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We introduce a diffusive predator-prey system with the double Allee effect, focusing on the stability and sufficient conditions for the coexistence of prey and predator. Subsequently, we derived the amplitude equation and explore secondary-order dynamic properties using methods such as Taylor series expansion and multiscaling. The novel approach outlined above provides a precise means to thoroughly analyze the predator-prey model. Through this analysis, we demonstrated that the inclusion of the Allee effect and diffusion leads to the system exhibiting more intricate dynamic behaviors compared to systems lacking these factors. On one hand, in the diffusive system without the Allee effect, the pattern formation regarding the distribution of species was relatively scattered, whereas in the diffusive system with the Allee effect, it is more intensive. On the other hand, the system with the Allee effect transitioned from unstable to stable when the diffusion parameter in prey increased, and the aggregation degree of pattern formation in the system with the Allee effect was higher than in the system without it. These findings highlight the significant roles played by the Allee effect and diffusion in determining the dynamic behaviors of prey and predator within the system.

Hyperuricemia is with growing incidence and of high risk to develop into gout and other metabolic diseases. The key enzyme catalyzing uric acid synthesis, xanthine oxidoreductase (XOR) is a vital target for anti-hyperuricemic drugs, while XOR inhibitors characterized as both potent and safe are currently in urgent need. In this study, a novel small molecule compound, CC15009, was identified as a specific XOR inhibitor. CC15009 exerted strongest in vitro XOR inhibitory activity among current XOR inhibitors. It also showed favorable dose-dependent uric acid-lowering effects in two different XOR substrate-induced hyperuricemic mouse models, which was significantly superior than the current first-line drug, allopurinol. Mechanically, the direct binding of CC15009 against XOR was confirmed by molecular docking and SPR analysis. The inhibition mode was competitive and reversible. Besides, the potential antioxidant activity of CC15009 was indicated by its strong inhibitory activity against the oxidized isoform of XOR, which reduced ROS generation as the byproduct. Regarding the safety concerns of current XOR inhibitors, especially in cardiovascular risks, the safety of CC15009 was comprehensively evaluated. No significant abnormality was observed in the acute, subacute toxicity tests and mini-AMES test. Notably, there was no obvious inhibition of CC15009 against cardiac ion channels, including hERG, Nav1.5, Cav1.2 at the concentration of 30 μM, indicating its lower cardiovascular risk. Taken together, our results supported CC15009 as a candidate of high efficacy and safety profile to treat hyperuricemia through direct XOR inhibition.

The synchronization of inertial complex-valued memristor-based neural networks (ICVMNNs) with time-varying delays was explored in the paper with the non-separation and non-reduced approach. Sufficient conditions required for the exponential synchronization of the ICVMNNs were identified with the construction of comprehensive Lyapunov functions and the design of a novel control scheme. The adaptive synchronization was also investigated based on the derived results, which is easier to implement in practice. What's more, a numerical example that verifies the obtained results was presented.

Abstract Atmospheric pressure planar plumes are desirable for the applications of low temperature plasmas, such as rapid modification of large‐scale surfaces. Up to now, only single‐mode planar plumes with either a streamer mode or a filamentary mode have been reported in the literature. Distinctive from the single‐mode planar plumes, a double‐mode argon planar plume has been generated in this article, which operates in the streamer mode with a larger distance away from a plasma jet and transits to the filamentary mode with decreasing the distance. Discharge characteristics and plasma parameters are compared for the two modes. Results indicate that the streamer mode and the filamentary mode correspond to pulsed and humped discharges respectively. Fast photography reveals that the streamer‐mode plume is composed of stochastically branching streamers, while the filamentary‐mode plume results from a series of moving filaments similar to those in barrier discharge. In contrast to the streamer mode, the filamentary mode has lower excited electron temperature and vibrational temperature, whereas higher electron density and gas temperature. In addition, better hydrophilicity of polyethylene terephthalate surface is achieved in the filamentary mode.

BackgroundSoft tissue tumors (STTs) are benign or malignant superficial neoplasms arising from soft tissues throughout the body with versatile pathological types. Although Ultrasonography (US) is one of the most common imaging tools to diagnose malignant STTs, it still has several drawbacks in STT diagnosis that need improving.ObjectivesThe study aims to establish this deep learning (DL) driven Artificial intelligence (AI) system for predicting malignant STTs based on US images and clinical indexes of the patients.MethodsWe retrospectively enrolled 271 malignant and 462 benign masses to build the AI system using 5-fold validation. A prospective dataset of 44 malignant masses and 101 benign masses was used to validate the accuracy of system. A multi-data fusion convolutional neural network, named ultrasound clinical soft tissue tumor net (UC-STTNet), was developed to combine gray scale and color Doppler US images and clinic features for malignant STTs diagnosis. Six radiologists (R1-R6) with three experience levels were invited for reader study.ResultsThe AI system achieved an area under receiver operating curve (AUC) value of 0.89 in the retrospective dataset. The diagnostic performance of the AI system was higher than that of one of the senior radiologists (AUC of AI vs R2: 0.89 vs. 0.84, p=0.022) and all of the intermediate and junior radiologists (AUC of AI vs R3, R4, R5, R6: 0.89 vs 0.75, 0.81, 0.80, 0.63; p

