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Motivation Constructing a phylogenetic tree requires calculating the evolutionary distance between samples or species via large-scale resequencing data, a process that is both time-consuming and computationally demanding. Striking the right balance between accuracy and efficiency is a significant challenge. Results To address this, we introduce a new algorithm, MIKE (MinHash-based k -mer algorithm). This algorithm is designed for the swift calculation of the Jaccard coefficient directly from raw sequencing reads and enables the construction of phylogenetic trees based on the resultant Jaccard coefficient. Simulation results highlight the superior speed of MIKE compared to existing state-of-the-art methods. We used MIKE to reconstruct a phylogenetic tree, incorporating 238 yeast, 303 Zea , 141 Ficus , 67 Oryza , and 43 Saccharum spontaneum samples. MIKE demonstrated accurate performance across varying evolutionary scales, reproductive modes, and ploidy levels, proving itself as a powerful tool for phylogenetic tree construction. Availability and implementation MIKE is publicly available on Github at https://github.com/Argonum-Clever2/mike.git. [ABSTRACT FROM AUTHOR]

Background: Diagnosis and treatment management for head and neck squamous cell carcinoma (HNSCC) is guided by routine diagnostic head and neck computed tomography (CT) scans to identify tumor and lymph node features. The extracapsular extension (ECE) is a strong predictor of patients' survival outcomes with HNSCC. It is essential to detect the occurrence of ECE as it changes staging and treatment planning for patients. Current clinical ECE detection relies on visual identification and pathologic confirmation conducted by clinicians. However, manual annotation of the lymph node region is a required data preprocessing step in most of the current machine learning‐based ECE diagnosis studies. Purpose: In this paper, we propose a Gradient Mapping Guided Explainable Network (GMGENet) framework to perform ECE identification automatically without requiring annotated lymph node region information. Methods: The gradient‐weighted class activation mapping (Grad‐CAM) technique is applied to guide the deep learning algorithm to focus on the regions that are highly related to ECE. The proposed framework includes an extractor and a classifier. In a joint training process, informative volumes of interest (VOIs) are extracted by the extractor without labeled lymph node region information, and the classifier learns the pattern to classify the extracted VOIs into ECE positive and negative. Results: In evaluation, the proposed methods are well‐trained and tested using cross‐validation. GMGENet achieved test accuracy and area under the curve (AUC) of 92.2% and 89.3%, respectively. GMGENetV2 achieved 90.3% accuracy and 91.7% AUC in the test. The results were compared with different existing models and further confirmed and explained by generating ECE probability heatmaps via a Grad‐CAM technique. The presence or absence of ECE has been analyzed and correlated with ground truth histopathological findings. Conclusions: The proposed deep network can learn meaningful patterns to identify ECE without providing lymph node contours. The introduced ECE heatmaps will contribute to the clinical implementations of the proposed model and reveal unknown features to radiologists. The outcome of this study is expected to promote the implementation of explainable artificial intelligence‐assiste ECE detection. [ABSTRACT FROM AUTHOR]

[Display omitted] Designing two-dimensional (2D) porous carbon nanosheets is expected to boost the water splitting efficiency of low-cost iron (Fe) and cobalt (Co)-based catalysts. Nevertheless, the aggregations, tedious preparation procedures, and expensive precursors for synthesizing 2D porous carbon nanosheets have hindered their widespread application. Herein, for the first time, we developed a low-cost method for large-scale and rapid synthesis of the three-dimensional (3D) hierarchically porous architectures self-assembled by the ultrafine FeCo nanoparticles embedded and boron/nitrogen-codoped 2D porous carbon nanosheets (denoted as FeCo@BNPCNS). The optimal FeCo@BNPCNS-900 exhibited abundant porous channels, a large surface area, and vast carbon edges/defects. Therefore, 8.10 at% electrochemically active boron (B)/nitrogen (N) centers were doped into the porous carbon nanosheets. In an alkaline solution, the optimal FeCo@BNPCNS-900 nanosheets revealed excellent hydrogen evolution reaction (HER) electrocatalytic activity, surpassing commercial 20 wt% Pt/C. For instance, the HER potential at 10 mA cm−2 [-50.6 mV vs. reversible hydrogen electrode (RHE)] of FeCo@BNPCNS-900 was even 19.3 mV more positive than that of commercial 20 wt% Pt/C (-69.9 mV vs. RHE). Meanwhile, its oxygen evolution reaction (OER) catalytic activity was just a little worse than ruthenium oxide (RuO 2). The water electrolysis cell of FeCo@BNPCNS-900 nanosheets just required a small voltage of 1.589 V for full water splitting to achieve 10 mA cm−2, even 70.3 mV more negative than that of the state-of-the-art 20 wt% Pt/C||RuO 2 benchmark (1.660 V) with outstanding stability. The perfect 3D hierarchically porous and honeycomb-like architecture, abundant porous channels/mesopores, and uniformly dispersed electrocatalytically active sites on FeCo@BNPCNS-900 nanosheets were responsible for the outstanding water splitting performance. Finally, this study provides an efficient strategy for the large-scale, rapid, and low-cost synthesis of 2D porous carbon nanosheets without using any template, surfactant, or expensive precursors. [ABSTRACT FROM AUTHOR]

Cobalt (Co) in spent lithium ion batteries was recycled to design a hollow and porous CoN/HPCF/CoN bifunctional electrocatalyst. It reveals superior rechargeable zinc–air battery performance (peak power density is 161.6 mW cm−2) with excellent stability. [ABSTRACT FROM AUTHOR]

In nature, some semiaquatic arthropods evolve biomechanics for jumping on the water surface with the controlled burst of kinetic energy. Emulating these creatures, miniature jumping robots deployable on the water surface have been developed, but few of them achieve the controllability comparable to biological systems. The limited controllability and agility of miniature robots constrain their applications, especially in the biomedical field where dexterous and precise manipulation is required. Herein, an insect‐scale magnetoelastic robot with improved controllability is designed. The robot can adaptively regulate its energy output to generate controllable jumping motion by tuning magnetic and elastic strain energy. Dynamic and kinematic models are developed to predict the jumping trajectories of the robot. On‐demand actuation can thus be applied to precisely control the pose and motion of the robot during the flight phase. The robot is also capable of making adaptive amphibious locomotion and performing various tasks with integrated functional modules. [ABSTRACT FROM AUTHOR]

Background: Abscisic acid (ABA) receptor pyrabactin resistance 1/PYR1-like/regulatory components of ABA receptor proteins (PYR/PYL/RCARs) have been demonstrated to play pivotal roles in ABA signaling and in response to diverse environmental stimuli including drought, salinity and osmotic stress in Arabidopsis. However, whether and how GhPYL9-5D and GhPYR1-3A, the homologues of Arabidopsis PYL9 and PYR1 in cotton, function in responding to ABA and abiotic stresses are still unclear. Results: GhPYL9-5D and GhPYR1-3A were targeted to the cytoplasm and nucleus. Overexpression of GhPYL9-5D and GhPYR1-3A in Arabidopsis wild type and sextuple mutant pyr1pyl1pyl2pyl4pyl5pyl8 plants resulted in ABA hypersensitivity in terms of seed germination, root growth and stomatal closure, as well as seedling tolerance to water deficit, salt and osmotic stress. Moreover, the VIGS (Virus-induced gene silencing) cotton plants, in which GhPYL9-5D or GhPYR1-3A were knocked down, showed clearly reduced tolerance to polyethylene glycol 6000 (PEG)-induced drought, salinity and osmotic stresses compared with the controls. Additionally, transcriptomic data revealed that GhPYL9-5D was highly expressed in the root, and GhPYR1-3A was strongly expressed in the fiber and stem. GhPYL9-5D, GhPYR1-3A and their homologs in cotton were highly expressed after treatment with PEG or NaCl, and the two genes were co-expressed with redox signaling components, transcription factors and auxin signal components. These results suggest that GhPYL9-5D and GhPYR1-3A may serve important roles through interplaying with hormone and other signaling components in cotton adaptation to salt or osmotic stress. Conclusions: GhPYL9-5D and GhPYR1-3A positively regulate ABA-mediated seed germination, primary root growth and stomatal closure, as well as tolerance to drought, salt and osmotic stresses likely through affecting the expression of multiple downstream stress-associated genes in Arabidopsis and cotton. [ABSTRACT FROM AUTHOR]

