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Atmospheric chemistry models play a major role for relating greenhouse gases and pollutants concentrations to emissions at high temporal resolutions over large areas. On that account, it is fundamental to use up-to-date anthropogenic emissions maps as model inputs. Despite efforts by researchers to create global emission datasets with high temporal resolutions, for countries with no national data, generic activity maps and emission factors are used, thus the accurate representation of the anthropogenic emissions in a local scale still remains challenging. This study presents an improved spatially explicit dataset for anthropogenic emissions of CO2 and NOx over the Middle-East, a region characterized by extensive gas power plants and heavy industries operations. Our dataset was developed by combining a detailed infrastructure map for point sources in the area and it is used to simulate the distribution of CO2 and NO2 using the WRF-Chem mesoscale atmospheric transport chemistry model. Furthermore, the chemistry scheme of the WRF-Chem model in the simulation of CO2 and NO2 plumes is examined, in comparison with satellite observations. In the framework of the Eastern Mediterranean and Middle East – Climate and Atmosphere Research (EMME-CARE) project, our new detailed infrastructure map for power plants and gas flaring has been implemented in WRF-Chem simulations for the Middle-East region to complete the Emission Database for Global Atmospheric Research (EDGAR) as input. The EDGAR data consists of emissions by various sectors such as power plants, industry, residential, transportation and agriculture. Furthermore, hourly scaling factors have been applied to the anthropogenic emissions according to the electricity consumption of the particular urban areas, taking into account the weekly as well as the monthly variations. The periods under study are January 2021 and June 2021. By comparing the WRF-Chem outputs to TROPOMI satellite observations for NO2, the results show that the addition of point sources was crucial for the detection of some NO2 plumes. Moreover, the WRF-Chem model systematically overestimated the NO2 concentrations in the area with the current EDGAR dataset, therefore we introduced a new relationship between monthly and annual emissions for the Middle-East region. By carrying out WRF-Chem simulations with NO2 acting as a passive tracer it was also possible to examine the impact of the model chemistry in NO2 plumes development. Finally, CO2 was also simulated by the WRF-Chem model as a passive tracer and the results showed a good agrement with XCO2 data observed by the OCO-2 and OCO-3 instruments.

International audience; Fossil fuel carbon dioxide (CO 2ff), the main driver of global warming and climate change, is often co-emitted with nitrogen oxides (NO x) and precursors to ground-level ozone from anthropogenic sources like power plants or vehicles. In urban and suburban areas, satellite-based NO 2 can be used as a proxy to track the emissions of CO 2ff. Because of NO 2 's shorter lifetime, urban NO 2 plumes are more distinguishable from backgrounds and more sensitive to variations in emissions. However, the combination of these two gases is limited by the asynchrony among NO 2 and CO 2 monitoring satellites. We used CO 2ff simulated by the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) model to reconcile the tropospheric NO 2 vertical column density (VCD) from Tropospheric Monitoring Instrument (TROPOMI) and column-averaged dry-air mole fractions of carbon dioxide enhancements (ΔXCO 2) from Orbiting Carbon Observatory 3 (OCO-3) Snapshot Area Maps (SAMs) over a multicity area, Washington D.C.-Baltimore (DC-Balt), and a basin city, Mexico City. NO 2 /CO 2ff ratios over DC-Balt are smaller than Mexico City, indicative of stricter emission restrictions, a more combustionefficient vehicle fleet, and higher combustion efficiency due to lower altitude in DC-Balt. For single-track cases, the spatial correlations between NO 2 and ΔXCO 2 over Mexico City are stronger than DC-Balt because the NO 2 and CO 2 are mostly trapped in the valley of Mexico City, while DC-Balt is severely affected by distant sources (i. e., US East Coast cities). Using multi-track averaging, spatial correlation coefficients increase with the number of days used for averaging. The correlations reached a maximum when averaging >12 continuous images for DC-Balt and >10 continuous images for Mexico City. This finding indicates that multi-track averaging using modeled CO 2ff as a proxy is helpful to filter the noise in single-track images, to cancel the interference from distant sources, and to magnify correlations between NO 2 and CO 2ff. Mexico City showed stronger spatial correlations but weaker temporal correlations than DC-Balt due to biomass burning hot spots and large transport errors caused by the trapping effects of the surrounding mountains. Tracking the 20-day moving average of CO 2ff emissions using TROPOMI NO 2 seems technically feasible, considering the relationship between correlation coefficients and the number of available satellite images.

