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The deformation of open-pit mine slopes is influenced by various factors such as geological structure, hydrogeological conditions, mining activities, etc., making the prediction model complex. It is difficult to accurately capture all influencing factors. At present, a large number of monitoring devices are deployed around the slope of open-pit mines to record real-time displacement data of open-pit mine slopes. The data has the features of high-dimensional, temporal correlation, and nonlinear. Traditional slope stability analysis methods cannot effectively predict slope deformation without knowing other conditions and only data, it is necessary to use a data-based model to predict the displacement data of open-pit mine slopes in advance for slope stability analysis. In order to solve the above problems, a deformation prediction model for open-pit mine slopes based on the golden jackal optimized multilayer perception machine (GJO-MLP) is proposed. Each agent in GJO is independent of each other and can accelerate the training process of optimizing MLP through parallel computing. GJO can combine the nonlinear modeling and feature extraction capabilities of MLP, making the optimized MLP more advantageous in dealing with complex problems. To test the feasibility and effectiveness of GJO-MLP, GJO-MLP is compared and analyzed with ant colony algorithm optimization based MLP (ACO-MLP), gravity search algorithm optimization based MLP (GSA-MLP), and differential evolution algorithm optimization based MLP (DE-MLP). The simulation results on six datasets show that under the same experimental conditions, GJO-MLP shows better optimization performance compared to the other three algorithms. The slope deformation prediction model based on GJO-MLP is applied to the slope deformation prediction of Baorixile open-pit mine and Huapingzi slope deformation prediction. The results show that under the same conditions, compared to the other three algorithms, the slope deformation prediction model based on GJO-MLP not only show better predictive performance in predicting slope deformation data, but also has better feasibility and robustness.

In order to solve the problem of unmanned truck transportation scheduling in open-pit mines, the minimum sum of fuel cost, fixed start-up cost, breakdown maintenance cost, and network base station construction and maintenance cost are taken as the objective functions. The mining amount of mining station, crushing amount of crushing station, truck number and truck transportation workload are taken as the constraint conditions. The optimization model of unmanned truck transportation scheduling in open-pit mines is established. To solve the problem of imbalance between global exploration and local mining ability in the tunicate swarm algorithm, an improved tunicate swarm algorithm (ITSA) based on Singer mapping and adaptive updating mechanism of parameter position is proposed. And it is applied to solve the optimization model of unmanned truck transportation scheduling in open-pit mines. Singer mapping is introduced to enhance the distribution of the initial tunicate swarm in the solution space and accelerate the compression of the solution space, thus improving the convergence speed of the algorithm. Through the adaptive updating mechanism of parameter position, the positions of the tunicate and the optimal tunicate are adjusted to increase the search range of the solution space. Therefore, the algorithm jumps out of the local optimization. The simulation results show that ITSA has better convergence precision, convergence speed and stability compared with the four population intelligent optimization algorithms of grey wolf optimization algorithm (GWO), whale optimization algorithm (WOA), atom search optimization algorithm (ASO) and tunicate swarm algorithm (TSA). In the unimodal benchmark function, the evaluation indexes of ITSA are far better than those of the other four algorithms, which shows that ITSA has better local mining capacity. In the multi-peak benchmark function, the evaluation indexes of ITSA show better optimization performance, which indicates that ITSA has better global exploration performance. The practical application scenario verification shows that ITSA has faster convergence speed and higher convergence precision when used for solving the unmanned truck transportation scheduling optimization model. And ITSA reduces the truck transportation cost and transportation distance.

Peanut leaf spot is a worldwide disease whose prevalence poses a major threat to peanut yield and quality, and accurate prediction models are urgently needed for timely disease management. In this study, we proposed a novel peanut leaf spot prediction method based on an improved long short-term memory (LSTM) model and multi-year meteorological data combined with disease survey records. Our method employed a combination of convolutional neural networks (CNNs) and LSTMs to capture spatial–temporal patterns from the data and improve the model's ability to recognize dynamic features of the disease. In addition, we introduced a Squeeze-and-Excitation (SE) Network attention mechanism module to enhance model performance by focusing on key features. Through several hyper-parameter optimization adjustments, we identified a peanut leaf spot disease condition index prediction model with a learning rate of 0.001, a number of cycles (Epoch) of 800, and an optimizer of Adma. The results showed that the integrated model demonstrated excellent prediction ability, obtaining an RMSE of 0.063 and an R 2 of 0.951, which reduced the RMSE by 0.253 and 0.204, and raised the R 2 by 0.155 and 0.122, respectively, compared to the single CNN and LSTM. Predicting the occurrence and severity of peanut leaf spot disease based on the meteorological conditions and neural networks is feasible and valuable to help growers make accurate management decisions and reduce disease impacts through optimal fungicide application timing. [ABSTRACT FROM AUTHOR]

There are environmental problems such as pollutant emission in the construction and service of road asphalt pavement. In order to explore the hazards of road asphalt to the environment, the types of pollutants from the construction and use of road asphalt pavement are analyzed. The various harmful components of pavement asphalt materials and their influencing factors are discussed. The corresponding pollution inhibition measures are introduced. The existing research work of asphalt pavement pollution is analyzed and suggestions for future research are proposed.

