Unique Transcriptional Profiles Underlie Osteosarcomagenesis Driven by Different p53 Mutants

UNLABELLED: Missense mutations in the DNA binding domain of p53 are characterized as structural or contact mutations based on their effect on the conformation of the protein. These mutations show gain-of-function (GOF) activities, such as promoting increased metastatic incidence compared with p53 loss, often mediated by the interaction of mutant p53 with a set of transcription factors. These interactions are largely context specific. To understand the mechanisms by which p53 DNA binding domain mutations drive osteosarcoma progression, we created mouse models, in which either the p53 structural mutant p53R172H or the contact mutant p53R245W are expressed specifically in osteoblasts, yielding osteosarcoma tumor development. Survival significantly decreased and metastatic incidence increased in mice expressing p53 mutants compared with p53-null mice, suggesting GOF. RNA sequencing of primary osteosarcomas revealed vastly different gene expression profiles between tumors expressing the missense mutants and p53-null tumors. Further, p53R172H and p53R245W each regulated unique transcriptomes and pathways through interactions with a distinct repertoire of transcription factors. Validation assays showed that p53R245W, but not p53R172H, interacts with KLF15 to drive migration and invasion in osteosarcoma cell lines and promotes metastasis in allogeneic transplantation models. In addition, analyses of p53R248W chromatin immunoprecipitation peaks showed enrichment of KLF15 motifs in human osteoblasts. Taken together, these data identify unique mechanisms of action of the structural and contact mutants of p53. SIGNIFICANCE: The p53 DNA binding domain contact mutant p53R245W, but not the structural mutant p53R172H, interacts with KLF15 to drive metastasis in somatic osteosarcoma, providing a potential vulnerability in tumors expressing p53R245W mutation

0078 Influence of Light on Brain Activity Upon Waking From Slow Wave Sleep

Funded by Naval Postgraduate School17 USC 105 interim-entered record; under review.The article of record as published may be found at https://doi.org/10.1093/sleep/zsaa056.076Introduction: Waking from sleep is associated with reduced alertness due to sleep inertia. Light acutely improves alertness during sleep deprivation. In this study we assessed the influence of light on brain activity and connectivity after waking from slow wave sleep (SWS). Methods: Twelve participants kept an actigraphy-confirmed stable sleep schedule with 8.5 hours for five nights and five hours for one night prior to an overnight laboratory visit. Participants completed two three-minute Karolinska Drowsiness Tests (KDT) before going to bed at their habitual bedtime. They were monitored continuously using high-density EEG (32-channel; Brain Products GmbH). Participants were woken twice and exposed to red light (0.01 melanopic-lux; control) or blue-enriched light (63.62 melanopic-lux) for one hour, in a randomized order, following at least five minutes of SWS. EEG artifact were removed algorithmically and the spectral composition of each electrode (i.e., fast fourier transform, FFT) and effective connectivity (i.e., partial directed coherence, PDC) between each electrode were estimated. A graphical analysis was conducted to extract features relevant to the facilitation of efficient communication between electrodes. All data were averaged within frequency bins of interest that correspond to delta (1-3Hz), theta (4-7Hz), alpha (8-12Hz), and beta (13-25Hz) bands and expressed relative to the pre-sleep baseline. Results: Compared to the pre-sleep baseline, participants exposed to blue-enriched light experienced reduced theta and alpha activity; however, these results were not significantly different from the control. In contrast, the communication of frontal electrodes significantly increased across all frequency bands compared to the control, and this effect was most prominent in the alpha (t(11)=3.80, p=.005) and beta bands (t(11)=3.92, p=.004). Conclusion: Exposure to blue-enriched light immediately after waking from SWS may accelerate the process of waking and help to improve alertness by facilitating communication between brain regions. Future analyses will explore the temporal persistence and granularity of the communicative properties associated with this response.Naval Postgraduate School Grant. NASA Airspace Operations and Safety Program, System-Wide Safety Project

Reconfigurations in brain networks upon awakening from slow wave sleep: Interventions and implications in neural communication

