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Myc proteins (c-myc, Mycn and Mycl) target proliferative and apoptotic pathways vital for progression in cancer. Amplification of the MYCN gene has emerged as one of the clearest indicators of aggressive and chemotherapy-refractory disease in children with neuroblastoma, the most common extracranial solid tumor of childhood. Phosphorylation and ubiquitin-mediated modulation of Myc protein influence stability and represent potential targets for therapeutic intervention. Phosphorylation of Myc proteins is controlled in-part by the receptor tyrosine kinase/phosphatidylinositol 3-kinase/Akt/mTOR signaling, with additional contributions from Aurora A kinase. Myc proteins regulate apoptosis in part through interactions with the p53/Mdm2/Arf signaling pathway. Mutation in p53 is commonly observed in patients with relapsed neuroblastoma, contributing to both biology and therapeutic resistance. This review examines Myc function and regulation in neuroblastoma, and discusses emerging therapies that target Mycn.

As a neuroendocrine tumor, neuroblastoma expresses various gastrointestinal (GI) hormones, such as vasoactive intestinal peptide, gastrin‐releasing peptide (GRP), neurotensin, and somatostatin, which exert diverse cellular functions in neuroblastoma. In particular, we have recently found that GRP and its cell surface receptor, GRP‐R, are abundantly expressed in neuroblastomas. Moreover, more advanced‐stage neuroblastomas demonstrated an increased level of GRP‐R, suggesting an important role of GRP in aggressive tumor behavior. This review describes the role of several GI hormones commonly expressed in neuroblastoma and discusses in depth the mitogenic actions of GRP in neuroblastoma. In addition, the molecular mechanisms involved in the GRP‐induced stimulation of neuroblastoma cell growth are discussed. Our study results demonstrate a role of GRP as an autocrine/paracrine growth factor and elucidate involvement of specific intracellular signaling, the phosphatidylinositol 3‐kinase pathway, in the growth regulation of neuroblastoma.

A fully coupled meteorology-chemistry-aerosol model (WRF-Chem) is applied to simulate mineral dust and its shortwave (SW) radiative forcing over North Africa. Two dust emission schemes (GOCART and DUSTRAN) and two aerosol models (MADE/SORGAM and MOSAIC) are adopted in simulations to investigate the modeling sensitivities to dust emissions and aerosol size treatments. The modeled size distribution and spatial variability of mineral dust and its radiative properties are evaluated using measurements (ground-based, aircraft, and satellites) during the AMMA SOP0 campaign from 6 January to 3 February of 2006 (the SOP0 period) over North Africa. Two dust emission schemes generally simulate similar spatial distributions and temporal evolutions of dust emissions. Simulations using the GOCART scheme with different initial (emitted) dust size distributions require ~40% difference in total emitted dust mass to produce similar SW radiative forcing of dust over the Sahel region. The modal approach of MADE/SORGAM retains 25% more fine dust particles (radius<1.25 μm) but 8% less coarse dust particles (radius>1.25 μm) than the sectional approach of MOSAIC in simulations using the same size-resolved dust emissions. Consequently, MADE/SORGAM simulates 11% higher AOD, up to 13% lower SW dust heating rate, and 15% larger (more negative) SW dust radiative forcing at the surface than MOSAIC over the Sahel region. In the daytime of the SOP0 period, the model simulations show that the mineral dust heats the lower atmosphere with an average rate of 0.8 ± 0.5 K day−1 over the Niamey vicinity and 0.5 ± 0.2 K day−1 over North Africa and reduces the downwelling SW radiation at the surface by up to 58 W m−2 with an average of 22 W m−2 over North Africa. This highlights the importance of including dust radiative impact in understanding the regional climate of North Africa. When compared to the available measurements, the WRF-Chem simulations can generally capture the measured features of mineral dust and its radiative properties over North Africa, suggesting that the model is suitable for more extensive simulations of dust impact on regional climate over North Africa.