In the process of multi-label learning, feature selection methods are often adopted to solve the high-dimensionality problem in feature spaces. Most existing multi-label feature selection algorithms focus on exploring the correlation between features and labels and then obtain the target feature subset by importance ranking. These algorithms commonly use single-channel structure to obtain important features, which induces the excessive reliance on the ranking results and causes the loss of important features. However, the correlation between label-specific feature and label-instance is ignored. Therefore, this paper proposes Parallel Dual-channel Multi-label Feature Selection algorithm (PDMFS). We first introduce the concept of dual channel and design the algorithm model as two independent modules. The algorithm obtained different feature correlation sequences, thus avoided relevant feature loss. And then, the proposed algorithm uses the subspace model to select the feature subset with the maximum correlation and minimum redundancy for each sequence, thus obtaining feature subsets under respective correlations. Finally, the subsets are cross-merged to reduce the important feature loss caused by the serial structure processing single feature correlation. The experimental results on eight datasets and statistical hypothesis testing indicate that the proposed algorithm is effective. [ABSTRACT FROM AUTHOR]

This article discusses the role of histone demethylase KDM5 in the maturation of cardiomyocytes, which are heart muscle cells. The post-natal maturation of mammalian hearts involves significant changes at the structural, metabolic, and electrophysiological levels. The study found that inhibiting KDM5-mediated histone methylation in human induced pluripotent stem cell-derived cardiomyocytes led to changes in gene expression related to oxidative phosphorylation, fatty acid metabolism, and myogenesis, indicating a more advanced state of cardiomyocyte maturity. This research contributes to our understanding of the molecular drivers of cardiomyocyte maturation and has potential implications for cell-based therapy and the study of heart diseases. Further studies are needed to establish the physiological relevance of KDM5 in the maturation of mammalian hearts. [Extracted from the article]

In the acoustics-based power transformer fault diagnosis, a transformer acoustic signal collected by an acoustic sensor is generally mixed with a large number of interference signals. In order to separate transformer acoustic signals from mixed acoustic signals obtained by a small number of sensors, a blind source separation (BSS) method of transformer acoustic signal based on sparse component analysis (SCA) is proposed in this paper. Firstly, the mixed acoustic signals are transformed from time domain to time–frequency (TF) domain, and single source points (SSPs) in the TF plane are extracted by identifying the phase angle differences of the TF points. Then, the mixing matrix is estimated by clustering SSPs with a density clustering algorithm. Finally, the transformer acoustic signal is separated from the mixed acoustic signals based on the compressed sensing theory. The results of the simulation and experiment show that the proposed method can separate the transformer acoustic signal from the mixed acoustic signals in the case of underdetermination. Compared with the existing denoising methods of the transformer acoustic signal, the denoising results of the proposed method have less error and distortion. It will provide important data support for the acoustics-based power transformer fault diagnosis. [ABSTRACT FROM AUTHOR]

Due to the scattering of light and the influence of different water types, underwater images usually suffer from different type of hybrid degradation, e.g. color distortion, blurred details and low contrast. Existing underwater image enhancement methods are weak at handling hybrid degradation simultaneously, resulting in low quality results. Inspired by the fact that wavelet-based enhancement methods can correct color and enhance details in frequency domain and the color compensation prior can compensate missing color information in spatial domain, we design the Multi-level Wavelet-based Underwater Image Enhancement Network (MWEN) with the color compensation prior to enhance image in both frequency domain and spatial domain. Specifically, we integrate the multi-level wavelet transform and the color compensation prior into a multi-stage enhancement framework, where each stage consists of a Multi-level Wavelet-based Enhancement Module (MWEM), a Color Compensation Prior Extraction Module (CCPEM) and a color filter with prior-aware weights. The MWEM decomposes image features into low frequency and high frequency by a wavelet transform, and then enhances them by a low frequency enhancement branch and several high frequency enhancement branches, respectively. The low frequency reduces the color distortion of different water types using Instance Normalization for style transfer, while the high frequency enhancement enhances sparse details using a non-local sparse attention mechanism. After the inverse wavelet transform, the preliminary enhanced result by the MWEM is obtained. Then, the color filter whose weights are customized by the color compensation information extracted from the CCPEM dynamically is applied to output of the MWEM for color compensation. Such an operation enables network to adapt to hybrid degradation and achieve better performance. The experiments demonstrate MWEN outperforms existing UIE methods quantitatively and qualitatively. • A new Multi-level Wavelet-based Underwater Image Enhancement Network is proposed. • A new Multi-level Wavelet-based Enhancement Module is proposed. • A new Color filter inspired by color compensation prior is proposed. [ABSTRACT FROM AUTHOR]

Brain functional connectivity (FC) based on resting-state functional magnetic resonance imaging (rs-fMRI) has been in vogue to predict Autism Spectrum Disorder (ASD), which is a neuropsychiatric disease up the plight of locating latent biomarkers for clinical diagnosis. Albeit massive endeavors have been made, most studies are fed up with several chronic issues, such as the intractability of harnessing the interaction flourishing within brain regions, the astriction of representation due to vanishing gradient within deeper network architecture, and the poor interpretability leading to unpersuasive diagnosis. To ameliorate these issues, a FC-learned Residual Graph Transformer Network, namely RGTNet, is proposed. Specifically, we design a Graph Encoder to extract temporal-related features with long-range dependencies, from which interpretable FC matrices would be modeled. Besides, the residual trick is introduced to deepen the GCN architecture, thereby learning the higher-level information. Moreover, a novel Graph Sparse Fitting followed by weighted aggregation is proposed to ease dimensionality explosion. Empirically, the results on two types of ABIDE data sets demonstrate the meliority of RGTNet. Notably, the achieved ACC metric reaches 73.4%, overwhelming most competitors with merely 70.9% on the AAL atlas using a five-fold cross-validation policy. Moreover, the investigated biomarkers concord closely with the authoritative medical knowledge, paving a viable way for ASD-clinical diagnosis. Our code is available at https://github.com/CodeGoat24/RGTNet. • Our graph encoder surpasses linear FC matrix generation, capturing intricate brain node activity patterns. • We employ residual learning to enable deeper GCN architectures, enhancing feature extraction by facilitating deeper message diffusion among brain nodes. • Our Graph Sparse Fitting module efficiently reduces graph dimensionality by evaluating inductive node scores, enabling our model to accurately highlight salient brain regions. • RGTNet identifies ASD biomarkers aligned with referenced medical research, offering unique insights into clinical diagnosis. [ABSTRACT FROM AUTHOR]

Super-aligned carbon nanotubes (CNTs) film has strong anisotropy to light propagation. In order to better integrate the self-assembled CNTs into microelectromechanical system (MEMS) for polarization applications, some inherent impacts on polarization properties of CNT film were investigated. We described the polarization effects of the film thickness variation in detail, giving an optimum thickness range which is around 700â€"800 nm. The amorphous carbon content of CNT film was reduced by oxidation process where the transmittance increased by almost 4 folds. The alignment of CNT arrangement was optimized from 0.41 (Chebyshev orientation parameter) to 0.54 by manipulating the C2H4 flow rate from 54 to 80 sccm. More specifically, a sample possessing a degree of polarization up to 99% and transmittance over 45% was obtained through proper regulations. The validated optimization makes the aligned CNT films more feasible and valuable for the integration of the CNT polarimeters with MEMS technology. [ABSTRACT FROM AUTHOR]

