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Abstract Afforestation is a major carbon dioxide removal technology but can negatively affect food and land systems. Here, we used an integrated assessment model to quantitatively demonstrate how the selection of forest type to use in afforestation could increase global carbon sequestration without compromising global food and land sustainability. Our findings indicate that if a carbon-intensive forest type is selected, afforestation would increase carbon sequestration by 25% compared to the level assuming the native forest type. At the same time, if implemented inappropriately at a large scale, afforestation would worsen the economy, food, and land systems due to decreased land efficiency in carbon removal compared to bioenergy with carbon capture and storage, leading to increased land expansion for carbon removal, higher food prices, and increased risk of hunger. These results suggest the need to implement carbon-intensive forest types with complementary measures to reduce the adverse impacts on food and land sustainability.

Abstract As a result of climate change, the pan-Arctic region has seen greater temperature increases than other geographical regions on the Earth’s surface. This has led to substantial changes in terrestrial ecosystems and the hydrological cycle, which have affected the distribution of vegetation and the patterns of water flow and accumulation. Various remote sensing techniques, including optical and microwave satellite observations, are useful for monitoring these terrestrial water and vegetation dynamics. In the present study, satellite and reanalysis datasets were used to produce water and vegetation maps with a high temporal resolution (daily) and moderate spatial resolution (500 m) at a continental scale over Siberia in the period 2003–2017. The multiple data sources were integrated by pixel-based machine learning (random forest), which generated a normalized difference water index (NDWI), normalized difference vegetation index (NDVI), and water fraction without any gaps, even for areas where optical data were missing (e.g., cloud cover). For the convenience of users handling the data, an aggregated product is provided, formatted using a 0.1° grid in latitude/longitude projection. When validated using the original optical images, the NDWI and NDVI images showed small systematic biases, with a root mean squared error of approximately 0.1 over the study area. The product was used for both time-series trend analysis of the indices from 2003 to 2017 and phenological feature extraction based on seasonal NDVI patterns. The former analysis was used to identify areas where the NDVI is decreasing and the NDWI is increasing, and hotspots where the NDWI at lakesides and coastal regions is decreasing. The latter analysis, which employed double-sigmoid fitting to assess changes in five phenological parameters (i.e., start and end of spring and fall, and peak NDVI values) at two larch forest sites, highlighted a tendency for recent lengthening of the growing period. Further applications, including model integration and contribution to land cover mapping, will be developed in the future.

Gastrointestinal stromal tumor (GIST) is the most common mesenchymal tumor of the alimentary tract. The prognosis depends on the primary site, and small intestinal GISTs have a worse prognosis than gastric GISTs. Molecularly targeted drugs to inhibit tyrosine kinase activity of KIT were used for unresectable or recurrent GISTs. However, secondary resistance to the drugs is often acquired, and treatments based on other mechanisms are needed. Previously, we reported that cell adhesion molecule 1 (CADM1) was highly expressed in most of small intestinal GISTs but not in most of gastric GISTs. In the present study, we examined whether the antibody-drug conjugate (ADC) with anti-CADM1 antibody and monomethyl auristatin E (anti-CAD-ADC) shows anti-tumor effect on CADM1-expressing human GIST cells. The ADC adhibited in this study was previously used for CADM1-expressing human mesothelioma cells and showed anti-tumor effect for them in vitro. GIST-T1 cell line of gastric origin which scarcely expresses CADM1 and GIST-T1 cells transfected with CADM1 cDNA (GIST-T1-CAD cells) which highly expresses CADM1 and represents small intestinal GIST were used. In vitro, anti-CAD-ADC showed remarkable cytotoxic activity on GIST-T1-CAD cells, but control ADC did not. Both anti-CAD-ADC and control ADC did not show anti-tumor effect on original GIST-T1 cells. When GIST-T1-CAD cells were subcutaneously injected to the nude mice, intravenous administration of anti-CAD-ADC showed inhibitory effect for tumor enlargement. Tumor of GIST-T1 cells grew even after anti-CAD-ADC injection. When GIST-T1-CAD cells were injected into peritoneal cavity of the SCID mice, intraperitoneal administration of anti-CAD-ADC showed reduction of the peritoneal tumor. On the other hand, peritoneal tumor grew after control ADC administration. Tissue and organ damage due to administration of anti-CAD-ADC was not apparent by macroscopic and histological examinations in mice. These results indicate that anti-CAD-ADC could have apparent anti-tumor effect on CADM1-expressing human GIST cells both in in vitro and in vivo mouse models.

Introduction: Immune checkpoint inhibitors have recently been approved for the treatment of early-stage NSCLC in the perioperative setting on the basis of phase 3 trials. However, the characteristics of such patients who are susceptible to recurrence after adjuvant chemotherapy or who are likely to benefit from postoperative immunotherapy have remained unclear. Methods: This biomarker study (WJOG12219LTR) was designed to evaluate cancer stem cell markers (CD44 and CD133), programmed death-ligand 1 (PD-L1) expression on tumor cells, CD8 expression on tumor-infiltrating lymphocytes, and tumor mutation burden in completely resected stage II to IIIA NSCLC with the use of archived DNA and tissue samples from the prospective WJOG4107 trial. Tumors were classified as inflamed or noninflamed on the basis of the PD-L1 tumor proportion score and CD8+ tumor-infiltrating lymphocyte density. The association between each potential biomarker and relapse-free survival (RFS) during adjuvant chemotherapy was assessed by Kaplan-Meier analysis. Results: A total of 117 patients were included in this study. The median RFS was not reached (95% confidence intervals [CI]: 22.4 mo–not reached; n = 39) and 23.7 months (95% CI: 14.5–43.6; n = 41) in patients with inflamed or noninflamed adenocarcinoma, respectively (log-rank p = 0.02, hazard ratio of 0.52 [95% CI: 0.29–0.93]). Analysis of the combination of tumor inflammation category and TP53 mutation status revealed that inflamed tumors without TP53 mutations were associated with the longest RFS. Conclusions: PD-L1 expression on tumor cells, CD8+ T cell infiltration, and TP53 mutation status may help identify patients with early-stage NSCLC susceptible to recurrence after adjuvant chemotherapy.

Introduction Inflammatory myofibroblastic tumors are borderline malignant soft tissue tumors primarily affecting the lungs and pelvic organs. This report presents a rare case of an inflammatory myofibroblastic tumor originating from the prostate gland in a young male. Case presentation A 20‐year‐old man developed gross hematuria and dysuria, revealing a prostatic mass. Pathological examination of a biopsy displayed spindle‐shaped myofibroblast proliferation and an infiltrate of inflammatory cells, leading to a diagnosis of inflammatory myofibroblastic tumor. Following fertility preservation measures, the patient underwent a robot‐assisted laparoscopic total prostatectomy with bilateral nerve sparing, resulting in a postoperative diagnosis of inflammatory myofibroblastic tumor. No recurrence was observed in subsequent imaging, and urinary continence was maintained. Conclusion Surgical resection appears effective in managing inflammatory myofibroblastic tumors of the prostate. This case underscores the importance of complete tumor resection due to the significant recurrence risk associated with inflammatory myofibroblastic tumors. Radical total prostatectomy emerges as a potential treatment strategy for prostate originating inflammatory myofibroblastic tumors.

Abstract The release of carbon dioxide from the soil to the atmosphere, known as soil respiration, is the second largest terrestrial carbon flux after photosynthesis, but the convergence of the data-driven estimates is unclear. Here we collate all historical data-driven estimates of global soil respiration to analyze convergence and uncertainty in the estimates. Despite the development of a dataset and advanced scaling techniques in the last two decades, we find that inter-model variability has increased. Reducing inter-model variability of global soil respiration is not an easy task, but when the puzzle pieces of the carbon cycle fit together perfectly, climate change prediction will be more reliable.