Currently, there are insufficient indicators for the reliable assessment of treatment response following neoadjuvant chemoradiotherapy (nCRT) in patients with esophageal squamous cell carcinoma (ESCC). Considering the essential role of protein-coding and non-coding RNAs in gene regulation and cellular processes, we systematically explored the molecular features and clinical significance of mRNA and lncRNA in 249 pretreatment biopsies from four hospitals in three districts with a high incidence of ESCC patients in China.During the discovery phrase, 13 differentially expressed genes were identified and validated between samples with a complete pathological response (pCR) and those with an incomplete pathological response (pCR). Subsequently, we constructed a predictive mRNA and lncRNA signature (SERPINE1, LINC00592, and PRKAG2-AS1) using Fisher's linear discriminant analysis (FLDA) with stepwise variant-selection, followed by validation of its predictive ability in both internal and external cohorts.Our signature showed great value in predicting the response to nCRT among ESCC samples and acted as an independent predictive indicator, in addition to demonstrating great potential in estimating patient prognosis. Interestingly, we found that patients with a high signature score had lower PD-L1 and IDO1 expression levels but higher CD8The present study identified a promising three-gene-based predictive signature that has powerful clinical implications for the identification of pCR and a good prognosis among patients with ESCC. Further immune-related exploration may provide an opportunity for future therapeutic combination.

Objective To investigate the clinicopathologic features and immunophenotype of primary squamous cell carcinoma of the breast (PSCCB) with HER2 overexpression. Methods Two cases of PSCCB with HER2 overexpression were retrospectively reviewed, and the pathological features, immunophenotype and prognosis were discussed. Results The tumor showed malignant squamous cells arranged in sheets, groups and nests, forming keratin-pearl and intercellular bridges. Immunohistochemical (IHC) analysis showed that the tumor cells were positive for 34βE12, p63, CK5/6, E-cadherin and P120, while negative for ER and PR. Furthermore, HER2 overexpression showed strong continuous expression in cell membrane with a score of 3+ by IHC, or amplification by FISH. Conclusions PSCCB is a rare tumor in breast cancer and HER2 overexpression is rather unusual in PSCCB. The diagnosis mainly depends on the clinicopathologic features together with the immunophenotype. HER2 positive indicates poor prognosis. However, targeted therapy for HER2 may be a new hope for patients.

Background Methylated SDC2 and TFPI2 are widely used for colorectal cancer (CRC) detection. However, they often miss some CRCs, which directly diminishes the sensitivity. Further investigations of the underlying mechanisms leading to the missed samples will facilitate developing more eligible methylation markers. Methods CRC samples from TCGA and GEO datasets were divided into three groups, High-methylation/ High-methylation (HH), High-methylation/Low-methylation (HL), and Low-methylation/Low-methylation (LL) according to the methylation status of SDC2 and TFPI2 promoters. Variations in age, tumor location and microsatellite instable were then assessed between the three groups and verified in our custom cohort. Results Samples of HL group preferred to derive from left-sided CRCs (P P = 0.0055). Almost all mutations of BRAF, one of the five typical CpG island methylator phenotype (CIMP) related genes, were observed in HH group (HH/HL/LL: 51/0/1, P = 0.018). Besides, older patients were frequently found in HH group. Expression analysis identified 37, 84, and 22 group-specific differentially expressed genes (DEGs) for HH, HL, and LL, respectively. Functional enrichment analysis revealed that HH-specific DEGs were mainly related to transcription regulation, while LL-specific DEGs were enriched in the biological processes of extracellular matrix interaction and cell migration. Conclusions The current study revealed that the performance of methylation-based markers might be affected by tumor location, patient age, mutation load and MSI, and these respective sides should be considered when developing new methylation markers for CRC detection.