The high cost of precursors and the complexity of synthesis procedures have hindered the widespread use of two-dimensional (2D) porous carbon nanosheets in water splitting. In this study, we successfully developed a low-cost method for the rapid synthesis of three-dimensional (3D) hierarchically porous architectures self-assembled from iron–copper nanoparticles embedded in boron (B)/nitrogen (N)-codoped 2D porous carbon nanosheets (denoted as FeCu@BNPCNS). The optimal FeCu@BNPCNS-900 nanosheet exhibited a large surface area, abundant porous channels, meso/macropores, and carbon edges/defects. Particularly, 10.25 atom% of B/N electrochemically active centers (such as pyridinic-N (including the metal–nitrogen–carbon species), pyrrolic-N, graphitic-N, and BC 3) were successfully doped into the optimal FeCu@BNPCNS-900 nanosheets. In an alkaline solution, FeCu@BNPCNS-900 exhibited excellent electrocatalytic activity for hydrogen evolution reaction (HER), which was higher than that of the commercial 20 wt% Pt/C. For example, the HER potential of FeCu@BNPCNS-900 at 10 mA cm−2 [ E 10 ; −202.3 mV vs. reversible hydrogen electrode (RHE)] was only 140.2 mV more negative than that of 20 wt% Pt/C (−62.1 mV vs. RHE). Additionally, FeCu@BNPCNS-900 exhibited a slightly lower oxygen evolution reaction (OER) electrocatalytic activity than the ruthenium oxide (RuO 2). Particularly, the OER E 10 potential (+1.634 V vs. RHE) of FeCu@BNPCNS-900 was only 76 mV more positive than that of RuO 2 (+1.558 V vs. RHE). The FeCu@BNPCNS-900||FeCu@BNPCNS-900 cell achieved 10 mA cm−2 at 1.613 V, which was 58 mV more negative than that of the 20 wt% Pt/C||RuO 2 cell (1.671 V). The excellent water-splitting performance of FeCu@BNPCNS-900 could be attributed to the 3D hierarchically porous architecture, abundant channels/mesopores, and uniformly dispersed electrocatalytically active sites. Therefore, we developed an efficient strategy for the large-scale and low-cost synthesis of 2D porous carbon nanosheets without the need for precursors, templates, or surfactants. A novel approach for large-scale, rapid, and low-cost synthesis of FeCu nanoparticles functionalized and B-, N- codoped 2D porous carbon nanosheets to be efficient bifunctional full water splitting electrocatalysts in alkaline solution without using any expensive precursor, template, surfactant or tedious production process. [Display omitted] • Abundant mesopores and carbon defects/edges of 2D porous FeCu@BNPCNS nanosheets. • High-density defects induced ultrahigh B/N active centers of 10.25 atom %. • HER E 10 potential of FeCu@BNPCNS-900 just 140.2 mV more negative than 20 wt % Pt/C. • OER E 10 potential of FeCu@BNPCNS-900 just 76 mV more positive than RuO 2. • A voltage of 1.613 V at 10 mA cm−2 for FeCu@BNPCNS-900 electrolyser just 58 mV smaller than Pt/C.||RuO 2. [ABSTRACT FROM AUTHOR]

Obtaining ground-truth label information from real-world data along with uncertainty quantification can be difficult or even infeasible. In the absence of labeled data for a certain task, unsupervised domain adaptation (UDA) techniques have shown great accomplishment by learning transferable knowledge from labeled source domain data and applying it to unlabeled target domain data, yet scarce studies consider addressing uncertainties under domain shifts to improve the model robustness. Distributionally robust learning (DRL) is emerging as a high-potential technique for building reliable learning systems that are robust to distribution shifts. In this study, we propose a distributionally robust unsupervised domain adaptation (DRUDA) method to enhance the machine learning model generalization ability under input space perturbations. The DRL-based UDA learning scheme is formulated as a min–max optimization problem by optimizing worst-case perturbations of the training source data. Our Wasserstein distributionally robust framework can reduce the shifts in the joint distributions across domains. The proposed DRUDA has been tested on digit datasets and the Office-31 dataset, compared with other state-of-the-art domain adaptation techniques. Our experimental results show that the proposed DRUDA leads to improvements in domain adaptation accuracy performance on target domains. [ABSTRACT FROM AUTHOR]

Homogeneous nucleation and heterogeneous condensation of salt vapors near the wall of superheater or reheater tubes greatly improve the sticky propensity of deposited surfaces or impacting particles and then lead to a fast‐growing rate of initial layer. Based on the deposition experiment of mechanically mixed KCl + SiO2 particles in an entrained flow reactor, a numerical model with considering the salt particle vaporization, salt vapor condensation, and its effect on SiO2 deposition is proposed for simulating impaction and adhesion behavior of molten and solid particles. The results show that deposits are mainly from the impaction of solid and molten particles and the condensation of salt vapors. The condensation rate of salt vapors in the stagnation zone at the windward side of metal probe is maximal. In comparison with the overall deposition rate, although the amount of salt vapors condensed on the probe surface can be negligible, it significantly affects the deposition rate of SiO2 particles. The coupled CFD model over a link between particle sticking and salt vapor condensation could well simulate the deposition behavior of mechanically mixed ash particles under rich‐salt‐vapor atmosphere. [ABSTRACT FROM AUTHOR]

• The proposed network contains an attentive recurrent network and a U-recurrent encoder-decoder network. • The attentive recurrent network generates a haze attention map for highlighting the haze regions. • The U-recurrent encoder-decoder network predicts the clear image with the guidance of the haze attention map. • A new residual pyramid pooling module enlarges the receptive field of the whole network. Haze removal is an important pre-processing step in many computer vision tasks. Convolutional neural networks, especially the U-shaped networks, have shown to be effective in image dehazing. Nevertheless, these networks have three main limitations. First, the relevant haze information, e.g. concentration of haze, is totally ignored. Second, spatial inconsistency and information dilution usually occur when the networks refine the dehazed results with a coarse-to-fine strategy. Third, the receptive field of the network is not large enough to capture structural information. Motivated by these problems, a new attentive U-recurrent encoder-decoder dehazing network is presented, which consists of an attentive recurrent network and a U-recurrent encoder-decoder network. By assuming that haze layers with different depths can be detected by multiple stages, we use an attentive recurrent network to generate the haze attention map for guiding the U-recurrent encoder-decoder network with the concentration of haze to better estimate the clear image. Meanwhile, the features for dehazing are further enhanced and the dehazing results are refined in the U-recurrent encoder-decoder network. This design not only enables spatial consistency but also reduces information dilution with short recurrent pathways. Furthermore, a novel residual pyramid pooling module is also proposed and used in the U-recurrent encoder-decoder network, which provides the network with structural information and with an enlarged receptive field. The experimental results demonstrate that our method outperforms state-of-the-art dehazing algorithms on both synthetic and real hazy images. [ABSTRACT FROM AUTHOR]

Label correlations have always been one of the hotspots of multi-label learning. Using label correlations to complete the original label can enrich the information of the label matrix. At the same time, label-specific features give a thought that different labels have inherent characteristics that can be distinguished, and we can use label correlations to enhance the learning process of label-specific features among similar labels. At present, most of the algorithms combine label correlations and label-specific features to improve the multi-label learning effect, but do not consider the impact of label marking errors or defaults in data sets. In fact, the label completion method can further enrich the information of label matrix, and then the joint learning framework of joint label-specific features can effectively improve the robustness of the multi-label learning algorithm. Based on this, this paper proposes a multi-label learning algorithm for joint label completion and label-specific features, and constructs a new multi-label learning algorithm framework by means of joint label completion and label-specific features. Completion matrix and label-specific features are obtained by alternating iteration method, and the label matrix updating the optimization framework fully considers the label correlations. The algorithm in this paper has been demonstrated and trained on several benchmark multi-label data sets by extensive experiments, which verifies the effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]