Abstract Termites with symbiotic methanogens are a known source of atmospheric methane (CH4), but large uncertainties remain regarding the flux magnitude. This study estimated global termite CH4 emissions using a framework similar to previous studies but with contemporary datasets and a biogeochemical model. The global termite emission in 2020 was estimated as 14.8 ± 6.7 Tg CH4 year−1, mainly from tropical and subtropical ecosystems, indicating a major natural source from upland regions. Uncertainties associated with estimation methods were assessed. The emission during the historical period 1901–2021 was estimated to have increased gradually (+ 0.7 Tg CH4 year−1) as a result of combined influences of elevated CO2 (via vegetation productivity), climatic warming, and land-use change. Future projections using climate and land-use scenarios (shared socioeconomic pathways [ssp] 126 and 585) also showed increasing trends (+ 0.5 to 5.9 Tg CH4 year−1 by 2100). These results suggest the importance of termite emissions in the global CH4 budget and, thus, in climatic prediction and mitigation.

Abstract We developed a near-real-time estimation method for temporal changes in fossil fuel CO2 (FFCO2) emissions from China for 3 months [January, February, March (JFM)] based on atmospheric CO2 and CH4 observations on Hateruma Island (HAT, 24.06° N, 123.81° E) and Yonaguni Island (YON, 24.47° N, 123.01° E), Japan. These two remote islands are in the downwind region of continental East Asia during winter because of the East Asian monsoon. Previous studies have revealed that monthly averages of synoptic-scale variability ratios of atmospheric CO2 and CH4 (ΔCO2/ΔCH4) observed at HAT and YON in JFM are sensitive to changes in continental emissions. From the analysis based on an atmospheric transport model with all components of CO2 and CH4 fluxes, we found that the ΔCO2/ΔCH4 ratio was linearly related to the FFCO2/CH4 emission ratio in China because calculating the variability ratio canceled out the transport influences. Using the simulated linear relationship, we converted the observed ΔCO2/ΔCH4 ratios into FFCO2/CH4 emission ratios in China. The change rates of the emission ratios for 2020–2022 were calculated relative to those for the preceding 9-year period (2011–2019), during which relatively stable ΔCO2/ΔCH4 ratios were observed. These changes in the emission ratios can be read as FFCO2 emission changes under the assumption of no interannual variations in CH4 emissions and biospheric CO2 fluxes for JFM. The resulting average changes in the FFCO2 emissions in January, February, and March 2020 were 17 ± 8%, − 36 ± 7%, and − 12 ± 8%, respectively, (− 10 ± 9% for JFM overall) relative to 2011–2019. These results were generally consistent with previous estimates. The emission changes for January, February, and March were 18 ± 8%, − 2 ± 10%, and 29 ± 12%, respectively, in 2021 (15 ± 10% for JFM overall) and 20 ± 9%, − 3 ± 10%, and − 10 ± 9%, respectively, in 2022 (2 ± 9% for JFM overall). These results suggest that the FFCO2 emissions from China rebounded to the normal level or set a new high record in early 2021 after a reduction during the COVID-19 lockdown. In addition, the estimated reduction in March 2022 might be attributed to the influence of a new wave of COVID-19 infections in Shanghai.

Abstract The dramatic increase of natural gas use in China, as a substitute for coal, helps to reduce CO2 emissions and air pollution, but the climate mitigation benefit can be offset by methane leakage into the atmosphere. We estimate methane emissions from 2010 to 2018 in four regions of China using the GOSAT satellite data and in-situ observations with a high-resolution (0.1° × 0.1°) inverse model and analyze interannual changes of emissions by source sectors. We find that estimated methane emission over the north-eastern China region contributes the largest part (0.77 Tg CH4 yr−1) of the methane emission growth rate of China (0.87 Tg CH4 yr−1) and is largely attributable to the growth in natural gas use. The results provide evidence of a detectable impact on atmospheric methane observations by the increasing natural gas use in China and call for methane emission reductions throughout the gas supply chain and promotion of low emission end-use facilities.

Abstract Radiography is non-destructive imaging for engineering, medical diagnostics, airport security checks, and decontamination activities in nuclear plants. Inorganic scintillators are phosphor materials that convert radiation into visible photons with high luminescence and fast response, and scintillators with a few tens of micrometers thickness can improve sensitivity in radiation detection and imaging. To date, a production method for thick film scintillators is a time and cost consuming way of slicing and poshing bulk single crystals and transparent ceramics. Here, the chemically vapor deposited Ce3+-doped Lu3Al5O12 thick film scintillators (CVD-Ce3+:LuAG) with a thickness of 1–25 μm were produced at deposition time of 1–30 min. Numerical simulations indicated the penetration depth of α-particle in Ce3+:LuAG is 12.8 μm, and the 14-μm-thick CVD-Ce3+:LuAG showed highest light yield (31,000 photons 5.5 MeV−1), superior to the commercial Ce3+:LuAG single crystal scintillator (21,000 photons 5.5 MeV−1). In the X-ray radiograph taken with CVD-Ce3+:LuAG as a scintillation screen, 5-μm-width bar of metal microgrids can be identified. Vapor deposition technique can be a novel high-throughput production way of a thick film scintillator which is in a micrometer-thickness effective to converting radiations into photons for sensitive α-emitter detection and high-resolution X-ray imaging.

Abstract Accurate estimates of the carbon dioxide (CO2) fluxes at the earth’s surface are imperative for comprehending the carbon cycle mechanisms and providing reliable global warming predictions. Furthermore, they can also provide valuable science-based information that will be helpful in reducing human-induced CO2 emissions. Inverse analysis is a prominent method of quantitatively estimating spatiotemporal variations in CO2 fluxes; however, it involves a certain level of uncertainty and requires technical refinement, specifically to improve the horizontal resolution so that local fluxes can be compared with other estimates made at the regional or national level. In this study, a novel set of inversion schemes was incorporated into a state-of-the-art inverse analysis system named NISMON-CO2. The introduced schemes include a grid conversion, observational weighting, and anisotropic prior error covariance, the details of which are described. Moreover, pseudo-observation experiments were performed to examine the effect of the new schemes and to assess the reliability of NISMON-CO2 for long-term analysis with practical inhomogeneous observations. The experiment results evidently demonstrate the advantages of the grid conversion scheme for high-resolution flux estimates (1° × 1°), with notable improvements being achieved through the observational weighting and anisotropic prior error covariance. Furthermore, the estimated seasonal and interannual variations in regional CO2 fluxes were confirmed to be reliable, although some potential bias in terms of global land–ocean partitioning was observed. Thus, these results are useful for interpreting the flux variations that result from real-observation inverse analysis by NISMON-CO2 ver. 2021.1.

Abstract Background Sarcopenia is characterized by the loss of skeletal muscle mass and strength and is associated with poor prognosis in patients with chronic obstructive pulmonary disease (COPD). Cigarette smoke (CS) exposure, a major cause for COPD, induces mitochondrial damage, which has been implicated in sarcopenia pathogenesis. The current study sought to examine the involvement of insufficient Parkin‐mediated mitophagy, a mitochondrion‐selective autophagy, in the mechanisms by which dysfunctional mitochondria accumulate with excessive reactive oxygen species (ROS) production in the development of COPD‐related sarcopenia. Methods The involvement of Parkin‐mediated mitophagy was examined using in vitro models of myotube formation, in vivo CS‐exposure model using Parkin−/− mice, and human muscle samples from patients with COPD‐related sarcopenia. Results Cigarette smoke extract (CSE) induced myotube atrophy with concomitant 30% reduction in Parkin expression levels (P

Introduction: Despite a considerable benefit of adding immune checkpoint inhibitors (ICIs) to platinum-based chemotherapy for patients with extensive-stage SCLC (ES-SCLC), a durable response to ICIs occurs in only a small minority of such patients. Methods: A total of 135 patients with ES-SCLC treated with chemotherapy either alone (chemo-cohort, n = 71) or together with an ICI (ICI combo-cohort, n = 64) was included in this retrospective study. Tumors were classified pathologically as inflamed or noninflamed on the basis of programmed death-ligand 1 expression and CD8+ tumor-infiltrating lymphocyte density. Immune-related gene expression profiling was performed, and predicted neoantigen load was determined by whole-exome sequencing. Results: Among patients in the ICI combo-cohort, median progression-free survival was 10.8 and 5.1 months for those with inflamed (n = 7) or noninflamed (n = 56) tumors, respectively (log-rank test p = 0.002; hazard ratio of 0.26). Among the 89 patients with immune-related gene expression profiling data available, inflamed tumors had a higher T cell-inflamed GEP score than did noninflamed tumors (−0.18 versus −0.58, p < 0.001). The 12-month progression-free survival rate was 16.1% and 0% for patients in the ICI combo-cohort harboring tumors with a high (n = 26) or low (n = 18) frameshift neoantigen load, respectively. A high-frameshift neoantigen load was associated with up-regulation of gene signatures related to antigen presentation and costimulatory signaling. A durable clinical benefit of ICI therapy was observed only in patients with inflamed tumors and a high-frameshift neoantigen load. Conclusions: Expression of programmed death-ligand 1, CD8+ T cell infiltration, and a high-frameshift neoantigen load are associated with clinical benefit of ICI therapy in ES-SCLC. Clinical trial registration: UMIN000041056