Staphylococcus aureus is a major human pathogen responsible for a wide range of clinical infections. SaeRS is one of the two-component systems in S. aureus that modulate multiple virulence factors. Although SaeR is required for S. aureus to develop an infection, inhibitors have not been reported. Using an in vivo knockdown method, we demonstrated that SaeR is targetable for the discovery of antivirulence agent. HR3744 was discovered through a high-throughput screening utilizing a GFP-Lux dual reporter system driven by saeP1 promoter. The antivirulence efficacy of HR3744 was tested using Western blot, Quantitative Polymerase Chain Reaction, leucotoxicity, and haemolysis tests. In electrophoresis mobility shift assay, HR3744 inhibited SaeR-DNA probe binding. WaterLOGSY-NMR test showed HR3744 directly interacted with SaeR’s DNA-binding domain. When SaeR was deleted, HR3744 lost its antivirulence property, validating the target specificity. Virtual docking and mutagenesis were used to confirm the target’s specificity. When Glu159 was changed to Asn, the bacteria developed resistance to HR3744. A structure–activity relationship study revealed that a molecule with a slight modification did not inhibit SaeR, indicating the selectivity of HR3744. Interestingly, we found that SAV13, an analogue of HR3744, was four times more potent than HR3744 and demonstrated identical antivirulence properties and target specificity. In a mouse bacteraemia model, both HR3744 and SAV13 exhibited in vivo effectiveness. Collectively, we identified the first SaeR inhibitor, which exhibited in vitro and in vivo antivirulence properties, and proved that SaeR could be a novel target for developing antivirulence drugs against S. aureus infections.

Farmers must accurately and promptly identify sugarcane leaf diseases with identical symptoms. RGB images have a beneficial function in disease identification. Nevertheless, complex backgrounds and identical symptoms can significantly reduce the recognition accuracy and robustness. To overcome these challenges, the SLViT hybrid network is presented, in which the transformer encoder is converted to a flexible plug-in (LViT) that is subsequently integrated into several locations of a lightweight CNN architecture (SHDC). SLViT is initially trained on the publicly available disease dataset Plant Village before being moved to the self-created sugarcane leaf disease dataset SLD10k, which consists of seven classes and 10,309 images. The ablation experiments demonstrate that all the adjustments to SLViT have contributed positively to its overall performance. SLViT outperforms six SOTA models and three custom-designed leaf-disease recognition models on Plant Village in terms of speed (1,832 FPS), weight (2 MB), consumption (50 M), and precision (98.84 %). SLViT also outperformed MobileNetV3_small on the SLD10k dataset with an accuracy bonus of 1.87 % and a size reduction of 66.3 %. The experiment also reveals that SLViT has absorbed the advantages of both the lightweight CNN and the noise-resistant transformer. This study demonstrates the applicability of SLViT for sugarcane leaf diagnosis in the field.

Hyperuricemia has become a global burden with the increasing prevalence and risk of associated metabolic disorders and cardiovascular diseases. Uricosurics act as a vital urate-lowering therapy by promoting uric acid excretion via the kidneys. However, potent and safe uricosurics are still in urgent demand for use in the clinic. In this study, we aimed to establish in vitro and in vivo models to aid the discovery of novel uricosurics, and to search for potent active compounds, especially targeting urate transporter 1 (URAT1), the major urate transporter in the kidney handling uric acid homeostasis. As a result, for preliminary screening, the in vitro URAT1 transport activity was assessed using a non-isotopic uric acid uptake assay in hURAT1-stably expressed HEK293 cells. The in vivo therapeutic effect was evaluated in a subacute hyperuricemic mouse model (sub-HUA) and further confirmed in a chronic hyperuricemic mouse model (Ch-HUA). By utilizing these models, compound CC18002 was obtained as a potent URAT1 inhibitor, with an IC50 value of 1.69 μM, and favorable uric acid-lowering effect in both sub-HUA and Ch-HUA mice, which was comparable to that of benzbromarone at the same dosage. Moreover, the activity of xanthine oxidoreductase, the key enzyme catalyzing uric acid synthesis, was not altered by CC18002 treatment. Taken together, we have developed a novel screening system, including a cell model targeting URAT1 and two kinds of mouse models, for the discovery of novel uricosurics. Utilizing this system, compound CC18002 was investigated as a candidate URAT1 inhibitor to treat hyperuricemia.

Abstract This paper mainly studies the exponential synchronization issue for the inertial complex-valued fuzzy cellular neural networks (ICVFCNNs) with time-varying delays via periodically intermittent control. To achieve exponential synchronization, we use a non-reduced order and non-separation approach, which is a supplement and innovation to the previous method. Based on directly constructing Lyapunov functional and a novel periodically intermittent control scheme, sufficient conditions for achieving the exponential synchronization of the ICVFCNNs are established. Finally, an example is given to illustrate the validity of the obtained results.

