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Transportation and storage for hydrogen have garnered increasing attention in recent years because of the rapid development of low-carbon hydrogen energy. Pipeline is regarded as one of the most efficient ways for hydrogen transportation. However, many research found that the active hydrogen atoms can penetrate into the material and induce cracking on the pipe. As the initial hydrogen induced cracking is small, detecting these small defects can be challenging. To enhance the detectability of these small defects, we propose a novel capacitive sensor structure featuring two differential excitations. It is noted that the lift-off noise is always a challenging problem in electromagnetic NDE method. Fortunately, this problem can be alleviated by the proposed method. The simulation result shows the output signal will not be significantly influenced by the lift-off changing. Two metallic samples with defects are tested with a PCB-based prototype probe. Experiment result shows that the developed sensor can suppress the lift-off noise by 81.0% and increase the SNR by 592.28%, comparing to the results of a conventional sensor. A defects extraction algorithm is developed based on morphological image processing method to extract the defects from the raw data automatically. Size estimation is conducted and the average quantization error rate is 7.01% for 10 mm defects. Therefore, from the simulation and experimental results, the proposed capacitive sensing method can be a potential approach for hydrogen pipeline inspection. [ABSTRACT FROM AUTHOR]

Spiking neural networks (SNNs) possess energy-efficient potential due to event-based computation. However, supervised training of SNNs remains a challenge as spike activities are non-differentiable. Previous SNNs training methods can be generally categorized into two basic classes, i.e., backpropagation-like training methods and plasticity-based learning methods. The former methods are dependent on energy-inefficient real-valued computation and non-local transmission, as also required in artificial neural networks (ANNs), whereas the latter are either considered to be biologically implausible or exhibit poor performance. Hence, biologically plausible (bio-plausible) high-performance supervised learning (SL) methods for SNNs remain deficient. In this paper, we proposed a novel bio-plausible SNN model for SL based on the symmetric spike-timing dependent plasticity (sym-STDP) rule found in neuroscience. By combining the sym-STDP rule with bio-plausible synaptic scaling and intrinsic plasticity of the dynamic threshold, our SNN model implemented SL well and achieved good performance in the benchmark recognition task (MNIST dataset). To reveal the underlying mechanism of our SL model, we visualized both layer-based activities and synaptic weights using the t-distributed stochastic neighbor embedding (t-SNE) method after training and found that they were well clustered, thereby demonstrating excellent classification ability. Furthermore, to verify the robustness of our model, we trained it on another more realistic dataset (Fashion-MNIST), which also showed good performance. As the learning rules were bio-plausible and based purely on local spike events, our model could be easily applied to neuromorphic hardware for online training and may be helpful for understanding SL information processing at the synaptic level in biological neural systems. [ABSTRACT FROM AUTHOR]

The brain is highly plastic, with synaptic weights changing across a wide range of time scales, from hundreds of milliseconds to days. Changes occurring at different temporal scales are believed to serve different purposes, with long-term changes for learning and memory and short-term changes for adaptation and synaptic computation. By studying the performance of reservoir computing (RC) models in a memory task, we revealed that short-term synaptic plasticity is fundamentally important for long-term synaptic changes in neural networks. Specifically, short-term depression (STD) greatly expands the operational range of a neural network in which it can accommodate long-term synaptic changes while maintaining system performance. This is achieved by dynamically adjusting neural networks close to a critical state. The effects of STD can be further strengthened by synaptic weight heterogeneity, resulting in networks that can tolerate very large, long-term changes in synaptic weights. Our results highlight a potential mechanism used by the brain to organize plasticity at different time scales, thereby maintaining optimal information processing while allowing internal structural changes necessary for learning and memory. [ABSTRACT FROM AUTHOR]

Spatially separated brain areas interact with each other to form networks with coordinated activities, supporting various brain functions. Interaction structures among brain areas have been widely investigated through pairwise measures. However, interactions among multiple (e.g., triple and quadruple) areas cannot be reduced to pairwise interactions. Such higher order interactions (HOIs), e.g., exclusive-or (XOR) operation, are widely implemented in computation systems and are crucial for effective information processing. However, it is currently unclear whether any HOIs are present in large-scale brain functional networks when subjects are executing specific tasks. Here we analyzed functional magnetic resonance imaging (fMRI) data collected from human subjects executing various perceptual, motor, and cognitive tasks. We found that HOI strength in the macroscopic functional networks was very weak for all tasks, suggesting that major brain activities do not rely on HOIs on the macroscopic level at the timescale of hundreds of milliseconds. These weak HOIs during tasks were further investigated with a neural network model activated by external inputs, which suggested that weak pairwise interactions among brain areas organized the system without involving HOIs. Taken together, these results demonstrated the dominance of pairwise interactions in organizing coordinated activities among different brain areas to support various brain functions. • The lack of HOIs at functional brain networks was revealed during various tasks. • The weakly coupled regime of macroscopic brain networks was suggested. • The lack of HOIs provides the methodological foundation for pairwise approaches. [ABSTRACT FROM AUTHOR]