Cold fronts are mesoscale meteorological phenomena that play important roles in chemical transport processes. Effects of a single cold front episode on surface ozone may vary since meteorological factors may alter ozone in different (increasing or decreasing) directions. We studied cold front events and their effects on surface maximum daily 8-h average (MDA8) ozone over the Contiguous United States (CONUS) during 2003–2017. The average number of cold front days in the CONUS was 50.02 days per year per site with a slightly increasing trend (1.06 per year) during 2003–2017. The Rocky Mountains blocked most cold fronts for the Northwest and the Southwest. Percentages of 24 h back trajectories from north side in 12 sample cities show that cold front effects exist ±12 h to cold fronts' arrival at least. Compared to all days’ average, MDA8 ozone differs from prefrontal days, cold front 1st days, cold front 2 + days, and post frontal days by 0.10, −0.94, −0.84, and −1.89 ppbv (−0.89 ppbv on average), respectively. By contrast, they overlapped 9.85%, 5.82%, 0.89%, and 5.04%, respectively (21.60% in total) with ozone exceedance days. Regional consistent long-term effects of cold fronts on surface MDA8 ozone have been found. Enhancements during prefrontal days can be seen in the Northeast and the Midwest during non-winter seasons. For cold front days and post frontal days, ozone differences in the Southwest, the Northwest, and the Northeast were negative in non-winter seasons then reversed to positive in winter. The areas along the coast of the Gulf of Mexico showed positive ozone difference in non-winter seasons and expanded to the inland area during summer then reversed to negative in winter. Synergy of cold fronts and other climatic and meteorological factors (e.g., prefrontal stagnation, southerly flow from the Gulf of Mexico, and winter stratospheric intrusions) can preliminarily explain these consistent long-term effects.

Objective: To investigate the clinicopathologic features and immunophenotype of invasive-stratified mucin-producing carcinoma (ISMC). Methods: We retrospectively analyzed three patients who underwent surgery for pathologically confirmed ISMC from January 2017 to December 2017 in Anyang Tumor Hospital. The pathological features, immunophenotype, and prognosis were discussed. Results: Clinical symptoms and imaging were atypical. Microscopically, the arrangement of tumor cells is close to that of squamous cell carcinoma, showing flake or nested growth. Morphologically, tumor cells were reminiscent of adenocarcinoma. The tumor cells showed abundant intracytoplasmic mucus which routinely created spacing between adjacent nuclei. The nuclei was round or oval with irregular karyotypes, thick nuclear membrane, staining empty light, rough chromatin, visible small nucleoli. Mucous vacuoles or pink-stained foam were visible in the cytoplasm. Mitotic features and apoptotic bodies were seen in the invasive component of all three cases, whereas all but one of these showed a neutrophil-dominant inflammatory cells infiltration. A large number of histocytes were found in the stroma of two cases. Special staining of mucus confirmed the presence of mucus in cytoplasm. Immunohistochemical results showed that tumor cells were strongly and diffusely positive for p16 and CK7 and had high Ki-67 expression. Conclusions: ISMC is a rare tumor in female genital tract and is often misdiagnosed as squamous cell carcinoma and other cervical cancers. The diagnosis mainly depends on the unique clinicopathologic features together with the immunophenotype. Treatment and prognosis, like other cervical cancer, are mainly based on clinical stages.

International audience; NASA's Orbiting Carbon Observatory-3 (OCO-3) was designed to support the quantification and monitoring of anthropogenic CO 2 emissions. Its Snapshot Area Map (SAM) and target mode measurements provide an innovative dataset for carbon studies on sub-city scales. Unlike any other current space-based instrument, OCO-3 has the ability to scan large contiguous areas of emission hot spots like cities, power plants, and volcanoes. These measurements result in dense, fine-scale spatial maps of column averaged dry-air mole fractions of carbon dioxide (X CO 2). For the first time, we present and analyze X CO 2 distributions over the Los Angeles megacity (LA) derived from OCO-3 SAM and target mode observations. Urban X CO 2 enhancements range from 0 − 6 ppm (median enhancements ≃ 2 ppm) relative to a clean background and show excellent agreement with nearby ground-based TCCON measurements of X CO 2. OCO-3's dense observations reveal intra-urban variations of X CO 2 over the city that have never been observed from space before. The spatial variations are mainly driven by the complex fossil fuel emission patterns and meteorological conditions in the LA Basin and are in good agreement with those from co-located TROPOMI measurements of co-emitted NO 2. Differences between measured and simulated X CO 2 enhancements from two models (WRF-Chem and X-STILT) are typically below 1 ppm with larger differences for some sub regions. Both models capture the observed intra-urban X CO 2 gradients. Further, OCO-3's multi-swath measurements capture about three times as much of the city emissions compared to single-swath overpasses. OCO-3's frequent target and SAM mode observations will pave the way to constrain urban emissions at finer, sub-city scales.

