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Tigecycline is a broad‐spectrum antibacterial agent. As the incidence of multidrug‐resistant bacterial infections has increased in intensive care units (ICUs) over the past decades, tigecycline is often used in ICUs. Information about tigecycline‐associated hepatotoxicity in ICU patients is limited. To investigate the potential risk factors for tigecycline‐associated hepatotoxicity in ICU patients, 148 patients from 2 centers who had received tigecycline for at least 4 days were retrospectively analyzed. Hepatotoxicity was classified according to the National Cancer Institute Common Terminology Criteria for Adverse Events (5.0) grading system. As a result, 33.8% of patients experienced hepatotoxicity events in the ICU. The multivariate analysis showed that an albumin concentration <25 g/L at baseline (odds ratio, 3.714; 95%CI, 1.082‐12.744; P =.037) and treatment duration (odds ratio, 1.094; 95%CI, 1.032‐1.160; P =.003) were significantly correlated with tigecycline‐associated hepatotoxicity. The median time to onset of hepatotoxicity was 8.0 days. The median duration ICU stay and the in‐hospital mortality rate were not different between the hepatotoxicity group and the nonhepatotoxicity group (33.5 days (interquartile range, 21.0‐72.0) vs 31.0 days (interquartile range, 21‐62.5), P =.850; 38.0% vs 43.8%; P =.504). Therefore, close monitoring of liver function is recommended for patients with baseline albumin concentrations <25 g/L or for patients who receive tigecycline therapy for >8 days. [ABSTRACT FROM AUTHOR]

This experiment prepared magnetic composite siderophores (DMPs) with strong magnetism, excellent adsorption capacity, and high specific surface area. Exploring the synergistic effect of magnetic nanoparticles and siderophores on Microcystis aeruginosa growth under iron-deficient condition, by utilizing the characteristics of the three-layer core-shell structure of DMPs. This study elucidated the potential mechanism by which DMPs promote the cyanobacterial growth through physiological indicators and transcriptome analysis. On the experiment's final day, cell density in DMPs treatment group at 2, 4, and 8 mg/L were 1.10, 1.14 and 1.16 times higher than those in the control group (Ct), respectively. Similarly, chlorophyll and photosynthetic efficiency results showed improved algae growth with increasing DMPs dosage. The microcystin content in DMPs experimental groups at low, medium, and high concentration were 0.91, 0.86, and 0.83 times that of Ct, indicating alleviation of iron deficiency stress. Additionally, based on extracellular polymers, intracellular and extracellular siderophores, and visualization techniques, DMPs nanoparticles captured free iron sources in the environment, promoting algae growth by entering algal cells and facilitating the uptake and utilization of free iron ions from the solution. During the experiment, the iron uptake and transport genes (feoA and feoB) were significantly upregulated, whereas the algal siderophore synthesis gene (pchF) and the TonB-dependent transport system gene (TonB_C) were significantly downregulated, suggesting heightened activity in intracellular iron uptake and transport. This indicates an abundance of intracellular iron, eliminating the need for secrete siderophores to overcome iron deficiency. Microcystis aeruginosa increased iron bioavailability by using iron transported through DMPs in the environment while internalizing these DMPs. This study explored the mechanism of this synergistic effect to boost algal growth, and provided new ideas for elucidating the mechanism of cyanobacterial bloom outbreaks as well as the innovative application of biotechnology. [Display omitted] • Deepening the interaction with M. aeruginosa through modifying siderophores. • The mechanism of DMPs promoting algal growth via transcriptomics. • DMPs facilitated algae to acquire free iron and were internalized by algae. • High-dose DMPs boosted photosynthesis, glycolysis and protein synthesis in algae. [ABSTRACT FROM AUTHOR]

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]

Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is a destructive fungal disease with a significant economic impact. Aegilops tauschii, the D-genome progenitor of wheat (Triticum aestivum, AABBDD), offers valuable gene pool for Pst resistance. The Ae. tauschii gene YrAS2388 confers resistance to a wide range of Pst races and encodes a typical nucleotide oligomerization domain-like receptor (NLR). The functional YrAS2388R has duplicated 3′ untranslated regions (3′UTRs). In the present study, we have developed two gene-specific kompetitive allele specific PCR (KASP) markers for YrAS2388R by comparing multiple homoeologous and paralogous genomic sequences of YrAS2388 alleles from allopolyploid wheat genomes. KASP-E5 was developed based on SNP in the exon5 sequences of YrAS2388, which behaves as a co-dominant marker. KASP-E6′ was developed based on the 3′UTR sequences of YrAS2388, which behaves as a dominant marker. These markers were validated in different types of wheat populations and showed clear functional differentiation that was completely agreement with the gel based gene-specific marker for YrAS2388R. Our results indicate that KASP-E5 and KASP-E6′ are perfect diagnostic markers for YrAS2388R and would be useful for marker assisted selection in wheat resistance breeding. [ABSTRACT FROM AUTHOR]

Based on the non-orthogonal multiple-relaxation-time lattice Boltzmann method (MRT–LBM), natural convection in a porous square cavity with a pair of isothermally hot and cold blocks inside was studied numerically in the current study. The influence of arrangements (Cases 1, 2, 3, 4, and 5), spacing ratio (S), and size ratio (A) of the hot and cold sources and the Rayleigh number (Ra) on the heat exchange efficiency were studied. The results show that different arrangements produce different heat-transfer effects. Two arrangements, hot and cold blocks placed horizontally (Case 1) and a cold block located in the upper left corner while a hot block is located in the bottom right corner (Case 4), have better heat exchange performance than the other three cases because the flow directions of hot and cold fluids are closer to that of the heat transfer. Then, the influence of the spacing between blocks and the size of the blocks on the heat transfer rate was further studied in Cases 1 and 4. Heat transfer performance improved with increasing A. Additionally, the variation in the heat transfer performance with spacing is related to the arrangement and size ratio of the blocks. For Ra = 104, 105, and 106, the best heat transfer characteristics were obtained in Case 1 when S = 0.05 and A = 0.20. For Ra = 107, Case 4 exhibited the best heat transfer effect when S = 0.35 and A = 0.20. [ABSTRACT FROM AUTHOR]

Protein conformational changes play crucial roles in their biological functions. In recent years, the Markov State Model (MSM) constructed from extensive Molecular Dynamics (MD) simulations has emerged as a powerful tool for modeling complex protein conformational changes. In MSMs, dynamics are modeled as a sequence of Markovian transitions among metastable conformational states at discrete time intervals (called lag time). A major challenge for MSMs is that the lag time must be long enough to allow transitions among states to become memoryless (or Markovian). However, this lag time is constrained by the length of individual MD simulations available to track these transitions. To address this challenge, we have recently developed Generalized Master Equation (GME)-based approaches, encoding non-Markovian dynamics using a time-dependent memory kernel. In this Tutorial, we introduce the theory behind two recently developed GME-based non-Markovian dynamic models: the quasi-Markov State Model (qMSM) and the Integrative Generalized Master Equation (IGME). We subsequently outline the procedures for constructing these models and provide a step-by-step tutorial on applying qMSM and IGME to study two peptide systems: alanine dipeptide and villin headpiece. This Tutorial is available at https://github.com/xuhuihuang/GME%5ftutorials. The protocols detailed in this Tutorial aim to be accessible for non-experts interested in studying the biomolecular dynamics using these non-Markovian dynamic models. [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]

Integral equation theory (IET) provides an effective solvation model for chemical and biological systems that balances computational efficiency and accuracy. We present a new software package, the expanded package for IET‐based solvation (EPISOL), that performs 3D‐reference interaction site model (3D‐RISM) calculations to obtain the solvation structure and free energies of solute molecules in different solvents. In EPISOL, we have implemented 22 different closures, multiple free energy functionals, and new variations of 3D‐RISM theory, including the recent hydrophobicity‐induced density inhomogeneity (HI) theory for hydrophobic solutes and ion‐dipole correction (IDC) theory for negatively charged solutes. To speed up the convergence and enhance the stability of the self‐consistent iterations, we have introduced several numerical schemes in EPISOL, including a newly developed dynamic mixing approach. We show that these schemes have significantly reduced the failure rate of 3D‐RISM calculations compared to AMBER‐RISM software. EPISOL consists of both a user‐friendly graphic interface and a kernel library that allows users to call its routines and adapt them to other programs. EPISOL is compatible with the force‐field and coordinate files from both AMBER and GROMACS simulation packages. Moreover, EPISOL is equipped with an internal memory control to efficiently manage the use of physical memory, making it suitable for performing calculations on large biomolecules. We demonstrate that EPISOL can efficiently and accurately calculate solvation density distributions around various solute molecules (including a protein chaperone consisting of 120,715 atoms) and obtain solvent free energy for a wide range of organic compounds. We expect that EPISOL can be widely applied as a solvation model for chemical and biological systems. EPISOL is available at https://github.com/EPISOLrelease/EPISOL. [ABSTRACT FROM AUTHOR]

