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Low cloud fractions (LCFs) and meteorological factors (MFs) over an oceanic region containing multiple cloud regimes are examined for three data sets: one Energy Exascale Earth System Model (E3SM) simulation with the default 72‐layer vertical grid (E3SM72), another one with 8‐times vertical resolution via the Framework for Improvement by Vertical Enhancement (E3SM×8), and one with MFs from ERA5 reanalysis and LCFs from the CERES SSF product (ERA5‐SSF). Neural networks (NNs) are trained to capture the relationship between MFs and LCF and to select the best‐performing MF subsets for predicting LCF. NN ensembles are used to (a) confirm the performance of selected MF subsets, (b) to serve as proxy models for each data set to predict LCFs for MFs from all data sets, and (c) to classify MFs into those in shared and uniquely occupied MF subspaces. Overall, E3SM72 and E3SM×8 have large fractions of MFs in shared MF subspace, but less so near the Californian and Peruvian stratocumulus decks. E3SM×8 and ERA5 have small fractions of MFs in shared MF subspace but greater than E3SM72 and ERA5, especially in the Southeast Pacific. The differences in LCFs between three pairs of data sets are decomposed into those associated with the differences in the LCF‐MF relationship and those involving different MFs. Given the same MFs, LCFs produced by E3SM×8 are greater than those produced by E3SM72 but are still different from those in ERA5‐SSF. In general, the shift in MFs dominates the difference in the LCFs. Plain Language Summary: Marine warm low clouds are critical for both present day and future climate because they reflect a lot of solar energy back to space. To make more reliable projections of our changing climate, scientists need to improve these clouds in climate models. One question that scientists ask is, why do the climate models predict so much less marine warm low cloud cover than the satellites see? Is it because the models misrepresent the meteorology (like temperature and humidity) or because they are not able to produce enough clouds even if they predict the meteorology well. In this work, we use neural networks, a machine learning technique, to answer these questions. We find that our recent efforts to improve a climate model help the model produce more marine warm low clouds given the same meteorology; these efforts also lead to changes in the meteorology predicted by the model. Further model improvements are needed to bring the model predictions closer to the observations. Key Points: Neural network ensembles are able to detect how different meteorological factors are between E3SM, E3SM‐FIVE, and observationsE3SM‐FIVE high vertical resolution simulation improves marine warm low clouds fractions given the same meteorological factorsMeteorological factors between the three data sets are large enough to dominate the differences in marine warm low cloud fractions [ABSTRACT FROM AUTHOR]

Abstract: The control over the regio- and/or stereo-selective aliphatic C H oxidation by metalloenzymes is of great interest to scientists. Typically, these enzymes invoke host–guest chemistry to sequester the substrates within the protein pockets, exploiting sizes, shapes and specific interactions such as hydrogen-bonding, electrostatic forces and/or van der Waals interactions to control the substrate specificity, regio-specificity and stereo-selectivity. Over the years, we have developed a series of deuterated and fluorinated variants of these hydrocarbon substrates as probes to gain insights into the controlled C H oxidations of hydrocarbons facilitated by these enzymes. In this review, we illustrate the application of these designed probes in the study of three monooxygenases: (i) the particulate methane monooxygenase (pMMO) from Methylococcus capsulatus (Bath), which oxidizes straight-chain C1–C5 alkanes and alkenes to form their corresponding 2-alcohols and epoxides, respectively; (ii) the recombinant alkane hydroxylase (AlkB) from Pseudomonas putida GPo1, which oxidizes the primary C H bonds of C5–C12 linear alkanes; and (iii) the recombinant cytochrome P450 from Bacillus megaterium, which oxidizes C12–C20 fatty acids at the ω-1, ω-2 or ω-3 CH positions. [Copyright &y& Elsevier]

Highlights: [•] We report the DHA biosynthesis through zebrafish fatty acid desaturase (Z-FADS), and elongases (ELOVL2, 4 and 5). [•] First report to demonstrate that Z-FADS interacts with CYB5Rs (2 and 3) and ELOVLs (2, 4, 5 and 7) by FRET. [•] Modeling the trans-membrane helices for ELOVL2, 4, 5 and 7 by FRET. [•] Z-FADS locates not only in endoplasmic reticulum but also in mitochondria in HeLa cells. [ABSTRACT FROM AUTHOR]

Abstract: Grouper iridovirus (GIV) is one of the most devastating infectious pathogens of aquaculture fish. When infecting a susceptible cell line, such as GK-2, GIV causes antigenic changes in host cellular proteins. To understand the host gene expression characteristics after viral infection, we developed an immunostaining method to screen differentially expressed genes of fish cells in response to GIV infection using phage display complementary DNA libraries. In total, 66 genes were identified from grouper kidney and brain cell lines. These genes are related to replication, transcription, translation, immunity, apoptosis, structure proteins, metabolism, energy, protein modification, and homeostasis. Four dynamic antigenic patterns were observed among these immunocloned genes upon GIV infection. Microarray analysis further confirmed the transcriptional patterns of 80% of the identified genes. This immunostaining screening method provides insights into a host’s cellular protein response to viral infection on a translational basis. [Copyright &y& Elsevier]

