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Abstract The effects of courgette polysaccharides (CP) and coumalic acid (COA) on gelatinization, rheology, thermodynamics, microstructure, freeze–thaw stability, and in vitro digestibility of potato starch (PS) were studied. The synergistic effect of CP and COA on PS was further analyzed. The results showed that peak viscosity (PV) decreased from 6649.00 to 3462.50 mPa s and 3825.00 mPa s, respectively, after CP and COA were added. Under the combined effect of the two, it will be as low as 3225.50 mPa s. Besides, trough viscosity (TV), breakdown viscosity (BV), and final viscosity (FV) had the same trend. The presence of CP and COA can significantly delay the short‐term retrogradation of PS, especially in the case of high dose of CP and low dose of COA. Rheological tests showed that all sample gels belonged to the weak gel system (tan δ

IntroductionAstragalus mongholicus Bunge is an important medicinal legume species widely cultivated in northeastern China (NEC) and northwestern China (NWC) and can establish a symbiotic relationship with nitrogen-fixing rhizobial strains. However, there are limited reports comparing the genetic diversity, differentiation, and gene flow of rhizobial strains associated with this plant in different geographic regions.MethodsWe used multilocus sequence analysis (MLSA) to investigate the phylogeny and genetic diversity of rhizobia and to estimate their intra- and inter-regional gene flow and genetic differentiation based on the analysis of concatenated core genes (recA, atpD, and glnII) and the critical symbiotic gene nodC.ResultsWe isolated eight known and three novel genospecies representing four genera, among which Rhizobium yanglingense was the most predominant microsymbiont. Phylogenetic analysis revealed a highly diverse rhizobial community nodulating Astragalus mongholicus in NEC, consisting of the four genera Rhizobium, Bradyrhizobium, Sinorhizobium, and Mesorhizobium. This community differed markedly from the rhizobial community found in NWC. Various rhizobial genospecies with different symbiotic gene nodC sequences were capable of nodulating A. mongholicus in NEC. Therefore, A. mongholicus exhibits promiscuity in its association with symbionts in the natural environment, showing no strong preference for either the species-defining core genes or the symbiotic genes of rhizobia. We also found that the Glyco_tranf_GTA_type superfamily (Glycosyltransferase family A) is the most highly conserved and essential domain in the NodC protein, which is encoded by the symbiotic nodC gene, across nodulating rhizobia. In addition, we found independent genetic differentiation among rhizobial communities geographically, and the frequency of gene flow among microsymbionts between NEC and NWC was low. We speculate that the formation of the highly diverse rhizobial community in NEC resulted from the independent evolution of each ancestral lineage. This diversity likely arose from intraregional genetic differentiation driven by mutations rather than recombination.ConclusionEcogeographical isolation between NEC and NWC restricted inter-regional genetic drift and gene flow. Therefore, intraregional genetic differentiation is the major evolutionary force underlying the genetic diversity of rhizobia.

Dyke-Davidoff-Masson Syndrome (DDMS) is a rare neurological disease with an unknown incidence. The manifestations of DDMS are variable, while typical symptoms are seizures, hemiparesis, and mental retardation. Here, we present a case involving a 19-year-old male patient who presents with headaches, mood changes, and a history of seizures during childhood. Based on the neuroimages, a diagnosis of DDMS was established. The application of sertraline hydrochloride as a therapeutic intervention has alleviated the symptoms. This case report illustrates the importance of understanding the clinical features of DDMS based on imaging.

Objective: To establish a Bama minipigs model with Non-Alcoholic Fatty Liver (NAFL) induced by a high-fat diet and investigate the application of attenuation coefficient (ATT) and ultrasound-derived fat fraction (UDFF) in the diagnosis of NAFL. Methods: Six-month-old male Bama minipigs were randomly divided into normal control and high-fat groups (n = 3 pigs per group), and fed with a control diet and high-fat diet for 32 weeks. Weight and body length were measured every four weeks, followed by quantitative ultrasound imaging (ATT and UDFF), blood biochemical markers, and liver biopsies on the same day. Using the Non-Alcoholic Fatty Liver Disease (NAFLD) Activity Score (NAS) as a reference, we analyzed the correlation between ATT, UDFF, and their score results. Results: Compared with the normal control group, the body weight, body mass index (BMI), and serum levels of triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) in the High-fat group were significantly different at Week 12 (P

