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Abstract MicroRNAs (miRNAs) are important regulators of gene expression and are involved in bacterial pathogenesis and host–pathogen interactions. In this study, we investigated the function of miRNAs in the regulation of host responses to Pasteurella multocida infection. Using next-generation sequencing, we analyzed miRNA expression pattern and identified differentially expressed miRNAs in Pasteurella multocida-infected goat lungs. In addition, we investigated the function of differentially expressed miRNAs andtheir targeted signaling pathways in bacterial infection processes. The results showed that Pasteurella multocida infection led to 69 significantly differentially expressed miRNAs, including 28 known annotated miRNAs with miR-497-3p showing the most significant difference. Gene target prediction and functional enrichment analyses showed that the target genes were mainly involved in cell proliferation, regulation of the cellular metabolic process, positive regulation of cellular process, cellular senescence, PI3K-Akt signaling pathway, FoxO signaling pathway and infection-related pathways. In conclusion, these data provide a new perspective on the roles of miRNAs in Pasteurella multocida infection.

Abstract As an efficient and environmental‐friendly strategy, electrocatalytic oxidation can realize biomass lignin valorization by cleaving its aryl ether bonds to produce value‐added chemicals. However, the complex and polymerized structure of lignin presents challenges in terms of reactant adsorption on the catalyst surface, which hinders further refinement. Herein, NiCo‐based metal‐organic frameworks (MOFs) are employed as the electrocatalyst to enhance the adsorption of reactant molecules through π‐π interaction. More importantly, lattice strain is introduced into the MOFs via curved ligand doping, which enables tuning of the d‐band center of metal active sites to align with the reaction intermediates, leading to stronger adsorption and higher electrocatalytic activity toward bond cleavage within lignin model compounds and native lignin. When 2′‐phenoxyacetophenone is utilized as the model compound, high yields of phenol (76.3%) and acetophenone (21.7%) are achieved, and the conversion rate of the reactants reaches 97%. Following pre‐oxidation of extracted poplar lignin, >10 kinds of phenolic compounds are received using the as‐designed MOFs electrocatalyst, providing ≈12.48% of the monomer, including guaiacol, vanillin, eugenol, etc., and p‐hydroxybenzoic acid dominates all the products. This work presents a promising and deliberately designed electrocatalyst for realizing lignin valorization, making significant strides for the sustainability of this biomass resource.

Abstract Soybeans are a significant agricultural product in China, with certain geographical locations often yielding higher quality, and thus more expensive, soybean crops. In this study, metabolomics and transcriptomics analyses were conducted on soybean samples from nine regions in Heilongjiang and Liaoning Provinces using untargeted liquid chromatography–mass spectrometry (LC–MS) and Illumina sequencing technologies. The primary objective was to devise an effective and unbiased method for determining the geographical origin of each soybean variety to mitigate potential fraudulent practices. Through multidimensional and unidimensional analyses, successful identification of differentially expressed metabolites (DEMs) and differentially expressed genes (DEGs) was achieved, yielding statistically significant outcomes. Integration of the metabolomics and transcriptomics datasets facilitated the construction of a correlation network model capable of distinguishing soybeans originating from different geographical locations, leading to the identification of significant biomarkers exemplifying noteworthy distinctions. To validate the feasibility of this method in practical applications, partial least squares discriminant analysis was employed to differentiate soybean samples from the nine regions. The results convincingly showcased the applicability and reliability of this approach in accurately pinpointing the geographical origin of soybeans. Distinguishing itself from prior research in soybean traceability, this study incorporates an integrated analysis of metabolomics and transcriptomics data, thereby unveiling biomarkers that offer a more precise differentiation of soybean traits across distinct regions, thereby bridging a critical research gap within the soybean traceability domain. This innovative dual-data integration analysis methodology is poised to enhance the accuracy of soybean traceability tools and lay a new foundation for future agricultural product identification research.

Influenza pandemic with H1N1 (H1N1pdms) causes severe lung damage and “cytokine storm,” leading to higher mortality and global health emergencies in humans and animals. Explaining host antiviral molecular mechanisms in response to H1N1pdms is important for the development of novel therapies. In this study, we organised and analysed multimicroarray data for mouse lungs infected with different H1N1pdm and nonpandemic H1N1 strains. We found that H1N1pdms infection resulted in a large proportion of differentially expressed genes (DEGs) in the infected lungs compared with normal lungs, and the number of DEGs increased markedly with the time of infection. In addition, we found that different H1N1pdm strains induced similarly innate immune responses and the identified DEGs during H1N1pdms infection were functionally concentrated in defence response to virus, cytokine-mediated signalling pathway, regulation of innate immune response, and response to interferon. Moreover, comparing with nonpandemic H1N1, we identified ten distinct DEGs (AREG, CXCL13, GATM, GPR171, IFI35, IFI47, IFIT3, ORM1, RETNLA, and UBD), which were enriched in immune response and cell surface receptor signalling pathway as well as interacted with immune response-related dysregulated genes during H1N1pdms. Our discoveries will provide comprehensive insights into host responding to pandemic with influenza H1N1 and find broad-spectrum effective treatment.

