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Background:The MHC class I chain-related protein A (MICA) and protein B (MICB) participate in tumor immunosurveillance and may be important in colorectal cancer, but have not been examined in colorectal cancer development.Methods:sMICA and sMICB blood levels were measured by SomaScan in Visit 2 (1990–92, baseline) and Visit 3 (1993–95) samples in cancer-free participants in the Atherosclerosis Risk in Communities Study. We selected rs1051792, rs1063635, rs2516448, rs3763288, rs1131896, rs2596542, and rs2395029 that were located in or in the vicinity of MICA or MICB and were associated with cancer or autoimmune diseases in published studies. SNPs were genotyped by the Affymetrix Genome-Wide Human SNP Array. We applied linear and Cox proportional hazards regressions to examine the associations of preselected SNPs with sMICA and sMICB levels and colorectal cancer risk (236 colorectal cancers, 8,609 participants) and of sMICA and sMICB levels with colorectal cancer risk (312 colorectal cancers, 10,834 participants). In genetic analyses, estimates adjusted for ancestry markers were meta-analyzed.Results:Rs1051792-A, rs1063635-A, rs2516448-C, rs3763288-A, rs2596542-T, and rs2395029-G were significantly associated with decreased sMICA levels. Rs2395029-G, in the vicinity of MICA and MICB, was also associated with increased sMICB levels. Rs2596542-T was significantly associated with decreased colorectal cancer risk. Lower sMICA levels were associated with lower colorectal cancer risk in males (HR = 0.68; 95% confidence interval, 0.49–0.96) but not in females (Pinteraction = 0.08).Conclusions:Rs2596542-T associated with lower sMICA levels was associated with decreased colorectal cancer risk. Lower sMICA levels were associated with lower colorectal cancer risk in males.Impact:These findings support an importance of immunosurveillance in colorectal cancer.

Supplemental Table 1 shows the results from previous studies that found significant associations between the pre-selected SNPs and risk of cancers or autoimmune diseases.

Supplemental Table 7 shows the association of sMICA and sMICB levels (continuous variables) and pre-selected SNPsa with risk of CRC stratified by family history of CRC.

Supplemental Table 9 shows the associations between pre-selected SNPs and mean of Visit 2 and Visit 3 sMICA and sMICB levels (continuous variables).

Supplemental Table 6 shows the associations of sMICA and sMICB levels (continuous variables) and pre-selected SNPsb with risk of CRC and subtypes of CRC.

Supplemental table 5 shows the associations between pre-selected SNPs and risk of CRC with and without adjustment for sMICA and sMICB levels.

Resistance to chemotherapeutic drugs is a major cause of treatment failure in Acute Myeloid Leukemias (AML). To better characterize the mechanisms of chemoresistance, we first identified genes whose expression is dysregulated in AML cells resistant to daunorubicin (DNR) or cytarabine (Ara-C), the main drugs used for the induction therapy. The genes found activated are mostly linked to immune signaling and inflammation. Among them, we identified a strong up-regulation of the NOX2 NAPDH oxidase subunit genes (CYBB, CYBA, NCF1, NCF2, NCF4 and RAC2). The ensuing increase in NADPH oxidase activity, which is particularly strong in DNR-resistant cells, participates in the acquisition and/or maintenance of resistance to DNR. In addition, analyzing gp91phox (CYBB-encoded Nox2 catalytic sub-unit) expression at the surface of leukemic blasts from 74 patients at diagnosis showed that NOX2 is generally more expressed and active in leukemic cells from the FAB M4/M5 subtypes compared to FAB M0-M2 ones. Using a gene expression-based score we demonstrate that high NOX2 subunit genes expression is a marker of adverse prognosis, independent of the cytogenetic-based risk classification, in AML patients.

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Seagrass meadows are globally distributed ecosystems found on coastal shelves, where they typically occupy the intertidal and shallow subtidal zones. Their sensitivity to environmental changes and proximity to human activities puts them at risk of degradation; as highly valuable marine habitats and potent carbon sequestration agents, they are therefore the target of numerous conservation programmes.The presence of seagrass strongly influences both wave and current propagation as well as sediment mobility, affecting the morphodynamics of entire estuarine systems. However, quantifying this influence is difficult, because our knowledge of seagrass cover is limited by its dynamic nature. Sensitivity to environmental factors such as nutrient load, available sunlight (mediated by turbidity) and temperature makes seagrass meadows prone to widespread changes in extent and density. Further degradation may occur stochastically through fishing and aquaculture. Conversely, seasonal cycles of high productivity allow meadows to recover and colonize new grounds through clonal and sexual reproduction. We propose a novel and cost-effective method to monitor seagrass cover in shallow waters across its seasonal and interannual variations. Combining machine learning and simple numerical modelling, we create a dense time-series of seagrass extent using over 100 LandSat scenes covering a 20-year-long period in the Venice Lagoon, Italy. Based on an expert-lead ecological survey (2004), we train one binary Random Forest Classifier in each of 5 environmentally-homogeneous geographical subzones, using spectral reflectance in the blue, green, red and near-infrared bands of the corresponding LandSat scene as recognition features. We then predict seagrass presence probability for LandSat scenes spanning the 1999-2019 period. Such predictions are made unstable by their sensitivity to sediment plumes as well as algal or gelbstoff blooms. Classification is therefore constrained by a simple numerical model that simulates clonal and sexual reproduction, regional die-off and punctual degradation. The model examines the potential areas colonised or degraded with respect to previous scenes, iteratively building stabilised maps of seagrass cover over time.Results are verified using further expert-lead estival surveys of the lagoon (2009, 2010, 2017) and of the inlets of Lido, Malamocco and Chioggia (2006 to 2015), as well as 10 digitised seagrass patches for a subsample of 20 invernal scenes. Accuracy metrics improve on the raw predictions (>80% to >85%), and scene-to-scene variability is reduced(>50% to

