softer approach to climate change through the AETS than the European Union ETS(EUETS). The paper assesses key issues in the White Paper such as emissions reduction targets, GHG coverage, sectoral coverage, inclusion of unlimited quantities of offsets from Kyoto international markets and exclusion of deforestation activities

HCVerso3: An Open-Label, Phase IIb Study of Faldaprevir and Deleobuvir with Ribavirin in Hepatitis C Virus Genotype-1b-Infected Patients with Cirrhosis and Moderate Hepatic Impairment

This study evaluated the interferon-free, oral combination of deleobuvir (non-nucleoside HCV NS5-RNA-polymerase inhibitor) and faldaprevir (HCV NS3/4A-protease inhibitor) with ribavirin in patients with HCV genotype-1b and moderate (Child-Pugh B [CPB], n = 17) or mild hepatic impairment (Child-Pugh A [CPA], n = 18). Patients received faldaprevir 120 mg and deleobuvir (600 mg [CPA], 400 mg [CPB]) twice-daily with weight-based ribavirin for 24 weeks. Baseline characteristics were similar between groups. Among CPA patients, 13/18 completed treatment; discontinuations were for adverse events (AEs, n = 1), lack of efficacy (n = 3) and withdrawal (n = 1). Among CPB patients, 8/17 completed treatment; discontinuations were for AEs (n = 6), withdrawal (n = 1) and 'other' (n = 2). Sustained virologic response at post-treatment Week 12 (SVR12) was achieved by 11 (61%) CPA patients (95% confidence interval: 38.6%-83.6%) and 9 (53%) CPB patients (95% confidence interval: 29.2%-76.7%), including most CPA (11/16) patients with Week 4 HCV RNA <25 IU.mL-1 (target detected or not detected) and most CPB (8/9) patients with Week 4 HCV RNA <25 IU.mL-1 (target not detected); 0/4 CPB patients with Week 4 HCV RNA <25 IU.mL-1 (target detected) achieved SVR12. The most common AEs in both groups were nausea, diarrhoea and vomiting. Serious AEs were observed in 9 (53%) CPB patients and 1 (6%) CPA patient. Plasma trough concentrations of deleobuvir and faldaprevir were not substantially different between the CPA and CPB groups. In conclusion, in this small study the safety and efficacy profiles for 24 weeks of treatment with faldaprevir+deleobuvir+ribavirin in patients with mild or moderate hepatic impairment were consistent with the safety and efficacy profile of this regimen in non-cirrhotic patients. Faldaprevir+deleobuvir+ribavirin resulted in SVR12 in 53-61% of patients: proportions achieving SVR4 but not SVR12 were higher than in non-cirrhotic patients and overall response rates were lower than rates reported with other all-oral regimens in patients with cirrhosis

eIF2α Phosphorylation Bidirectionally Regulates the Switch from Short- to Long-Term Synaptic Plasticity and Memory

SummaryThe late phase of long-term potentiation (LTP) and memory (LTM) requires new gene expression, but the molecular mechanisms that underlie these processes are not fully understood. Phosphorylation of eIF2α inhibits general translation but selectively stimulates translation of ATF4, a repressor of CREB-mediated late-LTP (L-LTP) and LTM. We used a pharmacogenetic bidirectional approach to examine the role of eIF2α phosphorylation in synaptic plasticity and behavioral learning. We show that in eIF2α+/S51A mice, in which eIF2α phosphorylation is reduced, the threshold for eliciting L-LTP in hippocampal slices is lowered, and memory is enhanced. In contrast, only early-LTP is evoked by repeated tetanic stimulation and LTM is impaired, when eIF2α phosphorylation is increased by injecting into the hippocampus a small molecule, Sal003, which prevents the dephosphorylation of eIF2α. These findings highlight the importance of a single phosphorylation site in eIF2α as a key regulator of L-LTP and LTM formation