Matrix metalloproteinase 14 (MMP14) expression is implicated in progression of colorectal cancer, but its role in the tumor microenvironment (TME) has been unclear. The relevance of MMP14 to colorectal cancer progression was explored by analysis of transcriptomic data for colorectal adenocarcinoma patients (n = 592) in The Cancer Genome Atlas. The role of MMP14 in the TME was investigated in a retrospective analysis of tumor samples from 86 individuals with stage III colorectal cancer by single cell–based spatial profiling of MMP14 expression as performed by 12-color multiplex immunohistochemistry (mIHC). Analysis of gene expression data revealed that high MMP14 expression was associated with tumor progression and implicated both cancer-associated fibroblasts (CAFs) and tumor-associated macrophages in such progression. Spatial profiling by mIHC revealed that a higher percentage of MMP14+ cells among intratumoral CAFs (MMP14+ CAF/CAF ratio) was associated with poorer relapse-free survival. Multivariable analysis including key clinical factors identified the MMP14+ CAF/CAF ratio as an independent poor prognostic factor. Moreover, the patient subset with both a high MMP14+ CAF/CAF ratio and a low tumor-infiltrating lymphocyte density showed the worst prognosis. Our results suggest that MMP14+ CAFs play an important role in progression of stage III colorectal cancer and may therefore be a promising therapeutic target.

Malignant pleural mesothelioma (MPM) is a highly aggressive malignant tumor, and the effective therapeutic drugs are limited. Thus, the establishment of novel therapeutic method is desired. Considerable proportion of MPMs are shown to express cell adhesion molecule 1 (CADM1), and to use CADM1 to bind to and proliferate on the pleural mesothelial surface, suggesting that CADM1 is a possible therapeutic target. Here, anti-CADM1 ectodomain chicken monoclonal antibodies, 3E1 and 9D2, were examined for their possible therapeutic utility. The full-length form of CADM1 was expressed in eight out of twelve human MPM cell lines. MPM cell lines were cultured on a confluent monolayer of mesothelial MeT-5A cells in the presence of 9D2, the neutralizing antibody. 9D2 suppressed the cell growth of CADM1-positive MPM cells with the loss and aggregation of CADM1 molecules on the MPM cell membrane, but not of CADM1-negative MPM cells. Co-addition of 3E1, lacking the neutralizing action, enhanced the growth-suppressive effect of 9D2. The two antibodies were tested as drug delivery vectors. 3E1 was converted into a humanized antibody (h3E1) and conjugated with monomethyl auristatin E (MMAE), a tubulin polymerization inhibitor. When the resulting h3E1–MMAE antibody-drug conjugate (ADC) was added to the standard cultures of CADM1-positive MPM cells, it suppressed the cell growth in a dose-dependent manner. Co-addition of 9D2 enhanced the growth-suppressive effect of h3E1–MMAE ADC. Anti-CADM1 ectodomain antibodies were suggested to serve as both antibody drugs and drug vectors in the treatment of MPM.

Abstract The measurements of one of the major greenhouse gases, carbon dioxide (CO2), are being made using dedicated satellite remote sensing since the launch of the greenhouse gases observing satellite (GOSAT) by a three-way partnership between the Japan Aerospace Exploration Agency (JAXA), the Ministry of Environment (MoE) and the National Institute for Environmental Studies (NIES), and the National Aeronautics and Space Administration (NASA) Orbiting Carbon Observatory-2 (OCO-2). In the past 10 years, estimation of CO2 fluxes from land and ocean using the earth system models (ESMs) and inverse modelling of in situ atmospheric CO2 data have also made significant progress. We attempt, for the first time, to evaluate the CO2 fluxes simulated by an earth system model (MIROC-ES2L) and the fluxes estimated by an inverse model (MIROC4-Inv) using in situ data by comparing with GOSAT and OCO-2 observations. Both MIROC-ES2L and MIROC4-Inv fluxes are used in the MIROC4-atmospheric chemistry transport model (referred to as ACTM_ES2LF and ACTM_InvF, respectively) for calculating total column CO2 mole fraction (XCO2) that are sampled at the time and location of the satellite measurements. Both the ACTM simulations agreed well with the GOSAT and OCO-2 satellite observations, within 2 ppm for the spatial maps and time evolutions of the zonal mean distributions. Our results suggest that the inverse model using in situ data is more consistent with the OCO-2 retrievals, compared with those of the GOSAT XCO2 data due to the higher accuracy of the former. This suggests that the MIROC4-Inv fluxes are of sufficient quality to evaluate MIROC-ES2L simulated fluxes. The ACTM_ES2LF simulation shows a slightly weaker seasonal cycle for the meridional profiles of CO2 fluxes, compared with that from the ACTM_InvF. This difference is revealed by greater XCO2 differences for ACTM_ES2LF vs GOSAT, compared with those of ACTM_InvF vs GOSAT. Using remote sensing–based global products of leaf area index (LAI) and gross primary productivity (GPP) over land, we show a weaker sensitivity of MIROC-ES2L biospheric activities to the weather and climate in the tropical regions. Our results clearly suggest the usefulness of XCO2 measurements by satellite remote sensing for evaluation of large-scale ESMs, which so far remained untested by the sparse in situ data.

Abstract The Yedoma layer, a permafrost layer containing a massive amount of underground ice in the Arctic regions, is reported to be rapidly thawing. In this study, we develop the Permafrost Degradation and Greenhouse gasses Emission Model (PDGEM), which describes the thawing of the Arctic permafrost including the Yedoma layer due to climate change and the greenhouse gas (GHG) emissions. The PDGEM includes the processes by which high-concentration GHGs (CO2 and CH4) contained in the pores of the Yedoma layer are released directly by dynamic degradation, as well as the processes by which GHGs are released by the decomposition of organic matter in the Yedoma layer and other permafrost. Our model simulations show that the total GHG emissions from permafrost degradation in the RCP8.5 scenario was estimated to be 31-63 PgC for CO2 and 1261-2821 TgCH4 for CH4 (68th percentile of the perturbed model simulations, corresponding to a global average surface air temperature change of 0.05–0.11 °C), and 14-28 PgC for CO2 and 618-1341 TgCH4 for CH4 (0.03–0.07 °C) in the RCP2.6 scenario. GHG emissions resulting from the dynamic degradation of the Yedoma layer were estimated to be less than 1% of the total emissions from the permafrost in both scenarios, possibly because of the small area ratio of the Yedoma layer. An advantage of PDGEM is that geographical distributions of GHG emissions can be estimated by combining a state-of-the-art land surface model featuring detailed physical processes with a GHG release model using a simple scheme, enabling us to consider a broad range of uncertainty regarding model parameters. In regions with large GHG emissions due to permafrost thawing, it may be possible to help reduce GHG emissions by taking measures such as restraining land development.

Estimates of future climate change impacts using numerical impact models are commonly based on a limited selection of projections of climate and other key drivers. However, the availability of large ensembles of such projections offers an opportunity to estimate impact responses probabilistically. This study demonstrates an approach that combines model-based impact response surfaces (IRSs) with probabilistic projections of climate change and population to estimate the likelihood of exceeding pre-specified thresholds of impact.The changing likelihood of exceeding impact thresholds during the 21st century was estimated for selected indicators in three European case study regions (Iberian Peninsula, Scotland and Hungary), comparing simulations that incorporate adaptation to those without adaptation. The results showed high likelihoods of increases in heat-related human mortality and of yield decreases for some crops, whereas a decrease of NPP was estimated to be exceptionally unlikely. For a water reservoir in a Portuguese catchment, increased likelihoods of severe water scarce conditions were estimated for the current rice cultivation. Switching from rice to other crops with lower irrigation demand changes production risks, allowing for expansion of the irrigated areas but introducing a stronger sensitivity to changes in rainfall.The IRS-based risk assessment shown in this paper is of relevance for policy making by addressing the relative sensitivity of impacts to key climate and socio-economic drivers, and the urgency for action expressed as a time series of the likelihood of crossing critical impact thresholds. It also examines options to respond by incorporating alternative adaptation actions in the analysis framework, which may be useful for exploring the types, choice and timing of adaptation responses.