Reusing agro-industrial co-products has been the research focus of sustainable development worldwide. To upcycle ethanol by-product and corncob into a balanced nutritional feed for pigs, Aspergillus niger , Trichoderma reesei , Bacillus subtilis , Bacillus coagulans , and Candida utilis were employed and investigated their nutrition and flavor improving abilities. The results showed that fermentation effectively improved the total protein content of distillers dried grains with solubles (DDGS), and the highest increasing was 96.3%, by Aspergillus niger. The essential amino acids for pig growth, including lysine, isoleucine, threonine, arginine, and valine, were increased after Aspergillus niger fermentation, and it increased by 191%, 16.0%, 91.1%, 60.2% and 200%, respectively. The leucine content decreased by 44.5% after fermentation with Aspergillus niger. It provided an alternative solution for the problem of pig inhibiting digestion by high leucine content. The highest degradation rate of cellulose was 15.7% with Trichoderma reesei, while the highest degradation rate of hemicellulose was 19.4% with Aspergillus niger. Besides, the flavor of furanal in feed fermented by Aspergillus niger was increased, which would improve the feeding rate of pig since furanal is favorite for pigs. Consequently, co-fermentation of DDGS and corncob by Aspergillus niger or Trichoderma reesei have a better effect on nutrition and flavor. The results proved a viable way of producing nutritional-improved pig feed from agro-industrial co-products of corn. • The first limiting amino acid Lys was increased to 4%, 6.20 mg/g in fermented feed. • The soluble carbohydrate was increased by 207.3% via A. niger fermentation. • Furanal in feed improved to 14.2 ng/g, would be more favorable for pigs. [ABSTRACT FROM AUTHOR]

With the wide application of plastic products, microplastic pollution has become a major environmental issue of global concern. Microplastics in aquatic environments can interact with organic pollutants, causing a combined effect on submerged macrophytes. This study investigated the response mechanisms of the submerged plant Myriophyllum verticillatum and epiphytic biofilm to the antibiotic enrofloxacin, microplastics, and their combined exposure in a high nitrogen and phosphorus environment. The results indicated that Myriophyllum verticillatum was not sensitive to enrofloxacin of 1 mg L−1, while 10 and 50 mg L−1 enrofloxacin inhibited the uptake of nitrogen and phosphorus by the plants, as well as triggered oxidative stress in the plant leaves, causing irreversible damage to the plant cells. In addition, enrofloxacin altered the structure of the leaf epiphytic biofilm community. Interestingly, 1, 5, and 20 mg L−1 microplastics had no significant effect on the plant, while they facilitated the aggregation of microorganisms, increasing the abundance of the leaf epiphyte biofilm. The combination of enrofloxacin and microplastics induced a synergistic effect on Myriophyllum verticillatum. Specifically, the rate of nitrogen and phosphorus uptake by the plant was reduced, the content of photosynthetic pigments decreased, and antioxidant enzyme activity was further increased. In addition, the diversity of the leaf epiphytic biofilm community was similar to the single enrofloxacin exposure. These results demonstrated the differences between single and combined exposures and provided a new theoretical basis to evaluate the harmful effects of enrofloxacin and microplastics on submerged macrophytes. [Display omitted] • Microplastics have no ecotoxicological effects on M. verticillatum. • Microplastics contribute to the enrichment of leaf epiphytic biofilms. • Enrofloxacin has ecotoxicological effects on M. verticillatum. • Enrofloxacin alters leaf epiphytic biofilm structure. • Microplastics can exacerbate the toxicity of enrofloxacin. [ABSTRACT FROM AUTHOR]

Rehydration capacity, water distribution, and microstructure of sea cucumbers subjected to ultrasound-assisted rehydration (UAR) were investigated. Rehydration ratio and water holding capacity (WHC) were found to increase when ultrasound power was increased from 100 W to 300 W, to increase when ultrasound frequency was decreased from 45 KHz to 28 KHz. Nuclear magnetic resonance analysis revealed that water mobility increased with increasing ultrasound power, resulting in more immobilized water and free water, which facilitated better and faster water uptake. Analysis of scanning electron microscope micrographs revealed that with the accelerated water uptake, sea cucumber swelled faster and formed a structure with higher porosity which increased water uptake even faster and led to an accelerated rehydration and higher WHC. Combined with UAR, the rehydration efficiency of dried sea cucumber was increased 12-fold, and 44 h were saved in the rehydration procedure without any negative effect on texture. [ABSTRACT FROM AUTHOR]