Via the non-orthogonal multiple-relaxation time Lattice Boltzmann Method, the natural convection phenomenon inside I-shape heat sink under the effect of Lorentz force is investigated. The cavity is filled with MWCNT-Fe3O4/water hybrid nanofluid, and three cold and three hot tubes exist inside the cavity at the same time. The influences of Rayleigh number (103–106), Hartmann number (0–100), magnetic field tilt angle θ (0 – π/2), and different cold and heat pipe arrangements (Case 1–Case 5) on the heat transfer and fluid flow are numerically simulated. The calculated results are shown by the variation of flow lines, isotherms and the average Nusselt number. The results show that the amplitude of the flow function is always the largest for Case 5, which is the best arrangement from the fluid motion point of view, while Case 2 has the largest Nusselt number for different Rayleigh numbers, magnetic field inclination angle θ and different Hartmann numbers, which is the best arrangement from the heat transfer efficiency point of view. However, with different cold and hot pipe arrangements, the average Nusselt number increases when the Rayleigh number and the magnetic field inclination angle θ increase. In contrast, as Hartmann number increases, the average Nusselt number decreases. The local Nusselt number of the cold and hot tubes is further investigated, comparing the discrepancy of the heat transfer performance near each wall surface. [ABSTRACT FROM AUTHOR]

The generalized master equation (GME) provides a powerful approach to study biomolecular dynamics via non-Markovian dynamic models built from molecular dynamics (MD) simulations. Previously, we have implemented the GME, namely the quasi Markov State Model (qMSM), where we explicitly calculate the memory kernel and propagate dynamics using a discretized GME. qMSM can be constructed with much shorter MD trajectories than the MSM. However, since qMSM needs to explicitly compute the time-dependent memory kernels, it is heavily affected by the numerical fluctuations of simulation data when applied to study biomolecular conformational changes. This can lead to numerical instability of predicted long-time dynamics, greatly limiting the applicability of qMSM in complicated biomolecules. We present a new method, the Integrative GME (IGME), in which we analytically solve the GME under the condition when the memory kernels have decayed to zero. Our IGME overcomes the challenges of the qMSM by using the time integrations of memory kernels, thereby avoiding the numerical instability caused by explicit computation of time-dependent memory kernels. Using our solutions of the GME, we have developed a new approach to compute long-time dynamics based on MD simulations in a numerically stable, accurate and efficient way. To demonstrate its effectiveness, we have applied the IGME in three biomolecules: the alanine dipeptide, FIP35 WW-domain, and Taq RNA polymerase. In each system, the IGME achieves significantly smaller fluctuations for both memory kernels and long-time dynamics compared to the qMSM. We anticipate that the IGME can be widely applied to investigate biomolecular conformational changes. [ABSTRACT FROM AUTHOR]

Uncovering slow collective variables (CVs) of self-assembly dynamics is important to elucidate its numerous kinetic assembly pathways and drive the design of novel structures for advanced materials through the bottom-up approach. However, identifying the CVs for self-assembly presents several challenges. First, self-assembly systems often consist of identical monomers, and the feature representations should be invariant to permutations and rotational symmetries. Physical coordinates, such as aggregate size, lack high-resolution detail, while common geometric coordinates like pairwise distances are hindered by the permutation and rotational symmetry challenges. Second, self-assembly is usually a downhill process, and the trajectories often suffer from insufficient sampling of backward transitions that correspond to the dissociation of self-assembled structures. Popular dimensionality reduction methods, such as time-structure independent component analysis, impose detailed balance constraints, potentially obscuring the true dynamics of self-assembly. In this work, we employ GraphVAMPnets, which combines graph neural networks with a variational approach for Markovian process (VAMP) theory to identify the slow CVs of the self-assembly processes. First, GraphVAMPnets bears the advantages of graph neural networks, in which the graph embeddings can represent self-assembly structures in high-resolution while being invariant to permutations and rotational symmetries. Second, it is built upon VAMP theory, which studies Markov processes without forcing detailed balance constraints, which addresses the out-of-equilibrium challenge in the self-assembly process. We demonstrate GraphVAMPnets for identifying slow CVs of self-assembly kinetics in two systems: the aggregation of two hydrophobic molecules and the self-assembly of patchy particles. We expect that our GraphVAMPnets can be widely applied to molecular self-assembly. [ABSTRACT FROM AUTHOR]