AbstractSleep inertia is the brief period of impaired alertness and performance experienced immediately after waking. Little is known about the neural mechanisms underlying this phenomenon. A better understanding of the neural processes during sleep inertia may offer insight into the awakening process. We observed brain activity every 15 min for 1 hr following abrupt awakening from slow wave sleep during the biological night. Using 32-channel electroencephalography, a network science approach, and a within-subject design, we evaluated power, clustering coefficient, and path length across frequency bands under both a control and a polychromatic short-wavelength-enriched light intervention condition. We found that under control conditions, the awakening brain is typified by an immediate reduction in global theta, alpha, and beta power. Simultaneously, we observed a decrease in the clustering coefficient and an increase in path length within the delta band. Exposure to light immediately after awakening ameliorated changes in clustering. Our results suggest that long-range network communication within the brain is crucial to the awakening process and that the brain may prioritize these long-range connections during this transitional state. Our study highlights a novel neurophysiological signature of the awakening brain and provides a potential mechanism by which light improves performance after waking

Inhibition of translation initiation factor eIF4a inactivates heat shock factor 1 (HSF1) and exerts anti-leukemia activity in AML

Eukaryotic initiation factor 4A (eIF4A), the enzymatic core of the eIF4F complex essential for translation initiation, plays a key role in the oncogenic reprogramming of protein synthesis, and thus is a putative therapeutic target in cancer. As important component of its anticancer activity, inhibition of translation initiation can alleviate oncogenic activation of HSF1, a stress-inducible transcription factor that enables cancer cell growth and survival. Here, we show that primary acute myeloid leukemia (AML) cells exhibit the highest transcript levels of eIF4A1 compared to other cancer types. eIF4A inhibition by the potent and specific compound rohinitib (RHT) inactivated HSF1 in these cells, and exerted pronounced in vitro and in vivo anti-leukemia effects against progenitor and leukemia-initiating cells, especially those with FLT3-internal tandem duplication (ITD). In addition to its own anti-leukemic activity, genetic knockdown of HSF1 also sensitized FLT3-mutant AML cells to clinical FLT3 inhibitors, and this synergy was conserved in FLT3 double-mutant cells carrying both ITD and tyrosine kinase domain mutations. Consistently, the combination of RHT and FLT3 inhibitors was highly synergistic in primary FLT3-mutated AML cells. Our results provide a novel therapeutic rationale for co-targeting eIF4A and FLT3 to address the clinical challenge of treating FLT3-mutant AML.R01 CA175744 - NCI NIH HHS; R35 GM118173 - NIGMS NIH HHS; P30 CA016672 - NCI NIH HHSPublished versionSupporting documentationAccepted manuscrip

A Review on the Mechanical Modeling of Composite Manufacturing Processes

© 2016, The Author(s). The increased usage of fiber reinforced polymer composites in load bearing applications requires a detailed understanding of the process induced residual stresses and their effect on the shape distortions. This is utmost necessary in order to have more reliable composite manufacturing since the residual stresses alter the internal stress level of the composite part during the service life and the residual shape distortions may lead to not meeting the desired geometrical tolerances. The occurrence of residual stresses during the manufacturing process inherently contains diverse interactions between the involved physical phenomena mainly related to material flow, heat transfer and polymerization or crystallization. Development of numerical process models is required for virtual design and optimization of the composite manufacturing process which avoids the expensive trial-and-error based approaches. The process models as well as applications focusing on the prediction of residual stresses and shape distortions taking place in composite manufacturing are discussed in this study. The applications on both thermoset and thermoplastic based composites are reviewed in detail

Thermo-Chemical Modelling Strategies for the Pultrusion Process

In the present study, three dimensional (3D) numerical modeling strategies of a thermosetting pultrusion process are investigated considering both transient and steady state approaches. For the transient solution, an unconditionally stable alternating direction implicit Douglas-Gunn (ADI-DG) scheme is implemented as a first contribution of its kind in this specific field of application. The corresponding results are compared with the results obtained from the transient fully implicit scheme, the straightforward extension of the 2D ADI and the steady state approach. The implementation of the proposed approach is described in detail. The calculated temperature and cure degree profiles at steady state are found to agree well with results obtained from similar analyses in the literature. Detailed case studies are carried out investigating the computational accuracy and the efficiency of the 3D ADI-DG solver. It is found that the steady state approach is much faster than the transient approach in terms of the computational time and the number of iteration loops to obtain converged results for reaching the steady state. Hence, it is highly suitable for automatic process optimization which often involves many design evaluations. On the other hand sometimes the transient regime may be of interest and here the proposed ADI-DG method shows to be considerably faster than the transient fully implicit method which is generally used by the general purpose commercial finite element solvers. Finally, using the proposed steady-state approach, a design of experiments is carried out for the curing characteristic of the product based on pulling speed and part thicknes