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Clubroot (Plasmodiophora brassicae) is an important soilborne disease that causes severe damage to cruciferous crops in China. This study aims to compare the differences in chemical properties and microbiomes between healthy and clubroot-diseased soils. To reveal the difference, we measured soil chemical properties and microbial communities by sequencing 18S and 16S rRNA amplicons. The available potassium in the diseased soils was higher than in the healthy soils. The fungal diversity in the healthy soils was significantly higher than in the diseased soils. Ascomycota and Proteobacteria were the most dominant fungal phylum and bacteria phylum in all soil samples, respectively. Plant-beneficial microorganisms, such as Chaetomium and Sphingomonas, were more abundant in the healthy soils than in the diseased soils. Co-occurrence network analysis found that the healthy soil networks were more complex and stable than the diseased soils. The link number, network density, and clustering coefficient of the healthy soil networks were higher than those of the diseased soil networks. Our results indicate that the microbial community diversity and network structure of the clubroot-diseased soils were different from those of the healthy soils. This study is of great significance in exploring the biological control strategies of clubroot disease.

Advanced hepatocellular carcinoma (HCC) is a formidable public health problem with limited curable treatment options. Axitinib, an oral tyrosine kinase inhibitor, is a potent and selective second-generation inhibitor of vascular endothelial growth factor receptor (VEGFR) 1, 2, and 3. This anti-angiogenic drug was found to have promising activity in various solid tumors, including advanced HCC. At present, however, there is no relevant review article that summarizes the exact roles of axitinib in advanced HCC. In this review, 24 eligible studies (seven studies in the ClinicalTrials, eight experimental studies, and nine clinical trials) were included for further evaluation. The included randomized or single-arm phase II trials indicated that axitinib could not prolong the overall survival compared to the placebo for the treatment of advanced HCC, but improvements in progression free survival and time to tumor progression were observed. Experimental studies showed that the biochemical effects of axitinib in HCC might be regulated by its associated genes and affected signaling cascades (e.g. VEGFR2/PAK1, CYP1A2, CaMKII/ERK, Akt/mTor, and miR-509-3p/PDGFRA). FDA approved sorafenib combined with nivolumab (an inhibitor of PD-1/PD-L1) as the first line regimen for the treatment of advanced HCC. Since both axitinib and sorafenib are tyrosine kinase inhibitors as well as the VEGFR inhibitors, axitinib combined with anti-PDL-1/PD-1 antibodies may also exhibit tremendous potential in anti-tumoral effects for advanced HCC. The present review highlights the current clinical applications and the molecular mechanisms of axitinib in advanced HCC. To move toward clinical applications by combining axitinib and other treatments in advanced HCC, more studies are still warranted in the near future.

Clubroot is one of the most serious soil-borne diseases on crucifer crops worldwide. Seed treatment with biocontrol agents is an effective and eco-friendly way to control clubroot disease. However, there is a big challenge to inoculating the seed with bacterial cells through seed pelleting due to the harsh environment on the seed surface or in the rhizosphere. In this study, a method for microbial seed pelleting was developed to protect pak choi seedlings against clubroot disease. Typically, a biocontrol bacterium, Paenibacillus polymyxa ZF129, was encapsulated by the spray-drying method with gum arabic as wall material, and then pak choi seeds were pelleted with the microencapsulated Paenibacillus polymyxa ZF129 (ZF129m). The morphology, storage stability, and release behavior of ZF129 microcapsules were evaluated. Compared with the naked Paenibacillus polymyxa ZF129 cells, encapsulated ZF129 cells showed higher viability during ambient storage on pak choi seeds. Moreover, ZF129m-pelleted seeds showed higher control efficacy (71.23%) against clubroot disease than that of nonencapsulated ZF129-pelleted seeds (61.64%) in pak choi. Seed pelleting with microencapsulated biocontrol Paenibacillus polymyxa ZF129 proved to be an effective and eco-friendly strategy for the control of clubroot disease in pak choi.