Skeletal muscle satellite cells, the resident stem cells in pig skeletal muscle, undergo proliferation and differentiation to enable muscle tissue repair. The proliferative and differentiative abilities of these cells gradually decrease during in vitro cultivation as the cell passage number increases. Despite extensive research, the precise molecular mechanisms that regulate this process are not fully understood. To bridge this knowledge gap, we conducted transcriptomic analysis of skeletal muscle satellite cells during in vitro cultivation to quantify passage number-dependent changes in the expression of genes associated with proliferation. Additionally, we explored the relationships between gene transcriptional activity and chromatin accessibility using transposase-accessible chromatin sequencing. This revealed the closure of numerous open chromatin regions, which were primarily located in intergenic regions, as the cell passage number increased. Integrated analysis of the transcriptomic and epigenomic data demonstrated a weak correlation between gene transcriptional activity and chromatin openness in expressed genic regions; although some genes (e.g., GNB4 and FGD5) showed consistent relationships between gene expression and chromatin openness, a substantial number of differentially expressed genes had no clear association with chromatin openness in expressed genic regions. The p53-p21-RB signaling pathway may play a critical regulatory role in cell proliferation processes. The combined transcriptomic and epigenomic approach taken here provided key insights into changes in gene expression and chromatin openness during in vitro cultivation of skeletal muscle satellite cells. These findings enhance our understanding of the intricate mechanisms underlying the decline in cellular proliferation capacity in cultured cells.

Influenza A virus (IAV) is an infectious pathogen, threatening the population and public safety with its epidemics. Therefore, it is essential to better understand influenza virus biology to develop efficient strategies against its pathogenicity. Autophagy is an important cellular process to maintain cellular homeostasis by cleaning up the hazardous substrates in lysosome. Accumulating research has also suggested that autophagy is a critical mechanism in host defense responses against IAV infection by degrading viral particles and activating innate or acquired immunity to induce viral clearance. However, IAV has conversely hijacked autophagy to strengthen virus infection by blocking autophagy maturation and further interfering host antiviral signalling to promote viral replication. Therefore, how the battle for autophagy between host and IAV is carried out need to be known. In this review, we describe the role of autophagy in host defence and IAV survival, and summarize the role of influenza proteins in subverting the autophagic process as well as then concentrate on how host utilize antiviral function of autophagy to prevent IAV infection.

With increasing population and urbanization, the amount of municipal sewage sludge generated is huge and growing rapidly. In order to minimize resource inputs and pollutant emissions in the sludge disposal process, it is crucial to carry out an environmental impact analysis and sustainability assessment of different strategies based on life cycle assessment (LCA). LCA provides a flexible framework for quantifying the consumption and emissions of different processes to determine the energy consumption and environmental impact of sewage sludge treatment and disposal. The aim of this review is to compare the energy consumption and GHG emissions of existing sludge management options for energy and nutrient recovery. At the same time, the characteristics of sewage sludge and the potential to convert sludge from waste to valuable products were assessed. While the excessive moisture content and ash content make sludge unsuitable for use as fuel, and the potential risk of contamination with heavy metals makes it less suitable for use as organic fertilizer, energy and material recovery during disposal can reduce disposal costs and environmental impacts. In the context of the current limitations reviewed, the level of potential GHG emissions of existing sludge treatment and disposal routes is: composting > anaerobic digestion > pyrolysis > incineration. With suitable sludge treatment routes, negative GHG emissions could potentially be achieved by substituting fossil fuels for heat and electricity generation, or as a fertilizer substitute. The development and application of future sludge management strategies should aim at reduction and harmless disposal, thereby reducing the operating costs and environmental burdens through resources.

In recent years, with the fast development of the technology and the economy associated with the growth of the global population, the construction of economical, sustainable, and eco-friendly infrastructures with improved ductility, resistance to external elements, and durability has increased the need for the development of high-performance construction materials [...]