Abstract Land-use change is one of the focal processes in Earth system models because it has strong impacts on terrestrial biogeophysical and biogeochemical conditions. However, modeling land-use impacts is still challenging because of model complexity and uncertainty. This study examined the results of simulations of land-use change impacts by the Model for Interdisciplinary Research on Climate, Earth System version 2 for long-term simulations (MIROC-ES2L) conducted under the Land-Use Model Intercomparison Project protocol. In a historical experiment, the model reproduced biogeophysical impacts such as decreasing trends in land-surface net radiation and evapotranspiration by about 1970. Among biogeochemical impacts, the model captured the global decrease of vegetation and soil carbon stocks caused by extensive deforestation. By releasing ecosystem carbon stock to the atmosphere, land-use change shortened the mean residence time of terrestrial carbon and accelerated its turnover rate, especially in low latitudes. Future projections based on Shared Socioeconomic Pathways indicated substantial alteration of land conditions caused primarily by climatic change and secondarily by land-use change. Sensitivity experiments conducted by exchanging land-use data between different future projection baseline experiments showed that, at the global scale, the anticipated extent of land-use conversion would likely play a modest role in the future terrestrial radiation, water, and carbon budgets. Regional investigations revealed that future land use would exert a considerable influence on runoff and vegetation carbon stock. Further model refinement is required to improve its capability to analyze its complicated terrestrial linkages or nexus (e.g., food, bioenergy, and carbon sequestration) to climate-change impacts.

The clinicopathological, immunohistochemical, and molecular characteristics of α-fetoprotein (AFP)-producing endometrial carcinoma (AFP+ EC) are poorly understood. From 284 cases of endometrial carcinoma in our pathology archive, we identified five cases (1.8%) of AFP+ EC with fetal gut–like (4/5) and/or hepatoid (2/5) morphology. All cases exhibited lymphovascular infiltration. In addition, 24 cases of endometrial carcinoma with elevated serum AFP levels were retrieved from the literature. The patient age ranged from 44 to 86 years (median: 63). Of 26 cases whose FIGO (International Federation of Gynecology and Obstetrics) stage and follow-up information was available (mean follow-up 24 months), 15 were stage I or II and 11 were stage III or IV. Even in stage I or II disease, death or relapse occurred in more than half of the patients (8/15). Detailed analysis of our five cases revealed that, on immunohistochemistry, AFP+ EC was positive for SALL4 (4/5), AFP (3/5), and HNF1β (4/5) in >50% of neoplastic cells and negative for estrogen and progesterone receptors (5/5), PAX8 (4/5), and napsin A (5/5). Four cases exhibited aberrant p53 immunohistochemistry and were confirmed to harbor TP53 mutations by direct sequencing. No mutation was found in POLE, CTNNB1, or KRAS. In conclusion, AFP+ EC merits recognition as a distinct subtype of endometrial carcinoma, which occurs in 1.8% of endometrial carcinoma cases, are associated with TP53 abnormalities, exhibit lymphovascular infiltration, and can show distant metastasis even when treated in early stage.

Elevation of intraocular pressure is a major risk factor for glaucoma development, which causes the loss of retinal ganglion cells (RGCs). Lipocalin 2 (Lcn2) is upregulated in glaucomatous retinae; however, whether Lcn2 is directly involved in glaucoma is debated. In this study, retinal explant cultures were subjected to increased water pressure using a two-chamber culture device, and Lcn2 protein levels were examined by immunoblotting. In situ TdT-mediated dUTP nick and labeling (TUNEL) and glial fibrillary acidic protein (GFAP) immunohistochemical assays were performed to assess apoptosis and gliosis, respectively. The neurotoxicity of Lcn2 in the retinal explant culture was determined with exogenous administration of recombinant Lcn2. The Lcn2 protein levels, percentage of TUNEL-positive cells, and GFAP-positive area were significantly higher in retinae cultured under 50 cm H2O pressure loads compared to those cultured under 20 cm H2O. We found that Lcn2 exhibited neurotoxicity in retinae at dose of 1 μg/ml. The negative effects of increased hydrostatic pressure were attenuated by the iron chelator deferoxamine. This is the first report demonstrating the direct upregulation of Lcn2 by elevating hydrostatic pressure. Modulating Lcn2 and iron levels may be a promising therapeutic approach for retinal degeneration.

Abstract Background Immune checkpoint inhibitors (ICIs) confer a survival benefit in many cancer types. Given that the survival outcome for cancer of unknown primary site (CUP) remains poor, we investigated the potential of CUP for immunotherapy. Methods A total of 164 patients with CUP (favorable subset, 34 patients; unfavorable subset, 130 patients) who were treated between January 2009 and March 2017 was identified from a review of medical records at Kindai University Hospital. They included 92 patients for whom pretreatment tumor tissue was available both for determination of programmed cell death–ligand 1 expression and tumor-infiltrating lymphocyte (TIL) density by immunohistochemistry (IHC) and for immune-related gene expression profiling (irGEP). The results of irGEP for CUP were compared with published data for ICI-treated solid cancers classified into progressive disease (PD) and non-PD subsets according to their best response to ICIs. Results The median overall survival of all CUP patients was 29.3 months (95% confidence interval [CI], 15.7–not reached) and 7.1 months (95% CI, 5.0–9.4) for favorable and unfavorable subsets, respectively. IHC and irGEP revealed that pretreatment immune activity—including expression of immune checkpoint molecules—for CUP was similar to that for ICI-responsive malignancies (antitumor immune cell signatures: CUP versus PD, P = 0.002–0.067; CUP versus non-PD, P = 0.591–0.999), although VEGFA expression was associated with suppression of antitumor immunity in CUP (P = 0.008, false discovery rate = 0.010). In addition, one case of CUP in the unfavorable subset that was associated with prominent PD-L1 expression on TILs and showed a durable response to nivolumab is presented. Conclusions The survival outcome of CUP remains unsatisfactory. However, our clinical and immune profiling of CUP has revealed a potential to benefit from immunotherapy, with ICIs thus being a potential option for CUP treatment.

Impact models projections are used in integrated assessments of climate change. Here the authors test systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions.

Adult T-cell leukemia/leukemia (ATLL) is an aggressive peripheral T-cell malignancy, caused by infection with the human T-cell leukemia virus type 1 (HTLV-1). We have recently shown that cell adhesion molecule 1 (CADM1), a member of the immunoglobulin superfamily, is specifically and consistently overexpressed in ATLL cells, and functions as a novel cell surface marker. In this study, we first show that a soluble form of CADM1 (sCADM1) is secreted from ATLL cells by mainly alternative splicing. After developing the Alpha linked immunosorbent assay (AlphaLISA) for sCADM1, we showed that plasma sCADM1 concentrations gradually increased during disease progression from indolent to aggressive ATLL. Although other known biomarkers of tumor burden such as soluble interleukin-2 receptor α (sIL-2Rα) also increased with sCADM1 during ATLL progression, multivariate statistical analysis of biomarkers revealed that only plasma sCADM1 was selected as a specific biomarker for aggressive ATLL, suggesting that plasma sCADM1 may be a potential risk factor for aggressive ATLL. In addition, plasma sCADM1 is a useful marker for monitoring response to chemotherapy as well as for predicting relapse of ATLL. Furthermore, the change in sCADM1 concentration between indolent and aggressive type ATLL was more prominent than the change in the percentage of CD4+CADM1+ ATLL cells. As plasma sCADM1 values fell within normal ranges in HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP) patients with higher levels of serum sIL-2Rα, a measurement of sCADM1 may become a useful tool to discriminate between ATLL and other inflammatory diseases, including HAM/TSP.