Unconventional reservoirs have become the main alternative for increasing oil and gas reserves around the world. Owing to their ultralow permeability properties and special pore structure, hydraulic fracturing technology is necessary to realize the efficient development and economic management of unconventional resources. To maximize the production capacity of wells, several fracture parameters, including fracture number, length, width, conductivity, and spacing, need to be optimized effectively. The optimization of hydraulic fracture parameters in shale gas reservoirs generally demands intensive computations owing to the necessity of numerous physicalmodel simulations. This study proposes a machine learning (ML)–assisted global optimization framework to rapidly obtain optimal fracture parameters. We employed three supervised ML models, including the radialbasis function, K-nearest neighbor, and multilayer perceptron, to emulate the relationship between fracture parameters and shale gas productivity for multistage fractured horizontal wells. Firstly, several forward shale gas simulations with embedded discrete fracture models generate training samples. Then, the samples are divided into training and testing samples to train these ML models and optimize network hyper parameters, respectively. Finally, the trained ML models are combined with an intelligent differential evolution algorithm to optimize the fracture parameters. This novel method has been applied to a naturally fractured reservoir model based on the real-field Barnett shale formation. The obtained results are compared with those of conventional optimizations with high-fidelity models. The results confirm the superiority of the proposed method owing to its very low computational cost. The use of ML modeling technology and an intelligent optimization algorithm could greatly contribute to simulation optimization and design, prompting progress in the intelligent development of unconventional oil and gas reservoirs in China.

IntroductionTo develop a novel deep learning model to automatically grade adenoid hypertrophy, based on nasal endoscopy, and asses its performance with that of E.N.T. clinicians.MethodsA total of 3,179 nasoendoscopic images, including 4-grade adenoid hypertrophy (Parikh grading standard, 2006), were collected to develop and test deep neural networks. MIB-ANet, a novel multi-scale grading network, was created for adenoid hypertrophy grading. A comparison between MIB-ANet and E.N.T. clinicians was conducted.ResultsIn the SYSU-SZU-EA Dataset, the MIB-ANet achieved 0.76251 F1 score and 0.76807 accuracy, and showed the best classification performance among all of the networks. The visualized heatmaps show that MIB-ANet can detect whether adenoid contact with adjacent tissues, which was interpretable for clinical decision. MIB-ANet achieved at least 6.38% higher F1 score and 4.31% higher accuracy than the junior E.N.T. clinician, with much higher (80× faster) diagnosing speed.DiscussionThe novel multi-scale grading network MIB-ANet, designed for adenoid hypertrophy, achieved better classification performance than four classical CNNs and the junior E.N.T. clinician. Nonetheless, further studies are required to improve the accuracy of MIB-ANet.

Summary: Here, we present a protocol of rapid protein desulfurization in tandem with native chemical ligation for facile syntheses of proteins with site-specific modifications. We describe using sodium tetraethylborate (NaBEt4) to carry out this desulfurization in an add-and-done manner under ambient conditions without requirement of inert atmosphere protection, UV irradiation, heating, or exogenous thiol additives. Specifically, we detail the semisynthesis of serotonylated histone H3(H3Q5ser) via one-pot ligation desulfurization. This protocol can be applied to synthesize proteins of interest with homogenous post-translational modifications.For complete information on the generation and use of this protocol, please refer to Sun et al. (2022).1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Abstract Since the implementation of the Chinese economic reforms. The habitat quality of coastal has gradually deteriorated with economic development, but the concept of "ecological construction" has slowed the negative trend. For quantitative analysis of the correlation between the Pearl River Delta urban expansion and changes in habitat quality under the influence of the policy, we first analyzed the habitat quality change based on the InVEST model and then measured the impact of construction land expansion on the habitat quality through habitat quality change index (HQCI) and contribution index (CI) indicators. Finally, the correlation between urbanization level and habitat quality was evaluated using geographically weighted regression (GWR) and the Self-organizing feature mapping neural network (SOFM). The results indicated that: (1) during the study period from 2000 to 2020, habitat quality declined due to urban sprawl, indicating a deterioration of ecological structure and function, and the decrease was most significant from 2000 to 2010. (2) The urbanization index had a negative effect on the habitat quality, but the negative effect have improved after 2000, reflecting the positive effect of policies such as "ecological civilization construction" (3) The implementation degree of ecological civilization varies greatly among cities in the study area: Shenzhen, Dongguan, Foshan, and Zhongshan have the best level of green development. These results reflect the positive role of policies in the prevention of damage to habitat quality caused by economic development and provide a reference for the formulation of sustainable urban development policies with spatial differences.

The Coronavirus Disease 2019 (COVID-19) pandemic is unlikely to abate until sufficient herd immunity is built up by either natural infection or vaccination. We previously identified ten linear immunodominant sites on the SARS-CoV-2 spike protein of which four are located within the RBD. Therefore, we designed two linkerimmunodominant site (LIS) vaccine candidates which are composed of four immunodominant sites within the RBD (RBD-ID) or all the 10 immunodominant sites within the whole spike (S-ID). They were administered by subcutaneous injection and were tested for immunogenicity and in vivo protective efficacy in a hamster model for COVID-19. We showed that the S-ID vaccine induced significantly better neutralizing antibody response than RBD-ID and alum control. As expected, hamsters vaccinated by S-ID had significantly less body weight loss, lung viral load, and histopathological changes of pneumonia. The S-ID has the potential to be an effective vaccine for protection against COVID-19.