Vehicle state estimation during anti-lock braking is considered. A novel nonlinear observer based on a vehicle dynamics model and a simplified Pacejka tire model is introduced in order to provide estimates of longitudinal and lateral vehicle velocities and the tire-road friction coefficient for vehicle safety control systems, specifically anti-lock braking control. The approach differs from previous work on vehicle state estimation in two main respects. The first is the introduction of a switched nonlinear observer in order to deal with the fact that in some driving situations the information provided by the sensor is not sufficient to carry out state estimation (i.e., not all states are observable). This is shown through an observability analysis. The second contribution is the introduction of tire-road friction estimation depending on vehicle longitudinal motion. Stability properties of the observer are analyzed using a Lyapunov function based method. Practical applicability of the proposed nonlinear observer is shown by means of experimental results. [ABSTRACT FROM AUTHOR]

[Display omitted] • Relationship between frying methods and nutrient loss of hairtail was established. • Flavor formation of hairtail under different frying methods were analyzed. • More harmful substances generated during air frying than traditional frying. • Vacuum frying contributes to the lowest amount of HAAs of hairtail. • The balance regulation between aroma and hazards for fried hairtail was proposed. The balance regulation between characteristic aroma and hazards in high-temperature processed fish is a hot spot. This study was aimed to explore the interactive relationship between the nutritional value, microstructures, aroma, and harmful substances of hairtail under different frying methods including traditional frying (TF), air frying (AF), and vacuum frying (VF) via chemical pattern recognition. The results indicated that VF-prepared hairtail could form a crunchy mouthfeel and retain the highest content of protein (645.53 mg/g) and the lowest content of fat (242.03 mg/g). Vacuum frying reduced lipid oxidation in hairtail, resulting in the POV reaching 0.02 mg/g, significantly lower than that of TF (0.05 mg/g) and AF (0.21 mg/g), and TBARS reached 0.83 mg/g, significantly lower than that of AF (1.96 mg/g) (P < 0.05), respectively. Notable variations were observed in the aroma profile of hairtail prepared from different frying methods. Vacuum frying of hairtail resulted in higher levels of pyrazines and alcohols, whereas traditional frying and air frying were associated with the formation of aldehydes and ketones, respectively. Air frying was not a healthy way to cook hairtail which produced the highest concentration of harmful substances (up to 190.63 ng/g), significantly higher than VF (5.72 ng/g) and TF (52.78 ng/g) (P < 0.05), especially norharman (122.57 ng/g), significantly higher than VF (4.50 ng/g) and TF (32.63 ng/g) (P < 0.05). Norharman and acrylamide were the key harmful substances in hairtail treated with traditional frying. The vacuum frying method was an excellent alternative for deep-fried hairtail as a snack food with fewer harmful substances and a fine aroma, providing a theoretic guidance for preparing healthy hairtail food with high nutrition and superior sensory attraction. [ABSTRACT FROM AUTHOR]

This paper investigates the impacts of weather shocks on athlete performance, focusing on soccer players in the Chinese Soccer Super League over three consecutive seasons from 2014 to 2016. Utilizing daily meteorological data, we construct the temperature and precipitation bin variables to explore the marginal effects on the physical and cognitive performance of soccer players. The empirical findings document a sizeable impact of high temperatures and heavy precipitation on players' performance indicators, including physical performance and cognitive performance. Specifically, relative to conditions with temperatures below 15 °C, the total running distances, the number of passes, and the number of fouls for soccer players significantly decrease by 7.6%, 6.0%, and 23.1%, respectively, when temperatures exceed 30 °C. The results for precipitation bins show that relative to conditions with precipitation below 0.1 mm, the total running distances, the number of passes, and the number of fouls for soccer players significantly decrease by 1.2%, 8.2%, and 4.7%, respectively, when precipitation exceeds 50 mm. Moreover, the heterogeneity analysis reveals that the negative effects of high temperatures and heavy precipitation are more pronounced and significant for older players, for matches performed away from home, and for matches performed in areas with higher temperatures or more precipitation. Evidence of player adaptations suggests that players from regions with higher temperatures or more precipitation perform better in terms of physical and cognitive abilities when playing in areas with lower temperatures or less precipitation compared to players from regions with lower temperatures or less precipitation when they compete in areas with higher temperatures or more precipitation. Finally, policy suggestions are proposed to mitigate the impact of weather shocks on soccer players and to promote the sustainability of the soccer industry. [ABSTRACT FROM AUTHOR]

