JunD, not c-Jun, is the AP-1 transcription factor required for Ras-induced lung cancer.

The AP-1 transcription factor c-Jun is required for Ras-driven tumorigenesis in many tissues and is considered as a classical proto-oncogene. To determine the requirement for c-Jun in a mouse model of K-RasG12D-induced lung adenocarcinoma, we inducibly deleted c-Jun in the adult lung. Surprisingly, we found that inactivation of c-Jun, or mutation of its JNK phosphorylation sites, actually increased lung tumor burden. Mechanistically, we found that protein levels of the Jun family member JunD were increased in the absence of c-Jun. In c-Jun-deficient cells, JunD phosphorylation was increased, and expression of a dominant-active JNKK2-JNK1 transgene further increased lung tumor formation. Strikingly, deletion of JunD completely abolished Ras-driven lung tumorigenesis. This work identifies JunD, not c-Jun, as the crucial substrate of JNK signaling and oncogene required for Ras-induced lung cancer

Thalidomide-Related Eosinophilic Pneumonia: A case report and brief literature review

Thalidomide has regained value in the multimodality treatment of leprosy, multiple myeloma, prostate, ovarian and renal cancer. Complications related to arterial and venous complications are well described. However, pulmonary complications remain relatively uncommon. The most common pulmonary side-effect reported is non-specific dyspnea. We report a patient with multiple myeloma, who developed an eosinophilic pneumonia, shortly after starting thalidomide. She had complete resolution of her symptoms and pulmonary infiltrates on discontinuation of the drug and treatment with corticosteroids. Physicians should be cognizant of this potential complication in patients receiving thalidomide who present with dyspnea and pulmonary infiltrates

Factors Associated with Physician Agreement on Verbal Autopsy of over 11500 Injury Deaths in India

Worldwide, injuries account for 9.8% of all deaths. The majority of these deaths occur in low- and middle-income countries where vital registration systems are often inadequate. Verbal autopsy (VA) is a tool used to ascertain cause of death in such settings. Validation studies for VA using hospital diagnosed causes of death as comparisons have shown that injury deaths can be reliably diagnosed by VA. However, no study has assessed the factors that may affect physicians' abilities to code specific causes of injury death using VA.This study used data from over 11 500 verbal autopsies of injury deaths from the Million Death Study (MDS) in which 6.3 million people in India were monitored from 2001–2003 for vital events. Deaths that occurred in the MDS were coded by two independent physicians. This study focused on whether physician agreement on the classification of injury deaths was affected by characteristics of the deceased and respondent. Agreement was analyzed using three primary methods: 1) kappa statistic; 2) sensitivity and specificity analysis using the final VA diagnosed category of injury death as gold standard; and 3) multivariate logistic regression using a conceptual hierarchical model. The overall agreement for all injury deaths was 77.9% with a kappa of 0.74 (99% CI 0.74–0.75). Deaths in the injury categories of “transport”, “falls”, “drowning” and “other unintentional injury” occurring outside the home were associated with greater physician agreement than those occurring at home. In contrast, self-inflicted injury deaths that occurred outside the home were associated with lower physician agreement.With few exceptions, most characteristics of the deceased and the respondent did not influence physician agreement on the classification of injury deaths. Physician training and continued adaptation of the VA tool should focus on the reasons these factors influenced physician agreement

Occurrence and Treatment of Bone Atrophic Non-Unions Investigated by an Integrative Approach

Recently developed atrophic non-union models are a good representation of the clinical situation in which many nonunions develop. Based on previous experimental studies with these atrophic non-union models, it was hypothesized that in order to obtain successful fracture healing, blood vessels, growth factors, and (proliferative) precursor cells all need to be present in the callus at the same time. This study uses a combined in vivo-in silico approach to investigate these different aspects (vasculature, growth factors, cell proliferation). The mathematical model, initially developed for the study of normal fracture healing, is able to capture essential aspects of the in vivo atrophic non-union model despite a number of deviations that are mainly due to simplifications in the in silico model. The mathematical model is subsequently used to test possible treatment strategies for atrophic non-unions (i.e. cell transplant at post-osteotomy, week 3). Preliminary in vivo experiments corroborate the numerical predictions. Finally, the mathematical model is applied to explain experimental observations and identify potentially crucial steps in the treatments and can thereby be used to optimize experimental and clinical studies in this area. This study demonstrates the potential of the combined in silico-in vivo approach and its clinical implications for the early treatment of patients with problematic fractures