Atmospheric Carbon dioxide (CO2) has reached 150% of its pre-industrial level and has contributed to more than 60% of the global direct radiative forcing from Greenhouse Gases (GHGs). Global fossil fuel CO2 (CO2ff) emissions exceeded 38 Gt in 2020 accounting for more than 77% of fossil fuel greenhouse gas emissions. City areas, where gathering more than 55% of the global population, alone contributed to more than 70% of anthropogenic CO2ff emissions. Proper management of fossil fuel sources designed to achieve the 2.0-degree temperature threshold of the Paris Agreement requires accurate monitoring of emissions from major metropolitan areas globally to track this commitment. Satellite-based inversion is unique among the “top-down” approaches, potentially allowing us to track and monitor fossil fuel emission changes over cities globally. However, its accuracy is still limited by incomplete background information, cloud blockages, aerosol contaminations, and uncertainties in models and priori fluxes. To evaluate the current potential of space-based quantification techniques, we present the first attempt to monitor long-term changes in CO2ff emissions based on the OCO-2 satellite measurements over a fast-growing Asian metropolitan area: Lahore, Pakistan. We first examined the OCO-2 data availability at the global scale. About 17% of OCO-2 soundings are marked as high-quality soundings by quality flags over the global 70 most populated cities. Cloud blockage and aerosol contamination are the two main causes of data loss. As an attempt to recover additional retrievals, we evaluated the effectiveness of OCO-2 quality flags at the city level by comparing the satellite/reference ratios derived from three independent methods (WRF-Chem, X-STILT, and Flux cross-sectional integration method), all based on the ODIAC inventory. The satellite/reference ratios of the high-quality tracks better converged across the three methods compared to the all-data tracks with reduced uncertainties in emissions. Thus, we conclude that OCO-2 quality flags are highly relevant to filter unrealistic OCO-2 retrievals even at local scales, although originally designed for global-scale studies. All three methods consistently suggested that the ratio medians are greater than 1, which implies that the ODIAC slightly underestimated the CO2ff emissions over Lahore. The posterior CO2ff emission trend was about 734 kt C/year (i.e., an annual 6.7% increase), while the a priori emission ODIAC showed that the trend was about 650 kt C/year (i.e., an annual 5.9% increase). The 10,000 Monte Carlo simulations of the Mann-Kendall upward trend test showed that less than 10% prior uncertainty for 8 tracks (or less than 20% prior uncertainty for 25 tracks) is required to achieve a greater-than-50% trend significant possibility at a 95% confidence level. It implies that the trend is driven by the prior rather than the optimized emissions. The key to improving the role of satellite and model in emission trend detection is to obtain more high-quality tracks near metropolitan areas to achieve significant constraints from XCO2 retrievals.

The OCO-3 instrument was launched on May 4, 2019 from Kennedy Space Center to the International Space Station. Since August 2019, the instrument has taken measurements of reflected sunlight in three near-infrared bands from which column averaged dry-air mole fractions of carbon dioxide (XCO2) are derived. The instrument was specifically designed to measure anthropogenic emissions and its snapshot area map (SAM) and target (TG) observational modes allow to scan large contiguous areas (up to 80×80 km2) on a single overpass over emission hotspots like cities, power plants, or volcanoes. These measurements result in fine-scale spatial maps of XCO2 unlike what can be done with any other current space-based instrument. Here, we present and analyze XCO2 distributions over the Los Angeles (LA) megacity derived from multiple OCO-3 TG and SAM mode observations using the vEarly data product. We find that urban XCO2 values are elevated by 2-6 ppm relative to a clean background. The dense, high resolution OCO-3 observations reveal fine-scale, intra-urban variations of XCO2 over the LA megacity that have not been observed from space before. We further analyze the intra-urban characteristics and compare the XCO2 enhancements observed by OCO-3 with simulated values from two models that can resolve XCO2 variations across the city: an Eulerian (WRF-Chem) and a Lagrangian approach (X-STILT). We show that the observed variations are mainly driven by the complex and highly variable meteorological condition in the LA Basin. Median XCO2 differences between model and observation are typically below 1.3 ppm over the entirety of the LA megacity with slightly larger differences for some sub regions. Further, we find that OCO-3’s multi-swath measurements capture about three times as much of the city emissions compared to single-swath overpasses. In the future, these observations will help to better constrain urban emissions at finer spatiotemporal scales.