The degradation of systems in service, including pipelines, over time highlights the critical need for reliable and accurate defect detection to ensure safe operations. However, single modality-based Nondestructive Evaluation (NDE) data used in practical applications often suffers from noise contamination and errors caused by various factors like lift-off/standoff distances, probe drift, scanning speed, variation in data acquisition rates, and poor sensor sensitivity. The presence of agnostic noise types poses a challenge in extracting defect signals. To address these challenges, this paper presents an automated NDE theory-based data fusion framework aimed at enhancing the detection of surface and near-surface defects in magnetizable and conductive specimens. The Magnetic Flux Leakage (MFL) and Eddy Current (EC) based NDE sensing methods demonstrate the highly heterogeneous nature of noise distributions. Given the heterogeneity of the inspection methods, a screening rule is proposed to determine the conditions under which fusion would be beneficial. An important aspect of the proposed fusion method is registration, which ensures accurate alignment of multi-sensor image data. Two registration methods are proposed in this study as performing blind fusion without registration leads to erroneous results. The first registration method is translational, whereas the second method is registration based on linear optimal transport (OT) which proves to be effective in the boundary conditions. Finally, the registered source images from the EC and MFL modalities are fused using pixel-based fusion algorithms, including transform domain and spatial domain-based methods. Qualitative and quantitative assessments demonstrate that the registered fusion results exhibit higher accuracy and reliability compared to unregistered fused results and source images. Although the fusion method is applied to MFL and EC data in this paper, it is also suitable for other NDE modalities. • Heterogeneous Fusion. • Registration based on Optimal Transport. • Near field NDE sensors. [ABSTRACT FROM AUTHOR]

[Display omitted] • The tail exhibited lower moisture and higher protein, ash, carbohydrate content. • The middle part of eel had higher hardness and good water-holding capacity. • The tail possessed a higher proportion of n − 3/n − 6 polyunsaturated fatty acids. • DGs and MGs bond to saturated fatty acids were primarily existed near the tail. With the diversity of consumer demands for healthy food, stricter requirements have been put forward for the product quality of sea eel (Astroconger myriaster). From the common experience, remarkable differences could be observed between different parts of the sea eel. The textures, basic nutritional compositions, and lipid compositions from seven parts of sea eel were investigated to reach a comprehensive evaluation of the nutritional value. Sea eel was high-fat fish which contained 21.65% to 22.84% crude fat from part one to part seven. The seventh segment exhibited a lower moisture content (51.32%) and higher contents of protein (22.76%), ash (2.46%), carbohydrate (0.80%). The third and fourth parts remained higher hardness and good water-holding capacity. Sea eel had sixteen fatty acids, and the tail possessed a higher proportion of n − 3/n − 6 polyunsaturated fatty acids. Twenty-seven lipid species were determined in sea eel, and highly unsaturated fatty acids mainly stemmed from triglycerides, while saturated fatty acids mainly existed as diglycerides. Section six and seven were primarily diglycerides and monoglycerides. According to the characteristics of different parts, it can provide support for standardized segmentation of sea eel and quality control of different parts. [ABSTRACT FROM AUTHOR]

[Display omitted] • The tail exhibited lower moisture and higher protein, ash, carbohydrate content. • The middle part of eel had higher hardness and good water-holding capacity. • The tail possessed a higher proportion of n − 3/n − 6 polyunsaturated fatty acids. • DGs and MGs bond to saturated fatty acids were primarily existed near the tail. With the diversity of consumer demands for healthy food, stricter requirements have been put forward for the product quality of sea eel (Astroconger myriaster). From the common experience, remarkable differences could be observed between different parts of the sea eel. The textures, basic nutritional compositions, and lipid compositions from seven parts of sea eel were investigated to reach a comprehensive evaluation of the nutritional value. Sea eel was high-fat fish which contained 21.65% to 22.84% crude fat from part one to part seven. The seventh segment exhibited a lower moisture content (51.32%) and higher contents of protein (22.76%), ash (2.46%), carbohydrate (0.80%). The third and fourth parts remained higher hardness and good water-holding capacity. Sea eel had sixteen fatty acids, and the tail possessed a higher proportion of n − 3/n − 6 polyunsaturated fatty acids. Twenty-seven lipid species were determined in sea eel, and highly unsaturated fatty acids mainly stemmed from triglycerides, while saturated fatty acids mainly existed as diglycerides. Section six and seven were primarily diglycerides and monoglycerides. According to the characteristics of different parts, it can provide support for standardized segmentation of sea eel and quality control of different parts. [ABSTRACT FROM AUTHOR]