Abstract Homogenous nucleation or heterogeneous condensation of gaseous alkali salts commonly occurs in biomass-fired power plants, and is mainly responsible for forming fine particles and triggering deposition or corrosion on tubes. This work aims to investigate the influence of surface temperature and exposure time on the initial condensation characteristics of KCl(g) in air atmosphere. It includes both experiment and simulation calculation to qualitatively and quantitatively study the condensation and gas-to-solid conversion of KCl(g) under different temperature gradients. Experiments were carried out in an electrically heated vertical tubular furnace, in which a defined evaporating source of KCl(g) was designed. A sampling probe equipped with a temperature controlled Fe-Cr-Ni alloy condensation surface, was inserted into the furnace to capture KCl(g). For each case, the morphology of condensed salt on the probe surface was analyzed via using Scanning Electron Microscope with Energy Dispersive Spectrometer (SEM-EDS). The results showed significant differences in morphologies of the condensed salts which were respectively observed at the condensation surface temperature of Fe-Cr-Ni alloy of 673.15, 793.15 and 873.15 K. At the same tubular furnace temperature, due to the appearance of dendritic structure, the condensation rate of KCl(g) of 3.28 × 10−6 kg/m2·s at the surface temperature of 793.15 K was greater than that obtained at 673.15 K. The calculation of gas-to-solid conversion found that condensed KCl particles whose diameter is larger than 1 μm could not be formed only relying on the mechanism of nucleation and coagulation, when the gas temperature decreased from 1073.15 K to 673.15/793.15/873.15 K, respectively. The faster the cooling rate is, the smaller the size of formed particles is, and the more the number concentration of ultra-fine particles is. In addition, severe corrosion and cracks of surface material of the condensation surface were clearly observed at 793.15/873.15 K, which may be induced by couple attacks of condensed salts, thermal stress and molecular oxygen. [ABSTRACT FROM AUTHOR]

Fatty liver syndrome (FLS) is a kind of nutritional metabolic disease in laying hens. Revealing FLS pathogenesis during the early period is what really makes sense for the prevention or nutritional regulation strategies. In the study, 9 healthy or naturally occurring early FLS birds were screened based on visual inspection, liver index and morphologic analysis. Liver and fresh cecal content samples were collected. Then transcriptomic and 16S rRNA technologies are applied to investigate hepatic transcriptome and cecum microbiota composition. Unpaired Student t test and some omics methods were used for statistical analysis. Results showed higher liver weight and index were found in FLS group; morphologic analysis indicated that there existed more lipid droplets in the liver of birds with FLS. Based on DESeq2 analysis, there were 229 up- and 487 down-regulated genes in the FLS group, among which most genes related to de novo fatty acid synthesis were up-regulated such as acetyl-CoA carboxylase, fatty acid synthase, stearoyl-CoA desaturase, and ELOVL fatty acid elongase 6 (ELOVL6). Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis indicated that pathways associated with lipid metabolism and liver damage were affected. 16S rRNA sequencing analysis of cecum microbiota showed that there was a significant difference between the Con and FLS groups. LEfSe analysis revealed that the relative abundance of Coprococcus, Odoribacter, Collinsella, Turicibacter, YRC22, Enterococcus, Shigella , and Bifidobacterium were down-regulated in the FLS group, whereas the abundance of Bacteroides, Mucispirillum, Butyricicoccus, Campylobacter, Akkermansia , and Clostridium were up-regulated. The KEGG enrichment from differential microbiota suggested that some metabolism-related functions were altered to some extent. Taken together, during the developmental of early fatty liver of laying hens, lipogenesis was enhanced, whereas abnormal metabolism occurs not only in lipid transportation but also in hydrolysis, which caused structural damage to the liver organ. Moreover, the dysbiosis of the cecum microbiota occurred. All of these serve as targets or provide theoretical references for the development of probiotics for fatty liver prevention in laying hens. [ABSTRACT FROM AUTHOR]

Trehalose is a non-reducing disaccharide sugar that widely exists in a variety of organisms, such as bacteria and eukaryotes except the vertebrates. It plays an important role in a number of critical metabolic functions especially in response to stressful environmental conditions. However, the biosynthetic pathways of trehalose in cold-adapted yeast and its responses to temperature and salinity changes remain little understood. In this study, the genome of Antarctic-isolated Pseudozyma sp. NJ7 was generated from which we identified the gene coding for trehalose phosphate synthase (TPS1) and trehalose phosphate phosphatase (TPS2), the two enzymes most critical for trehalose production. The whole draft genome length of Pseudozyma sp. NJ7 was 18,021,233 bp, and encoded at least 34 rRNA operons and 72 tRNAs. The open reading frame of tps1 contained 1827 nucleotide encoding 608 amino acids with a molecular weight of 67.64 kDa, and an isoelectric point of 5.54, while tps2 contained 3948 nucleotide encoding 1315 amino acids with a molecular weight of 144.47 kDa and an isoelectric point of 6.36. The TPS1 and TPS2 protein sequences were highly homologous to Moesziomyces antarcticus T-34, but TPS2 had obvious specificity and differently with others which suggest species specificity and different evolutionary history. Expression level of tps1 gene was strongly influenced by temperature and high salinity. In addition, addition of 0.5% trehalose preserved yeast cells in the short term but was not effective for cryopreservation for more than 5 days, but still suggesting that exogenous trehalose could indeed significantly improve the survival of yeast cells under freezing conditions. Our results provided new insights on the molecular basis of cold adaptations of Antarctic Pseudozyma sp., and also generated new information on the roles trehalose play in yeast tolerance to extreme conditions in the extreme Antarctic environments. [ABSTRACT FROM AUTHOR]

Trehalose is a non-reducing disaccharide sugar that widely exists in a variety of organisms, such as bacteria and eukaryotes except the vertebrates. It plays an important role in a number of critical metabolic functions especially in response to stressful environmental conditions. However, the biosynthetic pathways of trehalose in cold-adapted yeast and its responses to temperature and salinity changes remain little understood. In this study, the genome of Antarctic-isolated Pseudozyma sp. NJ7 was generated from which we identified the gene coding for trehalose phosphate synthase (TPS1) and trehalose phosphate phosphatase (TPS2), the two enzymes most critical for trehalose production. The whole draft genome length of Pseudozyma sp. NJ7 was 18,021,233 bp, and encoded at least 34 rRNA operons and 72 tRNAs. The open reading frame of tps1 contained 1827 nucleotide encoding 608 amino acids with a molecular weight of 67.64 kDa, and an isoelectric point of 5.54, while tps2 contained 3948 nucleotide encoding 1315 amino acids with a molecular weight of 144.47 kDa and an isoelectric point of 6.36. The TPS1 and TPS2 protein sequences were highly homologous to Moesziomyces antarcticus T-34, but TPS2 had obvious specificity and differently with others which suggest species specificity and different evolutionary history. Expression level of tps1 gene was strongly influenced by temperature and high salinity. In addition, addition of 0.5% trehalose preserved yeast cells in the short term but was not effective for cryopreservation for more than 5 days, but still suggesting that exogenous trehalose could indeed significantly improve the survival of yeast cells under freezing conditions. Our results provided new insights on the molecular basis of cold adaptations of Antarctic Pseudozyma sp., and also generated new information on the roles trehalose play in yeast tolerance to extreme conditions in the extreme Antarctic environments. [ABSTRACT FROM AUTHOR]