The influenza virus induces cellular apoptosis during viral propagation, and controlling this virus-induced apoptosis process has been shown to have significant antiviral effects. The proapoptotic BH3-only protein Noxa is a strong inducer of apoptosis that can be activated by this virus, suggesting that Noxa has the potential as an anti-influenza target. To assess the value of Noxa as an antiviral target, we utilized CRISPR/Cas9 technology to produce a Noxa-knockout cell line. We found that the knockout of Noxa resulted in a dramatic reduction in the cytopathic effect induced by the influenza virus. Moreover, Noxa knockout decreased the expression of influenza viral proteins (NP, M2, HA, and NS2). In addition, Noxa deficiency triggered a complete autophagic flux to weaken influenza virus-induced autophagosome accumulation, indicating that Noxa may be a promising antiviral target for controlling influenza virus infections.

Mountainous expressways with bridge-tunnel groups are characterized by complex environments and high driving risks, making them crucial sections for highway safety. This study applied eye-tracking techniques to evaluate driving safety and comfort in bridge-tunnel groups. Drivers’ pupil diameter and fixation point distribution were measured in real vehicle tests. The influence of tunnel length, adjacent tunnel spacing, and natural lighting on drivers’ pupil diameters were compared and analyzed. The maximum transient velocity of pupil area was introduced to describe the drivers’ visual load and driving comfort. The results indicate that the driving workload reaches its maximum in the first tunnel in bridge-tunnel groups and is positively correlated with the tunnel length in other sections. Excessive or insufficient distance between adjacent tunnels is detrimental to driving comfort. The driving workload is higher at night compared to during the day. Moreover, the greater tunnel length in bridge-tunnel groups and the larger number of tunnels, suggest a higher driving workload for drivers. Above all, strengthening the design and management of bridge-tunnel groups in mountainous expressways is necessary.

Acid mine drainage (AMD) is a major anthropogenic source of heavy metal discharge worldwide. However, little research has been carried out on the development of AMD in abandoned pyrite mines and the heavy metal contamination of mine surface water. The aim of this study was to investigate and assess heavy metal pollution in three streams within an abandoned pyrite mine area in southeastern Shaanxi Province, China. Surface water pollution was assessed using the pollution index assessment method and the health risk assessment model. The results showed that the combined heavy metal pollution indices of the surveyed rivers were Tielu Creek (4699.227), Jiancao Creek (228.840), and Daoban Creek (68.106). After multivariate statistical analysis, it was found that the tailings slag and mine chamber in the abandoned mine area were the main causes of AMD, and AMD posed a serious risk of heavy metal pollution to the surrounding waters. The risk of carcinogenicity of heavy metals is also quite high in the surface water of mining area. Therefore, there is an urgent need to ecologically manage heavy metal pollution from abandoned mine sites, and this study provides insights into understanding heavy metal pollution in the aquatic environment of abandoned mine sites.

Developing a bioactive scaffold with biocompatible material is a substantial approach to bone regeneration and functional healing. Hydroxyapatite (HAP) is the main component in bone formation as an inorganic component and regeneration due to its osteoconductive properties. In this study, we prepared a scaffold material composed of HAP and collagen (COL) cross-linked via carboxylic carbon quantum dots (CCQD) with a chrysin (CRN) molecule. CRN is a flavonoid that has been shown to encourage the bone development of bone marrow-derived mesenchymal stem cells. It is loaded for enhancing bone regeneration and HAP’s growth ability. XRD, FT-IR, SEM, and TEM analysis have characterized the prepared composites for their crystalline nature, functional behavior, and morphological evaluations. The HAP has retained its original crystalline lattice confirmed from XRD analysis in the prepared composites. The addition of CRN molecule has decreased the length of HAP rods from ∼932 nm to ∼459 nm, as confirmed by TEM images. The increased particle sizes have been observed for the prepared composites. It reaches the maximum at 938.0 nm for the final HAP/COL/CCQD/CRN composite, which was confirmed by particle size analysis. The in-vitro CRN release behavior shows that the CRN molecule has controlled release up to 23% for 48 h. The biocompatibility of prepared material was investigated and confirmed on human bone marrow-derived mesenchymal stem cells (hBMSCs). This examination has proven that the prepared material is good for bone cell regeneration. The material may apply for bone regeneration applications after in-vivo and clinical investigations.