Abstract This study assessed historical changes in emissions of nitrous oxide (N2O), a potent greenhouse gas and stratospheric ozone-depleting substance, from the soils of East Asia to the atmosphere. A process-based terrestrial ecosystem model (VISIT) was used to simulate the nitrogen cycle and associated N2O emissions as a function of climate, land use, atmospheric deposition, and agricultural inputs from 1901 to 2016. The mean regional N2O emission rate in the 2000s was estimated to be 2.03 Tg N2O year−1 (1.29 Tg N year−1; approximately one-third from natural ecosystems and two-thirds from croplands), more than triple the rate in 1901. A sensitivity analysis suggested that the increase of N2O emissions was primarily attributable to the increase of agricultural inputs from fertilizer and manure. The simulated N2O emissions showed a clear seasonal cycle and interannual variability, primarily in response to meteorological conditions and nitrogen inputs. The spatial pattern of the simulated N2O emissions revealed hot spots in agricultural areas of China, South Korea, and Japan. The average N2O emission factor (emission per unit nitrogen input) was estimated to be 1.38%, a value comparable to previous estimates. These biogeochemical modeling results will facilitate identifying ways to mitigate global warming and manage agricultural practices in this region.

Cell adhesion molecule 1 (CADM1) is an immunoglobulin superfamily member strongly expressed on renal tubular epithelia in the urinary tract. Enzymatic cleavage of its ectodomain increases in chronic kidney disease (CKD), and is assumed to contribute to tubulointerstitial lesion formation. Because the cleaved ectodomain fragments are likely to be released into the urine, a sandwich enzyme-linked immunosorbent assay (ELISA) system for urinary CADM1 was developed using two anti-ectodomain antibodies. Urinary CADM1 concentrations in patients with CKD based on various forms of glomerulonephritis and nephropathy (n = 127) were measured. A total of 44 patients (35%) had elevated CADM1 concentrations over the normal upper limit (362 pg/mL), with a mean of 1,727 pg/mL. Renal biopsy specimens of all patients were pathologically scored for tubulointerstitial lesions using epithelial degeneration, interstitial inflammation, and fibrosis. There were no correlations between urinary CADM1 concentrations and pathological scores or any widely used renal markers, including glomerular filtration rate (GFR), but there was a weak inverse correlation between pathological scores and GFR (R2 = 0.292). Notably, this correlation gradually increased in patients with increasing CADM1 concentrations, and reached a maximum R2 (0.899) at a cutoff of 1,569 pg/mL. The results of this study suggest that urinary CADM1 is a useful marker indicating tubulointerstitial damage from elevated GFR levels in CKD.

Nitrification in terrestrial soils is one of the major processes of emission of nitrous oxide (N2O), a potent greenhouse gas and stratospheric-ozone-depleting substance. We assessed the fraction of N2O emission associated with nitrification in soil through a meta-analysis and sensitivity analysis using a process-based model. We corrected observational values of gross nitrification and associated N2O emission rates from 71 records for various soils in the world spanning from 0.006% to 29.5%. We obtained a median value of 0.14%, and then assessed how the nitrification-associated N2O emission fraction has been considered in terrestrial nitrogen cycle models. Using a process-based biogeochemical model, we conducted a series of sensitivity analyses for the effects of different values of nitrification-associated N2O emission fraction on soil N2O emission. Using an empirical relationship between soil pH and nitrification-associated N2O emission fraction, the model well simulated global emission patterns (global total in the 2000s, 16.8 Tg N2O yr-1). Differences in the nitrification-associated N2O emission fraction caused differences in total N2O emission of as much as 2.5 Tg N2O yr-1. Therefore, to obtain reliable estimation of soil N2O emission for nitrogen and climate management, it is important to constrain the parameterization in models by ensuring extensive and accurate observations.

A disintegrin and metalloproteinases (ADAMs) are a Zn2+-dependent transmembrane and secreted metalloprotease superfamily, so-called “molecular scissors,” and they consist of an N-terminal signal sequence, a prodomain, zinc-binding metalloprotease domain, disintegrin domain, cysteine-rich domain, transmembrane domain and cytoplasmic tail. ADAMs perform proteolytic processing of the ectodomains of diverse transmembrane molecules into bioactive mediators. This review summarizes on their most well-known members, ADAM10 and 17, focusing on the kidneys. ADAM10 is expressed in renal tubular cells and affects the expression of specific brush border genes, and its activation is involved in some renal diseases. ADAM17 is weakly expressed in normal kidneys, but its expression is markedly induced in the tubules, capillaries, glomeruli, and mesangium, and it is involved in interstitial fibrosis and tubular atrophy. So far, the various substrates have been identified in the kidneys. Shedding fragments become released ligands, such as Notch and EGFR ligands, and act as the chemoattractant factors including CXCL16. Their ectodomain shedding is closely correlated with pathological factors, which include inflammation, interstitial fibrosis, and renal injury. Also, the substrates of both ADAMs contain the molecules that play important roles at the plasma membrane, such as meaprin, E-cadherin, Klotho, and CADM1. By being released into urine, the shedding products could be useful for biomarkers of renal diseases, but ADAM10 and 17 per se are also notable as biomarkers. Furthermore, ADAM10 and/or 17 inhibitions based on various strategies such as small molecules, antibodies, and their recombinant prodomains are valuable, because they potentially protect renal tissues and promote renal regeneration. Although temporal and spatial regulations of inhibitors are problems to be solved, their inhibitors could be useful for renal diseases.

In Asia, much effort is put into reducing methane (CH _4 ) emissions due to the region’s contribution to the recent rapid global atmospheric CH _4 concentration growth. Accurate quantification of Asia’s CH _4 budgets is critical for conducting global stocktake and achieving the long-term temperature goal of the Paris Agreement. In this study, we present top-down estimates of CH _4 emissions from 2009 to 2018 deduced from atmospheric observations from surface network and GOSAT satellite with the high-resolution global inverse model NIES-TM-FLEXPART-VAR. The optimized average CH _4 budgets are 63.40 ± 10.52 Tg y ^−1 from East Asia (EA), 45.20 ± 6.22 Tg y ^−1 from Southeast Asia (SEA), and 64.35 ± 9.28 Tg y ^−1 from South Asia (SA) within the 10 years. We analyzed two 5 years CH _4 emission budgets for three subregions and 13 top-emitting countries with an emission budget larger than 1 Tg y ^−1 , and interannual variabilities for these subregions. Statistically significant increasing trends in emissions are found in EA with a lower emission growth rate during 2014–2018 compared to that during 2009–2013, while trends in SEA are not significant. In contrast to the prior emission, the posterior emission shows a significant decreasing trend in SA. The flux decrease is associated with the transition from strong La Ninña (2010–2011) to strong El Ninño (2015–2016) events, which modulate the surface air temperature and rainfall patterns. The interannual variability in CH _4 flux anomalies was larger in SA compared to EA and SEA. The Southern Oscillation Index correlates strongly with interannual CH _4 flux anomalies for SA. Our findings suggest that the interannual variability in the total CH _4 flux is dominated by climate variability in SA. The contribution of climate variability driving interannual variability in natural and anthropogenic CH _4 emissions should be further quantified, especially for tropical countries. Accounting for climate variability may be necessary to improve anthropogenic emission inventories.

The CO _2 efflux from soil (soil respiration (SR)) is one of the largest fluxes in the global carbon (C) cycle and its response to climate change could strongly influence future atmospheric CO _2 concentrations. Still, a large divergence of global SR estimates and its autotrophic (AR) and heterotrophic (HR) components exists among process based terrestrial ecosystem models. Therefore, alternatively derived global benchmark values are warranted for constraining the various ecosystem model output. In this study, we developed models based on the global soil respiration database (version 5.0), using the random forest (RF) method to generate the global benchmark distribution of total SR and its components. Benchmark values were then compared with the output of ten different global terrestrial ecosystem models. Our observationally derived global mean annual benchmark rates were 85.5 ± 40.4 (SD) Pg C yr ^−1 for SR, 50.3 ± 25.0 (SD) Pg C yr ^−1 for HR and 35.2 Pg C yr ^−1 for AR during 1982–2012, respectively. Evaluating against the observations, the RF models showed better performance in both of SR and HR simulations than all investigated terrestrial ecosystem models. Large divergences in simulating SR and its components were observed among the terrestrial ecosystem models. The estimated global SR and HR by the ecosystem models ranged from 61.4 to 91.7 Pg C yr ^−1 and 39.8 to 61.7 Pg C yr ^−1 , respectively. The most discrepancy lays in the estimation of AR, the difference (12.0–42.3 Pg C yr ^−1 ) of estimates among the ecosystem models was up to 3.5 times. The contribution of AR to SR highly varied among the ecosystem models ranging from 18% to 48%, which differed with the estimate by RF (41%). This study generated global SR and its components (HR and AR) fluxes, which are useful benchmarks to constrain the performance of terrestrial ecosystem models.