Tobacco is an agricultural product with extremely high economic value. Manufacturers have realized that the chemical nature of fresh tobacco leaves influences the flavor properties of tobacco products. To explore the key components that cause the differences in tobacco leaves, high-precision mass spectrometry was employed for multi-omics analysis of three groups (upper, middle, and lower parts) of tobacco leaves. The results showed that the fresh leaves from different parts of Yunyan 87 tobacco plant had significant differences. It was not unique compounds that caused these differences, but more likely variations in shared compounds. The species of glycerolipids, glycerophospholipids, and fatty acyls were the most numerous, their numbers account for 76.68% of total lipids components. The number of glycerolipids accounted for 70% of the identified key lipid components, with the majority being polyunsaturated glycerolipids. It suggested that the disparities in polyunsaturated glycerolipids were the primary cause of lipids differentiation in fresh leaves from different parts. Glycerolipids are effective storage forms of carbon and energy. Carbohydrates and carbohydrate conjugates are the main products of tobacco photosynthesis. In key components, they had the highest relative abundance in the lower leaves. In addition, terpenoids, and organic oxygen compounds, all exhibit high relative abundances in the lower leaves. Amino acids, peptides, and analogues were more abundant in the upper leaves. Differences in the chemical composition of fresh tobacco will result in different sensory qualities and styles. In addition to providing insights into the differences and diversity of tobacco leaves in various parts of the plant during growth, the results present potentially rewarding information for directional cultivation of tobacco plants, grading of tobacco leaves, and optimization of resource utilization. [Display omitted] • The chemical composition of fresh tobacco is the basis of product sensory. • Tobacco underwent a multi-omics analysis via high-precision mass spectrometry. • Screening key components to analyze fresh tobacco differences further. • The study can guide tobacco cultivation and application. [ABSTRACT FROM AUTHOR]

In this study, the overall sensory characteristics and low-molecule-weight compounds were analyzed to achieve the discrimination of different commercial salmons and investigate the salmon's sensory and nutritional quality. The results showed that above the overall sensory properties, O. mykiss, S. salar, and O. kisutch were the most satisfied salmons by the panel with the desirable texture and flavor, which displayed a large potential for growth in the consumption market. The alcohols and sulfur compounds were key volatile compounds contributing to typical aroma of O. masou and O. gorbuscha , response higher than others by 147% to 167%. The oligopeptides and phospholipids in salmon could be used as biomarkers for discrimination of these salmon. Oligopeptides were also closely related to the taste quality of salmon. Seventeen oligopeptides showed potential umami activity based on molecular docking results, especially Arg-Val and Ser-Asn, which were the key tastants contributing to the umami of salmon. [Display omitted] • Discriminating six salmons by the profile of oligopeptides and phospholipids • Oligopeptides were closely related to the umami of salmon, as Arg-Val and Ser-Asn • O. mykiss , S. salar and O. kisutch were the most satisfied salmons by the panel • Alcohol and sulfur compounds suggested to be the mainly contributor to fishy aroma • Providing theoretical guidance for grading, discrimination and consuming of salmon [ABSTRACT FROM AUTHOR]

Abstract: Exploring the principle and relationship of gene transcriptional regulations (TR) has been becoming a generally researched issue. So far, two major mathematical methods, ordinary differential equation (ODE) method and Boolean map (BM) method have been widely used for these purposes. It is commonly believed that simplified BMs are reasonable approximations of more realistic ODEs, and both methods may reveal qualitatively the same essential features though the dynamical details of both systems may show some differences. In this Letter we exhaustively enumerated all the 3-gene networks and many autonomous randomly constructed TR networks with more genes by using both the ODE and BM methods. In comparison we found that both methods provide practically identical results in most of cases of steady solutions. However, to our great surprise, most of network structures showing periodic cycles with the BM method possess only stationary states in ODE descriptions. These observations strongly suggest that many periodic oscillations and other complicated oscillatory states revealed by the BM rule may be related to the computational errors of variable and time discretizations and rarely have correspondence in realistic biology transcriptional regulatory circuits. [ABSTRACT FROM AUTHOR]

Abstract: Recently, self-sustained oscillations in complex networks consisting of non-oscillatory nodes have attracted great interest in diverse natural and social fields. Oscillatory genomic regulatory networks are one of the most typical examples of this kind. Given an oscillatory genomic network, it is important to reveal the central structure generating the oscillation. However, if the network consists of large numbers of genes and interactions, the oscillation generator is deeply hidden in the complicated interactions. We apply the dominant phase-advanced driving path method proposed in Qian et al. (2010) to reduce complex genomic regulatory networks to one-dimensional and unidirectionally linked network graphs where negative regulatory loops are explored to play as the central generators of the oscillations, and oscillation propagation pathways in the complex networks are clearly shown by tree branches radiating from the loops. Based on the above understanding we can control oscillations of genomic networks with high efficiency. [Copyright &y& Elsevier]