Ultra-high performance cementitious composite (UHPCC) is an advanced composite material with superior compressive strength. UHPCC with low steel fiber content typically fails in a single-crack mode under tension, resulting in a high risk of catastrophic structural collapse and limiting its wide application. However, high steel fiber content adversely affects the electrochemical corrosion resistance and long-term performance of UHPCC. Therefore, enhancing the tensile performance of UHPCC with low fiber content has attracted great attention. Polyvinyl alcohol (PVA) fiber is characterized by outstanding crack control ability in cementitious materials. In this study, the macroscale flowability, tensile and flexural properties, ductility and failure mode of UHPCC containing steel and PVA fibers at low fiber content level were explored and analyzed. Results indicate that the post-crack energy absorption of UHPCC improved by more than 40% following fibers hybridization. The failure mode of UHPCC with low fiber content shifted from single crack mode to ductile multiple cracks mode. Microscale observations show that PVA fibers can bridge crack and transfer load at the interface after first cracking, and impede slippage between steel fiber and matrix, thus endows UHPCC with desirable ductile multiple cracks failure mode. The findings of this study provide a foundation for designing UHPCC with ductile tensile performance and give an in-depth understanding of underlying mechanisms of hybrid fibers, promoting the application of ductile UHPCC in innovative structures.

Estrus is crucial for cow fertility in modern dairy farms, but almost 50% of cows do not show the behavioral signs of estrus due to silent estrus and lack of suitable and high-accuracy methods to detect estrus. MiRNA and exosomes play essential roles in reproductive function and may be developed as novel biomarkers in estrus detection. Thus, we analyzed the miRNA expression patterns in milk exosomes during estrus and the effect of milk exosomes on hormone secretion in cultured bovine granulosa cells in vitro. We found that the number of exosomes and the exosome protein concentration in estrous cow milk were significantly lower than in non-estrous cow milk. Moreover, 133 differentially expressed exosomal miRNAs were identified in estrous cow milk vs. non-estrous cow milk. Functional enrichment analyses indicated that exosomal miRNAs were involved in reproduction and hormone-synthesis-related pathways, such as cholesterol metabolism, FoxO signaling pathway, Hippo signaling pathway, mTOR signaling pathway, steroid hormone biosynthesis, Wnt signaling pathway and GnRH signaling pathway. Consistent with the enrichment signaling pathways, exosomes derived from estrous and non-estrous cow milk both could promote the secretion of estradiol and progesterone in cultured bovine granulosa cells. Furthermore, genes related to hormonal synthesis (CYP19A1, CYP11A1, HSD3B1 and RUNX2) were up-regulated after exosome treatment, while exosomes inhibited the expression of StAR. Moreover, estrous and non-estrous cow-milk-derived exosomes both could increase the expression of bcl2 and decrease the expression of p53, and did not influence the expression of caspase-3. To our knowledge, this is the first study to investigate exosomal miRNA expression patterns during dairy cow estrus and the role of exosomes in hormone secretion by bovine granulosa cells. Our findings provide a theoretical basis for further investigating milk-derived exosomes and exosomal miRNA effects on ovary function and reproduction. Moreover, bovine milk exosomes may have effects on the ovaries of human consumers of pasteurized cow milk. These differential miRNAs might provide candidate biomarkers for the diagnosis of dairy cow estrus and will assist in developing new therapeutic targets for cow infertility.

We assessed differentially expressed (DE) mRNAs and lncRNAs in the liver of septic pigs to explore the key factors regulating lipopolysaccharide (LPS)-induced liver injury. We identified 543 DE lncRNAs and 3642 DE mRNAs responsive to LPS. Functional enrichment analysis revealed the DE mRNAs were involved in liver metabolism and other pathways related to inflammation and apoptosis. We also found significantly upregulated endoplasmic reticulum stress (ERS)-associated genes, including the receptor protein kinase receptor-like endoplasmic reticulum kinase (PERK), the eukaryotic translation initiation factor 2α (EIF2S1), the transcription factor C/EBP homologous protein (CHOP), and activating transcription factor 4 (ATF4). In addition, we predicted 247 differentially expressed target genes (DETG) of DE lncRNAs. The analysis of protein-protein interactions (PPI) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway detected key DETGs that are involved in metabolic pathways, such as N-Acetylgalactosaminyltransferase 2 (GALNT2), argininosuccinate synthetase 1 (ASS1), and fructose 1,6-bisphosphatase 1 (FBP1). LNC_003307 was the most abundant DE lncRNA in the pig liver, with a marked upregulation of >10-fold after LPS stimulation. We identified three transcripts for this gene using the rapid amplification of the cDNA ends (RACE) technique and obtained the shortest transcript sequence. This gene likely derives from the nicotinamide N-methyltransferase (NNMT) gene in pigs. According to the identified DETGs of LNC_003307, we hypothesize that this gene regulates inflammation and endoplasmic reticulum stress in LPS-induced liver damage in pigs. This study provides a transcriptomic reference for further understanding of the regulatory mechanisms underlying septic hepatic injury.