International audience; By using ZnO thin films doped with Ce, Tb or Eu, deposited via radiofrequency magnetron sputtering, we have developed monochromatic (blue, green and red, respectively) light emitting devices (LEDs). The rare earth ions introduced with doping rates lower than 2% exhibit narrow and intense emission peaks due to electronic transitions in relaxation processes induced after electrical excitation. This study proves zinc oxide to be a good host for these elements, its high conductivity and optical transparency in the visible range being as well exploited as top transparent electrode. After structural characterization of the different doped layers, a device structure with intense electroluminescence is presented, modeled, and electrically and optically characterized. The different emission spectra obtained are compared in a chromatic diagram, providing a reference for future works with similar devices. The results hereby presented demonstrate three operating monochromatic LEDs, as well as a combination of the three species into another one, with a simply-designed structure compatible with current Si technology and demonstrating an integrated red-green-blue emission.

Salt marshes filter pollutants, protect coastlines against storm surges, and sequester carbon, yet are under threat from sea level rise and anthropogenic modification. The sustained existence of the salt marsh ecosystem depends on the topographic evolution of marsh platforms. Quantifying marsh platform topography is vital for improving the management of these valuable landscapes. The determination of platform boundaries currently relies on supervised classification methods requiring near-infrared data to detect vegetation, or demands labour-intensive field surveys and digitisation. We propose a novel, unsupervised method to reproducibly isolate salt marsh scarps and platforms from a digital elevation model (DEM), referred to as Topographic Identification of Platforms (TIP). Field observations and numerical models show that salt marshes mature into subhorizontal platforms delineated by subvertical scarps. Based on this premise, we identify scarps as lines of local maxima on a slope raster, then fill landmasses from the scarps upward, thus isolating mature marsh platforms. We test the TIP method using lidar-derived DEMs from six salt marshes in England with varying tidal ranges and geometries, for which topographic platforms were manually isolated from tidal flats. Agreement between manual and unsupervised classification exceeds 94% for DEM resolutions of 1 m, with all but one site maintaining an accuracy superior to 90% for resolutions up to 3 m. For resolutions of 1 m, platforms detected with the TIP method are comparable in surface area to digitised platforms and have similar elevation distributions. We also find that our method allows for the accurate detection of local block failures as small as 3 times the DEM resolution. Detailed inspection reveals that although tidal creeks were digitised as part of the marsh platform, unsupervised classification categorises them as part of the tidal flat, causing an increase in false negatives and overall platform perimeter. This suggests our method may benefit from combination with existing creek detection algorithms. Fallen blocks and high tidal flat portions, associated with potential pioneer zones, can also lead to differences between our method and supervised mapping. Although pioneer zones prove difficult to classify using a topographic method, we suggest that these transition areas should be considered when analysing erosion and accretion processes, particularly in the case of incipient marsh platforms. Ultimately, we have shown that unsupervised classification of marsh platforms from high-resolution topography is possible and sufficient to monitor and analyse topographic evolution.

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Retreat and progradation make the edges of salt marsh platforms their most active features. If we have a single topographic snapshot of a marsh, is it possible to tell if some areas have retreated or prograded recently or if they are likely to do so in the future? We explore these questions by characterising marsh edge topography in mega-tidal Moricambe Bay (UK) in 2009, 2013 and 2017. We first map outlines of marsh platform edges based on lidar data and from these we generate transverse topographic profiles of the marsh edge 10 m long and 20 m apart. By associating profiles with individual retreat or progradation events, we find that they produce distinct profiles when grouped by change event, regardless of event magnitude. Progradation profiles have a shallow scarp and low relief that decreases with event magnitude, facilitating more progradation. Conversely, steep-scarped, high-relief retreat profiles dip landward as retreat reveals older platforms. Furthermore, vertical accretion of the marsh edge is controlled by elevation rather than its lateral motion, suggesting an even distribution of deposition that would allow bay infilling were it not limited by the migration of creeks. While we demonstrate that marsh edges can be quantified with currently available DTMs, oblique observations are crucial to fully describe scarps and better inform their sensitivity to wave and current erosion.

High energy, rocky coastlines often feature sandy beaches within headland‐bound embayments. Not all such embayments have beaches however, and beaches in embayments can be removed by storms and may subsequently reform. What dictates the presence or absence of an embayed beach and its resilience to storms? In this paper, we explore the effect of offshore slope and wind conditions on nearshore sediment transport within idealised embayments to give insight into nearshore sediment supplies. We use numerical simulations to show that sand can accumulate near shore if the offshore slope is >0.025 m/m, but only under persistent calm conditions. Our modelling also suggests that if sediment in an embayment with an offshore gradient steeper than 0.025 m/m is removed during a period of persistent stormy conditions, it will be unlikely to return in sub‐decadal timescales. In contrast, sediment located in embayments with shallower gradients can reform swiftly in both calm and stormy conditions. Our findings have wide implications for contemporary coastal engineering in the face of future global climate change, but also for Quaternary environmental reconstruction. Our simple method to predict beach stability based on slope can be used to interpret differing responses of embayments to periods of changing coastal storminess such as the medieval climate anomaly‐little ice age (MCA‐LIA) transition.