Value of information analysis for assessing risks and benefits of nanotechnology innovation

Background Decisions on adoption of technological innovation are difficult for manufacturers, especially for small and medium enterprises (SMEs) who have limited resources but often drive product development. Decision analytic methods have been applied to regulatory issues in the nanotechnology sector but such applications to market innovation are not found in the literature. Value of information (VoI) is a decision analytic method for quantifying the benefit of acquiring additional information to support such analyses that can be used to help in a wide range of manufacturing decisions. Results This paper develops a VoI methodology for comparative evaluation of technological alternatives and applies it to a real case study aimed at the selection between a coating system containing nano-TiO2 and alternative conventional paints. The aim of this approach is to aid SMEs and larger industries in deciding whether to further develop the nano-enabled product and in evaluating to which extent investing in more research about risks and/or benefits would be worthwhile. Conclusions Results demonstrated how prioritization in information gaining can improve risk–benefit analyses and impact on both risk management and innovation decision making. By applying the proposed methodology, SMEs and larger industries might easily identify optimal data gathering and/or research strategies to formulate solid development and risk management plans

Adults with autism overestimate the volatility of the sensory environment.

Insistence on sameness and intolerance of change are among the diagnostic criteria for autism spectrum disorder (ASD), but little research has addressed how people with ASD represent and respond to environmental change. Here, behavioral and pupillometric measurements indicated that adults with ASD are less surprised than neurotypical adults when their expectations are violated, and decreased surprise is predictive of greater symptom severity. A hierarchical Bayesian model of learning suggested that in ASD, a tendency to overlearn about volatility in the face of environmental change drives a corresponding reduction in learning about probabilistically aberrant events, thus putatively rendering these events less surprising. Participant-specific modeled estimates of surprise about environmental conditions were linked to pupil size in the ASD group, thus suggesting heightened noradrenergic responsivity in line with compromised neural gain. This study offers insights into the behavioral, algorithmic and physiological mechanisms underlying responses to environmental volatility in ASD

Integrating BDI agents with Agent-based simulation platforms

Agent-Based Models (ABMs) is increasingly being used for exploring and supporting decision making about social science scenarios involving modelling of human agents. However existing agent-based simulation platforms (e.g., SWARM, Repast) provide limited support for the simulation of more complex cognitive agents required by such scenarios. We present a framework that allows Belief-Desire Intention (BDI) cognitive agents to be embedded in an ABM system. Architecturally, this means that the "brains" of an agent can be modelled in the BDI system in the usual way, while the "body" exists in the ABM system. The architecture is exible in that the ABM can still have non-BDI agents in the simulation, and the BDI-side can have agents that do not have a physical counterpart (such as an organisation). The framework addresses a key integration challenge of coupling event-based BDI systems, with time-stepped ABM systems. Our framework is modular and supports integration off-the-shelf BDI systems with off-the-shelf ABM systems. The framework is Open Source, and all integrations and applications are available for use by the modelling community

The Relationship Between Low Family Income and Psychological Disturbance in Young Children: An Australian Longitudinal Study

Objective This study examines the relationship between low family income (LFI) experienced at different points in time, chronic low income status and its impact on child behaviour measured at 5 years of age. Method Longitudinal data from the Mater University Study of Pregnancy were used to measure LFI in families at three points in time (the antenatal period, 6 months post birth and at 5 years of age). Outcome variables were three independent groups of behaviour problems labelled as externalising, social, attentional and thought (SAT) problems, and internalising problems. These groups were developed from the Child Behaviour Checklist. An analysis based on logistic regression modelling was carried out examining the relationship between LFI and a range of intermediate variables known to be associated with child behaviour problems. Results The more often families experienced low income, the higher the rate of child behaviour problems at age 5. Low family income was still independently associated with SAT behaviour problems after controlling for smoking in the first trimester, parenting styles, maternal depression and marital disharmony at age 5. The association between LFI and internalising and externalising behaviour problems was largely mediated by maternal depression. Conclusion Low family income is a significant factor in the aetiology of a variety of child behaviour problems. The mechanisms involved in the link between LFI and childhood internalising and externalising behaviours involve the exposure of the children to maternal depression. However, the relationship between LFI and SAT behaviour problems remains to be elucidated