This paper presents a supply-insensitive low-power quadrature local oscillation (LO) generator based on the current-reused voltage-controlled oscillator (VCO) and divide-by-two frequency divider (FD). By utilizing the mutual power-supply rejection (M-PSR) technique, a voltage regulator is embedded into the FD to provide a supply-insensitive voltage for VCO. Meanwhile, the feedback loop provides a supply-insensitive current and time constant compensation for FD. The M-PSR technique does not require extra voltage headroom, thus the proposed quadrature LO generator can work under the supply of 0.9 V. A prototype of the proposed quadrature LO generator is implemented in a 28-nm CMOS process. Measurement results indicate that the LO generator achieves a phase noise of −110.5 dBc/Hz@1MHz at the carrier of 5.9 GHz and the power consumption is 1.8 mW. This work has a competitive figure of merit in supply sensitivity or in area (FOMss or FOMa respectively) among the state-of-the-art works.

As a gasoline surrogate fuel, the physical and chemical properties of toluene reference fuel (TRF) are relatively simple and stable, and the TRF chemical kinetic mechanism may be used in simulating combustion processes of gasoline. However, simulations using detailed or semi-detailed mechanisms have been limited due to the computational complexity and long computational time. For the construction of the reduced mechanism, the directed relation graph with error propagation (DRGEP) method is used to wipe out insignificant components efficiently, followed by the use of the quasi-steady state assumption (QSSA) method to separate quasi-steady-state (QSS) species from the kinetic ODEs. In addition, some elementary reactions involving the formation and destruction of H and phenyl methyl radicals are subjected to sensitivity analysis and some kinetic parameters of the relevant elementary reactions are revised. As a result, a reduced mechanism involving 234 reactions and 60 species is developed. Comparing the experimental records with the analog data by utilizing the reduced mechanism, good agreement can be obtained when ignition delay time (τ), laminar flame speed (SL) and molar fraction of vital species are measured. Moreover, the mechanism may predict SL more accurately under lean mixture (equivalence ratio φ < 1.0) conditions. The reduced mechanism is small and reliable in performance, which can commendably reproduce the combustion characteristics of gasoline surrogate.

Abstract Content delivery network (CDN) has gained increasing popularity in recent years for facilitating content delivery. Most existing CDN-based works upload the content generated by mobile users to the cloud data center firstly. Then, the cloud data center delivers the content to the proxy server. Finally, the mobile users request the required content from the proxy server. However, uploading all the collected content to the cloud data center increases the pressure on the core network. In addition, it also wastes a lot of bandwidth resources because most of the content does not have to be uploaded. To make up for the shortcomings of existing CDN-based works, this article proposes an edge content delivery and update (ECDU) framework based on mobile edge computing architecture. In the ECDU framework, we deploy a number of content servers to store raw content collected from mobile users, and cache pools to store content that frequently requested at the edge of the network. Thus, it is not necessary to upload all content collected by mobile users to the cloud data center, thereby alleviating the pressure of the core network. Based on content popularity and cache pool ranking, we also propose edge content delivery (ECD) and edge content update (ECU) schemes. The ECD scheme is to deliver content from cloud data center to cache pool, and the ECU scheme is to mitigate the content to appropriate cache pools in terms of its request frequency and cache pool ranking. Finally, a representative case study is provided and several open research issues are discussed.

Large-span steel trusses are widely used in public buildings such as large-span factory buildings, exhibition halls, gymnasiums, and bridges because of their fast construction speed and easy industrial manufacturing. Due to construction errors and environmental factors, the material properties may change during their service life, and it is an important prerequisite for the structural safety assessment to identify the true material parameters of the structure. Among the many parameters, the elastic modulus is one that has the greatest impact on the accuracy of structural safety analysis. In this paper, a mathematical analysis model of elastic modulus identification was constructed, based on the strain test data and the improved gradient regularization method. The relationship between the strain test data and elastic moduli was established. A common finite element program based on the method was developed to identify the elastic modulus. A series of numerical simulations was carried out on a 53-element steel truss model to study the availability and numerical stability of the method. The effects of different initial values, numbers of strain tests, and locations of the strain test as well as the number of unknown parameters on the identification results were studied. The results showed that the proposed method had very high accuracy and computational efficiency. For the case of 53 unknown parameters without considering the test error, the identification accuracy could reach a 1 × 10−10 order of magnitude after only several iterations. This paper provides an effective solution to obtain the actual values of the elastic modulus of steel truss structures in practical engineering.