Pore-forming toxins (PFTs) are effective tools for pathogens infection. By disrupting epithelial barriers and killing immune cells, PFTs promotes the colonization and reproduction of pathogenic microorganisms in their host. In turn, the host triggers defense responses, such as endocytosis, exocytosis, or autophagy. Bacillus thuringiensis (Bt) bacteria produce PFT, known as crystal proteins (Cry) which damage the intestinal cells of insects or nematodes, eventually killing them. In insects, aminopeptidase N (APN) has been shown to act as an important receptor for Cry toxins. Here, using the nematode Caenorhabditis elegans as model, an extensive screening of APN gene family was performed to analyze the potential role of these proteins in the mode of action of Cry5Ba against the nematode. We found that one APN, MNP-1, participate in the toxin defense response, since the mnp-1(ok2434) mutant showed a Cry5Ba hypersensitive phenotype. Gene expression analysis in mnp-1(ok2434) mutant revealed the involvement of two protease genes, F19C6.4 and R03G8.6, that participate in Cry5Ba degradation. Finally, analysis of the transduction pathway involved in F19C6.4 and R03G8.6 expression revealed that upon Cry5Ba exposure, the worms up regulated both protease genes through the activation of the FOXO transcription factor DAF-16, which was translocated into the nucleus. The nuclear location of DAF-16 was found to be dependent on mnp-1 under Cry5Ba treatment. Our work provides evidence of new host responses against PFTs produced by an enteric pathogenic bacterium, resulting in activation of host intestinal proteases that degrade the PFT in the intestine. Author summary: Pore-forming toxins (PFTs) have a crucial role in the pathogenesis of microbial pathogens. Meanwhile, hosts mediate different strategies to resist PFTs at the cellular level, such as endocytosis, exocytosis, autophagy, and MAPK or inflammasome signaling pathways. Here we show that the nematode Caenorhabditis elegans respond to PFTs inducing their proteolysis by up regulating intestinal proteases through the induction of FOXO transcription factor DAF-16 that showed nuclear location. Our results indicate that animals not only trigger defense mechanisms after PFTs intoxication at the cellular level, but also could eliminate PFTs in the intestine lumen, an effective additional strategy for animals to resist PFTs, especially those produced by enteric bacterial pathogens. Since, the FOXO transcription factor DAF-16 is conserved from nematodes to mammals, it is possible that the degradation of PFT by modulating intestinal proteases may be a common defense strategy against bacterial infections. [ABSTRACT FROM AUTHOR]

Species of Fusarium have significant agro-economical and human health-related impact by infecting diverse crop plants and synthesizing diverse mycotoxins. Here, we investigated interactions of grain-feeding Tenebrio molitor larvae with four grain-colonizing Fusarium species on wheat kernels. Since numerous metabolites produced by Fusarium spp. are toxic to insects, we tested the hypothesis that the insect senses and avoids Fusarium-colonized grains. We found that only kernels colonized with F. avenaceum or Beauveria bassiana (an insect-pathogenic fungal control) were avoided by the larvae as expected. Kernels colonized with F. proliferatum, F. poae or F. culmorum attracted T. molitor larvae significantly more than control kernels. The avoidance/preference correlated with larval feeding behaviors and weight gain. Interestingly, larvae that had consumed F. proliferatum- or F. poae-colonized kernels had similar survival rates as control. Larvae fed on F. culmorum-, F. avenaceum- or B. bassiana-colonized kernels had elevated mortality rates. HPLC analyses confirmed the following mycotoxins produced by the fungal strains on the kernels: fumonisins, enniatins and beauvericin by F. proliferatum, enniatins and beauvericin by F. poae, enniatins by F. avenaceum, and deoxynivalenol and zearalenone by F. culmorum. Our results indicate that T. molitor larvae have the ability to sense potential survival threats of kernels colonized with F. avenaceum or B. bassiana, but not with F. culmorum. Volatiles potentially along with gustatory cues produced by these fungi may represent survival threat signals for the larvae resulting in their avoidance. Although F. proliferatum or F. poae produced fumonisins, enniatins and beauvericin during kernel colonization, the larvae were able to use those kernels as diet without exhibiting increased mortality. Consumption of F. avenaceum-colonized kernels, however, increased larval mortality; these kernels had higher enniatin levels than F. proliferatum or F. poae-colonized ones suggesting that T. molitor can tolerate or metabolize those toxins. [ABSTRACT FROM AUTHOR]