The seasonal-cycle amplitude (SCA) of the atmosphere–ecosystem carbon dioxide (CO2) exchange rate is a useful metric of the responsiveness of the terrestrial biosphere to environmental variations. It is unclear, however, what underlying mechanisms are responsible for the observed increasing trend of SCA in atmospheric CO2 concentration. Using output data from the Multi-scale Terrestrial Model Intercomparison Project (MsTMIP), we investigated how well the SCA of atmosphere–ecosystem CO2 exchange was simulated with 15 contemporary terrestrial ecosystem models during the period 1901–2010. Also, we made attempt to evaluate the contributions of potential mechanisms such as atmospheric CO2, climate, land-use, and nitrogen deposition, through factorial experiments using different combinations of forcing data. Under contemporary conditions, the simulated global-scale SCA of the cumulative net ecosystem carbon flux of most models was comparable in magnitude with the SCA of atmospheric CO2 concentrations. Results from factorial simulation experiments showed that elevated atmospheric CO2 exerted a strong influence on the seasonality amplification. When the model considered not only climate change but also land-use and atmospheric CO2 changes, the majority of the models showed amplification trends of the SCAs of photosynthesis, respiration, and net ecosystem production (+0.19 % to +0.50 % yr−1). In the case of land-use change, it was difficult to separate the contribution of agricultural management to SCA because of inadequacies in both the data and models. The simulated amplification of SCA was approximately consistent with the observational evidence of the SCA in atmospheric CO2 concentrations. Large inter-model differences remained, however, in the simulated global tendencies and spatial patterns of CO2 exchanges. Further studies are required to identify a consistent explanation for the simulated and observed amplification trends, including their underlying mechanisms. Nevertheless, this study implied that monitoring of ecosystem seasonality would provide useful insights concerning ecosystem dynamics.

When epithelial cells in vivo are stimulated to proliferate, they crowd and often grow in height. These processes are likely to implicate dynamic interactions among lateral membranous proteins, such as cell adhesion molecule 1 (CADM1), an immunoglobulin superfamily member. Pulmonary epithelial cell lines that express CADM1, named NCI-H441 and RLE-6TN, were grown to become overconfluent in the polarized 2D culture system, and were examined for the expression of CADM1. Western analyses showed that the CADM1 expression levels increased gradually up to 3 times in a cell density-dependent manner. Confocal microscopic observations revealed dense immunostaining for CADM1 on the lateral membrane. In the overconfluent monolayers, CADM1 knockdown was achieved by two methods using CADM1-targeting siRNA and an anti-CADM1 neutralizing antibody. Antibody treatment experiments were also done on 6 other epithelial cell lines expressing CADM1. The CADM1 expression levels were reduced roughly by half, in association with cell height decrease by half in 3 lines. TUNEL assays revealed that the CADM1 knockdown increased the proportion of TUNEL-positive apoptotic cells approximately 10 folds. Increased expression of CADM1 appeared to contribute to cell survival in crowded epithelial monolayers.

Paddy fields play very important environmental roles in food security, water resource management, biodiversity conservation, and climate change. Therefore, reliable broad-scale paddy field maps are essential for understanding these issues related to rice and paddy fields. Here, we propose a novel paddy field mapping method that uses Sentinel-1 synthetic aperture radar (SAR) time series that are robust for cloud cover, supplemented by Sentinel-2 optical images that are more reliable than SAR data for extracting irrigated paddy fields. Paddy fields were provisionally specified by using the Sentinel-1 SAR data and a conventional decision tree method. Then, an additional mask using water and vegetation indexes based on Sentinel-2 optical images was overlaid to remove non-paddy field areas. We used the proposed method to develop a paddy field map for Japan in 2018 with a 30 m spatial resolution. The producer’s accuracy of this map (92.4%) for non-paddy reference agricultural fields was much higher than that of a map developed by the conventional method (57.0%) using only Sentinel-1 data. Our proposed method also reproduced paddy field areas at the prefecture scale better than existing paddy field maps developed by a remote sensing approach.

Land-use change affects both the quality and quantity of soil organic carbon (SOC) and leads to changes in ecosystem functions such as productivity and environmental regulation. Future changes in SOC are, however, highly uncertain owing to its heterogeneity and complexity. In this study, we analyzed the outputs of simulations of SOC stock by Earth system models (ESMs), most of which are participants in the Land-Use Model Intercomparison Project. Using a common protocol and the same forcing data, the ESMs simulated SOC distribution patterns and their changes during historical (1850–2014) and future (2015–2100) periods. Total SOC stock increased in many simulations over the historical period (30 ± 67 Pg C) and under future climate and land-use conditions (48 ± 32 Pg C for ssp126 and 49 ± 58 Pg C for ssp370 ). Land-use experiments indicated that changes in SOC attributable to land-use scenarios were modest at the global scale, in comparison with climatic and rising CO _2 impacts, but they were notable in several regions. Future net soil carbon sequestration rates estimated by the ESMs were roughly 0.4‰ yr ^−1 (0.6 Pg C yr ^−1 ). Although there were considerable inter-model differences, the rates are still remarkable in terms of their potential for mitigation of global warming. The disparate results among ESMs imply that key parameters that control processes such as SOC residence time need to be better constrained and that more comprehensive representation of land management impacts on soils remain critical for understanding the long-term potential of soils to sequester carbon.

Arctic ecosystems are particularly vulnerable to climate change because of Arctic amplification. Here, we assessed the climatic impacts of low-end, 1.5 °C, and 2.0 °C global temperature increases above pre-industrial levels, on the warming of terrestrial ecosystems in northern high latitudes (NHL, above 60 °N including pan-Arctic tundra and boreal forests) under the framework of the Inter-Sectoral Impact Model Intercomparison Project phase 2b protocol. We analyzed the simulated changes of net primary productivity, vegetation biomass, and soil carbon stocks of eight ecosystem models that were forced by the projections of four global climate models and two atmospheric greenhouse gas pathways (RCP2.6 and RCP6.0). Our results showed that considerable impacts on ecosystem carbon budgets, particularly primary productivity and vegetation biomass, are very likely to occur in the NHL areas. The models agreed on increases in primary productivity and biomass accumulation, despite considerable inter-model and inter-scenario differences in the magnitudes of the responses. The inter-model variability highlighted the inadequacies of the present models, which fail to consider important components such as permafrost and wildfire. The simulated impacts were attributable primarily to the rapid temperature increases in the NHL and the greater sensitivity of northern vegetation to warming, which contrasted with the less pronounced responses of soil carbon stocks. The simulated increases of vegetation biomass by 30–60 Pg C in this century have implications for climate policy such as the Paris Agreement. Comparison between the results at two warming levels showed the effectiveness of emission reductions in ameliorating the impacts and revealed unavoidable impacts for which adaptation options are urgently needed in the NHL ecosystems.

We employed a global high-resolution inverse model to optimize the CH4 emission using Greenhouse gas Observing Satellite (GOSAT) and surface observation data for a period from 2011−2017 for the two main source categories of anthropogenic and natural emissions. We used the Emission Database for Global Atmospheric Research (EDGAR v4.3.2) for anthropogenic methane emission and scaled them by country to match the national inventories reported to the United Nations Framework Convention on Climate Change (UNFCCC). Wetland and soil sink prior fluxes were simulated using the Vegetation Integrative Simulator of Trace gases (VISIT) model. Biomass burning prior fluxes were provided by the Global Fire Assimilation System (GFAS). We estimated a global total anthropogenic and natural methane emissions of 340.9 Tg CH4 yr−1 and 232.5 Tg CH4 yr−1, respectively. Country-scale analysis of the estimated anthropogenic emissions showed that all the top-emitting countries showed differences with their respective inventories to be within the uncertainty range of the inventories, confirming that the posterior anthropogenic emissions did not deviate from nationally reported values. Large countries, such as China, Russia, and the United States, had the mean estimated emission of 45.7 ± 8.6, 31.9 ± 7.8, and 29.8 ± 7.8 Tg CH4 yr−1, respectively. For natural wetland emissions, we estimated large emissions for Brazil (39.8 ± 12.4 Tg CH4 yr−1), the United States (25.9 ± 8.3 Tg CH4 yr−1), Russia (13.2 ± 9.3 Tg CH4 yr−1), India (12.3 ± 6.4 Tg CH4 yr−1), and Canada (12.2 ± 5.1 Tg CH4 yr−1). In both emission categories, the major emitting countries all had the model corrections to emissions within the uncertainty range of inventories. The advantages of the approach used in this study were: (1) use of high-resolution transport, useful for simulations near emission hotspots, (2) prior anthropogenic emissions adjusted to the UNFCCC reports, (3) combining surface and satellite observations, which improves the estimation of both natural and anthropogenic methane emissions over spatial scale of countries.