Abstract Glioma-associated macrophages (GAMs) are pivotal chains in the tumor immune microenvironment (TIME). GAMs mostly display M2-like phenotypes with anti-inflammatory features related to the malignancy and progression of cancers. Extracellular vesicles derived from immunosuppressive GAMs (M2-EVs), the essential components of the TIME, greatly impact the malignant behavior of GBM cells. M1- or M2-EVs were isolated in vitro, and human GBM cell invasion and migration were reinforced under M2-EV treatment. Signatures of the epithelial-mesenchymal transition (EMT) were also enhanced by M2-EVs. Compared with M1-EVs, miR-146a-5p, considered the key factor in TIME regulation, was deficient in M2-EVs according to miRNA-sequencing. When the miR-146a-5p mimic was added, EMT signatures and the invasive and migratory abilities of GBM cells were correspondingly weakened. Public databases predicted the miRNA binding targets and interleukin 1 receptor-associated kinase 1 (IRAK1) and tumor necrosis factor receptor-associated factor 6 (TRAF6) were screened as miR-146a-5p binding genes. Bimolecular fluorescent complementation and coimmunoprecipitation confirmed interactions between TRAF6 and IRAK1. The correlation between TRAF6 and IRAK1 was evaluated with immunofluorescence (IF)-stained clinical glioma samples. The TRAF6-IRAK1 complex is the switch and the brake that modulates IKK complex phosphorylation and NF-κB pathway activation, as well as the EMT behaviors of GBM cells. Furthermore, a homograft nude mouse model was explored and mice transplanted with TRAF6/IRAK1-overexpressing glioma cells had shorter survival times while mice transplanted with glioma cells with miR-146a-5p overexpression or TRAF6/IRAK1 knockdown lived longer. This work indicated that in the TIME of GBM, the deficiency of miR-146a-5p in M2-EVs enhances tumor EMT through disinhibition of the TRAF6-IRAK1 complex and IKK-dependent NF-κB signaling pathway providing a novel therapeutic strategy targeting the TIME of GBM.

Polysaccharides are important natural products exhibiting many biological functions, such as antioxidant, anti-inflammatory and anti-tumor activities. They are widely used in food and pharmaceutical industries. The extraction method affects the yield, structure and activity of polysaccharides, influencing their application. Subcritical water extraction is environmentally friendly, non toxic and with high extraction efficiency. It is widely used in the preparation of natural products. Under high temperature and high pressure, subcritical water changes the polarity and dielectric constant of the solvent, thereby improving the mass transfer efficiency, in the meantime maintaining the biological activity of the extracts. In this paper, we introduced the basic principles of subcritical water extraction and summarized the application of subcritical water in the extraction of fruits and vegetables, edible fungus, seafood and other polysaccharides and modification , which provides theoretical basis and references for further researches on the application of subcritical water extraction technology in polysaccharide preparation.

The effects of subcritical water microenvironment on the physiochemical properties, antioxidant activity and in vitro digestion of polysaccharides (SWESPs) from squash were investigated. After single-factor experiments, twenty samples were successfully prepared at different extraction temperatures (110, 130, 150, 170 and 190 °C) and extraction times (4, 8, 12 and 16 min). Under a low temperature environment, the whole process was mainly based on the extraction of SWESP. At this time, the color of SWESP was white or light gray and the molecular mass was high. When the temperature was 150 °C, since the extraction and degradation of SWESP reached equilibrium, the maximum extraction rate (18.67%) was reached at 150 °C (12 min). Compared with traditional methods, the yield of squash SWESP extracted by subcritical water was 3–4 times higher and less time consuming. Under high temperature conditions, SWESPs were degraded and their antioxidant capacity and viscosity were reduced. Meanwhile, Maillard and caramelization reactions turned the SWESPs yellow-brown and produced harmful substances. In addition, different SWESPs had different effects on in vitro digestion. In brief, SWESPs prepared under different conditions have different structures and physicochemical properties, allowing the obtainment of the required polysaccharide. Our results show that squash polysaccharides prepared in different subcritical water states had good development potential and application in the food industry.