High-dynamic-range (HDR) images offer better visual quality that is much closer to reality by allowing a wider range of luminance. Because of the rarity of devices that directly capture/display scenes in HDR format, HDR images are usually generated using several low-dynamic-range (LDR) images with various exposure settings and then displayed on the conventional display, after tone mapping. This paper proposes HDR generation for multi-view images considering the need to provide the user with an expanded visual experience, not only in terms of a wider field of view (FOV), but also with a greater dynamic range. This novel technique generates HDR multi-view images in an efficient way, and only NLDR images are needed to render HDR images in N views. Furthermore, to efficiently transmit the multi-view image with various exposure, two coding architectures are proposed. The experimental results show that the proposed schemes are capable of achieving 39.5 % bitrate savings and give a rendered HDR image with greatly improved quality, compared to a conventional multi-view coding scheme. [ABSTRACT FROM AUTHOR]

Abstract: The rapid growth of energy consumption in conjunction with economic development during past decades in East Asia, especially China, caused severe air pollution problems at local and regional scales. Understanding of the meteorological conditions for air pollution is essential to the understanding of the formation mechanism of air pollutants and the development of effective emission control strategies to reduce air pollution. In this paper, the Fifth Generation National Center for Atmospheric Research (NCAR)/Pennsylvania State University (PSU) Mesoscale Model (MM5) modeling system is applied to simulate meteorological fields during selected six 1-month periods in 2007/2008 over a triple-nested modeling domain covering East Asia, the eastern China, and Shandong Province at horizontal grid resolutions of 36-, 12-, and 4-km, respectively. MM5 generally reproduces well the observations in the eastern China but performs worse in the western China and northeastern China. Largest biases occur in 2-m temperatures (T2) and wind speed and wind direction at 10-m in haze months (i.e., winter) and daily mean precipitation (Precip) in non-haze months (i.e., summer), due to limitations of the model in simulating snow cover and convective precipitation. Meteorological predictions agree more closely with observations at urban sites than those at the coastal and mountain sites where the model performance deteriorates because of complex terrains, influences of urban heat island effect and land/sea breezes, and higher elevations. Model results at 12-km in Shandong Province show an overall better performance than those at 4- or 36-km while the results at 4-km show worst performance due to inaccurate land use and the model’s incapability in simulating meteorological processes at a fine scale. [Copyright &y& Elsevier]

The potential for polarimetric Doppler radar measurements to improve predictions of ice microphysical processes within an idealized model–observational framework is examined. In an effort to more rigorously constrain ice growth processes (e.g., vapor deposition) with observations of natural clouds, a novel framework is developed to compare simulated and observed radar measurements, coupling a bulk adaptive-habit model of vapor growth to a polarimetric radar forward model. Bayesian inference on key microphysical model parameters is then used, via a Markov chain Monte Carlo sampler, to estimate the probability distribution of the model parameters. The statistical formalism of this method allows for robust estimates of the optimal parameter values, along with (non-Gaussian) estimates of their uncertainty. To demonstrate this framework, observations from Department of Energy radars in the Arctic during a case of pristine ice precipitation are used to constrain vapor deposition parameters in the adaptive habit model. The resulting parameter probability distributions provide physically plausible changes in ice particle density and aspect ratio during growth. A lack of direct constraint on the number concentration produces a range of possible mean particle sizes, with the mean size inversely correlated to number concentration. Consistency is found between the estimated inherent growth ratio and independent laboratory measurements, increasing confidence in the parameter PDFs and demonstrating the effectiveness of the radar measurements in constraining the parameters. The combined Doppler and polarimetric observations produce the highest-confidence estimates of the parameter PDFs, with the Doppler measurements providing a stronger constraint for this case. [ABSTRACT FROM AUTHOR]

The single-column model (SCM) functionality of the Energy Exascale Earth System Model version 1 (E3SMv1) is described in this paper. The E3SM SCM was adopted from the SCM used in the Community Atmosphere Model (CAM) but has evolved significantly since then. We describe changes made to the aerosol specification in the SCM, idealizations, and developments made so that the SCM uses the same dynamical core as the full general circulation model (GCM) component. Based on these changes, we describe and demonstrate the seamless capability to "replay" a GCM column using the SCM. We give an overview of the E3SM case library and briefly describe which cases may serve as useful proxies for replicating and investigate some long-standing biases in the full GCM runs while demonstrating that the E3SM SCM is an efficient tool for both model development and evaluation. [ABSTRACT FROM AUTHOR]

