Epithelial Membrane Protein 2 Suppresses Non-Small Cell Lung Cancer Cell Growth by Inhibition of MAPK Pathway

Epithelial membrane proteins (EMP1-3) are involved in epithelial differentiation and carcinogenesis. Dysregulated expression of EMP2 was observed in various cancers, but its role in human lung cancer is not yet clarified. In this study, we analyzed the expression of EMP1-3 and investigated the biological function of EMP2 in non-small cell lung cancer (NSCLC). The results showed that lower expression of EMP1 was significantly correlated with tumor size in primary lung tumors (p = 0.004). Overexpression of EMP2 suppressed tumor cell growth, migration, and invasion, resulting in a G1 cell cycle arrest, with knockdown of EMP2 leading to enhanced cell migration, related to MAPK pathway alterations and disruption of cell cycle regulatory genes. Exosomes isolated from transfected cells were taken up by tumor cells, carrying EMP2-downregulated microRNAs (miRNAs) which participated in regulation of the tumor microenvironment. Our data suggest that decreased EMP1 expression is significantly related to increased tumor size in NSCLC. EMP2 suppresses NSCLC cell growth mainly by inhibiting the MAPK pathway. EMP2 might further affect the tumor microenvironment by regulating tumor microenvironment-associated miRNAs.     

CD74 and CD44 Expression on CTCs in Cancer Patients with Brain Metastasis

Up to 40% of advance lung, melanoma and breast cancer patients suffer from brain metastases (BM) with increasing incidence. Here, we assessed whether circulating tumor cells (CTCs) in peripheral blood can serve as a disease surrogate, focusing on CD44 and CD74 expression as prognostic markers for BM. We show that a size-based microfluidic approach in combination with a semi-automated cell recognition system are well suited for CTC detection in BM patients and allow further characterization of tumor cells potentially derived from BM. CTCs were found in 50% (7/14) of breast cancer, 50% (9/18) of non-small cell lung cancer (NSCLC) and 36% (4/11) of melanoma patients. The next-generation sequencing (NGS) analysis of nine single CTCs from one breast cancer patient revealed three different CNV profile groups as well as a resistance causing ERS1 mutation. CD44 and CD74 were expressed on most CTCs and their expression was strongly correlated, whereas matched breast cancer BM tissues were much less frequently expressing CD44 and CD74 (negative in 46% and 54%, respectively). Thus, plasticity of CD44 and CD74 expression during trafficking of CTCs in the circulation might be the result of adaptation strategies.     

Disentangling oil weathering using GC x GC. 2. Mass transfer calculations

Hydrocarbon mass transfers to the atmosphere and water column drive the early weathering of oil spills and also control the chemical exposures of many coastal wildlife species. However, in the field, mass transfer rates of individual hydrocarbons to air and water are often uncertain. In the Part 1 companion to this paper, we used comprehensive two-dimensional gas chromatography (GC x GC) to identify distinct signatures of evaporation and dissolution encoded in the compositional evolution of weathered oils. In Part 2, we further investigate patterns of mass removal in GC x GC chromatograms using a mass transfer model. The model was tailored to conditions at a contaminated beach on Buzzards Bay, MA, after the 2003 Bouchard 120 oil spill. The model was applied to all resolved hydrocarbon compounds in the C11-C24 boiling range, based on their GC x GC-estimated vapor pressures and aqueous solubilities. With no fitted parameters, the model successfully predicted GC x GC chromatogram patterns of mass removal associated with evaporation, water-washing, and diffusion-limited transport. This enabled a critical field evaluation of the mass transfer model and also allowed mass apportionment estimates of hundreds of individual hydrocarbon compounds to air and water. Ultimately, this method should improve assessments of wildlife exposures to oil spill hydrocarbons.     

SARANA: language, compiler and run-time system support for spatially aware and resource-aware mobile computing

Increasingly, spatial awareness plays a central role in many distributed and mobile computing applications. Spatially aware applications rely on information about the geographical position of compute devices and their supported services in order to support novel functionality. While many spatial application drivers already exist in mobile and distributed computing, very little systems research has explored how best to program these applications, to express their spatial and temporal constraints, and to allow efficient implementations on highly dynamic real-world platforms. This paper proposes the SARANA system architecture, which includes language and run-time system support for spatially aware and resource-aware applications. SARANA allows users to express spatial regions of interest, as well as trade-offs between quality of result (QoR), latency and cost. The goal is to produce applications that use resources efficiently and that can be run on diverse resource-constrained platforms ranging from laptops to personal digital assistants and to smart phones. SARANA's run-time system manages QoR and cost trade-offs dynamically by tracking resource availability and locations, brokering usage/pricing agreements and migrating programs to nodes accordingly. A resource cost model permeates the SARANA system layers, permitting users to express their resource needs and QoR expectations in units that make sense to them. Although we are still early in the system development, initial versions have been demonstrated on a nine-node system prototype.     

Stereoselectivity of Four (R)‐Selective Transaminases for the Asymmetric Amination of Ketones

Four (R)‐ω‐transaminases originating from Hyphomonas neptunium (HN‐ωTA), Aspergillus terreus (AT‐ωTA) and Arthrobacter sp. (ArR‐ωTA), as well as an evolved transaminase (ArRmut11‐ωTA) were successfully employed for the amination of prochiral ketones leading to optically pure (R)‐amines. The first three transaminases displayed perfect stereoselectivity for the amination of all substrates tested (ee >99%). Furthermore, the transaminase AT‐ωTA led in most cases to better conversion than ArR‐ωTA and HN‐ωTA using D ‐alanine as amine donor. α‐Tetralone, which was the only substrate not accepted by HN‐ωTA, ArR‐ωTA, and AT‐ωTA, was successfully transformed with perfect enantioselectivity (ee >99%) into the corresponding optically pure amine employing the variant ArRmut11‐ωTA.