Large amounts of potassium and silicon elements contained in biomass ashes can substitute for equivalent quality of raw materials to make agricultural or industrial products. In this study, a multi-step extracting method for straw/woody biomass ashes is developed to enhance their utilization efficiencies. After the same treatment processes, different products are obtained from biomass ashes at 500 °C and also characterized by X-ray diffraction (XRD) and X-ray fluorescence (XRF). In addition, the slagging/fouling tendencies of three kinds of biomass ashes were well evaluated by adapting the coupling approach, which considering two compositional ternary diagrams, some empirical indices and soluble salts content. Moreover, it was also in comparison with that of fifty three kinds of biomasses from references. The results show that potassium element in extractive products from biomass ashes mainly exists as potassium chlorides and sulfates, such as KCl, K 2 SO 4 , KNaSO 4 and KNa 3 (SO 4 ) 2 . More potassium salts could be recycled from ashes by decreasing the burning temperature of straw/woody biomass. The extracting ratio of potassium salts from cotton straw ashes and sawdust ashes increases sharply at first, then tends to smooth. The initial extraction ratio of 64.04% for cotton straw ashes is larger than that of wheat straw ashes and sawdust ashes. The order in the total accumulated extracting ratio of potassium from ashes is cotton straw > wheat straw > sawdust. This method could be suggested as a feasible and sustainable utilization option for biomass solid wastes. In addition, the high deposition and corrosion risk are estimated for wheat straw, and the medium one for cotton straw and sawdust with the coupling approach, if they will be used as input material for boilers. [ABSTRACT FROM AUTHOR]

Quinone methide (QM) formation induced by endogenously generated H 2 O 2 is attractive for biological and biomedical applications. To overcome current limitations due to low biological activity of H 2 O 2 -activated QM precursors, we are introducing herein several new arylboronates with electron donating substituents at different positions of benzene ring and/or different neutral leaving groups. The reaction rate of the arylboronate esters with H 2 O 2 and subsequent bisquinone methides formation and DNA cross-linking was accelerated with the application of Br as a leaving group instead of acetoxy groups. Additionally, a donating group placed meta to the nascent exo-methylene group of the quinone methide greatly improves H 2 O 2 -induced DNA interstrand cross-link formation as well as enhances the cellular activity. Multiple donating groups decrease the stability and DNA cross-linking capability, which lead to low cellular activity. A cell-based screen demonstrated that compounds 2a and 5a with a OMe or OH group dramatically inhibited the growth of various tissue-derived cancer cells while normal cells were less affected. Induction of H2AX phosphorylation by these compounds in CLL lymphocytes provide evidence for a correlation between cell death and DNA damage. The compounds presented herein showed potent anticancer activities and selectivity, which represent a novel scaffold for anticancer drug development. [ABSTRACT FROM AUTHOR]

Alkali chlorides and sulfates are well-known species induced fouling, slagging and corrosion on the heat transfer surface in biomass combustion/gasification process. This paper aims to study the condensation behavior of alkali compound vapors (ACVs) during wheat straw combustion in laboratory, without the participation of ash particles. The effects of surface temperature of Fe-Cr-Ni alloy probe on condensation morphology, thermodynamic characteristics of mixed salt vapors, and mineralogical variation of straw ashes are also discussed. The K, Cl and S mainly existed as KCl, K 2 SO 4 and K 2 Ca(CO 3 ) 2 in wheat straw ashes produced at 400 °C. The main released ACVs were potassium chlorides and sulfates. The form of condensation for mixed chloride vapors at surface temperatures of 400/520/600 °C is varied at 815 °C. These mixed salt vapors could condense either separately as cubic crystal particles by homogeneous nucleation, or together as one or two solid solutions by heterogeneous nucleation. The side length of KCl crystal particle condensed homogeneously was less than 2μm. The aggregation and growth among crystal particles at surface temperature of 400 °C were observable. The chlorides are released completely from wheat straw ashes at 815 °C, and carbonates may disappear as either decomposition or sulfation with SO 2 /SO 3 . When the evaporation temperature was 1100 °C, K 2 SO 4 and Na 2 SO 4 were released and then condensed as one solid solution with hexagonal crystal structure on the probe surface of 520 °C. Finally, we propose a condensing mechanism for ACVs depending on surface temperature. [ABSTRACT FROM AUTHOR]

Metabolic remodeling is a hall-mark of cardiac maturation and pathology. The switch of substrate utilization from glucose to fatty acid is observed during post-natal maturation period in developing heart, but the process is reversed from fatty acids to glucose in the failing hearts across different clinic and experimental models. Majority of the current investigations have been focusing on the regulatory mechanism and functional impact of this metabolic reprogramming involving fatty acids and carbohydrates. Recent progress in metabolomics and transcriptomic analysis, however, revealed another significant remodeled metabolic branch associated with cardiac development and disease, i.e. Branched-Chain Amino Acid (BCAA) catabolism. These findings have established BCAA catabolic deficiency as a novel metabolic feature in failing hearts with potentially significant impact on the progression of pathological remodeling and dysfunction. In this review, we will evaluate the current evidence and potential implication of these discoveries in the context of heart diseases and novel therapies. This article is part of a Special Issue entitled: The role of post-translational protein modifications on heart and vascular metabolism edited by Jason R.B. Dyck & Jan F.C. Glatz. [ABSTRACT FROM AUTHOR]

Most photoinduced DNA cross-link formation by a bifunctional aryl derivative is through a bisquinone methide. DNA cross-linking via a bisarylcarbocation remains a less explored area. We designed and synthesized a series of naphthalene boronates that produce DNA interstrand cross-links via a carbocation upon UV irradiation. A free radical was generated from the naphthalene boronates with 350 nm irradiation and further converted to a carbocation by electron transfer. The activation mechanism was determined using the orthogonal traps, 2,2,6,6-tetramethylpiperidin-1-oxyl (TEMPO) and methoxyamine that react with either the free radical or the carbocation but not both. This represents a novel example of photoinduced DNA cross-link formation via carbocations generated from a bisaryl derivative. This work provides information useful for the design of novel photoactivated DNA cross-linking agents. [ABSTRACT FROM AUTHOR]

[Display omitted] • Characterization of bottom ashes/slags (BAS) from a pulverized coal boiler was studied. • BAS mainly contains SiO 2 , CaCO 3 and Al 2 O 3 except for C element enrichment. • Effect of fine/coarse BAS on slagging behavior of coal blend was studied. • 5% fine BAS addition converted glassy slags at 1200℃ into low molten deposits. • Different groups composed of BAS and PD inhibited the formation of more melting minerals. Coal cofiring with carbon-containing solid wastes can achieve resource utilization and promote the circular economy development. This work aims to investigate the effects of C-rich bottom ashes/slags (BAS), fine/coarse BAS separated by mechanical sieving, and the mixture of untreated BAS with purified dust (PD) from CaC 2 production acting as additive on slagging behavior and mineral phase transformation of Zhundong (ZD) coal blend. Detail characterizations including chemical composition, micro-morphology, mineral phases and weight loss of BAS were performed. The ash fusion tests for coal blend with varying proportions of additive were conducted. The compositional analyses of deposits on an un-cooled probe at different sampling temperatures (600/800/1000/1200 ℃) in a drop-tube furnace were investigated. The results show that three types of untreated BAS have similar physicochemical properties. The BAS addition has a negative influence on ash fusion temperatures, but they would completely change the types of crystal minerals in the melted deposits dominated by amorphous substance at 1200 ℃. The addition of 5 wt% coarse (>1 mm) or fine (<53 μm) BAS promotes glassy slags at 1200 ℃ converting into deposits with a low melt fraction, but the influence of fine BAS is more pronounced. A group composed of untreated BAS and PD at an appropriate ratio, promotes the formation of more crystal minerals with high melting points in deposits at 1200 ℃. [ABSTRACT FROM AUTHOR]