• We introduce a state-of-the-art protocol to build the MSM. • We recommend spectral oASIS to automatically select physical features. • We review applications of MSM on studying protein functional conformational changes. • We discuss the perspective of quasi-MSM and deep learning methods for MSM. Functional conformational changes of proteins can facilitate numerous biological events in cells. The Markov state model (MSM) built from molecular dynamics simulations provide a powerful approach to study them. We here introduce a protocol that is tailor-made for constructing MSMs to study the functional conformational changes of proteins. In this protocol, one of the important steps is to select proper molecular features that can collectively describe the slowest timescales of conformational changes of interest. We recommend spectral oASIS, the modified version of oASIS, as a promising approach for automatic feature selection. Recently developed deep learning methods could also serve efficient approaches for selecting features and finding collective variables. Using DNA repair enzymes and RNA polymerases as examples, we review recent applications of MSMs to elucidate molecular mechanisms of functional conformational changes. Finally, we discuss remaining challenges and future perspectives for constructing MSMs to study functional conformational changes of proteins. [ABSTRACT FROM AUTHOR]

Melatonin MT 1 and MT 2 receptors represent attractive drug targets for the treatment of various disorders. However, the high conservation of the melatonin binding pocket has hindered the development of subtype-selective compounds. By leveraging on the recently resolved crystal structures of MT 1 and MT 2 receptors, this study aims to elucidate the structural basis of MT 2 -selectivity of a panel of isoquinolinone derivatives. Molecular modelling and ligand docking approaches were employed to predict residues involved in forming interactions with the MT 2 -selective isoquinolinones. Seven conserved residues (Asn175, His208, Trp264, Asn268, Gly271, Tyr294 and Tyr298) were selected as targets for site-directed mutagenesis. Ca2+ mobilization, cAMP inhibition, phosphorylation of extracellular signal-regulated kinase, and ligand binding assays were performed to functionally characterize the receptor mutants in transfected CHO cells. Unlike melatonin, isoquinolinones bearing a 3-methoxybenzyloxyl substituent were unaffected by alanine substitution at His208 of MT 2. Although alanine substitutions at Tyr294 or Tyr298 reduced the potency of melatonin and some isoquinolinones on MT 2 , similar mutations on MT 1 allowed five hitherto ineffective isoquinolinones to act as agonists. An isoquinolinone antagonist bearing a 4-methoxybenzyloxyl moiety turned into an agonist at MT 2 mutants with alanine substitutions at His208, Tyr294 or Tyr298. A subset of residues is apparently involved in forming a hydrophobic binding cavity to confer selectivity upon the aromatic substituent of isoquinolinone compounds. Two conserved tyrosine residues on transmembrane helix 7 may confer ligand selectivity at MT 1 and MT 2 receptors, while a conserved histidine on transmembrane helix 5 is apparently involved in receptor activation. [ABSTRACT FROM AUTHOR]

• We propose a joint training framework where the knowledge of ANN is consistently transferred to the SNN during training. • We factorize the parameters of both ANN and SNN and restrict them to have the same singular vectors while learning different singular values. • Extensive experiments are conducted on vision benchmarks, demonstrating that our method reaches SOTA. Emerged as a biology-inspired method, Spiking Neural Networks (SNNs) mimic the spiking nature of brain neurons and have received lots of research attention. SNNs deal with binary spikes as their activation and therefore derive extreme energy efficiency on hardware. However, it also leads to an intrinsic obstacle that training SNNs from scratch requires a re-definition of the firing function for computing gradient. Artificial Neural Networks (ANNs), however, are fully differentiable to be trained with gradient descent. In this paper, we propose a joint training framework of ANN and SNN, in which the ANN can guide the SNN's optimization. This joint framework contains two parts: First, the knowledge inside ANN is distilled to SNN by using multiple branches from the networks. Second, we restrict the parameters of ANN and SNN, where they share partial parameters and learn different singular weights. Extensive experiments over several widely used network structures show that our method consistently outperforms many other state-of-the-art training methods. For example, on the CIFAR100 classification task, the spiking ResNet-18 model trained by our method can reach to 77.39 % top-1 accuracy with only 4 time steps. [ABSTRACT FROM AUTHOR]

• ATRA decreased Hepa1-6 tumor burden and tumor angiogenesis and fibrosis. • ATRA decreased the population of MDSCs. • ATRA decreased H22 tumor burden and tumor angiogenesis and fibrosis. • ATRA decreased protumor myeloid immune subsets. • ATRA increased cytotoxic T cell infiltration. Hepatocellular carcinoma is characterized by a high infiltration of myeloid-derived suppressor cells (MDSC), which are key drivers of maintaining the immunosuppressive tumor microenvironment. Therefore, targeting MDSCs will improve immunotherapies for cancers. It has been shown that all-trans retinoic acid (ATRA) can differentiate MDSCs into mature myeloid cells. However, whether ATRA suppression of MDSCs function could inhibit the growth of liver cancer remains unknown. Here we found that ATRA significantly inhibited hepatocellular carcinoma promotion, tumor cell proliferation, and angiogenesis markers. Moreover, ATRA decreased the number of mononuclear myeloid-derived suppressor cells (M−MDSCs), granulocytic myeloid-derived suppressor cells (G-MDSCs) and tumor-associated macrophages (TAMs) in spleens. In addition, ATRA significantly reduced the intratumoral infiltrating G-MDSCs and the expression of protumor immunosuppressive molecules (arginase 1, iNOS, IDO and S100A8 + A9), which was accompanied by increased cytotoxic T cell infiltration. Our study demonstrates that ATRA not only has direct intrinsic inhibitory effect on tumor angiogenesis and fibrosis, but also reeducates the tumor microenvironment toward an antitumor phenotype by altering the relative proportion between protumor and antitumor immune cells. This information introduces ATRA as a potential druggable target for treatment of hepatocellular carcinoma. [ABSTRACT FROM AUTHOR]