Background: Renal fibrosis, associated with oxidative stress and nitric oxide (NO) deficiency, contributes to the development of chronic kidney disease and renal failure. As major energy source in maintaining renal physiological functions, tubular epithelial cells with decreased fatty acid oxidation play a key role in renal fibrosis development. Inorganic nitrate, found in high levels in certain vegetables, can increase the formation and signaling by bioactive nitrogen species, including NO, and dampen oxidative stress. In this study, we evaluated the therapeutic value of inorganic nitrate treatment on development of kidney fibrosis and investigated underlying mechanisms including regulation of lipid metabolism in tubular epithelial cells. Methods: Inorganic nitrate was supplemented in a mouse model of complete unilateral ureteral obstruction (UUO)-induced fibrosis. Inorganic nitrite was applied in transforming growth factor β-induced pro-fibrotic cells in vitro. Metformin was administrated as a positive control. Fibrosis, oxidative stress and lipid metabolism were evaluated. Results: Nitrate treatment boosted the nitrate-nitrite-NO pathway, which ameliorated UUO-induced renal dysfunction and fibrosis in mice, represented by improved glomerular filtration and morphological structure and decreased renal collagen deposition, pro-fibrotic marker expression, and inflammation. In human proximal tubule epithelial cells (HK-2), inorganic nitrite treatment prevented transforming growth factor β-induced pro-fibrotic changes. Mechanistically, boosting the nitrate-nitrite-NO pathway promoted AMP-activated protein kinase (AMPK) phosphorylation, improved AKT-mediated peroxisome proliferator-activated receptor-γ coactivator 1-α (PGC1α) activity and restored mitochondrial function. Accordingly, treatment with nitrate (in vivo) or nitrite (in vitro) decreased lipid accumulation, which was associated with dampened NADPH oxidase activity and mitochondria-derived oxidative stress. Conclusions: Our findings indicate that inorganic nitrate and nitrite treatment attenuates the development of kidney fibrosis by targeting oxidative stress and lipid metabolism. Underlying mechanisms include modulation of AMPK and AKT-PGC1α pathways.

Nonalcoholic fatty liver disease (NAFLD) is one of the common metabolic diseases characterized by hepatic lipid accumulation. Insulin resistance and microcirculation dysfunction are strongly associated with NAFLD. CX08005, an inhibitor of PTP1B with the IC50 of 0.75 ± 0.07 μM, has been proven to directly enhance insulin sensitivity. The present study aimed to investigate the effects of CX08005 on hepatic lipid accumulation and microcirculation dysfunction in both KKAy mice and diet-induced obesity (DIO) mice. Hepatic lipid accumulation was evaluated by hepatic triglyceride determination and B-ultrasound analysis in KKAy mice. Insulin sensitivity and blood lipids were assessed by insulin tolerance test (ITT) and triglyceride (TG)/total cholesterol (TC) contents, respectively. In addition, the hepatic microcirculation was examined in DIO mice by in vivo microscopy. The results showed that CX08005 intervention significantly reduced the TG and echo-intensity attenuation coefficient in the livers of KKAy mice. Furthermore, we found that CX08005 treatment significantly enhanced insulin sensitivity, and decreased plasma TG and/or TC contents in KKAy and DIO mice, respectively. In addition, CX08005 treatment ameliorated hepatic microcirculation dysfunction in DIO mice, as evidenced by increased RBCs velocity and shear rate of the blood flow in central veins and in the interlobular veins, as well as enhanced rate of perfused hepatic sinusoids in central vein area. Additionally, CX08005 administration decreased the adhered leukocytes both in the center veins and in the hepatic sinusoids area. Taken together, CX08005 exhibited beneficial effects on hepatic lipid accumulation and microcirculation dysfunction associated with NAFLD, which was involved with modulating insulin sensitivity and leukocyte recruitment, as well as restoration of normal microcirculatory blood flow.

Rapid industrialization and urbanization accelerate land use and land cover change, resulting in problems of stability and health with ecosystem services losses. It remains unclear and needs to be detailed discussed what spatial–temporal characteristics of the production-living-ecological spaces (PLES) would be in a rapidly developing bay area under a certain development goal. A novel future land use simulation model integrated with a dual environment evaluation system consisting of the evaluation of resources and environmental carrying capacity and territorial spatial development suitability was conducted to predict the PLES in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) in a multi-scenario view; and then we figured out the spatial–temporal changes of the PLES in the GBA during 2015–2035. Results suggest: 1) Using the DEE to determine conversion probability estimation helps to simulate and predict land use changes with high accuracy. Under the CUA scenario, the PLES account for 21.76%, 14.60% and 63.64%, respectively. The production space in Shenzhen, Hong Kong and Dongguan is dispersed, while the living space in Dongguan is clustered. The patch boundary of ecological space in Zhaoqing, Huizhou and Jiangmen would become more complex. 2) The change of the PLES in the GBA is mainly manifested by the processes of production and ecological space transferring to living space even under CUA scenario, which mainly occurs on the edge of the existing living space, especially in Zhaoqing, Conghua District of Guangzhou, Longmen County and Boluo County of Huizhou. 3) With potential conflicts between production space and ecological space, more attention should be paid to reducing the occupation of basic farmland in ecological restoration in the GBA. The future PLES in the GBA would be characterized by the conflict between the living and non-living spaces and that between productive and ecological spaces. The predicted PLES under CUA scenario may provide a spatial reference for policy-making in the future territorial spatial development and construction of ecological security patterns in the GBA.