The single column model (SCM) functionality of the Energy Exascale Earth System Model version 1 (E3SMv1) is described in this paper. The E3SM SCM was adopted from the SCM used in the Community Atmosphere Model (CAM), but has evolved significantly since then. We describe changes made to the aerosol specification in the SCM, idealizations, and developments made so that the SCM uses the same dynamical core as the full general circulation model (GCM) component. Based on these changes, we describe and demonstrate the seamless capability to "replay" a GCM column using the SCM. We give an overview of the E3SM case library and briefly describe which cases may serve as useful proxies for replicating and investigate some long standing biases in the full GCM runs, while demonstrating that the E3SM SCM is an efficient tool for both model development and evaluation. [ABSTRACT FROM AUTHOR]

C1q/tumor necrosis factor-related protein 6 (CTRP6), an adipose-tissue secretory factor, plays an important role in inflammatory reaction and carcinogenesis. However, the biological function of CTRP6 in adipogenesis remains unclear. In this study, we examined the effects of CTRP6 knockdown on lipogenesis of 3T3-L1 adipocytes. The results showed that after 3T3-L1 adipocytes transfected with anti-CTRP6 small interfering RNA (siRNA), not only levels of secreted CTRP6 protein in the culture medium but also the expression level of the CTRP6 protein in the 3T3-L1 adipocytes was significantly reduced ( P < 0.01). In addition, the number of lipid droplets in the adipocytes was reduced, as well as the OD values reflecting the fat content being significantly decreased ( P < 0.01). Meanwhile the levels of adipogenic markers, including peroxisome proliferator activated receptor γ (PPARγ), CCAAT/enhancer-binding protein α (C/EBPα), CCAAT/enhancer-binding protein β (C/EBPβ) and adipocyte fatty acid-binding protein 4 (aP2), were decreased after treatment with anti-CTRP6 siRNA, whereas the expression of adipose triglyceride lipase (ATGL) and triacylglycerol hydrolase (TGH) were increased. Furthermore, after transfection, activity of phosphorylated Erk1/2 (p-Erk1/2) was inhibited in the early stage of differentiation, but in terminal differentiation of adipocytes, its activity was activated. Taken together, the results indicate that knockdown of CTRP6 can inhibit adipogenesis of 3T3-L1 adipocytes through lipogenic marker genes and Erk1/2 signaling pathway. [ABSTRACT FROM AUTHOR]

In this study, we describe efforts to clarify the role of the copper cofactors associated with subunit B (PmoB) of the particulate methane monooxygenase (pMMO) from Methylococcus capsulatus (Bath) (M. capsulatus). This subunit exhibits strong affinity toward CuI ions. To elucidate the high copper affinity of the subunit, the full-length PmoB, and the N -terminal truncated mutants PmoB 33–414 and PmoB 55–414 , each fused to the maltose-binding protein (MBP), are cloned and over-expressed into Escherichia coli (E. coli) K12 TB1 cells. The Y374F, Y374S and M300L mutants of these protein constructs are also studied. When this E. coli is grown with the pmoB gene in 1.0 mM CuII, it behaves like M. capsulatus (Bath) cultured under high copper stress with abundant membrane accumulation and high CuI content. The recombinant PmoB proteins are verified by Western blotting of antibodies directed against the MBP sub-domain in each of the copper-enriched PmoB proteins. Cu K -edge X-ray absorption near edge spectroscopy (XANES) of the copper ions confirms that all the PmoB recombinants are CuI proteins. All the PmoB proteins show evidence of a "dicopper site" according to analysis of the Cu extended X-ray absorption edge fine structure (EXAFS) of the membranes. No specific activities toward methane and propene oxidation are observed with the recombinant membrane-bound PmoB proteins. However, significant production of hydrogen peroxide is observed in the case of the PmoB 33–414 mutant. Reaction of the dicopper site with dioxygen produces hydrogen peroxide and leads to oxidation of the CuI ions residing in the C-terminal sub-domain of the PmoB subunit. Subunit B (PmoB) of the particulate methane monooxygenase (pMMO) in Methylococcus capsulatus (Bath) has been cloned and over-expressed in E. coli K12 TB1 cells as a multicopper cytoplasmic membrane protein with ca. 9 CuI ions and shown to produce H 2 O 2 upon reaction of O 2 with the dicopper site. Unlabelled Image • Subunit B (PmoB) of particulate methane monooxygenase (pMMO) is expressed in E. coli. • PmoB and its variants/mutants are expressed in the membranes as CuI proteins. • The PmoB of pMMO contains a CuI sponge with high reduction potentials for the Cu sites. • The PmoB proteins show evidence of a dinuclear copper site. • The PmoB-enriched E. coli membranes produce H 2 O 2. [ABSTRACT FROM AUTHOR]