Mutation of Bloom helicase (BLM) causes Bloom syndrome (BS), a rare human genetic disorder associated with genome instability, elevation of sister chromatid exchanges, and predisposition to cancer. Deficiency in BLM homologs in Drosophila and yeast brings about significantly increased rates of recombination between imperfectly matched sequences (“homeologous recombination,” or HeR). To assess whether BLM deficiency provokes an increase in HeR in human cells, we transfected an HeR substrate into a BLM-null cell line derived from a BS patient. The substrate contained a thymidine kinase ( tk )- neo fusion gene disrupted by the recognition site for endonuclease I-SceI, as well as a functional tk gene to serve as a potential recombination partner for the tk-neo gene. The two tk sequences on the substrate displayed 19% divergence. A double-strand break was introduced by expression of I-SceI and repair events were recovered by selection for G418-resistant clones. Among 181 events recovered, 30 were accomplished via HeR with the balance accomplished by nonhomologous end-joining. The frequency of HeR events in the BS cells was elevated significantly compared to that seen in normal human fibroblasts or in BS cells complemented for BLM expression. We conclude that BLM deficiency enables HeR in human cells. [ABSTRACT FROM AUTHOR]

The goals of the work described here were to study the pre-operative risk factors associated with early recurrence (ER) of hepatocellular carcinoma (HCC) after surgical resection and discuss the value of conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS) in predicting ER of HCC, so as to provide more information for optimizing clinical treatment and improving prognosis. A retrospective analysis was conducted on 59 patients who underwent both US and CEUS examinations pre-operatively and surgical resection for HCC between December 2010 and January 2014 in our hospital. The patients' clinical data, laboratory examination data and ultrasonic imaging diagnostic data were collected. Univariate analysis and logistic regression analysis were performed to determine the independent risk factors for ER of HCC after surgical resection. Diagnostic values of independent risk factors in predicting ER were further evaluated. The 59 patients were divided into the ER group (27 cases) and ER-free group (32 cases). There were no significant differences in age and sex between the two groups (p > 0.05). Univariate analysis revealed that differences in pre-operative serum α-fetoprotein level ≥400 ng/mL (p = 0.008), tumor diameter ≥5 cm (p = 0.012), macroscopic vascular invasion (p = 0.040), "fast wash-out" enhancement pattern (p = 0.006) and inhomogeneous distribution of contrast agent (p = 0.031) statistically significantly differed between the two groups. Logistic regression analysis indicated that pre-operative serum AFP level ≥400 ng/mL (p = 0.024), tumor diameter ≥5 cm (p = 0.042) and "fast wash-out" enhancement pattern (p = 0.009) were independent risk factors for ER of HCC; macrovascular invasion (p = 0.095) and inhomogeneous distribution of contrast agent (p = 0.628) did not statistically significantly differ between two groups (p = 0.628). Predictive values of the independent risk factors were further evaluated. The sensitivity of a "fast wash-out" enhancement pattern in predicting ER of HCC post-operatively did not statistically differ from that of tumor diameter ≥5 cm (p > 0.05), whereas it was significantly higher than the sensitivities of the other predictive indexes (p < 0.05). A pre-operative serum α-fetoprotein level ≥400 ng/mL, tumor diameter ≥5 cm and "fast wash-out" enhancement pattern are independent risk factors for ER of HCC after surgical resection. In addition, the "fast wash-out" enhancement pattern could probably be used to screen populations at high risk of recurrence owing to its high sensitivity in predicting ER of HCC post-operatively. All these findings provide beneficial information for management of HCC. [ABSTRACT FROM AUTHOR]

p38 kinases are members of the mitogen-activated protein kinases (MAPK) with established contribution to a wide range of signaling pathways and different biological processes. The prototypic p38 MAPK, p38α was originally identified as an essential signaling kinase for inflammatory cytokine production Extensive studies have now revealed that p38s have critical roles in many different tissues far beyond immune regulation and inflammatory responses. In this review, we will focus on the structure and molecular biology of p38s, and their specific roles in heart, especially regarding myocyte proliferation, apoptosis, and hypertrophic responses. [ABSTRACT FROM AUTHOR]

A novel mesh deformation technique is developed based on the Delaunay graph mapping (DGM) method and the radial basis function (RBF) method. The algorithm combines the advantages of the efficiency of DGM mesh deformation and the better control of the near surface mesh quality from the RBF method. The Delaunay graph is used to divide the mesh domain into a number of sub-domains. On each of the sub-domains, the radial basis function is applied to build a much smaller sized translation matrix between the original mesh and the deformed mesh, resulting in a similar efficiency for the mesh deformation as compared to the fast Delaunay graph mapping method. Furthermore, by separating the translation and rotation motion, the mesh quality near the wall can be substantially improved for extremely large rotational deformation. The paper will show how the near-wall mesh quality is controlled and improved by the new method while the computational time is maintained to be comparable to the original Delaunay graph mapping method. [ABSTRACT FROM AUTHOR]

Recent developments in Convolutional Neural Networks (CNNs) have made them one of the most powerful image dehazing methods. In particular, the Residual Networks (ResNets), which can avoid the vanishing gradient problem effectively, are widely deployed. To understand the success of ResNets, recent mathematical analysis of ResNets reveals that a ResNet has a similar formulation as the Euler method in solving the Ordinary Differential Equations (ODE's). Hence, image dehazing which can be formulated as an optimal control problem in dynamical systems can be solved by a single-step optimal control method, such as the Euler method. This optimal control viewpoint provides a new perspective to address the problem of image restoration. Motivated by the advantages of multi-step optimal control solvers in ODE's, which include better stability and efficiency than single-step solvers, e.g. Euler, we propose the Adams-based Hierarchical Feature Fusion Network (AHFFN) for image dehazing with modules inspired by a multi-step optimal control method named the Adams–Bashforth method. Firstly, we extend a multi-step Adams–Bashforth method to the corresponding Adams block, which achieves a higher accuracy than that of single-step solvers because of its more effective use of intermediate results. Then, we stack multiple Adams blocks to mimic the discrete approximation process of an optimal control in a dynamical system. To improve the results, the hierarchical features from stacked Adams blocks are fully used by combining Hierarchical Feature Fusion (HFF) and Lightweight Spatial Attention (LSA) with Adams blocks to form a new Adams module. Finally, we not only use HFF and LSA to fuse features, but also highlight important spatial information in each Adams module for estimating the clear image. The experimental results using synthetic and real images demonstrate that the proposed AHFFN obtains better accuracy and visual results than that of state-of-the-art methods. • We propose the Adams-based Hierarchical Feature Fusion Network (AHFFN) for image dehazing. • The Adams Module is designed based on Adams Blocks, inspired by multi-step high-order Adams–Bashforth methods. • HFF and LSA are proposed to fuse features and pay attention to heavy haze pixels within and among the Adams Module. [ABSTRACT FROM AUTHOR]

I632 --> 91.3 --> Gene expression is determined by both transcriptional as well as multiple layers of post‐transcriptional controls, including protein translation. One of the molecular hallmark observed in diseased hearts is augmented protein synthesis and marked reprogramming of translatome (defined as ribosomal loaded mRNAs). Furthermore, translatome reprogramming is often independent from the concurrent total transcriptome changes. However, the underlying dynamics and regulatory network remain largely unexplored. In this study, we observed a robust induction of protein synthesis associated with a rapid change of ribosome loaded mRNAs in response to hypertrophic stimulation in cultured myocytes and intact mouse hearts, associated with dynamic changes in nucleoli organization. This early onset of translatome reprogramming and subsequent protein synthesis induction requires the induction of a long non‐coding RNA (lncRNA) named Myocardial Infarction Associated Transcript (Miat). Molecular characterization reveals that Miat is specifically localized in nuclei and interacts with Nucleolin (NCL). Miat expression is essential for NCL mediated ribosome biogenesis and function. In Miat KO mouse hearts or cultured myocytes, pathological hypertrophy is significantly blunted in vitro and in vivo, along with blocked rRNA biogenesis and processing, and protein synthesis. These findings offer the first evidence that ribosome biogenesis and translatome reprogramming is an essential early molecular process of pathological hypertrophy in heart. Miat‐NCL mediated translatome reprogramming induced by pathological stimulation is a novel regulatory corner stone and post‐transcriptional check‐point for pathological hypertrophy and heart failure. [ABSTRACT FROM AUTHOR]

