Description: This paper presents global comparisons of fundamental global climate variables from a suite of four pairs of matched low- and high-resolution ocean and sea ice simulations that are obtained following the OMIP-2 protocol (Griffies et al., 2016) and integrated for one cycle (1958–2018) of the JRA55-do atmospheric state and runoff dataset (Tsujino et al., 2018). Our goal is to assess the robustness of climate-relevant improvements in ocean simulations (mean and variability) associated with moving from coarse (∼ 1∘) to eddy-resolving (∼ 0.1∘) horizontal resolutions. The models are diverse in their numerics and parameterizations, but each low-resolution and high-resolution pair of models is matched so as to isolate, to the extent possible, the effects of horizontal resolution. A variety of observational datasets are used to assess the fidelity of simulated temperature and salinity, sea surface height, kinetic energy, heat and volume transports, and sea ice distribution. This paper provides a crucial benchmark for future studies comparing and improving different schemes in any of the models used in this study or similar ones. The biases in the low-resolution simulations are familiar, and their gross features – position, strength, and variability of western boundary currents, equatorial currents, and the Antarctic Circumpolar Current – are significantly improved in the high-resolution models. However, despite the fact that the high-resolution models “resolve” most of these features, the improvements in temperature and salinity are inconsistent among the different model families, and some regions show increased bias over their low-resolution counterparts. Greatly enhanced horizontal resolution does not deliver unambiguous bias improvement in all regions for all models.

Description: The evaluation and model element description of the second version of the unstructured-mesh Finite-volumE Sea ice-Ocean Model (FESOM2.0) are presented. The new version of the model takes advantage of the finite-volume approach, whereas its predecessor version, FESOM1.4 was based on the finite-element approach. The model sensitivity to arbitrary Lagrangian–Eulerian (ALE) linear and nonlinear free-surface formulation, Gent–McWilliams eddy parameterization, isoneutral Redi diffusion and different vertical mixing schemes is documented. The hydrographic biases, large-scale circulation, numerical performance and scalability of FESOM2.0 are compared with its predecessor, FESOM1.4. FESOM2.0 shows biases with a magnitude comparable to FESOM1.4 and simulates a more realistic Atlantic meridional overturning circulation (AMOC). Compared to its predecessor, FESOM2.0 provides clearly defined fluxes and a 3 times higher throughput in terms of simulated years per day (SYPD). It is thus the first mature global unstructured-mesh ocean model with computational efficiency comparable to state-of-the-art structured-mesh ocean models. Other key elements of the model and new development will be described in follow-up papers.

Description: We present a new framework for global ocean–sea-ice model simulations based on phase 2 of the Ocean Model Intercomparison Project (OMIP-2), making use of the surface dataset based on the Japanese 55-year atmospheric reanalysis for driving ocean–sea-ice models (JRA55-do). We motivate the use of OMIP-2 over the framework for the first phase of OMIP (OMIP-1), previously referred to as the Coordinated Ocean–ice Reference Experiments (COREs), via the evaluation of OMIP-1 and OMIP-2 simulations from 11 state-of-the-science global ocean–sea-ice models. In the present evaluation, multi-model ensemble means and spreads are calculated separately for the OMIP-1 and OMIP-2 simulations and overall performance is assessed considering metrics commonly used by ocean modelers. Both OMIP-1 and OMIP-2 multi-model ensemble ranges capture observations in more than 80 % of the time and region for most metrics, with the multi-model ensemble spread greatly exceeding the difference between the means of the two datasets. Many features, including some climatologically relevant ocean circulation indices, are very similar between OMIP-1 and OMIP-2 simulations, and yet we could also identify key qualitative improvements in transitioning from OMIP-1 to OMIP-2. For example, the sea surface temperatures of the OMIP-2 simulations reproduce the observed global warming during the 1980s and 1990s, as well as the warming slowdown in the 2000s and the more recent accelerated warming, which were absent in OMIP-1, noting that the last feature is part of the design of OMIP-2 because OMIP-1 forcing stopped in 2009. A negative bias in the sea-ice concentration in summer of both hemispheres in OMIP-1 is significantly reduced in OMIP-2. The overall reproducibility of both seasonal and interannual variations in sea surface temperature and sea surface height (dynamic sea level) is improved in OMIP-2. These improvements represent a new capability of the OMIP-2 framework for evaluating process-level responses using simulation results. Regarding the sensitivity of individual models to the change in forcing, the models show well-ordered responses for the metrics that are directly forced, while they show less organized responses for those that require complex model adjustments. Many of the remaining common model biases may be attributed either to errors in representing important processes in ocean–sea-ice models, some of which are expected to be reduced by using finer horizontal and/or vertical resolutions, or to shared biases and limitations in the atmospheric forcing. In particular, further efforts are warranted to resolve remaining issues in OMIP-2 such as the warm bias in the upper layer, the mismatch between the observed and simulated variability of heat content and thermosteric sea level before 1990s, and the erroneous representation of deep and bottom water formations and circulations. We suggest that such problems can be resolved through collaboration between those developing models (including parameterizations) and forcing datasets. Overall, the present assessment justifies our recommendation that future model development and analysis studies use the OMIP-2 framework.