Abstract Daptomycin, as a lipopeptide antibiotic, exhibits high potency in the treatment of infections caused by clinically relevant drug‐resistant Gram‐positive pathogens, such as methicillin‐resistant Staphylococcus aureus and vancomycin‐resistant Enterococci. However, its bactericidal mechanism of action remains controversial. In this study, we report that daptomycin kills bacteria through triggering overproduction of deleterious reactive oxygen species (ROS). This outcome is attributed to daptomycin binding to the universal stress response protein (Usp2) and subsequent blocking its function, triggering stress, and anti‐ROS response. Based on these findings, we conclude that daptomycin causes bacterial cell death by simultaneously triggering ROS production through inflicting cell membrane damages and inhibiting antioxidant defense by blocking Usp2 function. This study depicts molecular mechanisms underlying the bactericidal effect of daptomycin, a combination of triggering ROS production and inhibiting anti‐ROS response. Key points Novel bactericidal mechanism of daptomycin by ROS Identification of first bacterial protein target, Usp2, for daptomycin Deciphering the dual role of Usp2 on daptomycin mediated bacterial killing

Summary: Dissecting the function of proteins’ post-translational modifications (PTMs) is seriously hindered by the difficulty in obtaining the homogeneous protein with the PTMs of interest. Chemical protein synthesis offers a great potential to overcome this limitation. Here, a detailed protocol is introduced for chemical synthesis of HMGA1a protein with site-specific modifications via Ser/Thr ligation strategy, by which we can systematically study the function of the triple phosphorylation (3pSer) in the HMGA1a acidic tail.For complete details on the use and execution of this protocol, please refer to Wei et al. (2021).

Deep neural networks (DNNs) have been widely applied to the automatic analysis of medical images for disease diagnosis and to help human experts by efficiently processing immense amounts of images. While the handcrafted feature has been used for eye disease detection or classification since the 1990s, DNN was recently adopted in this area and showed a very promising performance. Since handcrafted and deep feature can extract complementary information, we propose, in this paper, three different integration frameworks to combine handcrafted and deep feature for optical coherence tomography image-based eye disease classification. In addition, to integrate the handcrafted feature at the input and fully connected layers using existing networks, such as VGG, DenseNet, and Xception, a novel ribcage network (RC Net) is also proposed for feature integration at middle layers. For RC Net, two “rib” channels are designed to independently process deep and handcrafted features, and another so-called “spine” channel is designed for the integration. While dense blocks are the main components of the three channels, sum operation is proposed for the feature map integration. Our experimental results showed that the deep networks achieved better classification accuracy after the integration of the handcrafted features, e.g., scale-invariant feature transform and Gabor. The RC Net showed the best performance among all the proposed feature integration methods.

Point set registration under affine transformation is an important problem in computer vision because not only it has many direct applications, but it is also often used as an initial step for non-rigid registration. This problem is challenging when no correspondences between the two point sets are known, and most existing methods start from an initial pose and find a local optimal transformation. This paper presents a deterministic global optimization method for affine point set registration, which is called GO-APSR. We model the two sets to be registered with Gaussian Mixture Models (GMMs) and minimize the L2 distance between the two GMMs under affine transformation. Branch-and-Bound (BnB) is employed to search the transformation parameter space, and we propose a convex quadratic function as the under-estimator of the objective function in each branch. Therefore, calculation of the lower bound in each branch is casted into a bound-constrained convex quadratic programming problem, which can be solved globally and efficiently. Experiment results verify the global optimality of the proposed method and its robustness to noise and outliers. Furthermore, it works very well in the challenging partially-overlap scenarios.

Objective: Teixobactin and its analogues are a new class of antibiotics that have no detectable bacterial resistance. This study was designed to determine the antibacterial and antibiofilm activities of a novel teixobactin analogue, L-Chg10-teixobactin, against two strains of Enterococcus faecalis (E. faecalis). Materials and Methods: The efficacy of L-Chg10-teixobactin against two strains of E. faecalis (ATCC 29212 and 47077) was determined using Clinical and Laboratory Standards Institute methods. L-Chg10-teixobactin was prepared at a stock concentration of 1 mg/mL in 5% DMSO. The minimum inhibitory concentration (MIC) was calculated using a two-fold serial broth dilution method, utilizing a 96-well plate. The minimum bactericidal concentration (MBC) was determined by plating the bacteria onto agar to define the concentration that resulted in 99.9% of bacterial death. Ampicillin was used as the control. The effect of L-Chg10-teixobactin on the inhibition of ATCC 47077 strain biofilm formation was determined by measuring the minimum biofilm inhibitory concentration (MBIC) using the safranin assay, while the eradication of the preformed biofilm was determined by measuring the minimum biofilm eradication concentration (MBEC) using the XTT assay. For nonlinear data, the log dose–response curve was plotted to calculate the optimum concentration using Excel (version 16.51, Microsoft® excel. 2021, Microsoft Corporation, Reymond, WA, USA). The data are presented as mean ± standard deviation (SD). Results: The MIC and MBC values of L-Chg10-teixobactin against both strains of E. faecalis were 0.8 μg/mL. The MIC of ampicillin was 1.25 μg/mL for ATCC 29212 and ranged from 1.25 to 5 μg/mL for ATCC 47077. The MBC of ampicillin for ATCC 29212 and ATCC 47077 was 10 and 20 μg/mL, respectively. The MIC and MBC of ampicillin were much higher compared with those of L-Chg10-teixobactin. The MBEC80 of L-Chg10-teixobactin was 4.60 μg/mL for ATCC 47077, which was much lower than that of ampicillin (20 μg/mL). Conclusions:L-Chg10-teixobactin demonstrated potent antibacterial and antibiofilm effects against E. faecalis, suggesting its potential role an effective antibacterial and antibiofilm agent in endodontic treatment.