In air and railway transportation, corrosion and wear lead to the rapid failure of equipment. Epoxy (EP)-based coatings are widely used in research on the anti-corrosion of organic coatings, but their application as materials for wear resistance is limited due to their non-abrasive properties. In this study, a novel high-performance epoxy-based composite coating was developed through the self-assembly of silicon carbide (SiC) and graphene oxide (GO) and the tuning of the interfacial structure with epoxy resin. The coatings were comprehensively characterized, including their electrochemical behavior, a salt spray test, and friction and wear experiments, and the optimal addition ratio of SiC-G@GO (SiC-G@GO was prepared by the self-assembly of γ-(2,3-epoxypropoxy) propytrimethoxysilane (KH560)-modified SiC (SiC-G) on the surface of GO sheets) in the epoxy coatings was explored. Benefiting from the labyrinth effect and their rolling-friction-like microstructure, the 1 wt% SiC-G@GO/EP coating exhibits excellent wear and corrosion resistance. Compared with pure epoxy resin, the 1 wt% SiC-G@GO/EP coating increased by 4 orders of magnitude after 10 days of immersion. The average friction coefficient was 41.5% lower than that of the pure EP coating, and the wear rate was 56.6% lower. This research has positive implications for the development and application of anti-corrosion and wear-resistant organic coatings.

The clinical translation of therapeutic peptides is generally challenged by multiple issues involving absorption, distribution, metabolism and excretion. In this study, a macrophage membrane-coated poly(lactic-co-glycolic acid) (PLGA) nanodelivery system was developed to enhance the bioavailability of the somatostatin (SST) peptide, which faces the hurdles of short half-life and potential side effects in the treatment of chronic pancreatitis. Using a facile nanoprecipitation strategy, SST was loaded in the nanoparticles with an encapsulation efficiency (EE) and a loading efficiency (LE) of 73.68 ± 3.56% and 1.47 ± 0.07%, respectively. The final formulation of SST-loaded nanoparticles with the camouflage of macrophage membrane (MP-SST) showed a mean diameter of 151 ± 4 nm and an average zeta potential of −29.6 ± 0.3 mV, which were stable long term during storage. With an above 90% cell viability, a hemolysis level of about 2% (

Influenza A virus (IAV) has a higher genetic variation, leading to the poor efficiency of traditional vaccine and antiviral strategies targeting viral proteins. Therefore, developing broad-spectrum antiviral treatments is particularly important. Host responses to IAV infection provide a promising approach to identify antiviral factors involved in virus infection as potential molecular drug targets. In this study, in order to better illustrate the molecular mechanism of host responses to IAV and develop broad-spectrum antiviral drugs, we systematically analyzed mRNA expression profiles of host genes in a variety of human cells, including transformed and primary epithelial cells infected with different subtypes of IAV by mining 35 microarray datasets from the GEO database. The transcriptomic results showed that IAV infection resulted in the difference in expression of amounts of host genes in all cell types, especially those genes participating in immune defense and antiviral response. In addition, following the criteria of P

In this paper, a systematic experimental and kinetic model investigation was conducted over Cu-SSZ-13 catalyst to study the DeNOx efficiency and N 2 O formation for selective catalytic reduction of NOx with NH 3 (NH 3 -SCR). The kinetic model was developed for various reactions to take place in the NH 3 -SCR system, including NH 3 adsorption/desorption, NH 3 oxidation, NO oxidation, standard SCR, fast SCR, slow SCR and N 2 O formation reactions. In addition, the reaction of N 2 O formation from NH 3 non-selective oxidation was taken into account. All the experiments were performed in a flow reactor with a feed stream near to the real application of diesel engine vehicles exhaust. The current model can satisfactorily predict the steady state conversion rate of various species at the reactor outlet and the effect of gas hourly space velocities and ammonia nitrogen ratio on N 2 O formation. The results show that the kinetic model can simulate the reaction process of the Cu-SSZ-13 catalyst well. This is significant for the optimization of NH 3 -SCR system for achieving the higher DeNOx efficiency and the lower N 2 O emission.