The active distribution network (ADN) shows great potential for use in network restoration services, given its ability to actively control the network topology, distributed generation (DG) outputs, and demand response (DR) resources. However, its utility may be limited due to the geographical dispersion of DG and DR resources when applied to natural disasters such as windstorms, earthquakes, and floods. In addition, the increasing use of renewable energy creates fluctuations and uncertainties, hindering ADNs from realizing reliable energy scheduling during disasters. Mobile energy storage system (MESS) fleets can be used to economically provide flexible emergency power supply for network restoration services. MESSs can also hedge against load and DG output forecast risks. This article proposes a novel coordinated network reconfiguration and MESS fleets dispatching model considering the uncertainty in DG output and load forecasts to increase the resilience of the ADN after disasters. The MESS traveling strategy is modeled by an extended transit delay model. Then, a novel deterministic network restoration model incorporating the MESS, stationary energy storage system, DG, DR, and network reconfiguration is proposed and programmed using mixed-integer linear programming. Then, an ellipsoidal uncertainty set is employed to describe the uncertainty of load and DG output forecasts, and a robust network restoration model is proposed based on the deterministic one. The proposed deterministic and robust network restoration models are verified on a 59-bus rural distribution system in China.

Accurate prediction of machine RUL plays a crucial role in reducing human casualties and economic losses, which is of significance. The ability to handle spatiotemporal information contributes to improving the prediction performance of machine RUL. However, most existing models for spatiotemporal information processing are not only complex in structure but also lack adaptive feature extraction capabilities. Therefore, a lightweight operator with adaptive spatiotemporal information extraction ability named Involution GRU (Inv-GRU) is proposed for aero-engine RUL prediction. Involution, the adaptive feature extraction operator, is replaced by the information connection in the gated recurrent unit to achieve adaptively spatiotemporal information extraction and reduce the parameters. Thus, Inv-GRU can well extract the degradation information of the aero-engine. Then, for the RUL prediction task, the Inv-GRU-based deep learning (DL) framework is firstly constructed, where features extracted by Inv-GRU and several human-made features are separately processed to generate health indicators (HIs) from multi-raw data of aero-engines. Finally, fully connected layers are adopted to reduce the dimension and regress RUL based on the generated HIs. By applying the Inv-GRU-based DL framework to the Commercial Modular Aero Propulsion System Simulation (C-MAPSS) datasets, successful predictions of aero-engines RUL have been achieved. Quantitative comparative experiments have demonstrated the advantage of the proposed method over other approaches in terms of both RUL prediction accuracy and computational burden.

Maintaining the frequency of a power system close to its nominal value (50 Hz or 60 Hz) is critical, which comes mainly from generators and flexible loads in traditional power systems. Direct load control (DLC) is a method to control controllable loads for power system optimization. In general, it is used to reduce or shave peak demand. Nonetheless, DLC also can be used to provide frequency control services. Domestic electric water heater (DEWH) is an important kind of controllable load, which takes a high percentage of domestic electric power consumption and has a large thermal energy storage capacity. Hence, DEWH can be a prime candidate for DLC. This study proposes a framework to provide frequency control service with DEWHs. A virtual battery pack system (VBPS) is introduced to be equivalent to the capacity of DEWHs, and a series of measurable indicators are proposed to show the capacity of the VBPS when providing frequency control services. An adaptive criterion is applied to classify controllable DEWHs, which helps to maintain end-user comfort. The performances of the proposed frequency control method during normal and contingency conditions are verified through case studies in CYME.