Hcverso1 and 2: Faldaprevir with deleobuvir (BI 207127) and ribavirin for treatment-naïve patients with chronic hepatitis C virus genotype-1b infection

he interferon-free combination of once-daily faldaprevir 120 mg, twice-daily deleobuvir 600 mg, and weight-based ribavirin was evaluated in two Phase III studies (HCVerso1, HCVerso2) in hepatitis C virus genotype-1b-infected, treatment-naïve patients, including those ineligible for peginterferon (HCVerso2). Patients without cirrhosis were randomized to 16 weeks (Arm 1; n=208 HCVerso1, n=213 HCVerso2) or 24 weeks (Arm 2; n=211 in both studies) of faldaprevir + deleobuvir + ribavirin. Patients with compensated cirrhosis received open-label faldaprevir + deleobuvir + ribavirin for 24 weeks (Arm 3; n=51, n=72). Primary endpoints were comparisons of adjusted sustained virologic response (SVR) rates with historical rates: 71% (HCVerso1) and 68% (HCVerso2). Adjusted SVR12 rates were significantly greater than historical controls for Arms 1 and 2 in HCVerso2 (76%, 95% confidence interval [CI] 71-81, P=0.002; 81%, 95% CI 76-86, P<0.0001) and Arm 2 in HCVerso1 (81%, 95% CI 77-86, P<0.0001), but not for Arm 1 of HCVerso1 (72%, 95% CI 66-77, P=0.3989). Unadjusted SVR12 rates in Arms 1, 2, and 3 were 71.6%, 82.5%, and 72.5%, respectively, in HCVerso1 and 75.6%, 82.0%, and 73.6%, respectively, in HCVerso2. Virologic breakthrough and relapse occurred in 24-week arms in 8%-9% and 1% of patients, respectively, and in 16-week arms in 7%-8% and 9%-11% of patients, respectively. The most common adverse events were nausea (46%-61%) and vomiting (29%-35%). Adverse events resulted in discontinuation of all medications in 6%-8% of patients. In treatment-naïve patients with hepatitis C virus genotype-1b infection, with or without cirrhosis, faldaprevir + deleobuvir + ribavirin treatment for 24 weeks resulted in adjusted SVR12 rates significantly higher than historical controls. Both studies were registered in ClinicalTrials.gov (NCT01732796, NCT01728324)

Family history and risk of bladder cancer:an analysis accounting for first- and second-degree relatives

Although evidence suggests that a positive family history of bladder cancer in first-degree relatives is an important risk factor for bladder cancer occurrence, results remain unclear. The influence of family history of non-bladder cancers and more distant relatives on bladder cancer risk is inconsistent. This research therefore, aims to increase the understanding of the association between family history and bladder cancer risk based on worldwide case-control studies. In total 4,327 cases and 8,948 non-cases were included. Pooled odds ratios (ORs), with corresponding 95% confidence intervals (CIs), were obtained using multilevel logistic regression models, adjusted by age, sex, ethnicity, smoking status, and smoking pack-years. The results show bladder cancer risk increased by having a first- or second-degree relative affected with bladder cancer (OR 2.72, 95%CI 1.55-4.77 and OR 1.71, 95%CI 1.22-2.40, respectively), and non-urologic cancers (OR 1.61, 95%CI 1.19-2.18). Moreover, bladder cancer risk increased by number of cancers affected first-degree relatives (for 1 and >1 first-degree relatives: OR 1.42, 95% CI 1.02-2.04; OR 2.67, 95% CI 1.84-3.86, respectively). Our findings highlight an increased bladder cancer risk for a positive bladder cancer family history in first- and second-degree relatives, and indicate a possible greater effect for an increment of numbers of affected relatives

Parallel symbolic state-space exploration is difficult, but what is the alternative?

State-space exploration is an essential step in many modeling and analysis problems. Its goal is to find the states reachable from the initial state of a discrete-state model described. The state space can used to answer important questions, e.g., "Is there a dead state?" and "Can N become negative?", or as a starting point for sophisticated investigations expressed in temporal logic. Unfortunately, the state space is often so large that ordinary explicit data structures and sequential algorithms cannot cope, prompting the exploration of (1) parallel approaches using multiple processors, from simple workstation networks to shared-memory supercomputers, to satisfy large memory and runtime requirements and (2) symbolic approaches using decision diagrams to encode the large structured sets and relations manipulated during state-space generation. Both approaches have merits and limitations. Parallel explicit state-space generation is challenging, but almost linear speedup can be achieved; however, the analysis is ultimately limited by the memory and processors available. Symbolic methods are a heuristic that can efficiently encode many, but not all, functions over a structured and exponentially large domain; here the pitfalls are subtler: their performance varies widely depending on the class of decision diagram chosen, the state variable order, and obscure algorithmic parameters. As symbolic approaches are often much more efficient than explicit ones for many practical models, we argue for the need to parallelize symbolic state-space generation algorithms, so that we can realize the advantage of both approaches. This is a challenging endeavor, as the most efficient symbolic algorithm, Saturation, is inherently sequential. We conclude by discussing challenges, efforts, and promising directions toward this goal