The potential of purified dust (PD) and removed dust (RD) from calcium carbide production as additive to improve the slagging characteristic of Zhundong (ZD) coal blends was studied. Ash fusion tests with varying proportion of two additives (2.5, 5.0 and 7.5 wt%), and ash sample preparation at 1150/1250 °C were conducted. The deposits at different temperatures (1200/1000/800/600 °C) were collected by using an un-cooled probe which was inserted into a drop-tube furnace. The detail characterizations of ash or slag samples were used for analyzing the transformation of mineral phases, and evaluating the effectiveness of additives. The results show that PD and RD have a feature of Ca and C enrichment. The former has a higher Ca content, while the later owns more abundant C element. The addition of PD or RD improves ash fusion temperatures of coal blends, but the effectiveness of 5.0% PD is the best. The addition of 5.0% PD could convert the glassy slags collected at 1200 °C into deposits with low melting fraction, due to the formation of calcium-rich crystal minerals. Controlling the CaO/SiO 2 molar ratio at the range of 2.2– 3 would significantly relieve the high temperature melting behavior of ZD coal blends featured by high Ca and low Si. [Display omitted] • Characterization of purified and removed dusts from CaC 2 production was studied. • Purified dust contains much more Ca element and less C than removed dust. • Two types of solid wastes affecting ash fusion behavior of coal blend were studied. • 5% purified dust addition converted glassy slags at 1200 °C into low molten deposits. • Low melting compounds inhibited by controlling the molar ratio of CaO/SiO 2 at 2.2–3. [ABSTRACT FROM AUTHOR]

• Six types of additives influencing ash fusion temperatures of ZD coal were studied. • An optimal additive composed of alumina-rich ash, MgO and dolomite was proposed. • Formation of Mg-Fe-Al oxides delays the dissolving of Fe/Mg oxide into silicates. Fundamental research on the mineral transformation of iron-rich coal is very necessary for extending its utilization at elevated temperature. In this work twelve runs with six types of additives (halloysite, alumina-rich ash, dolomite, SiO 2 , CaO and MgO) at different mixing proportions were sorted, to adjust the relative content of Si, Al, Ca or Mg element in coal ashes targeting to improve the slagging characteristic. Ash fusion tests and the preparation of coal ashes at elevated temperatures (1100, 1150 and 1250℃) were performed, respectively. The effects of additive type and blending ratio on the fusion characteristic and the mineral phase transformation were explored. Elemental composition, crystalline mineral phases and micro-morphologies of coal ashes were characterized via various technical approaches. The results showed that 3% alumina-rich ash or dolomite significantly improve the deformation temperature of iron-rich coal. While the addition of halloysite or SiO 2 with a same proportion sharply decreases the softening and flow temperatures of coal ash, except for slightly increasing the deformation temperature. The composite additive consisting of alumina-rich ash, MgO and dolomite, could promote the formation of MgFe 2 O 4 , FeAl 2 O 4 , Mg(Fe,Al) 2 O 4 or MgAl 2 O 4 which inhibit the melting of coal ash. However, a low proportion of Si-rich additive into iron-rich coal is not suggested. [ABSTRACT FROM AUTHOR]

A micropolarizer array (MPA) that can be integrated into a scientific camera is proposed as a real-time polarimeter that is capable of extracting the polarization parameters. The MPA is based on highly aligned carbon nanotube (CNT) films inspired by their typical anisotropy and selectivity for light propagation over a wide spectral range. The MPA contains a dual-tier CNT pixel plane with 0° and 45° orientations. The thickness of the dual-tier structure of the CNT-based MPA is limited to less than 2 μm with a pixel size of 7.45 μm × 7.45 μm. The degree of polarization of the CNT-MPA reached 93% at a 632 nm wavelength. The specific designs in structure and semiconductor fabrication procedures are described. Compared with customary MPAs, CNT-based MPA holds great potential in decreasing the cross-talk risk associated with lower film thickness and can be extended to a wide spectral range. [ABSTRACT FROM AUTHOR]

Amplatzer septal occluder (ASO)-induced complications have been observed. However, little attention is paid to the atrioventricular block (AVB) induced by atrial septum defect (ASD) closure using the Amplatzer device. This study aimed to analyze the risk factors and prognosis of AVB after catheter closure and to reduce the incidence of adverse events. In this study, 706 ASD patients who received closure in our division were investigated retrospectively for the relationship between AVB and factors such as age, size of the ASD ( D), diameter of the occluder ( D), diameter of the septum ( D), D/ D ratio, and D/ D ratio. Data distribution was evaluated with the Kolmogorov-Smirnov normality test. The Wilcoxon rank sum test was used to compare non-normal distribution data. A p value lower than 0.05 was considered significant. Of the 706 patients, six had experienced the development of AVB, giving an incidence of 0.85 %. The risk factors included younger age, larger size of the ASD, larger size of the device, and the D/ D ratio (≥0.45). The milder AVB is, the better the prognosis. An AVB of III° and an unchanged electrocardiogram (ECG) within 3 days after the procedure are poor prognostic indicators. More attention should be paid to AVB induced by ASD closure. Younger age, size of the ASD, size of the device, and a D/ D ratio of 0.45 or higher are the risk factors associated with AVB after closure. A timely retrieval of the device should be considered for a good prognosis. [ABSTRACT FROM AUTHOR]

Abstract: A novel meshing method named the zipper layer method is presented, which links two topologically different multi-block structured meshes together without overlapping or hanging nodes. It can either locally or globally connect two dissimilar structured meshes with a small number of tetrahedra and pyramids on either side of the interface to form a conformal mesh. To test the method, the results using a zipper layer mesh and a fully structured mesh are compared regarding solution accuracy and convergence. This method has been demonstrated for several applications of turbomachinery interest, where quality multi-block structured meshes are connected and the numerical flow solutions on these zipper layer meshes are also shown. [Copyright &y& Elsevier]

Abstract: Amine elimination of rare earth metal tris(silylamide) complexes Ln[N(SiHMe2)2]3(THF)2 with 1 equiv of the pyridyl-functionalized indenyl ligand C9H7CMe2CH2C5H4N-α afforded the neutral mono-indenyl-ligated rare earth metal bis(silylamide) complexes (C9H6CMe2CH2C5H4N-α)Ln[N(SiHMe2)2]2 (Ln = Sc (1), Y (2), Nd (3)) in 70–82% isolated yields. These complexes were characterized by elemental analysis, FT-IR, NMR, and X-ray single crystal structural diffraction. X-ray determination showed that the metal centers are coordinated by one indenyl ring, one nitrogen atom from the pendent pyridyl group, and two amide groups to form a distorted tetrahedral geometry. In the presence of excess Al i Bu3 and on activation with 1 equiv of [Ph3C][B(C6F5)4] in toluene, 1–3 became active for syndiospecific polymerization of styrene in toluene at room temperature. [Copyright &y& Elsevier]

Nucleophilic addition of primary aromatic amines to carbodiimides in the presence of catalytic amount of the mono-indenyl-ligated rare earth metal bis(silylamide) complexes (C9H6CMe2CH2C5H4N- α)Ln[N(SiHMe2)2]2 at room temperature afforded efficiently a series of guanidines with a wide spectrum of substituents on the nitrogen atoms. [ABSTRACT FROM AUTHOR]