ABSTRACT In filamentous fungi, 1,8-dihydroxynaphthalene (DHN) melanin is a major component of the extracellular matrix, endowing fungi with environmental tolerance and some pathogenic species with pathogenicity. However, the subcellular location of the melanin biosynthesis pathway components remains obscure. Using the gray mold pathogen Botrytis cinerea, the DHN melanin intermediate scytalone was characterized via phenotypic and chemical analysis of mutants, and the key enzymes participating in melanin synthesis were fused with fluorescent proteins to observe their subcellular localizations. The Δbcscd1 mutant accumulated scytalone in the culture filtrate rather than in mycelium. Excessive scytalone appears to be self-inhibitory to the fungus, leading to repressed sclerotial germination and sporulation in the Δbcscd1 mutant. The BcBRN1/2 enzymes responsible for synthesizing scytalone were localized in endosomes and found to be trafficked to the cell surface, accompanied by the accumulation of BcSCD1 proteins in the cell wall. In contrast, the early-stage melanin synthesis enzymes BcPKS12/13 and BcYGH1 were localized in peroxisomes. Taken together, the results of this study revealed the subcellular distribution of melanin biosynthetic enzymes in B. cinerea, indicating that the encapsulation and externalization of the melanin synthetic enzymes need to be delicately orchestrated to ensure enzymatic efficiency and protect itself from the adverse effect of the toxic intermediate metabolite. IMPORTANCE The devastating gray mold pathogen Botrytis cinerea propagates via melanized conidia and sclerotia. This study reveals that the sclerotial germination of B. cinerea is differentially affected by different enzymes in the melanin synthesis pathway. Using gene knockout mutants and chemical analysis, we found that excessive accumulation of the melanin intermediate scytalone is inhibitory to B. cinerea. Subcellular localization analysis of the melanin synthesis enzymes of B. cinerea suggested two-stage partitioning of the melanogenesis pathway: the intracellular stage involves the steps until the intermediate scytalone was translocated to the cell surface, whereas the extracellular stage comprises all the steps occurring in the wall from scytalone to final melanin formation. These strategies make the fungus avert self-poisoning during melanin production. This study opens avenues for better understanding the mechanisms of secondary metabolite production in filamentous fungi.

An analytical method was developed to quantitatively determine residual monomers, namely, lactide (LA) and ε-caprolactone (CL), in poly(lactide-co-ε-caprolactone) (PLCL) using an internal-standard method of gas chromatography (GC). PLCL and diphenyl ether (DPE) as an internal standard were initially dissolved in dichloromethane (DCM), and then PLCL was precipitated in cyclohexane. The residual LA and CL monomers in PLCL, as well as DPE, were extracted into cyclohexane from the polymer solution. The resulting solution was directly injected into a GC system. This method was practical for measuring the residual LA and CL contents in PLCL. The relative standard deviation (RSD) (n = 5) denoting the repeatability of this method was less than 5.6% and 4.3% for the LA and CL measurements, respectively, indicating that the method was sufficiently precise. The recovery rate of standard addition was 96.5%–101.5% and 98.4%–104.2% for the determination of LA and CL in PLCL, respectively. The RSD of the recovery of standard addition (n = 5) was not more than 2.0%, indicating that the method was sufficiently accurate.

Summary: Phosphoglycerate dehydrogenase (PHGDH) is the first enzyme in the serine synthesis pathway in which it is also the rate-limiting enzyme. It is significantly upregulated in many cancers, especially breast cancer. However, the posttranslational mechanism of PHGDH upregulation in breast cancer is unknown. In this study, we find that RNF5, an E3 ubiquitin ligase, is essential for the degradation of PHGDH protein. PHGDH is degraded by RNF5 to prevent the proliferation of breast cancer cells. The acetylation of PHGDH at K58 is able to disrupt the interaction of RNF5-PHGDH and promote the proliferation of breast cancer cells. Tip60 and SIRT2 regulate the reversible acetylation modification of PHGDH in response to glucose alteration. Moreover, PHGDH is significantly upregulated in samples of human breast cancer and is associated with decreased RNF5 expression. This implies a potential therapeutic target through the interference interaction of PHGDH-RNF5 to degrade PHGDH in breast cancer.

Only a single drug against schistosomiasis is currently available and new drug development is urgently required but very few drug targets have been validated and characterised. However, regulatory systems including cyclic nucleotide metabolism are emerging as primary candidates for drug discovery. Here, we report the cloning of ten cyclic nucleotide phosphodiesterase (PDE) genes of S. mansoni, out of a total of 11 identified in its genome. We classify these PDEs by homology to human PDEs. Male worms displayed higher expression levels for all PDEs, in mature and juvenile worms, and schistosomula. Several functional complementation approaches were used to characterise these genes. We constructed a Trypanosoma brucei cell line in which expression of a cAMP-degrading PDE complements the deletion of TbrPDEB1/B2. Inhibitor screens of these cells expressing only either SmPDE4A, TbrPDEB1 or TbrPDEB2, identified highly potent inhibitors of the S. mansoni enzyme that elevated the cellular cAMP concentration. We further expressed most of the cloned SmPDEs in two pde1Δ/pde2Δ strains of Saccharomyces cerevisiae and some also in a specialised strain of Schizosacharomyces pombe. Five PDEs, SmPDE1, SmPDE4A, SmPDE8, SmPDE9A and SmPDE11 successfully complemented the S. cerevisiae strains, and SmPDE7var also complemented to a lesser degree, in liquid culture. SmPDE4A, SmPDE8 and SmPDE11 were further assessed in S. pombe for hydrolysis of cAMP and cGMP; SmPDE11 displayed considerable preferrence for cGMP over cAMP. These results and tools enable the pursuit of a rigorous drug discovery program based on inhibitors of S. mansoni PDEs.