Species of Fusarium have significant agro-economical and human health-related impact by infecting diverse crop plants and synthesizing diverse mycotoxins. Here, we investigated interactions of grain-feeding Tenebrio molitor larvae with four grain-colonizing Fusarium species on wheat kernels. Since numerous metabolites produced by Fusarium spp. are toxic to insects, we tested the hypothesis that the insect senses and avoids Fusarium-colonized grains. We found that only kernels colonized with F. avenaceum or Beauveria bassiana (an insect-pathogenic fungal control) were avoided by the larvae as expected. Kernels colonized with F. proliferatum, F. poae or F. culmorum attracted T. molitor larvae significantly more than control kernels. The avoidance/preference correlated with larval feeding behaviors and weight gain. Interestingly, larvae that had consumed F. proliferatum- or F. poae-colonized kernels had similar survival rates as control. Larvae fed on F. culmorum-, F. avenaceum- or B. bassiana-colonized kernels had elevated mortality rates. HPLC analyses confirmed the following mycotoxins produced by the fungal strains on the kernels: fumonisins, enniatins and beauvericin by F. proliferatum, enniatins and beauvericin by F. poae, enniatins by F. avenaceum, and deoxynivalenol and zearalenone by F. culmorum. Our results indicate that T. molitor larvae have the ability to sense potential survival threats of kernels colonized with F. avenaceum or B. bassiana, but not with F. culmorum. Volatiles potentially along with gustatory cues produced by these fungi may represent survival threat signals for the larvae resulting in their avoidance. Although F. proliferatum or F. poae produced fumonisins, enniatins and beauvericin during kernel colonization, the larvae were able to use those kernels as diet without exhibiting increased mortality. Consumption of F. avenaceum-colonized kernels, however, increased larval mortality; these kernels had higher enniatin levels than F. proliferatum or F. poae-colonized ones suggesting that T. molitor can tolerate or metabolize those toxins. [ABSTRACT FROM AUTHOR]

Rationale: The transition from acute inflammation to fibrosis following myocardial ischemia‒reperfusion (MIR) significantly affects prognosis. Macrophages play a pivotal role in inflammatory damage and repair after MIR. However, the heterogeneity and transformation mechanisms of macrophages during this transition are not well understood. Methods: In this study, we used single-cell RNA sequencing (scRNA-seq) and mass cytometry to examine murine monocyte-derived macrophages after MIR to investigate macrophage subtypes and their roles in the MIR process. S100a9 -/- mice were used to establish MIR model to clarify the mechanism of alleviating inflammation and fibrosis after MIR. Reinfusion of bone marrow-derived macrophages (BMDMs) after macrophage depletion (MD) in mice subjected to MIR were performed to further examine the role of S100a9 hi macrophages in MIR. Results: We identified a unique subtype of S100a9 hi macrophages that originate from monocytes and are involved in acute inflammation and fibrosis. These S100a9 hi macrophages infiltrate the heart as early as 2 h post-reperfusion and activate the Myd88/NFκB/NLRP3 signaling pathway, amplifying inflammatory responses. As the tissue environment shifts from proinflammatory to reparative, S100a9 activates transforming growth factor-β (Tgf-β)/p-smad3 signaling. This activation not only induces the transformation of myocardial fibroblasts to myofibroblasts but also promotes fibrosis via the macrophage-to-myofibroblast transition (MMT). Targeting S100a9 with a specific inhibitor could effectively mitigate acute inflammatory damage and halt the progression of fibrosis, including MMT. Conclusion: S100a9 hi macrophages are a promising therapeutic target for managing the transition from inflammation to fibrosis after MIR., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)