Description: Disintegration of ice shelves in the Amundsen Sea, in front of the West Antarctic Ice Sheet, has the potential to cause sea level rise by inducing an acceleration of ice discharge from upstream grounded ice. Moore et al. (2018) proposed that using a submarine wall to block the penetration of warm water into the subsurface cavities of these ice shelves could reduce this risk. We use a global sea ice–ocean model to show that a wall shielding the Amundsen Sea below 350 m depth successfully suppresses the inflow of warm water and reduces ice shelf melting. However, these warm water masses get redirected towards neighboring ice shelves, which reduces the net effectiveness of the wall. The ice loss is reduced by 10 %, integrated over the entire Antarctic continent.

Description: Drought stress is one of the most adverse environmental constraints to plant growth and productivity. Comparative proteomics of drought-tolerant and sensitive wheat genotypes is a strategy to understand the co...

Description: Background: RNA binding proteins (RBPs) play a fundamental role in posttranscriptional control of gene expression. Different RBPs have oncogenic or tumor-suppressive functions on human cancers. RNPC1 belongs to the RNA recognition motif (RRM) family of RBPs, which could regulate expression of diverse targets by mRNA stability in human cancer cells. Several studies reported that RNPC1 played an important role in cancer, mostly acting as an oncogene or up-regulating in tumors. However, its role in human breast cancer remains unclear. Methods: In the present study, we investigated the functional and mechanistic roles of RNPC1 in attenuating invasive signal including reverse epithelial-mesenchymal transition (EMT) to inhibit breast cancer cells aggressiveness in vitro. Moreover, RNPC1 suppress tumorigenicity in vivo. Further, we studied the expression of RNPC1 in breast cancer tissue and adjacent normal breast tissue by quantitative RT-PCR (qRT-PCR) and Western blot. Results: We observed that RNPC1 expression was silenced in breast cancer cell lines compared to breast epithelial cells. More important, RNPC1 was frequently silenced in breast cancer tissue compared to adjacent normal breast tissue. Low RNPC1 mRNA expression was associated with higher clinical stages and mutp53, while low level of RNPC1 protein was associated with higher lymph node metastasis, mutp53 and lower progesterone receptor (PR). Functional assays showed ectopic expression of RNPC1 could inhibit breast tumor cell proliferation in vivo and in vitro through inducing cell cycle arrest, and further suppress tumor cell migration and invasion partly through repressing mutant p53 (mutp53) induced EMT. Conclusions: Overall, our findings indicated that RNPC1 had a potential function to play a tumor-suppressor role which may be a potential marker in the therapeutic and prognostic of breast cancer.

Description: Background: High-risk human papillomavirus type 16 (HPV16) is a risk factor for cervical cancer. Previous studies suggest that polymorphisms in the E6 gene or the long control region(LCR)of HPV16 may alter the oncogenic potential of the virus. The aims of this study were to investigate the genetic variations of HPV16 E6 gene and LCR in isolates from Chinese population and correlation of the E6 and LCR polymorphisms with disease status of infected patients. Methods: HPV16 positive endocervical specimens were collected from 304 women living in Northeast of China. Sequences of E6 gene and LCR were analyzed by PCR-sequencing. Results: Two lineages were found in the populations, including EUR lineage and As lineage. Based on the HPV16 prototype, the most frequent variation in the E6 gene was T178A/G (48.7%), followed by mutations of G94A (12.2%) and T350G (9.9%). The rank orders of incidence of E6 variations in amino acid were as follows: D25E (46.3%), L83V (9.9%) and H78Y (4.3%). Nucleotide variations in LCR were found in all the 304 isolates from HPV16 positive cervical samples. The most commonly observed LCR variations were the transition replacement G7193T, 7434CIns, G7521A and 7863ADel (100%). The As lineage was associated with HPV persistent infections and with disease status of 〉=CIN2,3. The EUR lineage variants showed a negative trend of association with the severity of 〉=CIN2,3. Among 41 variations found in LCR, 25 (61.0%) were located at the binding sites for transcription factors. Occurrence of 〉=CIN2,3 was significantly associated with the mutations of R10G/L83V in E6 and the C7294T co-variation in LCR, after adjusting for ages of infected patients. Conclusions: Associations between As lineage and HPV persistent infections, and with disease status of 〉=CIN2,3, and an association between the EUR lineage and negative trend of association with the severity of 〉=CIN2,3 were found in this study. An association between a co-variation of R10G/L83V in E6 and C7294T in LCR and an increased risk for developing CIN-2,3 was found in a HPV16 infected population of Chinese women. These findings indicate that HPV16 polymorphism influences development of CIN-2,3.