Genetic markers in forensic DNA typing experienced the variable number of tandem repeats （VNTR） sequences and the short tandem repeats （STR） sequences. With the emerge of sequencing technology, the third generation of genetic markers were found out, which usually have two alleles including single nucleotide polymorphism （SNP） and insertion/deletion （InDel）, also known as biallelic genetic markers. Because of the insertions or deletions of DNA fragments, InDel genetic marker reveals DNA fragment length polymorphism and widely distributes across the whole genome. InDel genetic marker is numerous and has the characteristics of STR and SNP genetic markers, which has been applied in the fields of genetics and anthropology. This review focuses on the research progress of InDel genetic marker in forensic science, aiming to review and summarize the main research findings in recent years and provide clues for future researches.

Correct identifying analog circuit incipient faults is useful to the circuit's health monitoring, and yet it is very hard. In this paper, an analog circuit incipient fault diagnosis method using deep belief network (DBN) based features extraction is presented. In the diagnosis scheme, time responses of analog circuits are measured, and then features are extracted by using the DBN method. Meanwhile, the learning rates of DBN are produced by using quantum-behaved particle swarm optimization (QPSO) algorithm, which is beneficial to optimizing the structure parameters of DBN. Afterward, a support vector machine (SVM) based incipient fault diagnosis model is constructed on basis of the extracted features to classify incipient faulty components, where the regularization parameter and width factor of SVM are yielded by using the QPSO algorithm. Sallen-Key bandpass filter and four-op-amp biquad high pass filter incipient fault diagnosis simulations are conducted to demonstrate the proposed diagnosis method, and comparisons verify that the proposed diagnosis method can produce higher diagnosis accuracy than other typical analog circuit fault diagnosis methods.

Lithium-ion batteries are crucial to many types of electric equipments. Hence, lithium-ion battery capacity prognostic is significantly important, and it is yet very hard for the measured battery data that are regularly polluted by miscellaneous noises. In this paper, a battery capacity prognostic approach using the empirical mode decomposition (EMD) denoising method and multiple kernel relevance vector machine (MKRVM) approach is presented. The EMD denoising method is employed to process the measured capacity data to produce noise-free capacity data. The battery capacity prediction model using MKRVM is constructed based on the denoised capacity data. The MKRVM's kernel keeps diversity by using multiple heterogeneous kernel learning method. Meanwhile, sparse weights of basic kernel functions are yielded by using particle swarm optimization (PSO) algorithm. The measured battery capacity data are used to demonstrate the effect of EMD denoising method, and battery capacity prediction experiments reveal that the proposed MKRVM approach can predict the battery's future capacity precisely.

This paper provides an experimental investigation on the cracking process and residual mechanical properties of concrete after exposure to elevated temperatures. A total of 36 standard concrete prism specimens were tested after exposure to high temperatures of up to 600 °C. The failure modes, cracking process, residual mechanical properties, deformation characteristics and the strain distribution on the surface during the loading procedure were presented. The influences of exposure temperature and water−cement ratio (w/c) were interpreted. The digital image correlation (DIC) method was applied to quantitatively and visually characterize the development of cracking and relative displacement on the concrete surface. The findings suggest that the residual compressive strength and elastic modulus of the concrete decreases gradually with the increasing temperature, especially in the specimens with lower w/c ratio. The DIC technique provides an effective means to measure very precise and detailed information, including the crack opening and distribution of strain on the concrete surface.