Peanut (Arachis hypogaea L.) is a widely grown oilseed crop of great agricultural importance worldwide. In July 2022, disease symptoms were observed on peanut roots in Laixi (36º85' N, 120º54' E), Shandong Province, China. About 25% of the plants showed various symptoms, including stem and root rot and blackening, microsclerotia on the stem, yellowing and wilting of leaves, and even death. Twenty diseased plants were collected to confirm the pathogen. Symptomatic roots were cut into small pieces, disinfested with 75% ethanol for 1 min and 0.5% NaClO for 2 min, rinsed three times with sterile water, dried on sterile filter paper, and then spread on potato dextrose agar (PDA) supplemented with 100 μg/mL chloramphenicol and incubated at 25°C in the dark. At the beginning of growth, the fungus formed sparse, white mycelia, which white, then darkened with age and microsclerotia were formed in the medium after 5 days. The mycelium aggregated into black, round to oblong or irregularly shaped microsclerotia 84 to 163 μm long and 54 to 125 μm wide (n=40). These morphological characteristics were consistent with the description of Macrophomina phaseolina (Holliday and Punithalingam, 1970). Molecular identification was performed by sequencing the internal transcribed spacer (ITS) region with ITS1 and ITS4 and translation elongation factor 1-alpha (TEF) with EF1-728F/EF1-986R (Glass and Donaldson 1995) of a representative isolate SXY183. ITS (OR056369) and TEF (OR098356) of SXY183 showed 100% and 97.74% similarity with M. phaseolina (KF951622, KF951997), respectively. Phylogenetic analysis was performed using Neighbor-Joining (NJ) analysis based on the gene sequences of ITS and TEF. The fungus was identified as M. phaseolina based on molecular analysis and morphological characteristics. The pathogenicity of a representative isolate (SXY183) was tested on peanuts under greenhouse conditions. Two-week-old peanut (Huayu No. 9115) seedlings were inoculated with a mycelial plug (8 mm diameter) at the root base of each plant and cultured in a greenhouse (30°C during the day and 25°C at night, a 12-h photoperiod, and 80% RH). Ten plants were inoculated with a plug of non-colonized PDA as a control. Brown lesions were observed on the stem and root of all inoculated seedlings 7 days after inoculation, but not on the control plants. The experiment was repeated three times. M. phaseolina was re-isolated from the symptomatic root and confirmed based on morphological characteristics and DNA sequence analysis of ITS and TEF. M. phaseolina is a soil-borne fungus that is distributed worldwide and has a broad host range. Disease agent has previously been reported on several host plants such as adzuki bean, faba bean, watermelon, Plukenetia volubilis, Atractylodes lancea and Curcuma longa in China (Cai et al., 2020; Sun et al. 2016; Sun et al., 2019; Sun et al., 2020; Wang et al., 2020; Wu et al., 2022). However, this is the first report in which M. phaseolina was found to cause peanut root rot in Shandong Province, China. Our report will provide important information for studying the epidemiology and management of this disease.

In June 2021, a previously unreported leaf blight disease of peanut (Arachis hypogaea) was observed on field-grown peanut (Jinhua19) in Laixi city, Shandong province of China. Approximately 5% of plants showed disease symptoms in the fields we investigated. The symptoms first appeared as yellow round or irregular spots on leaves, and then the spots became brown. As the disease progressed, spots became larger and even converge, which later produced leaf chlorosis and abscission. Symptomatic leaves were cut into small pieces, surface disinfested with 70% ethanol for 30s, 1% NaClO for 60s, rinsed three times in sterile water, dried on sterile filter papers, placed on potato dextrose agar (PDA) media, and incubated at 25°C in darkness. Fungal cultures were initially white, with red pigment, then turned gray, and eventually turned black, and aerial hyphae were dense. Conidia were spherical or slightly ellipsoidal, black, smooth, and 8.6 to 11.5 × 8.7 to 14.5μm (n=50). Morphological characteristics of the isolates matched the description of Nigrospora aurantiaca (Wang et al. 2017). Molecular identification was performed by sequencing beta tubulin gene (TUB) with Bt2a/Bt2b and translation elongation factor 1-alpha (TEF) with EF1-728F/EF1-986R (Wang et al. 2021) of a representative isolate ZHX11. TUB (OK489789) and TEF (OK489790) of ZHX11 obtained 100% (401/401 nucleotides) and 99.64% (279/279 nucleotides) similar to those of N. aurantiaca (MN329935, MN264010), respectively. Alignment was conducted separately for each gene set using Clustal W algorithm implemented in MEGA 7.0 (Kumar et al. 2016), and multi-gene (TUB and TEF) phylogenetic analyses using Neighbor-Joining (NJ) method showed that the isolate was N. aurantiaca. To complete Koch's postulates, nine 2-week-old peanut (Zhonghua 12) seedlings were sprayed with conidia suspensions (106 conidia mL-1 in 0.05% Tween 20 buffer). The same number of seedlings were only treated with 0.05% Tween buffer as controls. The experiment was repeated three times. Plants were incubated in a growth chamber (30°C in the day and 25°C at night, a 12-h photoperiod and 80% RH). Ten days after inoculation, typical symptoms were observed on inoculated leaves but not on the controls. N. aurantiaca was reisolated from the diseased leaves but not from the controls. N. sphaerica was observed on peanut in China (Liu et al. 2020). To our knowledge, this is the first report of N. aurantiaca causing leaf blight on peanut in shandong province, China. These findings will help to develop better preventive measures in accordance with the emergence of the new disease.