Hyperuricemia is characterized by abnormally high level of circulating uric acid in the blood and is associated with increased risk of kidney injury. The pathophysiological mechanisms leading to hyperuricemic nephropathy (HN) involve oxidative stress, endothelial dysfunction, inflammation, and fibrosis. Mangiferin is a bioactive C-glucoside xanthone, which has been exerting anti-inflammatory, anti-fibrotic, and antioxidative effects in many diseases. This study aimed to evaluate the effect of mangiferin treatment in HN. In a mouse model of HN, we observed lower circulating urate levels and ameliorated renal dysfunction with mangiferin treatment, which was associated with reduced renal inflammation and fibrosis. We next investigated the mechanism of urate lowering effect of mangiferin. Metabolic cage experiment showed that mangiferin-administrated mice excreted significantly more urinary uric acid due to elevated urine output, but no marked change in urine uric acid concentration. Expressions of water channels and urate transporters were further assessed by western blot. Renal AQP2 expression was decreased, yet urate transporters URAT1, GLUT9, and OAT1 expressions were not affected by mangiferin in HN mice. Moreover, mangiferin treatment also normalized xanthine oxidase and SOD activity in HN mice, which would decrease uric acid synthesis and improve oxidative stress, respectively. Therefore, our results reveal a novel mechanism whereby mangiferin can reduce serum uric acid levels by promoting AQP2-related urinary uric acid excretion. This study suggested that mangiferin could be a multi-target therapeutic candidate to prevent HN via mechanisms that involve increased excretion and decreased production of uric acid and modulation of inflammatory, fibrotic, and oxidative pathways.

BackgroundLead is a common environmental hazard because of its past use as an additive to gasoline and household paint. Some evidence suggests that children with histories of child abuse and neglect are at elevated risk for residence in communities and households with less desirable characteristics and high levels of exposure to environmental hazards and toxins.ObjectivesTo understand whether childhood maltreatment leads to higher levels of household dust lead and blood lead in adulthood and the extent to which characteristics of a person's physical environment or individual level socio-economic status (SES) (based on unemployment, poverty, and receipt of public assistance) contribute to understanding the relationship.MethodsA large prospective cohort design study in which abused and neglected children (ages 0-11) were matched with non-maltreated children and assessed in adulthood. Objective and subjective neighborhood characteristics were assessed at approximate age 40 and household dust lead (cleaned and less often cleaned) and blood lead levels were measured at age 41. Blood was collected through venipuncture by a registered nurse as part of a medical status exam.ResultsChildhood maltreatment predicted higher levels of dust lead in less often cleaned household places, residence in worse neighborhoods defined by objective (census tract data) and subjective (reports of physical disorder and lack of social cohesion and control), and higher levels of poverty, receiving public assistance, and unemployment. Only objective neighborhood characteristics mediated the relationship between childhood maltreatment and dust lead level in adulthood. There were also significant paths from objective neighborhood disadvantage and individual level SES to higher levels of blood lead.DiscussionThirty years after their childhood experiences, individuals with documented histories of childhood maltreatment are at higher risk for living in environments as adults with elevated lead levels that may impact other aspects of their lives and compromise their health.

In this paper, the stability and stabilization issues for a class of delayed neural networks with time-varying hybrid impulses are investigated. The hybrid effect of two types of impulses including both stabilizing and destabilizing impulses is considered simultaneously in the analysis of systems. To characterize the occurrence features of impulses, the concepts of average impulse interval and average impulse strength are employed. Based on the analysis of stability, a pinning impulsive controller which can ensure the global exponential stability of the studied neural networks is designed by pinning a small fraction of neurons. Finally, two numerical examples are given to illustrate the effectiveness of the proposed control schemes for delayed neural networks with hybrid impulses.

Rapid urbanization has a significant impact on the ecological environment. Net primary productivity (NPP) can effectively reflect the growth of urban vegetation and the carbon sequestration capacity of an ecosystem. Taking the rapidly growing Pearl River Delta (PRD) as our study area, the relative contributions of human activities and climate change to NPP were analyzed using an improved two-step method based on residual trend analysis. The decoupling index was used to compare the coordinated development of socioeconomic factors and the NPP in different time periods. This study lays the foundation for formulating comprehensive and reasonable urban low-carbon development measures. The results showed that (1) NPP decreased significantly before 2010, but by 2019, NPP in most regions of the PRD showed a slight increase. The NPP of new urban land was better than that of original urban land. (2) The negative contribution of climatic factors to NPP was clearer than that of human activities, and human activities contributed positively to NPP outside urban land. (3) The decoupling status of socioeconomic factors and NPP is improving, and the degree of decoupling in 2010–2019 was higher than that in 2000–2010. In conclusion, as the first forest urban agglomeration in China, the PRD has shown a good implementation of carbon sequestration policies, which can provide a reference for the coordinated development of urbanization and carbon sequestration.