Mutations in protein phosphatase 2A (PP2A) are connected to intellectual disability and cancer. It has been hypothesized that these mutations might disrupt the autoinhibition and phosphorylation-induced activation of PP2A. Since they are located far from both the active and substrate binding sites, it is unclear how they exert their effect. We performed allosteric pathway analysis based on molecular dynamics simulations and combined it with biochemical experiments to investigate the autoinhibition of PP2A. In the wild type (WT), the C-arm of the regulatory subunit B56δ obstructs the active and substrate binding sites exerting a dual autoinhibition effect. We find that the disease mutant, E198K, severely weakens the allosteric pathways that stabilize the C-arm in the WT. Instead, the strongest allosteric pathways in E198K take a different route that promotes exposure of the substrate binding site. To facilitate the allosteric pathway analysis, we introduce a path clustering algorithm for lumping pathways into channels. We reveal remarkable similarities between the allosteric channels of E198K and those in phosphorylation-activated WT, suggesting that the autoinhibition can be alleviated through a conserved mechanism. In contrast, we find that another disease mutant, E200K, which is in spatial proximity of E198, does not repartition the allosteric pathways leading to the substrate binding site; however, it may still induce exposure of the active site. This finding agrees with our biochemical data, allowing us to predict the activity of PP2A with the phosphorylated B56δ and provide insight into how disease mutations in spatial proximity alter the enzymatic activity in surprisingly different mechanisms. [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]

The self-balanced loading test is a state-of-art pile testing method, but its suitability to pile bearing capacity determination in transformer substation engineering in mountainous and hilly areas is not yet clear. In this study, a two-dimensional axisymmetric numerical model is established by the PLAXIS software to simulate the behavior and bearing mechanism of shallow rock-socketed short piles based on the self-balanced loading test. The model is first validated by simulating the field tests of two adjacent piles under self-balanced loading. Then the influence factors of the load-displacement curves of piles are analyzed. Thereafter, the mechanical mechanism of the self-balanced loading tests is simulated and compared with the conventional static loading tests. It is observed that the rock modulus, rock-socketed depth of piles, and burial depth of the Osterberg Cell affect the load-displacement significantly, but the cohesion of the rocks affects little. Moreover, compared with the conventional static loading tests, the shear stress of the pile-soil interface distributes less uniformly under self-balanced loading conditions. On this basis, a bearing capacity computation method of shallow rock-socketed short piles based on the self-balanced loading test is proposed. [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]

Two genes are synthetic lethal if mutations in both genes result in impaired cell viability, while mutation of either gene does not affect the cell survival. The potential usage of synthetic lethality (SL) in anticancer therapeutics has attracted many researchers to identify synthetic lethal gene pairs. To include newly identified SLs and more related knowledge, we present a new version of the SynLethDB database to facilitate the discovery of clinically relevant SLs. We extended the first version of SynLethDB database significantly by including new SLs identified through Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) screening, a knowledge graph about human SLs, a new web interface, etc. Over 16 000 new SLs and 26 types of other relationships have been added, encompassing relationships among 14 100 genes, 53 cancers, 1898 drugs, etc. Moreover, a brand-new web interface has been developed to include modules such as SL query by disease or compound, SL partner gene set enrichment analysis and knowledge graph browsing through a dynamic graph viewer. The data can be downloaded directly from the website or through the RESTful Application Programming Interfaces (APIs). Database URL:   https://synlethdb.sist.shanghaitech.edu.cn/v2. [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]