A suite of physical parameterizations (deep and shallow convection, turbulent boundary layer, aerosols, cloud microphysics, and cloud fraction) from the global climate model Community Atmosphere Model version 5.1 (CAM5) has been implemented in the regional model Weather Research and Forecasting with chemistry (WRF-Chem). A downscaling modeling framework with consistent physics has also been established in which both global and regional simulations use the same emissions and surface fluxes. The WRF-Chem model with the CAM5 physics suite is run at multiple horizontal resolutions over a domain encompassing the northern Pacific Ocean, northeast Asia, and northwest North America for April 2008 when the ARCTAS, ARCPAC, and ISDAC field campaigns took place. These simulations are evaluated against field campaign measurements, satellite retrievals, and ground-based observations, and are compared with simulations that use a set of common WRF-Chem parameterizations. This manuscript describes the implementation of the CAM5 physics suite in WRF-Chem, provides an overview of the modeling framework and an initial evaluation of the simulated meteorology, clouds, and aerosols, and quantifies the resolution dependence of the cloud and aerosol parameterizations. We demonstrate that some of the CAM5 biases, such as high estimates of cloud susceptibility to aerosols and the underestimation of aerosol concentrations in the Arctic, can be reduced simply by increasing horizontal resolution. We also show that the CAM5 physics suite performs similarly to a set of parameterizations commonly used in WRF-Chem, but produces higher ice and liquid water condensate amounts and near-surface black carbon concentration. Further evaluations that use other mesoscale model parameterizations and perform other case studies are needed to infer whether one parameterization consistently produces results more consistent with observations.

Ocean melting has thinned Antarctica’s ice shelves at an increasing rate over the past two decades, leading to loss of grounded ice. The Ross Ice Shelf is currently close to steady state but geological records indicate that it can disintegrate rapidly, which would accelerate grounded ice loss from catchments equivalent to 11.6 m of global sea level rise. Here, we use data from the ROSETTA-Ice airborne survey and ocean simulations to identify the principal threats to Ross Ice Shelf stability. We locate the tectonic boundary between East and West Antarctica from magnetic anomalies and use gravity data to generate a new high-resolution map of sub-ice-shelf bathymetry. The tectonic imprint on the bathymetry constrains sub-ice-shelf ocean circulation, protecting the ice shelf grounding line from moderate changes in global ocean heat content. In contrast, local, seasonal production of warm upper-ocean water near the ice front drives rapid ice shelf melting east of Ross Island, where thinning would lead to faster grounded ice loss from both the East and West Antarctic ice sheets. We confirm high modelled melt rates in this region using ROSETTA-Ice radar data. Our findings highlight the significance of both the tectonic framework and local ocean–atmosphere exchange processes near the ice front in determining the future of the Antarctic Ice Sheet.The boundary between West and East Antarctica is a tectonic feature that bisects the Ross Ice Shelf. This boundary constrains ocean circulation under the ice, which affects ice stability, according to airborne survey data and ocean simulations.

The Weather Research and Forecasting model coupled with chemistry (WRF-Chem) is modified to include a volatility basis set (VBS) treatment of secondary organic aerosol formation. The VBS approach, coupled with SAPRC-99 gas-phase chemistry mechanism, is used to model gas-particle partitioning and multiple generations of gas-phase oxidation of organic vapors. In addition to the detailed 9-species VBS, a simplified mechanism using 2 volatility species (2-species VBS) is developed and tested for similarity to the 9-species VBS in terms of both mass and oxygen-to-carbon ratios of organic aerosols in the atmosphere. WRF-Chem results are evaluated against field measurements of organic aerosols collected during the MILAGRO 2006 campaign in the vicinity of Mexico City. The simplified 2-species mechanism reduces the computational cost by a factor of 2 as compared to 9-species VBS. Both ground site and aircraft measurements suggest that the 9-species and 2-species VBS predictions of total organic aerosol mass as well as individual organic aerosol components including primary, secondary, and biomass burning are comparable in magnitude. In addition, oxygen-to-carbon ratio predictions from both approaches agree within 25 %, providing evidence that the 2-species VBS is well suited to represent the complex evolution of organic aerosols. Model sensitivity to amount of anthropogenic semi-volatile and intermediate volatility (S/IVOC) precursor emissions is also examined by doubling the default emissions. Both the emission cases significantly under-predict primary organic aerosols in the city center and along aircraft flight transects. Secondary organic aerosols are predicted reasonably well along flight tracks surrounding the city, but are consistently over-predicted downwind of the city. Also, oxygen-to-carbon ratio predictions are significantly improved compared to prior studies by adding 15 % oxygen mass per generation of oxidation; however, all modeling cases still under-predict these ratios downwind as compared to measurements, suggesting a need to further improve chemistry parameterizations of secondary organic aerosol formation.