Background/Aims: Macrophages exhibit dynamic pro-inflammatory and resolving activities in myocardial infarction. The present study investigated whether caffeic acid derivatives could induce macrophage polarization towards a resolving M2 phenotype against myocardial infarction injury. Methods: Western blotting, RT-PCR and flow cytometry techniques are used to evaluate macrophage biomarkers expression and specific proteins in the related signaling pathways. Ligation of the left anterior descending artery induced rat model of myocardial infarction, TTC staining and immunohistochemical staining are used to examine cardioprotective effect in vivo. Results: We initially evaluated the anti-inflammatory activity of four caffeic acid derivatives including n-propargyl caffeamide (PACA) in RAW264.7 macrophages. As result, PACA selectively suppressed the up-regulation of inducible nitric oxide synthase (iNOS) over cyclooxygenase-2 (COX-2) in lipopolysaccharides (LPS)-stimulated cells. We subsequently examined the effects of PACA on macrophage polarization by determining macrophage biomarkers. PACA down-regulated M1 biomarkers (e.g., iNOS, tumor necrosis factor-α (TNF-α), C-X-C motif chemokine 10 (CXCL10) and CD80) but up-regulated M2 biomarkers (e.g., Ym-1 and arginase-1). On the other hand, PACA suppressed macrophage chemotaxis while enhanced macrophage phagocytosis. We further examined the in vivo cardioprotective activity of PACA in a rat model of myocardial infarction. Following ligation of the left anterior descending artery, PACA treatment effectively reduced myocardial infarct size and promoted macrophage M2 polarization. We finally explored the underlying mechanisms. We found that PACA attenuated LPS-induced NF-ĸB activation while activated Nrf2/HO-1 pathway. HO-1 inhibitor SnPP attenuated the effects of PACA on iNOS expression in LPS-challenged macrophages, possibly by regulating the cross-talk between HO-1 and NF-ĸB pathways. Conclusions: The key finding from the present study was that PACA promoted timely switch of macrophage phenotypes from pro-inflammatory M1 to resolving M2. We anticipate that PACA is a potential drug candidate for the resolution of inflammation and cardiac repair after myocardial infarction.

Abstract Scaling up atmospheric pressure glow discharge to large volume is desirable for low-temperature plasma applications. In this paper, an approach to generate a glow discharge in a planar shape with a fairly large volume is proposed in atmospheric pressure air through utilizing a direct-current excited rod array electrode. The planar discharge with a wide gap originates from three discrete discharges with a narrow gap. Based on electrical method and optical emission spectroscopy, it is found that gap voltage increases, while discharge current remains constant with increasing the gap width. Temperature and electron density of the discharge decrease with increasing the gap width.

Transition from a Townsend mode to a normal glow mode has been reported in the literature for uniform dielectric barrier discharge (DBD) at atmospheric pressure. In this paper, through a one-dimensional fluid model, more modes of uniform DBD in helium and transitions between them are found with varying rising time of a saw-tooth voltage. The results indicate that a positive discharge initiates at the positive-slope voltage phase, whose pulse duration decreases, while the peak value increases with decreasing rising time. During this process, a negative discharge initiating at the negative-slope voltage phase keeps weakening to almost zero current. The predominant positive discharge is then investigated through analyzing spatial distributions of electron density, ion density, and electric field at the peak current moment. In combination with the voltage-current curve, discharge modes of DBD are revealed to transit from a Townsend, a normal glow, to an abnormal glow with decreasing voltage rising time. These mode transitions are qualitatively explained by analyzing the gap voltage and electron density averaged in the gap just before discharge initiation. The results also suggest that by reducing the rising time or increasing voltage amplitude, DBD is prone to operate in the abnormal glow mode. Moreover, DBD in the abnormal glow mode has an increasing peak current and a decreasing pulse duration with increasing voltage amplitude. Finally, the critical voltage amplitude is given as a function of voltage rising time for the mode transitions from the Townsend to the normal glow and the normal glow to the abnormal glow.

Positron emission tomography (PET) imaging serves as one of the most competent methods for the diagnosis of various malignancies, such as lung tumor. However, with an elevation in the utilization of PET scan, radiologists are overburdened considerably. Consequently, a new approach of “computer-aided diagnosis” is being contemplated to curtail the heavy workloads. In this article, we propose a multiscale Mask Region–Based Convolutional Neural Network (Mask R-CNN)–based method that uses PET imaging for the detection of lung tumor. First, we produced 3 models of Mask R-CNN for lung tumor candidate detection. These 3 models were generated by fine-tuning the Mask R-CNN using certain training data that consisted of images from 3 different scales. Each of the training data set included 594 slices with lung tumor. These 3 models of Mask R-CNN models were then integrated using weighted voting strategy to diminish the false-positive outcomes. A total of 134 PET slices were employed as test set in this experiment. The precision, recall, and F score values of our proposed method were 0.90, 1, and 0.95, respectively. Experimental results exhibited strong conviction about the effectiveness of this method in detecting lung tumors, along with the capability of identifying a healthy chest pattern and reducing incorrect identification of tumors to a large extent.