Inner Mongolia is located in China’s arid and semi-arid regions, with sensitive and fragile ecosystems at risk of increased desertification, necessitating ecological restoration. However, economic resources for large-scale ecological restoration are often scarce, so it is vital to identify key areas for ecological restoration. Previous desertification research has focused mainly on the condition and changes in soil or vegetation. However, not all changes in soil or vegetation directly impact humans. New perspectives are increasingly needed to bridge the gap between biophysical and human well-being. We construct a framework to identify priority restoration areas based on ecosystem services and ecosystem vulnerability over a long time series. The results show that: (1) soil conservation services in northeast and southwest Inner Mongolia have degraded. Sand fixation services in central and eastern Inner Mongolia have shown a degradation trend. Habitat quality has been generally stable and sporadic in the past 20 years. (2) The areas with higher ecosystem vulnerability are concentrated in the northeast, mainly due to higher climate exposure and climate sensitivity but relatively lower climate resilience in the northeast. (3) Compared with the results of ecological restoration areas identified based on the trends of traditional vegetation indicators (fractional vegetation cover and net primary productivity), we found a greater proportion of land in northeastern Inner Mongolia in need of restoration. Additionally, there was identified a decreased restoration proportion in southwestern Inner Mongolia to ensure the self-restoration and regulation of desert ecosystems, which is conducive to realizing nature-based solutions.

The traditional decomposition–combination wind speed forecasting model has high complexity and a long calculation time. As a result, an ultra-short-term wind speed hybrid forecasting model based on a broad learning system (BLS) that combines improved variational mode decomposition (EPSO-VMD, EVMD) and subseries reconstruction (SR) is proposed in this work. The values of K and α in the EVMD are determined by minimum mean envelope entropy (MMEE) and enhanced particle swarm optimization (EPSO), and EVMD is used to decompose the original wind speed data. SR is applied to recombine the subseries obtained by EVMD to improve the forecasting efficiency. The sample entropy (SE) is used to quantify the subseries’ complexity, and they are then adaptively divided into high-entropy and low-entropy subseries. Adjacent high-entropy subseries of approximate entropy values are merged to obtain a new group of reconstructed high-entropy subseries, while the low-entropy subseries merge into a new subseries as well. Then, the forecasting results of the reconstructed high- and low-entropy subseries are calculated via the BLS and ARIMA models. Numerical simulation results show that the proposed method is more effective than traditional methods.

The oil-free lubrication seal of a piston rod plays an important role in the application of a Stirling engine. Parallel offset in a piston rod ruins the symmetry of the seal and affects the sealing performance when the seal is worn. In this paper, based on a motion analysis and the finite element method, a three-dimensional model of the Cap-seal was established, and its performance was numerically and experimentally investigated. The results show that parallel offset of the piston rod increases the possibility of seal damage and has no obvious effect on leakage. Under high pressures and low pre-compression ratios, the Cap-seal shows a good sealing capability and exhibits a higher propensity for mechanical damage. A good agreement was obtained between the numerical and experimental results. This study offers guidelines regarding the design and application of oil-free lubrication seals for a Stirling piston rod.

An experimental study regarding methanol–diesel dual-fuel (DF) engines was conducted on a modified engine to explore the effects of pilot injection timing and period on the two-stage combustion process caused by the pilot injection strategy. In this study, the two-stage combustion process was determined according to the first two peaks of the second derivative of an in-cylinder pressure (d2p/dφ2) curve. The results show that the peak pressure rise rate (PRR) tended to decrease with advancing pilot injection timing at a high co-combustion ratio (CCR), which reduced combustion noise. The start of the combustion of the main injection diesel (SOC2) could be advanced by increasing the pilot injection period or advancing pilot injection timing at a 42% CCR. At an 18% CCR, the pilot injection timing and period had no significant effect on SOC2. With the advancement of pilot injection timing, the start of the combustion of pilot injection diesel (SOC1) advanced, and generally, the coefficient of variation of the PRR (COVPRR) of the two-stage combustion process increased first and then decreased. However, with the increase in the pilot injection period, SOC1 almost always remained constant and the COVPRR of the two-stage combustion process generally increased.

Self-assembled peptide scaffolds based on D-RADA16 are an important matrix for controlled drug release and three-dimensional cell culture. In this work, D-RADA16 peptide hydrogels were coated on artificial bone composed of nano-hydroxyapatite/polyamide 66 (nHA/PA66) to obtain a porous drug-releasing structure for treating bone defects. The developed materials were characterized via transmission electron microscopy and scanning electron microscopy. The proliferation and adhesion of bone mesenchymal stem cells (BMSCs) were examined by confocal laser microscopy and CCK-8 experiments. The osteogenic ability of the porous materials towards bone BMSCs was examined in vitro by staining with Alizarin Red S and alkaline phosphatase, and bioactivity was evaluated in vivo. The results revealed that nHA/PA66/D-RADA16/bFGF reduces the degradation rate of D-RADA16 hydrogels and prolongs sustained release of bFGF, which would promote BMSCs proliferation, adhesion and osteogenesis in vitro and bone repair in vivo. Thus, it deserves more attention and is worthy of further research.