Predicting the consequences of manipulating genotype (G) and agronomic management (M) on agricultural ecosystem performances under future environmental (E) conditions remains a challenge. Crop modelling has the potential to enable society to assess the efficacy of G × M technologies to mitigate and adapt crop production systems to climate change. Despite recent achievements, dedicated research to develop and improve modelling capabilities from gene to global scales is needed to provide guidance on designing G × M adaptation strategies with full consideration of their impacts on both crop productivity and ecosystem sustainability under varying climatic conditions. Opportunities to advance the multiscale crop modelling framework include representing crop genetic traits, interfacing crop models with large-scale models, improving the representation of physiological responses to climate change and management practices, closing data gaps and harnessing multisource data to improve model predictability and enable identification of emergent relationships. A fundamental challenge in multiscale prediction is the balance between process details required to assess the intervention and predictability of the system at the scales feasible to measure the impact. An advanced multiscale crop modelling framework will enable a gene-to-farm design of resilient and sustainable crop production systems under a changing climate at regional-to-global scales. Climate change will not only challenge current crop modeling techniques, but require new types of models that can account for and operate at multiple scales to measure adaptation and resilience.

A diverse collection of models are used to simulate the marine boundary layer in the southeast Pacific region during the period of the October–November 2008 VOCALS REx (VAMOS Ocean Cloud Atmosphere Land Study Regional Experiment) field campaign. Regional models simulate the period continuously in boundary-forced free-running mode, while global forecast models and GCMs (general circulation models) are run in forecast mode. The models are compared to extensive observations along a line at 20° S extending westward from the South American coast. Most of the models simulate cloud and aerosol characteristics and gradients across the region that are recognizably similar to observations, despite the complex interaction of processes involved in the problem, many of which are parameterized or poorly resolved. Some models simulate the regional low cloud cover well, though many models underestimate MBL (marine boundary layer) depth near the coast. Most models qualitatively simulate the observed offshore gradients of SO2, sulfate aerosol, CCN (cloud condensation nuclei) concentration in the MBL as well as differences in concentration between the MBL and the free troposphere. Most models also qualitatively capture the decrease in cloud droplet number away from the coast. However, there are large quantitative intermodel differences in both means and gradients of these quantities. Many models are able to represent episodic offshore increases in cloud droplet number and aerosol concentrations associated with periods of offshore flow. Most models underestimate CCN (at 0.1% supersaturation) in the MBL and free troposphere. The GCMs also have difficulty simulating coastal gradients in CCN and cloud droplet number concentration near the coast. The overall performance of the models demonstrates their potential utility in simulating aerosol–cloud interactions in the MBL, though quantitative estimation of aerosol–cloud interactions and aerosol indirect effects of MBL clouds with these models remains uncertain.

Pharmacologically difficult targets, such as MYC transcription factors, represent a major challenge in cancer therapy. For the childhood cancer neuroblastoma, amplification of the oncogene MYCN is associated with high-risk disease and poor prognosis. Here, we deployed genome-scale CRISPR-Cas9 screening of MYCN-amplified neuroblastoma and found a preferential dependency on genes encoding the polycomb repressive complex 2 (PRC2) components EZH2, EED, and SUZ12. Genetic and pharmacological suppression of EZH2 inhibited neuroblastoma growth in vitro and in vivo. Moreover, compared with neuroblastomas without MYCN amplification, MYCN-amplified neuroblastomas expressed higher levels of EZH2. ChIP analysis showed that MYCN binds at the EZH2 promoter, thereby directly driving expression. Transcriptomic and epigenetic analysis, as well as genetic rescue experiments, revealed that EZH2 represses neuronal differentiation in neuroblastoma in a PRC2-dependent manner. Moreover, MYCN-amplified and high-risk primary tumors from patients with neuroblastoma exhibited strong repression of EZH2-regulated genes. Additionally, overexpression of IGFBP3, a direct EZH2 target, suppressed neuroblastoma growth in vitro and in vivo. We further observed strong synergy between histone deacetylase inhibitors and EZH2 inhibitors. Together, these observations demonstrate that MYCN upregulates EZH2, leading to inactivation of a tumor suppressor program in neuroblastoma, and support testing EZH2 inhibitors in patients with MYCN-amplified neuroblastoma.