Conventionally, the in-plane electronic band structure anisotropy originates from the low crystallographic symmetry in the layered material. Here, using angle-resolved photoemission spectroscopy and density functional theory the authors report that the observed in-plane anisotropic energy band structure of layered gallium telluride is dominated by a strong bulk-surface interaction rather than geometric factors, surface effect and quantum confinement effect.

This paper presents a path-planning strategy for unmanned aerial vehicles (UAVs) in urban environments with a ground risk map. The aim is to generate a UAV path that minimizes the ground risk as well as the flying cost, enforcing safety and efficiency over inhabited areas. A quantitative model is proposed to evaluate the ground risk, which is then used as a risk constraint for UAV path optimization. Subsequently, beetle swarm optimization (BSO) is proposed based on a beetle antennae search (BAS) that considers turning angles and path length. In this proposed BSO, an adaptive step size for every beetle and a random proportionality coefficient mechanism are designed to improve the deficiencies of the local optimum and slow convergence. Furthermore, a global optimum attraction operator is established to share the social information in a swarm to lead to the global best position in the search space. Experiments were performed and compared with particle swarm optimization (PSO), genetic algorithm (GA), firefly algorithm (FA), and BAS. This case study shows that the proposed BSO works well with different swarm sizes, beetle dimensions, and iterations. It outperforms the aforementioned methods not only in terms of efficiency but also in terms of accuracy. The simulation results confirm the suitability of the proposed BSO approach.

The relationship between gut microbiota and brain function has been studied intensively in recent years, and gut microbiota has been linked to a couple of neurological disorders including stroke. There are multiple studies linking gut microbiota to stroke in the “microbiota-gut-brain” axis. The aryl hydrocarbon receptor (AHR) is an important mediator of acute ischemic damage and can result in subsequent neuroinflammation. AHR can affect these responses by sensing microbiota metabolites especially tryptophan metabolites and is engaged in the regulation of acute ischemic brain injury and chronic neuroinflammation after stroke. As an important regulator in the “microbiota-gut-brain” axis, AHR has the potential to be used as a new therapeutic target for ischemic stroke treatment. In this review, we discuss the research progress on AHR regarding its role in ischemic stroke and prospects to be used as a therapeutic target for ischemic stroke treatment, aiming to provide a potential direction for the development of new treatments for ischemic stroke.

Abstract Pseudorabies virus (PRV) infection can elicit nervous system disorders. Curcumin has been reported to have neuroprotective effects. However, whether curcumin can protect neurons against PRV infection and the underlying mechanisms remain unclear. In the present study, for the first time, the protective effects of curcumin against PRV-induced oxidative stress, apoptosis, and mitochondrial dysfunction in rat hippocampal neurons and the brain-derived neurotrophic factor (BDNF)/tropomyosin-related kinase B (TrkB) pathway were investigated. Results indicated that PRV with a titer of 3.06 × 106 TCID50 (50% tissue culture infective dose) induced oxidative damage of hippocampal neurons 2 h post-infection and that 10 μM curcumin improved the viability of PRV-infected hippocampal neurons. Blocking the BDNF/TrkB pathway reversed the neuroprotective effects of curcumin, which were imparted by decreasing the PRV-induced upregulation of nitric oxide synthase expression, repressing the PRV-activated mitochondrial apoptotic pathway, and mitochondrial dysfunction. To conclude, curcumin exhibited a neuroprotective role against PRV infection by upregulating the BDNF/TrkB pathway. This study provides insight into the anti-PRV neuroprotective application of curcumin and the underlying mechanism in the prophylaxis and treatment of neurological disorders caused by PRV infection.