Identifying important nodes in complex networks is essential in disease transmission control, network attack protection, and valuable information detection. Many evaluation indicators, such as degree centrality, betweenness centrality, and closeness centrality, have been proposed to identify important nodes. Some researchers assign different weight to different indicator and combine them together to obtain the final evaluation results. However, the weight is usually subjectively assigned based on the researcher’s experience, which may lead to inaccurate results. In this paper, we propose an entropy-based self-adaptive node importance evaluation method to evaluate node importance objectively. Firstly, based on complex network theory, we select four indicators to reflect different characteristics of the network structure. Secondly, we calculate the weights of different indicators based on information entropy theory. Finally, based on aforesaid steps, the node importance is obtained by weighted average method. The experimental results show that our method performs better than the existing methods.

Cardiovascular diseases (CVD) are the leading cause of morbidity and mortality worldwide. Conventional therapies involving surgery or pharmacological strategies have shown limited therapeutic effects due to a lack of cardiac tissue repair. Gene therapy has opened an avenue for the treatment of cardiac diseases through manipulating the underlying gene mechanics. Several gene therapies for cardiac diseases have been assessed in clinical trials, while the clinical translation greatly depends on the delivery technologies. Non-viral vectors are attracting much attention due to their safety and facile production compared to viral vectors. In this review, we discuss the recent progress of non-viral gene therapies for the treatment of cardiovascular diseases, with a particular focus on myocardial infarction (MI). Through a summary of delivery strategies with which to target cardiac tissue and different cardiac cells for MI treatment, this review aims to inspire new insights into the design/exploitation of non-viral delivery systems for gene cargos to promote cardiac repair/regeneration.

Due to the high load-bearing capacity and light weight, composite leaf spring with variable width and variable thickness has been increasingly used in the automobile industry to replace the conventional steel leaf spring with a heavy weight. The optimum structural design of composite leaf spring is particularly favorable for the weight reduction. In this study, an effective algorithm is developed for structural optimization of composite leaf spring. The mechanical performance of composite leaf spring with designed dimensions is characterized using a combined experimental and computational approach. Specifically, the composite leaf spring with variable width and variable thickness was prepared using the filament winding process, and the three-dimensional finite element (FE) model of the designed composite leaf spring is developed. The experimental sample and FE model of composite leaf spring are tested under the three-point bending method. From experimental and simulation results, it is shown that the bending stiffness of the designed leaf spring meets the design requirement in the automotive industry, while the results of stress calculation along all directions meet the requirements of material strength requirement. The developed algorithm contributes to the design method for optimizing the stiffness and strength performance of the composite leaf spring.

Viscoelasticity is an important characteristic of gussasphalt mixtures. The aim of this study is to find the correct viscoelastic material parameters of the novel gussasphalt applied in the 4th Yangtze River Bridge based on the modified Burgers model. This study firstly derives the explicit Prony series form of the shear relaxation modulus of viscoelastic material from Laplace transformation, to fulfill the parameter inputting requirements of commonly used finite element software suites. Secondly, a kind of uniaxial penetration creep experiment on the gussasphalt mixtures is conducted. By fitting the creep compliance, the viscoelastic parameters characterized by the modified Burgers model are obtained. And thirdly, based on the viscoelastic test data of asphalt mixtures, the Prony series formula derived in this study is verified through the finite element simulation. The comparison results of the relative errors between the finite element simulation and the theoretical calculation confirm the reliability of the Prony series formulas deduced in this research. And finally, a stress-correcting method is proposed, which can significantly improve the accuracy of model parameters identification and reduce the relative error between the finite element simulation and the experimental data.

Defects between fiber reinforced polymer (FRP) and repaired concrete components may easily come out due to misoperation during manufacturing, environmental deterioration, or impact from external load during service life. The defects may cause a degraded structure performance and even the unexpected structural failure. Different non-destructive techniques (NDTs) and sensors have been developed to assess the defects in FRP bonded system. The information of linking up the detected defects by NDTs and repair schemes is needed by assessing the criticality of detected defects. In this study, FRP confined concrete columns with interfacial defects were experimentally tested to determine the interfacial defect criticality on structural performance. It is found that interfacial defect can reduce the FRP confinement effectiveness, and ultimate strength and its corresponding strain of column deteriorate significantly if the interfacial defect area is larger than 50% of total confinement area. Meanwhile, proposed analytical model considering the defect ratio is validated for the prediction of stress⁻strain behavior of FRP confined columns. The evaluation of defect criticality could be made by comparing predicted stress⁻strain behavior with the original design to determine corresponding maintenance strategies.