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 CH4 yr−1 for Russia, 12.8 to 14.3 Tg CH4 yr−1 for temperate South America, and 43.2 to 44.9 Tg CH4 yr−1 for contiguous USA, and the values decrease from 54 to 51.3 Tg CH4 yr−1 for China, 26.2 to 25.5 Tg CH4 yr−1 for Europe, and by 12.4 Tg CH4 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.

Pulmonary emphysema usually arises in cigarette smokers, and often progresses after smoking cessation and even in ex-smokers. Lung-epithelial cell adhesion molecule 1 (CADM1), an immunoglobulin superfamily member, is extracellularly shed to produce a proapoptotic C-terminal fragment (CTF) within the cell and contribute to the development of emphysema. Here, we made an ex-smoker model using C57BL/6 mice; mice (6-week-old; 5 mice per group) were exposed to passive smoke of eight cigarettes twice a day 5 days a week until 18 weeks of age, and were then left untreated until 30 weeks of age. We calculated the mean linear intercept (Lm) and the alveolar septal thickness in the lung histologic sections to estimate the alveolar space dilatation. At 18 weeks of age, Lm was marginally enlarged (P = 0.023) with a marked increase in the septal thickness (P < 0.001) in comparison with age-matched control mice (5 mice per group), while at 30 weeks, the increase in Lm was much more prominent (P = 0.006) and the septal thickness was normalized, suggesting that emphysema progressed with septal remodeling during smoking cessation. Western blot analyses of the lungs were performed for CADM1, a possible CADM1 sheddase ADAM10, an epithelial marker pan-cytokeratin, and a myofibroblastic marker α-smooth muscle actin to estimate the expression levels of CTF and ADAM10 per epithelial cell and the levels of pan-cytokeratin and αSMA per tissue. CADM1 shedding was increased in the treated mice than in control mice at both ages, in association with an increase in the CTF level at 30 weeks (P = 0.021). In total of the treated and control mice of 30 weeks of age, Lm was positively correlated with the CTF and ADAM10 levels, and pan-cytokeratin was negatively correlated with CTF, suggesting an involvement of CADM1 shedding in emphysema progression. Positive correlations were also found between CTF and ADAM10, and between ADAM10 and αSMA, suggesting that increased septal myofibroblasts might be involved in increased CADM1 shedding. Taken together, persisting increase in ectodomain shedding of CADM1 appeared to contribute to the progression of emphysema in ex-smokers, and might be accounted for by alveolar septal remodeling.

Intraluminal pressure elevation can cause degenerative disorders, such as ileus and hydronephrosis, and the threshold is fairly low and constant, 20–30 cm H2O. We previously devised a novel two-chamber culture system subjecting cells cultured on a semipermeable membrane to increased culture medium height (water pressure up to 60 cm H2O). Here, we sought to determine how a continuous pressure load of ~30 cm H2O affects proliferating epithelial cells with special interest in the link with cell morphology. We cultured several different cell lines using the low static pressure-loadable two-chamber system, and examined cell growth, cell cycle, and cell morphology. Madin–Darby canine kidney (MDCK) columnar epithelial cells were growth-suppressed in a manner dependent on static water pressure ranging from 2 to 50 cm H2O, without cell cycle arrest at any specific phase. Two other types of columnar epithelial cells exhibited similar phenotypes. By contrast, spherical epithelial and mesenchymal cells were not growth-suppressed, even at 50 cm H2O. Phalloidin staining revealed that 50 cm H2O pressure load vertically flattened and laterally widened columnar epithelial cells and made actin fiber distribution sparse, without affecting total phalloidin intensity per cell. When the mucosal protectant irsogladine maleate (100 nM) was added to 50-cm-high culture medium, MDCK cells were reduced in volume and their doubling time shortened. Cell proliferation and morphology are known to be regulated by the Hippo signaling pathway. A pressure load of 50 cm H2O enhanced serine-127 phosphorylation and cytoplasmic retention of YAP, the major constituent of this pathway, suggesting that Hippo pathway was involved in the pressure-induced cell growth suppression. RNA sequencing of MDCK cells showed that a 50 cm H2O pressure load upregulated keratin 14, an intermediate filament, 12-fold. This upregulation was confirmed at the protein level by immunofluorescence, suggesting a role in cytoskeletal reinforcement. These results provide evidence that cell morphology and the cytoskeleton are closely linked to cell growth. Pathological intraluminal pressure elevation may cause mucosal degeneration by acting directly on this linkage and the Hippo pathway.

Epithelial carcinomas occasionally have sarcomatous components that consist primarily of spindle and cuboidal cells, which often resemble osteoblasts. Sarcomatoid carcinomas consist of similar cells. Recent studies have characterized these phenomena as a manifestation of epithelial–mesenchymal transition in carcinoma cells, but the mesenchymal phenotypes that manifest in sarcomatous cells of epithelial carcinomas are not well understood. Here, we examined the expression profiles of four osteoblastic differentiation biomarkers in the sarcomatous components of multiple carcinoma types, including five renal clear cell, four breast invasive ductal, two esophageal, one maxillary squamous cell, three larynx, three lung, one liver, and one skin sarcomatoid carcinoma. Expression was analyzed by immunohistochemistry using antibodies against cell adhesion molecule 1, a member of the IgCAM superfamily, osterix transcription factor (Osterix), cluster of differentiation 151, a transmembrane 4 superfamily member, and alkaline phosphatase. Immunostaining intensity was rated in scale 0 (negative), 0.5 (weak), and 1 (strong) for each marker, and the four scale values were summed to calculate osteoblastic scores. In all, 10 cases had a osteoblastic score ≥3, and all of these 10 cases were cell adhesion molecule 1- and Osterix-positive. Eight and five of the nine samples with a osteoblastic score

Transparent Nd-doped Lu2O3 bodies were fabricated by spark plasma sintering, and the effect of LiF addition on sintering, microstructure and transparency of Nd-doped Lu2O3 bodies were investigated. LiF promoted the densification at an early stage of sintering, resulted in high transparency of the Nd-doped Lu2O3 body. The optimal content of LiF was 0.2 wt% and that Nd-doped Lu2O3 body showed a transmittance of 81.8% (99.5% of theoretical) at 1080 nm after annealing in air for 21.6 ks.

Litter production is a fundamental ecosystem process, which plays an important role in regulating terrestrial carbon and nitrogen cycles. However, there are substantial differences in the litter production simulations among ecosystem models, and a global benchmarking evaluation to measure the performance of these models is still lacking. In this study, we generated a global dataset of aboveground litterfall production (i.e. cLitter), a benchmark as the defined reference to test model performance, by combining systematic measurements taken from a substantial number of surveys (1079 sites) with a machine learning technique (i.e. random forest, RF). Our study demonstrated that the RF model is an effective tool for upscaling local litterfall production observations to the global scale. On average, the model predicted 23.15 Pg C yr ^−1 of aboveground litterfall production. Our results revealed substantial differences in the aboveground litterfall production simulations among the five investigated ecosystem models. Compared to the reference data at the global scale, most of models could reproduce the spatial patterns of aboveground litterfall production, but the magnitude of simulations differed substantially from the reference data. Overall, ORCHIDEE-MICT performed the best among the five investigated ecosystem models.