Teixobactin is a recently identified antibiotic that shows activity against drug resistant strains of bacteria. Here, the authors report a highly convergent total synthesis of this natural product, with sufficient flexibility to also allow the synthesis of a number of analogues.

Production prediction plays an important role in decision making, development planning, and economic evaluation during the exploration and development period. However, applying traditional methods for production forecasting of newly developed wells in the conglomerate reservoir is restricted by limited historical data, complex fracture propagation, and frequent operational changes. This study proposed a Gated Recurrent Unit (GRU) neural network-based model to achieve batch production forecasting in M conglomerate reservoir of China, which tackles the limitations of traditional decline curve analysis and conventional time-series prediction methods. The model is trained by four features of production rate, tubing pressure (TP), choke size (CS), and shut-in period (SI) from 70 multistage hydraulic fractured horizontal wells. Firstly, a comprehensive data preprocessing is implemented, including excluding unfit wells, data screening, feature selection, partitioning data set, z-score normalization, and format conversion. Then, the four-feature model is compared with the model considering production only, and it is found that with frequent oilfield operations changes, the four-feature model could accurately capture the complex variance pattern of production rate. Further, Random Forest (RF) is employed to optimize the prediction results of GRU. For a fair evaluation, the performance of the proposed model is compared with that of simple Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) neural network. The results show that the proposed approach outperforms the others in prediction accuracy and generalization ability. It is worth mentioning that under the guidance of continuous learning, the GRU model can be updated as soon as more wells become available.

The prevalence of non-alcoholic fatty liver disease (NAFLD), which is developed from hepatic steatosis, is increasing worldwide. However, no specific drugs for NAFLD have been approved yet. To observe the effects of Rho, a fraction from Rhodiola crenulate, on non-alcoholic hepatic steatosis, three mouse models with characteristics of NAFLD were used including high-fat diet (HFD)-induced obesity (DIO) mice, KKAy mice, and HFD combined with tetracycline stimulated Model-T mice. Hepatic lipid accumulation was determined via histopathological analysis and/or hepatic TG determination. The responses to insulin were evaluated by insulin tolerance test (ITT), glucose tolerance test (GTT), and hyperinsulinemic-euglycemic clamp, respectively. The pathways involved in hepatic lipid metabolism were observed via western-blot. Furthermore, the liver microcirculation was observed by inverted microscopy. The HPLC analysis indicated that the main components of Rho were flavan polymers. The results of histopathological analysis showed that Rho could ameliorate hepatic steatosis in DIO, KKAy, and Model-T hepatic steatosis mouse models, respectively. After Rho treatment in DIO mice, insulin resistance was improved with increasing glucose infusion rate (GIR) in hyperinsulinemic-euglycemic clamp, and decreasing areas under the blood glucose-time curve (AUC) in both ITT and GTT; the pathways involved in fatty acid uptake and de novo lipogenesis were both down-regulated, respectively. However, the pathways involved in beta-oxidation and VLDL-export on hepatic steatosis were not changed significantly. The liver microcirculation disturbances were also improved by Rho in DIO mice. These results suggest that Rho is a lead nature product for hepatic steatosis treatment. The mechanism is related to enhancing insulin sensitivity, suppressing fatty acid uptake and inhibiting de novo lipogenesis in liver.

By using fractional calculus and the summation by parts formula in this paper, the asymptotic behaviours of solutions of nonlinear neutral fractional delay pantograph equations with continuous arguments are investigated. The asymptotic estimates of solutions for the equation are obtained, which may imply asymptotic stability of solutions. In the end, a particular case is provided to illustrate the main result and the speed of the convergence of the obtained solutions.

Botulinum neurotoxins (BoNTs), the most potent naturally-occurring neurotoxins known to humans, comprise seven distinct serotypes (BoNT/A-G), each of which exhibits unique substrate specificity. Many methods have been developed for BoNT detection, in particular for BoNT/A, with various complexity and sensitivity, while substrate based FRET assay is considered as the most widely used approach due to its simplicity and sensitivity. In this study, we designed a vesicle-associated membrane protein 2 (VAMP2) based FRET assay based on the understanding of the VAMP2 and light chain/B (LC/B) interactions in our previous studies. The current design constituted the shortest peptide, VAMP2 (63-85), with FRET dyes (EDAN and Dabcyl) labelled at position 76 and 85, respectively, which showed minimal effect on VAMP2 substrate catalysis by LC/B and therefore enhanced the sensitivity of the assay. The FRET peptide, designated as FVP-B, was specific to LC/B, with a detection sensitivity as low as ∼20 pM in 2 h. Importantly, FVP-B showed the potential to be scaled up and used in high throughput screening of LC/B inhibitor. The currently developed FRET assay is one of the most economic and rapid FRET assays for LC/B detection.