Transcription elongation cycle (TEC) of RNA polymerase II (Pol II) is a process of adding a nucleoside triphosphate to the growing messenger RNA chain. Due to the long timescale events in Pol II TEC, an advanced computational technique, such as Markov State Model (MSM), is needed to provide atomistic mechanism and reaction rates. The combination of MSM and experimental results can be used to build a kinetic network model (KNM) of the whole TEC. This review provides a brief protocol to build MSM and KNM of the whole TEC, along with the latest findings of MSM and other computational studies of Pol II TEC. Lastly, we offer a perspective on potentially using a sequence dependent KNM to predict genome-wide transcription error. [ABSTRACT FROM AUTHOR]

At the core of RNA interference, the Argonaute proteins (Ago) load and utilize small guide nucleic acids to silence mRNAs or cleave foreign nucleic acids in a sequence specific manner. In recent years, based on extensive structural studies of Ago and its interaction with the nucleic acids, considerable progress has been made to reveal the dynamic aspects of various Ago-mediated processes. Here we review these novel insights into the guide-strand loading, duplex unwinding, and effects of seed mismatch, with a focus on two representative Agos, the human Ago 2 (hAgo2) and the bacterial Thermus thermophilus Ago (TtAgo). In particular, comprehensive molecular simulation studies revealed that although sharing similar overall structures, the two Agos have vastly different conformational landscapes and guide-strand loading mechanisms because of the distinct rigidity of their L1-PAZ hinge. Given the central role of the PAZ motions in regulating the exposure of the nucleic acid binding channel, these findings exemplify the importance of protein motions in distinguishing the overlapping, yet distinct, mechanisms of Ago-mediated processes in different organisms. [ABSTRACT FROM AUTHOR]

• We propose a three-stage clustering framework based on the pre-computed k nearest neighbors matrix. • A CD metric is developed in this paper to quantify the possibility of each data point as a boundary point. • The BS strategy completes the allocation of labels by shrinking the boundary points inwards. Locating the centers before assigning clustering labels is a traditional routine of clustering methods, which also limits the development of new clustering ideas. In this paper, we achieve the clustering task by firstly identifying the boundary points in the feature space, and then we shrink the boundary points to allocate the un-clustered points. Concretely, we propose a Centroid Drift (CD) metric and a Boundary Shrinkage (BS) strategy to detect boundary points in the feature space and allocate labels for un-clustered points, respectively. Both the CD and BS are closely related to the pre-computed k-nearest neighbor matrix, contributing to the decrease of algorithm parameters. Moreover, the common problems of noise points and non-uniform density distribution of data points in clustering task can also be alleviated with our proposed large value suppression and normalization of k-nearest neighbor distance techniques. The experiments on synthetic datasets, real-world face image datasets and hyperspectral images demonstrate the superiorities of our proposed clustering framework. [ABSTRACT FROM AUTHOR]

Considerable evidence implicates myeloid-derived suppressor cells (MDSCs) promote tumor progression and drug resistance. Sorafenib is the standard first-line therapy for advanced hepatocellular carcinoma (HCC). Clinical evidence indicates that sorafenib resistance is associated with increased MDSCs, by which MDSCs exerts these effects is obscure. This study aimed to investigate the mechanism of sorafenib resistance mediated by MDSCs. A syngeneic mouse-liver cancer cell line BNL was subcutaneously injected to build a tumor-bearing mouse model, and syngeneic MDSCs were adoptive transferred into the tumor-bearing mouse. Tumor tissue was obtained, and transcriptomic analysis of the tumor was carried out on RNAseq data. A coculture system was used to verify the crosstalk between MDSCs and BNL cells. Adoptive MDSCs transfer into tumor-bearing mice induced an increase of tumor-infiltrating MDSCs, which led to tumor growth and impaired antitumor activity of sorafenib in BNL HCC models. MDSCs transfer contributed to tumor fibrosis and tumor-associated fibroblast (CAF) activation, associated with fibroblast growth factor (FGF1) upregulation. In contrast, MDSC depletion by anti-Ly6G+ reduced fibrosis and increased sorafenib antitumor efficacy. Intriguingly, tumor-infiltrating MDSCs barely expressed FGF1. IL-6 derived from MDSCs increased FGF1 expression in BNL liver cancer cells, and anti-IL-6 attenuated this effect in vitro. MAPK pathway, one of the sorafenib targets, is the downstream signaling of FGF1 and is reactivated by MDSCs-mediated FGF1 upregulation. Our finding demonstrated that MDSCs led to tumor growth and sorafenib resistance via FGF1 upregulation and subsequent indirect CAF activation. We offered a novel mechanism of MDSCs-driven HCC progression and sorafenib resistance. [ABSTRACT FROM AUTHOR]