The Amazon is a significant source of atmospheric methane, but little is known about the source response to increasing drought severity and frequency. We investigated satellite observations of atmospheric column-averaged methane for the 2010 drought and subsequent 2011 wet year in the Amazon using an atmospheric inversion scheme. Our analysis indicates an increase in atmospheric methane over the southern Amazon region during the drought, representing an increase in annual emissions relative to the wet year. We attribute the increase to emissions from biomass burning driven by intense drought, combined with carbon monoxide showing seasonal variations corresponding to methane variations. We show that there is probably a strong correspondence between drought and methane emissions in the Amazon.

Runoff in the United States is changing, and this study finds that the measured change is dependent on the geographic region and varies seasonally. Specifically, observed annual total runoff had an insignificant increasing trend in the US between 1950 and 2010, but this insignificance was due to regional heterogeneity with both significant and insignificant increases in the eastern, northern, and southern US, and a greater significant decrease in the western US. Trends for seasonal mean runoff also differed across regions. By region, the season with the largest observed trend was autumn for the east (positive), spring for the north (positive), winter for the south (positive), winter for the west (negative), and autumn for the US as a whole (positive). Based on the detection and attribution analysis using gridded WaterWatch runoff observations along with semi-factorial land surface model simulations from the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), we found that while the roles of CO _2 concentration, nitrogen deposition, and land use and land cover were inconsistent regionally and seasonally, the effect of climatic variations was detected for all regions and seasons, and the change in runoff could be attributed to climate change in summer and autumn in the south and in autumn in the west. We also found that the climate-only and historical transient simulations consistently underestimated the runoff trends, possibly due to precipitation bias in the MsTMIP driver or within the models themselves.

Actual land evapotranspiration (ET) is a key component of the global hydrological cycle and an essential variable determining the evolution of hydrological extreme events under different climate change scenarios. However, recently available ET products show persistent uncertainties that are impeding a precise attribution of human-induced climate change. Here, we aim at comparing a range of independent global monthly land ET estimates with historical model simulations from the global water, agriculture, and biomes sectors participating in the second phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2a). Among the independent estimates, we use the EartH2Observe Tier-1 dataset (E2O), two commonly used reanalyses, a pre-compiled ensemble product (LandFlux-EVAL), and an updated collection of recently published datasets that algorithmically derive ET from observations or observations-based estimates (diagnostic datasets). A cluster analysis is applied in order to identify spatio-temporal differences among all datasets and to thus identify factors that dominate overall uncertainties. The clustering is controlled by several factors including the model choice, the meteorological forcing used to drive the assessed models, the data category (models participating in the different sectors of ISIMIP2a, E2O models, diagnostic estimates, reanalysis-based estimates or composite products), the ET scheme, and the number of soil layers in the models. By using these factors to explain spatial and spatio-temporal variabilities in ET, we find that the model choice mostly dominates (24%–40% of variance explained), except for spatio-temporal patterns of total ET, where the forcing explains the largest fraction of the variance (29%). The most dominant clusters of datasets are further compared with individual diagnostic and reanalysis-based estimates to assess their representation of selected heat waves and droughts in the Great Plains, Central Europe and western Russia. Although most of the ET estimates capture these extreme events, the generally large spread among the entire ensemble indicates substantial uncertainties.

This paper evaluates the ability of eight global vegetation models to reproduce recent trends and inter-annual variability of biomass in natural terrestrial ecosystems. For the purpose of this evaluation, the simulated trajectories of biomass are expressed in terms of the relative rate of change in biomass (RRB), defined as the deviation of the actual rate of biomass turnover from its equilibrium counterpart. Cumulative changes in RRB explain long-term changes in biomass pools. RRB simulated by the global vegetation models is compared with its observational equivalent, derived from vegetation optical depth reconstructions of above-ground biomass (AGB) over the period 1993–2010. According to the RRB analysis, the rate of global biomass growth described by the ensemble of simulations substantially exceeds the observation. The observed fluctuations of global RRB are significantly correlated with El Niño Southern Oscillation events (ENSO), but only some of the simulations reproduce this correlation. However, the ENSO sensitivity of RRB in the tropics is not significant in the observation, while it is in some of the simulations. This mismatch points to an important limitation of the observed AGB reconstruction to capture biomass variations in tropical forests. Important discrepancies in RRB were also identified at the regional scale, in the tropical forests of Amazonia and Central Africa, as well as in the boreal forests of north-western America, western and central Siberia. In each of these regions, the RRBs derived from the simulations were analyzed in connection with underlying differences in net primary productivity and biomass turnover rate ̶as a basis for exploring in how far differences in simulated changes in biomass are attributed to the response of the carbon uptake to CO _2 increments, as well as to the model representation of factors affecting the rates of mortality and turnover of foliage and roots. Overall, our findings stress the usefulness of using RRB to evaluate complex vegetation models and highlight the importance of conducting further evaluations of both the actual rate of biomass turnover and its equilibrium counterpart, with special focus on their background values and sources of variation. In turn, this task would require the availability of more accurate multi-year observational data of biomass and net primary productivity for natural ecosystems, as well as detailed and updated information on land-cover classification.

NASA has launched the decade-long Arctic-Boreal Vulnerability Experiment (ABoVE). While the initial phases focus on field and airborne data collection, early integration with modeling activities is important to benefit future modeling syntheses. We compiled feedback from ecosystem modeling teams on key data needs, which encompass carbon biogeochemistry, vegetation, permafrost, hydrology, and disturbance dynamics. A suite of variables was identified as part of this activity with a critical requirement that they are collected concurrently and representatively over space and time. Individual projects in ABoVE may not capture all these needs, and thus there is both demand and opportunity for the augmentation of field observations, and synthesis of the observations that are collected, to ensure that science questions and integrated modeling activities are successfully implemented.

This paper proposes a novel seismometer-type absolute displacement sensor aimed at detecting earthquake waves with a large magnitude and long period. However, since the measuring range of the conventional displacement sensor is higher than the natural frequency of itself, it is difficult to detect a low frequency vibration below 1Hz using conventional seismic-type displacement sensors. In order to provide an absolute displacement detection which is capable of lowering the natural frequency and enlarging the detectable amplitude without causing a structural defect, the relative signals of displacement, velocity, and acceleration between a detected object and the auxiliary mass of the sensor are fed back into the sensor. In addition, a phase lag compensation is inserted to adjust phase angles, which are below a frequency lower than 1Hz. Theoretically, this sensor is able to detect a lower frequency range from 0.2Hz to 10Hz and large amplitude with 100 times to the movable range of the sensor. It has been demonstrated by experiments that the developed sensor with a small size and lightweight has a detecting range from 0.2 Hz to 10Hz for absolute displacement and velocity. As an additional advantage, the measurement displacement amplitude has been expanded to about 40dB (100 times) for detecting earthquake waves with large magnitude and long period. As the typical application example of the developed absolute displacement sensor, a seismic wave based on Hachinohe wave is used with well observation results.

Somatic mutations in KRAS, NRAS, and BRAF genes are related to resistance to anti-EGFR antibodies in colorectal cancer. We have established an extended RAS and BRAF mutation assay using a next-generation sequencer to analyze these mutations. Multiplexed deep sequencing was performed to detect somatic mutations within KRAS, NRAS, and BRAF, including minor mutated components. We first validated the technical performance of the multiplexed deep sequencing using 10 normal DNA and 20 formalin-fixed, paraffin-embedded (FFPE) tumor samples. To demonstrate the potential clinical utility of our assay, we profiled 100 FFPE tumor samples and 15 plasma samples obtained from colorectal cancer patients. We used a variant calling approach based on a Poisson distribution. The distribution of the mutation-positive population was hypothesized to follow a Poisson distribution, and a mutation-positive status was defined as a value greater than the significance level of the error rate (α = 2 x 10(-5)). The cut-off value was determined to be the average error rate plus 7 standard deviations. Mutation analysis of 100 clinical FFPE tumor specimens was performed without any invalid cases. Mutations were detected at a frequency of 59% (59/100). KRAS mutation concordance between this assay and Scorpion-ARMS was 92% (92/100). DNA obtained from 15 plasma samples was also analyzed. KRAS and BRAF mutations were identified in both the plasma and tissue samples of 6 patients. The genetic screening assay using next-generation sequencer was validated for the detection of clinically relevant RAS and BRAF mutations using FFPE and liquid samples.