BackgroundSDC2 methylation is a potential biomarker for colorectal cancer detection with specificity over 90%, but its sensitivity is usually less than 90%. The study aims to improve the sensitivity and specificity by adding TFPI2 methylation as a complement.MethodsTFPI2 was identified using colorectal cancer samples from TCGA database with SDC2 methylation level lower than 0.2. SDC2/TFPI2 methylation specific PCR was performed using tissue samples (184 cancer and 54 healthy control) and stool samples (289 cancer, 190 adenoma and 217 healthy control). Detection sensitivity was calculated among tumors from different biopsy locations.Results88% of 50 TCGA specimens of colorectal cancer with SDC2 methylation level lower than 0.2 showed TFPI2 methylation level higher than 0.2. SDC2/TFPI2 combined detection in stool specimens showed AUC value of 0.98 with the specificity of 96.40% and sensitivity of 96.60% for cancer vs control, AUC value of 0.87 with the specificity of 95.70% and sensitivity of 80.00% for adenoma vs control. The sensitivities were much higher than those of SDC2, and the improvement was most significant in lesions from left colon and rectum.ConclusionsThis research indicated that the addition of TFPI2 can reduce the miss detection rate of colorectal cancer and adenomas while maintaining high specificity, probably by finding neoplasms in left colon.The method is non-invasive and has good compliance, also avoiding the pain of bowel preparation and risk of cross infection during endoscopy, so it will provide an easy and precise tool for colorectal cancer and its precancerous lesions screening.

Fossil fuel (FF) burning, the main energy source of the modern world’s economy, remains the major source of anthropogenic carbon dioxide (CO2) and pollutants in the atmosphere. Based on 18 years (2001–2018) of aerosol optical depth (AOD) data from Moderate Resolution Imaging Spectroradiometer satellite, FFCO2 emissions from the Open-Data Inventory for Anthropogenic Carbon dioxide, and gross domestic product (GDP) data from the World Bank, we found that air quality, FF consumption, and economy are strongly bonded at the continental scale but decoupled at the national level under favorable policies. The comparison of AOD vs PM2.5 and NO2 over urbanized areas shows that the pollutants leading to the AOD load can vary significantly by country. A strong connection between GDP and FFCO2 emissions indicates that economic growth deeply replies on FF consumption in most countries. Meanwhile, air pollution is more associated with the growing trend than the level of development of a country. With more mature technologies and renewable energy, economies can keep growing without compromising their environment and population health.

International audience; Urban areas, where more than 55% of the global population gathers, contribute more than 70% of anthropogenic fossil fuel carbon dioxide (CO2ff) emissions. Accurate quantification of CO2ff emissions from urban areas is of great importance for formulating global warming mitigation policies to achieve carbon neutrality by 2050. Satellite-based inversion techniques are unique among “top-down” approaches, potentially allowing us to track CO2ff emission changes over cities globally. However, their accuracy is still limited by incomplete background information, cloud blockages, aerosol contamination, and uncertainties in models and priori emission inventories. To evaluate the current potential of space-based quantification techniques, we present the first attempt to monitor long-term changes in CO2ff emissions based on the OCO-2 satellite measurements of column-averaged dry-air mole fractions of CO2 (XCO2) over a fast-growing Asian metropolitan area: Lahore, Pakistan. We first examined the OCO-2 data availability at global scale. About 17% of OCO-2 soundings over the global 70 most populated cities from 2014 to 2019 are marked as high-quality. Cloud blockage and aerosol contamination are the two main causes of data loss. As an attempt to recover additional soundings, we evaluated the effectiveness of OCO-2 quality flags at the city level by comparing three flux quantification methods (WRF-Chem, X-STILT, and the flux cross-sectional integration method). The satellite/bottom-up emissions (OCO-2/ODIAC) ratios of the high-quality tracks with reduced uncertainties in emissions are better agreed across the three methods compared to the all-data tracks. This demonstrates that OCO-2 quality flags are useful filters of low-quality OCO-2 retrievals at local scales. All three methods consistently suggested that the ratio medians are greater than 1, implying that the ODIAC slightly underestimated CO2ff emissions over Lahore. Additionally, our estimation of the a posteriori CO2ff emission trend was about 734 kt C/year (i.e., an annual 6.7% increase). 10,000 Monte Carlo simulations of the Mann-Kendall upward trend test showed that less than 10% prior uncertainty for 8 tracks (or less than 20% prior uncertainty for 25 tracks) is required to achieve a greater-than-50% trend significant possibility at a 95% confidence level. It implies that the trend is driven by the prior and not due to the assimilation of OCO-2 retrievals. The key to improving the role of satellite data in CO2 emission trend detection lies in collecting more frequent high-quality tracks near metropolitan areas to achieve significant constraints from XCO2 retrievals.