Favipiravir (T-705) has been developed as a potent anti-influenza drug and exhibited a strong inhibition effect against a broad spectrum of RNA viruses. Its active form, ribofuranosyl-triphosphate (T-705-RTP), functions as a competitive substrate for the RNA-dependent RNA polymerase (RdRp) of the influenza A virus (IAV). However, the exact inhibitory mechanisms of T-705 remain elusive and subject to a long-standing debate. Although T-705 has been proposed to inhibit transcription by acting as a chain terminator, it is also paradoxically suggested to be a mutagen towards IAV RdRp by inducing mutations due to its ambiguous base pairing of C and U. Here, we combined biochemical assay with molecular dynamics (MD) simulations to elucidate the molecular mechanism underlying the inhibitory functions exerted by T-705 in IAV RdRp. Our in vitro transcription assay illustrated that IAV RdRp could recognize T-705 as a purine analogue and incorporate it into the nascent RNA strand. Incorporating a single T-705 is incapable of inhibiting transcription as extra natural nucleotides can be progressively added. However, when two consecutive T-705 are incorporated, viral transcription is completely terminated. MD simulations reveal that the sequential appearance of two T-705 in the nascent strand destabilizes the active site and disrupts the base stacking of the nascent RNA. Altogether, our results provide a plausible explanation for the inhibitory roles of T-705 targeting IAV RdRp by integrating the computational and experimental methods. Our study also offers a comprehensive platform to investigate the inhibition effect of antivirals and a novel explanation for the designing of anti-flu drugs. [Display omitted] • Single T-705 could be incorporated by flu RdRp. • Double T-705 choke the transcription of flu RdRp. • T-705 inhibits polyadenylation. [ABSTRACT FROM AUTHOR]

An escalating pandemic by the novel SARS-CoV-2 virus is impacting global health and effective therapeutic options are urgently needed. We evaluated the in vitro antiviral effect of compounds that were previously reported to inhibit coronavirus replication and compounds that are currently under evaluation in clinical trials for SARS-CoV-2 patients. We report the antiviral effect of remdesivir, lopinavir, homorringtonine, and emetine against SARS-CoV-2 virus in Vero E6 cells with the estimated 50% effective concentration at 23.15 μM, 26.63 μM, 2.55 μM and 0.46 μM, respectively. Ribavirin or favipiravir that are currently evaluated under clinical trials showed no inhibition at 100 μM. Synergy between remdesivir and emetine was observed, and remdesivir at 6.25 μM in combination with emetine at 0.195 μM may achieve 64.9% inhibition in viral yield. Combinational therapy may help to reduce the effective concentration of compounds below the therapeutic plasma concentrations and provide better clinical benefits. • Remdesivir inhibits SARS-CoV-2 replication in Vero-E6 cells with EC 50 at 23.15 μM. • Lopinavir but not ritonavir inhibits SARS-CoV-2 replication with EC 50 at 26.63 μM. • Homoharringtonine and emetine inhibits SARS-CoV-2 replication with EC 50 at 2.55 and 0.46 μM, respectively. • Combination of remdesivir and emetine showed synergistic effect in vitro. [ABSTRACT FROM AUTHOR]

Summary Several unconventional myosins contain a highly charged single α helix (SAH) immediately following the calmodulin (CaM) binding IQ motifs, functioning to extend lever arms of these myosins. How such SAH is connected to the IQ motifs and whether the conformation of the IQ motifs-SAH segments are regulated by Ca 2+ fluctuations are not known. Here, we demonstrate by solving its crystal structure that the predicted SAH of myosin VIIa (Myo7a) forms a stable SAH. The structure of Myo7a IQ5-SAH segment in complex with apo-CaM reveals that the SAH sequence can extend the length of the Myo7a lever arm. Although Ca 2+ -CaM remains bound to IQ5-SAH, the Ca 2+ -induced CaM binding mode change softens the conformation of the IQ5-SAH junction, revealing a Ca 2+ -induced lever arm flexibility change for Myo7a. We further demonstrate that the last IQ motif of several other myosins also binds to both apo- and Ca 2+ -CaM, suggesting a common Ca 2+ -induced conformational regulation mechanism. [ABSTRACT FROM AUTHOR]