The study aims to understand the potential of Ca 3 (PO 4) 2 for relieving the slagging propensity of Ca-, Na- and Fe-rich Zhundong coal blends. Firstly, the effect of varying proportion of Ca 3 (PO 4) 2 on ash fusion temperatures of coal blends was studied. The experiment about cofiring coal blends with optimal blending ratio of Ca 3 (PO 4) 2 was then conducted in a drop tubular furnace. The chemical composition, mineral phase and micro-morphology of slags or deposits collected on an un-cooling probe at different temperatures (1200, 1000, 800 and 600 °C) were characterized. The results show that the deformation and softening temperatures of coal blends with 3% Ca 3 (PO 4) 2 can be increased by 200 °C and 150 °C, respectively. Without additive, the slags at 1200 °C appeared to be molten at a large proportion, which are mainly comprised of Fe 2 O 3 and Si-Al-Ca mineral phases. While for coal blends with 3% Ca 3 (PO 4) 2 , the particles adhered to the probe at 1200 °C presented to be granular and the melting proportion sharply decreased. At 1000 °C the deposits became loose and easy to be removed off. This is mainly due to the fact that Ca 3 (PO 4) 2 combining with Na- or Ca-containing components can transform into Ca 5 (PO 4) 2 SiO 4 , Ca 7 (PO 4) 2 Si 2 O 8 and Na 3 Ca 6 (PO 4) 5 with high melting point. • The addition of Ca 3 (PO 4) 2 could significantly increase the ash fusion temperatures of blending coal. • The blending ratio of 3% Ca 3 (PO 4) 2 is economic in consideration of additive cost and improvement of ash fusion temperatures. • Ca 5 (PO 4) 2 SiO 4 , Ca 7 (PO 4) 2 Si 2 O 8 and Na 3 Ca 6 (PO 4) 5 with a high melting point could inhibit the continue melting of slags. [ABSTRACT FROM AUTHOR]

One-pot salt metathesis reaction of anhydrous LnCl3 with one equivalent of guanidinate lithium [(SiMe3)2NC(NCy)2]Li (Cy = cyclohexyl), following the introduction of two equivalents of NaN(SiMe3)2 or LiN(SiHMe2)2 in THF at room temperature, afforded a family of mono(guanidinate) rare earth metal bis(amide) complexes [(SiMe3)2NC(NCy)2]Ln[N(SiRMe2)2]2(THF)n (R = Me, n = 0, Ln = Nd (1), Lu (2), Y (3); R = H, n = 1, Ln = Y (4)) in 62–79% isolated yields. These complexes were characterized by elemental analysis, NMR spectroscopy (except for 1 for its strong paramagnetic property of Nd3+), FT-IR spectroscopy, and X-ray single crystal diffraction. Single crystal structural determination revealed that the central metals in 1–3 are four-coordinated with a distorted tetrahedral geometry, while that in 4 is five-coordinated with a distorted trigonal bipyramidal geometry. These complexes could serve as highly active initiators for l-lactide polymerization in toluene at 50 °C. In addition, they also showed high activity towards rac-lactide polymerization in THF at room temperature, affording a moderate level of heterotactic polymers (Pr ＞ 0.70). Employing 4 as an initiator, a controllable polymerization fashion was observed both in l-lactide polymerization and rac-lactide polymerization under certain conditions. The polymerization proceeded via a coordination–insertion mechanism verified experimentally by end group analysis of the oligomer. [ABSTRACT FROM AUTHOR]

Common cardiovascular diseases, such as atherosclerosis and congestive heart failure, are exceptionally complex, involving a multitude of environmental and genetic factors that often show nonlinear interactions as well as being highly dependent on sex, age, and even the maternal environment. Although focused, reductionistic approaches have led to progress in elucidating the pathophysiology of cardiovascular diseases, such approaches are poorly powered to address complex interactions. Over the past decade, technological advances have made it possible to interrogate biological systems on a global level, raising hopes that, in combination with computational approaches, it may be possible to more fully address the complexities of cardiovascular diseases. In this Review, we provide an overview of such systems-based approaches to cardiovascular disease and discuss their translational implications. [ABSTRACT FROM AUTHOR]

Abstract: Mutation of BLM helicase causes Blooms syndrome, a disorder associated with genome instability, high levels of sister chromatid exchanges, and cancer predisposition. To study the influence of BLM on double-strand break (DSB) repair in human chromosomes, we stably transfected a normal human cell line with a DNA substrate that contained a thymidine kinase (tk)-neo fusion gene disrupted by the recognition site for endonuclease I-SceI. The substrate also contained a closely linked functional tk gene to serve as a recombination partner for the tk-neo fusion gene. We derived two cell lines each containing a single integrated copy of the DNA substrate. In these cell lines, a DSB was introduced within the tk-neo fusion gene by expression of I-SceI. DSB repair events that occurred via homologous recombination (HR) or nonhomologous end-joining (NHEJ) were recovered by selection for G418-resistant clones. DSB repair was examined under conditions of either normal BLM expression or reduced BLM expression brought about by RNA interference. We report that BLM knockdown in both cell lines specifically increased the frequency of HR events that produced deletions by crossovers or single-strand annealing while leaving the frequency of gene conversions unchanged or reduced. We observed no change in the accuracy of individual HR events and no substantial alteration of the nature of individual NHEJ events when BLM expression was reduced. Our work provides the first direct evidence that BLM influences DSB repair pathway choice in human chromosomes and suggests that BLM deficiency can engender genomic instability by provoking an increased frequency of HR events of a potentially deleterious nature. [Copyright &y& Elsevier]

Abstract: Thymidylate deprivation brings about “thymineless death” in prokaryotes and eukaryotes. Although the precise mechanism for thymineless death has remained elusive, inhibition of the enzyme thymidylate synthase (TS), which catalyzes the de novo synthesis of TMP, has served for many years as a basis for chemotherapeutic strategies. Numerous studies have identified a variety of cellular responses to thymidylate deprivation, including disruption of DNA replication and induction of DNA breaks. Since stalled or collapsed replication forks and strand breaks are generally viewed as being recombinogenic, it is not surprising that a link has been demonstrated between recombination induction and thymidylate deprivation in bacteria and lower eukaryotes. A similar connection between recombination and TS inhibition has been suggested by studies done in mammalian cells, but the relationship between recombination and TS inhibition in mammalian cells had not been demonstrated rigorously. To gain insight into the mechanism of thymineless death in mammalian cells, in this work we undertook a direct investigation of recombination in human cells treated with raltitrexed (RTX), a folate analog that is a specific inhibitor of TS. Using a model system to study intrachromosomal homologous recombination in cultured fibroblasts, we provide definitive evidence that treatment with RTX can stimulate accurate recombination events in human cells. Gene conversions not associated with crossovers were specifically enhanced several-fold by RTX. Additional experiments demonstrated that recombination events provoked by a double-strand break (DSB) were not impacted by treatment with RTX, nor was error-prone DSB repair via nonhomologous end-joining. Our work provides evidence that thymineless death in human cells is not mediated by corruption of DSB repair processes and suggests that an increase in chromosomal recombination may be an important element of cellular responses leading to thymineless death. [Copyright &y& Elsevier]

• Proposed an attention based neural network model for rice disease diagnosis. • Combined Bayesian optimization for hyperparameters tuning. • Achieved rice disease classification accuracy of 94.65%. • Outperformed the performance of existing models in the literature. • Analyzed the explainability of the proposed model. In this research, an attention-based depthwise separable neural network with Bayesian optimization (ADSNN-BO) is proposed to detect and classify rice disease from rice leaf images. Rice diseases frequently result in 20–40% corp production loss in yield and is highly related to the global economy. Rapid disease identification is critical to plan treatment promptly and reduce the corp losses. Rice disease diagnosis is still mainly performed manually. To achieve AI assisted rapid and accurate disease detection, we proposed the ADSNN-BO model based on MobileNet structure and augmented attention mechanism. Moreover, Bayesian optimization method is applied to tune hyper-parameters of the model. Cross-validated classification experiments are conducted based on a public rice disease dataset with four categories in total. The experimental results demonstrate that our mobile compatible ADSNN-BO model achieves a test accuracy of 94.65%, which outperforms all of the state-of-the-art models tested. To check the interpretability of our proposed model, feature analysis including activation map and filters visualization approach are also conducted. Results show that our proposed attention-based mechanism can more effectively guide the ADSNN-BO model to learn informative features. The outcome of this research will promote the implementation of artificial intelligence for fast plant disease diagnosis and control in the agricultural field. [ABSTRACT FROM AUTHOR]