Author(s): Liu, Zhu; Ciais, Philippe; Deng, Zhu; Lei, Ruixue; Davis, Steven J; Feng, Sha; Zheng, Bo; Cui, Duo; Dou, Xinyu; Zhu, Biqing; Guo, Rui; Ke, Piyu; Sun, Taochun; Lu, Chenxi; He, Pan; Wang, Yuan; Yue, Xu; Wang, Yilong; Lei, Yadong; Zhou, Hao; Cai, Zhaonan; Wu, Yuhui; Guo, Runtao; Han, Tingxuan; Xue, Jinjun; Boucher, Olivier; Boucher, Eulalie; Chevallier, Frederic; Tanaka, Katsumasa; Wei, Yiming; Zhong, Haiwang; Kang, Chongqing; Zhang, Ning; Chen, Bin; Xi, Fengming; Liu, Miaomiao; Breon, Francois-Marie; Lu, Yonglong; Zhang, Qiang; Guan, Dabo; Gong, Peng; Kammen, Daniel M; He, Kebin; Schellnhuber, Hans Joachim | Abstract: A Correction to this paper has been published: https://doi.org/10.1038/s41467-020-20254-5.

Background Current strategies are insufficient to predict pathologically complete response (pCR) for esophageal squamous cell carcinomas (ESCCs) before treatment. Here, we aim to develop a novel long noncoding RNA (lncRNA) signature for pCR and outcome prediction of ESCCs through a multicenter analysis for a Chinese population. Methods Differentially expressed lncRNAs (DELs) between pCRs and less than pCR (, This study revealed the first lncRNA signature that showed powerful predictive value for pathological response in ESCCs with nCRT; The three‐lncRNA signature was the first molecular model to show robust prognostic accuracy in patients with ESCC undergoing nCRT; and the number of cases from multi‐institutions enrolled in this project was considerably larger than any of the previous studiesfruit.

No clinically available biomarkers can predict pathological complete response (pCR) for esophageal squamous cell carcinomas (ESCCs) with neoadjuvant chemoradiotherapy (nCRT). Considering that antitumor immunity status is an important determinant for nCRT, we performed an integrative analysis of immune-related gene profiles from pretreatment biopsies and constructed the first individualized immune signature for pCR and outcome prediction of ESCCs through a multicenter analysis. During the discovery phase, 14 differentially expressed immune-related genes (DEIGs) with greater than a twofold change between pCRs and less than pCRs (SERPINE1, MMP12, PLAUR, and EPS8) was built based on the verified DEIGs from 71 cases in a Beijing training cohort, and achieved a high accuracy with an area under the receiver operating characteristic curve (AUC) of 0.970. The signature was further validated in an internal validation cohort and an integrated external cohort (Zhengzhou and Anyang cohorts) with AUCs of 0.890 and 0.859, respectively. Importantly, a multivariate analysis showed that the signature was the only independent predictor for pCR. In addition, patients with high predictive scores showed significantly longer overall and relapse-free survival across multiple centers (P

