Colorectal carcinoma with a micropapillary component (MP) is an exceptionally aggressive variant, but has never been investigated in terms of survival analysis. Thirty colorectal carcinomas with a MP were identified from a series of 221 colorectal carcinomas. Carcinomas with and without a MP were compared in terms of histologic and immunohistochemical markers. Colorectal carcinoma with a MP seemed to have a lower differentiation status, increased tumor budding, more frequent lymphovascular and perineural invasion, more frequent lymph node metastasis, higher tumor node metastasis (TNM) stage, and less nuclear beta-catenin staining (P<0.05). Further analysis revealed that the presence of a MP predicted more frequent lymph node metastasis in T1 and T2 stages but not in T3 and T4 stages. Five-year survival rates for patients with a MP and those without were 50% and 73%, respectively. Furthermore, in TNM stages I and II, but not in TNM stages III and IV, a MP was an unfavorable prognostic variable. A MP was demonstrated to be an independent unfavorable prognostic indicator in TNM stages I and II by the multivariate Cox proportional hazard model. Colorectal carcinoma with a MP should be distinguished from colorectal carcinoma of conventional histologic type.

Abstract:The resolution of single-shot coherent diffractive imaging at X-ray free-electron laser facilities is limited by the low signal-to-noise level of diffraction data at high scattering angles. The iterative reconstruction methods, which phase a continuous diffraction pattern to produce an image, must be able to extract information from these weak signals to obtain the best quality images. Here we show how to modify iterative reconstruction methods to improve tolerance to noise. The method is demonstrated with the hybrid input-output method on both simulated data and single-shot diffraction patterns taken at the Linac Coherent Light Source.

We present a global 0.1 • × 0.1 • high-resolution inverse model, NIES-TM-FLEXPART-VAR (NTFVAR), and a methane emission evaluation using the Greenhouse Gas Observing Satellite (GOSAT) satellite and ground-based observations from 2010-2012. Prior fluxes contained two variants of anthropogenic emissions, Emissions Database for Global Atmospheric Research (EDGAR) v4.3.2 and adjusted EDGAR v4.3.2 which were scaled to match the country totals by national reports to the United Nations Framework Convention on Climate Change (UNFCCC), augmented by biomass burning emissions from Global Fire Assimilation System (GFASv1.2) and wetlands Vegetation Integrative Simulator for Trace Gases (VISIT). The ratio of the UNFCCC-adjusted global anthropogenic emissions to EDGAR is 98%. This varies by region: 200% in Russia, 84% in China, and 62% in India. By changing prior emissions from EDGAR to UNFCCC-adjusted values, the optimized total emissions increased from 36.2 to 46 Tg CH 4 yr −1 for Russia, 12.8 to 14.3 Tg CH 4 yr −1 for temperate South America, and 43.2 to 44.9 Tg CH 4 yr −1 for contiguous USA, and the values decrease from 54 to 51.3 Tg CH 4 yr −1 for China, 26.2 to 25.5 Tg CH 4 yr −1 for Europe, and by 12.4 Tg CH 4 yr −1 for India. The use of the national report to scale EDGAR emissions allows more detailed statistical data and country-specific emission factors to be gathered in place compared to those available for EDGAR inventory. This serves policy needs by evaluating the national or regional emission totals reported to the UNFCCC.is slowing down [1][2][3]. Methane (CH 4 ) plays a growing role in anthropogenic climate change with its share of more than 20% of the total greenhouse gas (GHG) concentration [4][5][6]. Reducing methane emissions would make a significant contribution to climate change mitigation on a shorter time scale, due to its relatively short lifetime compared with that of CO 2 [7,8]. The determination of national emission reduction targets and policies is directly affected by the amount of methane emissions produced by individual countries [9]. However, studies on emission estimates suggest that there are still large uncertainties in methane budgets, and more effort should be made to better quantify the methane emissions [10][11][12][13][14][15]. Still, it is challenging to verify the accuracy of methane emissions on a country scale. The national reports submitted to the United Nations Framework Convention on Climate Change (UNFCCC) by different countries might use different methods to estimate emissions, which could be different from global inventory datasets produced by the scientific community, such as the Global Carbon Project (GCP) [16], and the Emissions Database for Global Atmospheric Research (EDGAR) [17][18][19]. Complementary to these bottom-up emission estimations, top-down estimations by inverse models combined with atmospheric measurements have been widely used and have proven worthy for emission inventory evaluation (e.g., [20][21][22][23][24][25][26]). Houweling et al. [27] reviewed the devel...

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