In recent years, using deep learning for large area building change detection has proven to be very efficient. However, the current methods for pixel-wise building change detection still have some limitations, such as a lack of robustness to false-positive changes and confusion about the boundary of dense buildings. To address these problems, a novel deep learning method called multiscale attention and edge-aware Siamese network (MAEANet) is proposed. The principal idea is to integrate both multiscale discriminative and edge structure information to improve the quality of prediction results. To effectively extract multiscale discriminative features, we design a contour channel attention module (CCAM) that highlights the edge of the changed region and combine it with the classical convolutional block attention module (CBAM) to construct multiscale attention (MA) module, which mainly contains channel, spatial and contour attention mechanisms. Meanwhile, to consider the structure information of buildings, we introduce the edge-aware (EA) module, which combines discriminative features with edge structure features to alleviate edge confusion in dense buildings. We conducted the experiments using LEVIR-CD and BCDD datasets. The proposed MA and EA modules can improve the F1-Score of the basic architecture by 1.13% on the LEVIR CD and by 1.39% on the BCDD with an accepted computation overhead. The experimental results demonstrate that the proposed MAEANet is effective and outperforms other state-of-the-art methods concerning metrics and visualization.

Chitosan-based active films were developed by incorporation of carvacrol (10 g/L), pomegranate peel extract (PPE, 10 g/L) and carvacrol + PPE (10 g/L of each) and their physical, antioxidant and antimicrobial properties were investigated. Incorporation of carvacrol and carvacrol + PPE into the films significantly decreased the water vapor permeability, tensile strength and percentage of elongation at break. Incorporation of carvacrol, PPE and carvacrol + PPE into the films decreased the transparency, but significantly increased the total phenol content and antioxidant activity. All the films, with the exception of PPE-incorporated film, exhibited antibacterial activity against Escherichia coli and Staphylococcus aureus. In addition, the antibacterial activity against Staphylococcus aureus of the film incorporated with carvacrol + PPE was moderately higher than that incorporated with carvacrol or PPE alone, suggesting a synergistic action between carvacrol and PPE.

A novel bandpass-to-all-stop switchable absorptive filter with an ultra-wideband reflectionless range is proposed in this paper. The bandpass section of the filter consists of a dual-mode resonator and two L-shaped feeding lines. The dual-port reflectionless characteristic is achieved by loading absorption networks at the end of the open stubs of the feeding lines, which are composed of two parallel coupled lines and absorption resistors. The switching of the reflectionless bandpass filter (RBPF) to the all-stop filter (ASF) is realized by controlling the on/off behavior of the PIN diode through the bias voltage. Measurements show that the filter prototype at the center frequency of 2.43 GHz with the 3-dB fractional bandwidth (FBW) is 8.23%. For the RBPF state, the filter has an ultra-wideband reflectionless FBW of 214% and upper stopband rejection better than 33 dB up to 6 GHz. Besides, the rejection is better than 30 dB from 0 to 5.32 GHz in the ASF state. [ABSTRACT FROM AUTHOR]

Auto insurance fraud detection plays an important role in promoting the healthy development of auto insurance.As the judgment of fraud involves the core content of civil rights,it is necessary for auto insurance experts to check the case and provide the reasons for fraud.Although the method based on machine learning have strongscalability and high accuracy,it lacks interpre-tability,while the rule method based on expert system has good interpretability,but it is limited by the trigger conditions of complex rules.To address the unexplainable problem of cases detected as“fraud” by machine learning methods without triggering the expert system fraud rules,this paper puts forward an analysis method of auto insurance fraud traceability based on network representationlear-ning.It first defines the abductive analysis task of auto insurance fraud.That is,for cases that are identified as “fraud ”ones by machine learning methods without triggering the expert system,it returns the ranking of the most likely fraud rules to auto insurance experts.Then,the method models the case-rule factor network based on the network representation lear-ning according to the fraud cases that have triggered the rules of the expert system,and learns the vector representation of these factors in fraud rules.To better measure the similarity between fraud cases and rules with incomplete triggering factors in the expert system,a weighted splicing strategy of factors in fraud rules is designed based on the principle of abductive reasoning,which can alleviate the problem of insufficient training data to some extent.Experimental results show that the proposed method can obtain better performances than existing methods in terms of three metrics.