Pledges from nations and cities to reduce their carbon footprints have reinforced the needs for accurate and transparent reporting of fossil fuel emissions at various scales, with the ultimate goal of the establishments of carbon stocktake as defined by the Paris Agreement. But the assessment of anthropogenic emissions results primarily in collecting socio-economic indicators and emission factors, hence difficult to evaluate, track, or compare without a more standardized and robust methodology. Atmospheric measurements of greenhouse gases are of particular interests by offering an independent and global source of information thanks to satellite platforms observing continuously the atmospheric content of the major gases responsible for human-induced climate change. Based on lessons learned from the NASA Orbiting Carbon Observatory (OCO)-2 mission, we present the potential of satellite-based approaches to monitor greenhouse gas emissions from large metropolitan areas across the world (Riyadh, Lahore, Los Angeles). After exploring the technical aspects and challenges of the approach, potential aerosol contamination (CALIPSO), and model requirements, we introduce the upcoming capabilities from the follow-up mission, OCO-3, dedicated in part to urban emissions with the Snapshot Area Mapping mode, the first imagery of atmospheric CO2 concentrations for hundreds of targeted cities and power plants. Early snapshots are examined with high-resolution simulations over a handful of cities. The ongoing development of assimilation systems to inform policy makers about current trends and inter-annual variations is presented and discussed. We finally examine the potential roles and objectives of satellite missions by exploring recent trends in fossil fuel emissions along with proxies of air quality (MODIS) as a unique opportunity to track not only greenhouse gas emissions but more generally the evolution of urban environments.

This chapter presents a frame memory compression method used in video coding. Frame memory compression compresses the data to be stored in the frame memory in order to reduce the external bandwidth and the related power consumption, as shown in Figure 7.1. When the pixels of a motion-compensated frame have to be written into external DRAM, the frame memory compression engine compresses those pixels. During motion estimation (ME), the frame memory compression engine decompresses the compressed pixels of previous frames and passes them to the video codec. As shown in Figure 7.2, most of the frame memory compression algorithms are composed of three stages: prediction, entropy coding and memory organization [1], which are respectively introduced in Sections 7.1, 7.2 and 7.3.

Objective: The aim of this study was to investigate the clinicopathological features and immunomarkers of Solid Pseudopapillary Neoplasm of the Pancreas (SPN) and to find the best possible immunomarker combination that can accurately diagnose it. Methods: We retrospectively analyzed 10 patients who underwent surgery for pathologically confirmed SPN from August 2013 to August 2017. Follow-up of the patients was between 9 and 57 months. Results: Clinical symptoms and imaging were atypical. In general, the mass was encapsulated and clearly defined by the surrounding tissues. Cut surface was dusty-red and associated with hemorrhage. The neoplastic cell cytoplasm was eosinophilic or clear, and the nuclei were round or oval, presenting typical features of pseudopapillary distribution around a fibrovascular core. Immunohistochemical results showed that tumor cells were consistently positive for vimentin, CD56, CD10, PR, CD99, β-catenin and negative for E-cadherin (100%) and chromogranin. CD99 presented a unique dot-like staining pattern in tumor cells. Conclusions: In view of the atypical clinical manifestations and imaging features of SPN, accurate diagnosis mainly relies on the histomorphology and immunomarker combination including PR, CD99, β-catenin, and E-cadherin, which might be useful method in the diagnosis of SPN.

We investigated the impacts of cold fronts on area-wide peak O3 and regional backgroundO3 mixing ratios on a daily scale over the Houston-Galveston-Brazoria (HGB) area of southeasternTexas during the O3 seasons (April–October) of 2003–2016. Back trajectories showed that an 18h timelag existed between arrival of cold fronts in the HGB area and onset of a predominately northerlyflow. Cold fronts showed increasing effects on both peak and background O3 over the HGB area.Compared to no front days, average peak O3 mixing ratios during the cold front 1st days, coldfront 2+ days, and post frontal days increased 0.7, 5.9, and 9.0 ppbv, respectively while averagebackground O3 increased 2.9, 6.8, and 8.6 ppbv, respectively. The change in wind direction fromsoutherly to northerly was the most important factor causing increasing O3 levels. Wind directionshifts caused variation of other meteorological factors (i.e., wind speed, precipitation, temperature,cloud cover, and relative humidity) and tended to overshadow their effects on O3 over the HGB area.On a long-term and large-scale view, cold fronts over the HGB area could be regarded as interruptionsin the cleansing effects of predominantly marine southerly flow from the Gulf of Mexico.