The three-dimensional target position is vital to automatic driving, which can efficiently detect the geometrical shape of obstacles and achieve automatic environment recognition for both indoor and outdoor scenarios. In this paper, we propose an RFID 3D localization prototype based on the polarization phase model. To eliminate the impacts of tag angle, we leverage the polarization effect to obtain polarized phases. After that, we use polarized phase decomposition to get pure phases, i.e., the phase corresponding to the line of sight path. Hence, we can calculate the raw phases using the HMFCW algorithm. Finally, we can estimate the target's 3D position according to unwrapped phase information. In this way, we implement a low-cost, high-precision, easy-for-deployment 3D position solution using commercial UHF RFID hardware. The experiments show that the method can obtain effective positioning results in various environments and achieve positioning accuracy with an average error of about 9 cm. [ABSTRACT FROM AUTHOR]

As an elementary mesh quality improvement technique, smoothing has been widely used in finite element (FE) analysis. Heuristic smoothing methods and optimization-based smoothing methods are the two main smoothing types. The former is efficient. However, it operates heuristically and may create low-quality elements. In contrast, optimization-based smoothing is very effective at improving mesh quality. However, it suffers from high computational cost since it calculates the optimal position of a free node iteratively. In this paper, we present a new smoothing method. The proposed method imitates the optimization-based smoothing based on a neural network, but it calculates the optimal position of a free node straightforwardly. Hence, the proposed method is more efficient than these optimization-based smoothing methods while being comparable in terms of mesh quality. We present various testing results to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Despite its functional importance, the molecular mechanism underlying target mRNA recognition by Argonaute (Ago) remains largely elusive. Based on extensive all-atom molecular dynamics simulations, we constructed quasi-Markov State Model (qMSM) to reveal the dynamics during recognition at position 6-7 in the seed region of human Argonaute 2 (hAgo2). Interestingly, we found that the slowest mode of motion therein is not the gRNA-target base-pairing, but the coordination of the target phosphate groups with a set of positively charged residues of hAgo2. Moreover, the ability of Helix-7 to approach the PIWI and MID domains was found to reduce the effective volume accessible to the target mRNA and therefore facilitate both the backbone coordination and base-pair formation. Further mutant simulations revealed that alanine mutation of the D358 residue on Helix-7 enhanced a trap state to slow down the loading of target mRNA. Similar trap state was also observed when wobble pairs were introduced in g6 and g7, indicating the role of Helix-7 in suppressing non-canonical base-paring. Our study pointed to a general mechanism for mRNA recognition by eukaryotic Agos and demonstrated the promise of qMSM in investigating complex conformational changes of biomolecular systems. Lizhe Zhu et al. use a quasi Markov State Model built from extensive molecular dynamics simulations to elucidate the dynamics of RISC-mRNA interactions. Their results provide further insight on how a target nucleotide is positioned before recognition by Argonaute. [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]

High glucose plays a critical role in diabetes. However, the point when high glucose induces diabetes and the organ that triggers the initiation of diabetes remain to be elucidated. The aim of the present study was to clarify the damage induced on different organs of rats, when administered a 2-week infusion of dietary glucose. SD rats (12 weeks old) were randomly divided into normal diet, high glucose infusion (IHG) and oral high glucose (OHG) groups. The levels of fasting blood sugar, tumor necrosis factor (TNF)-α and interleukin (IL)-6 were assessed. Intestine, kidney and liver samples were collected for pathological examination. Feces were collected from the rats for gut microbiota assessment. The results indicated that short-term high glucose induced hyperglycemia that lasted for at least 2 weeks after cessation of high glucose intake. Short-term high glucose also clearly increased the serum levels of IL-6 and TNF-α, led to jejunum mucosa injury and obvious steatosis in hepatocytes, and disturbed the balance of the gut microbiota. OHG led to swelling and necrosis of individual intestinal villi. IHG led to the necrosis and disappearance of cells in the upper layer of the intestinal mucosa. The lesions were confined to the mucosa. A degree of glomerular cell swelling and apoptosis were also observed. Short-term high glucose intake induced lesions in the liver, kidney and intestine, disturbed the balance of the gut microbiota and may consequently induce diabetes complications. [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]

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]