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A mechanistic understanding of interactions between atomically thin two-dimensional (2D) transition-metal dichalcogenides (TMDs) and their growth substrates is important for achieving the unidirectional alignment of nuclei and seamless stitching of 2D TMD domains and thus 2D wafers. In this work, we conduct a cross-sectional scanning transmission electron microscopy (STEM) study to investigate the atomic-scale nucleation and early stage growth behaviors of chemical vapor deposited monolayer (ML-) MoS

Purpose: Prognostic markers discovery is a strategy for early diagnosis and individualization therapy for human cancer. In this study, we focus to integrate different methods to identify specific biomarker and elucidate its clinical significance.Experimental Design: A powerful tool named Digital Gene Expression Display online was applied to isolate differentially expressed genes correlated with gastric cancer. Matrix metalloproteinase 11 (MMP11) was selected and confirmed at both mRNA and protein level in 10 cell lines, 123 cases of tumor tissues, and 305 cases of gastric cancer serum specimen by semiquantitative PCR, immunohistochemistry staining, and ELISA techniques, respectively.Results: Our data showed that overexpression of MMP11 at mRNA and protein level was consistently detected in cell lines and primary tumors compared with matched normal tissues. Importantly, serum MMP11 levels were also significantly elevated in gastric cancer patients compared with those of the control subjects (P < 0.001), and the positive expression was well correlated with metastasis in gastric cancer patients (P = 0.009). Furthermore, we have shown that overexpression of MMP11 was associated with the malignant proliferation of AGS cells.Conclusions: Combination of gene expression profiling and specific clinical resource is a promising approach to validate gene expression patterns associated with malignant phenotype. As a secreted protein, MMP11 may play an important role in carcinogenesis and has potential implication as a biomarker for the diagnosis and prognosis of human cancers including gastric cancer.

Purpose: We herein examined whether the single nucleotide polymorphism (SNP) at −2518 of the MCP-1 gene promoter region influences clinical outcomes among nasopharyngeal carcinoma (NPC) patients.Experimental Design: The study population consisted of 411 NPC patients without metastasis at diagnosis. All patients were treated at the Chang Gung Memorial Hospital from March 1994 to November 2004. The MCP-1 SNP−2518 genotype of each patient was determined by TaqMan genotyping kit. Statistical analyses were conducted to compare disease-specific survival (DSS), progression-free survival (PFS), local recurrence-free survival (LRFS), and distant metastasis-free survival (DMFS) of patients according to genotype. MCP-1 expression in tumor biopsies was examined by immunohistochemistry.Results: Among 411 NPC patients, carriers of AA and AG genotypes were prone to distant metastasis than that of GG genotype (hazard ratio, 2.21; P = 0.017, and hazard ratio, 2.23; P = 0.005, for AA and AG genotype, respectively) after initial radiotherapy. No genotype-specific significant difference was found in DSS, PFS, and LRFS. Furthermore, immunohistochemistry revealed that MCP-1 expression level was higher in NPC tumor cells from GG carriers compared with those from AA and AG carriers.Conclusions:MCP-1 SNP−2518 may be a valuable genetic marker for assessing the risk of developing distant metastasis after the radiotherapy in NPC patients. Carriers of A allele may require more aggressive chemotherapy implicating a potential marker for personalized medicine. We speculate that a regulatory SNP may be associated with the distant metastasis of NPC. Validation studies are warranted.

Supplementary Figure S1; Supplementary Materials and Methods; Supplementary Tables S1-S2.

Supplementary Data from Identification of Matrix Metalloproteinase 11 as a Predictive Tumor Marker in Serum Based on Gene Expression Profiling

Supplementary Figure 4B from Activation of DNA Methyltransferase 1 by EBV LMP1 Involves c-Jun NH2-Terminal Kinase Signaling

Supplementary Figure 2 from Activation of DNA Methyltransferase 1 by EBV LMP1 Involves c-Jun NH2-Terminal Kinase Signaling

Supplementary Materials and Methods from Activation of DNA Methyltransferase 1 by EBV LMP1 Involves c-Jun NH2-Terminal Kinase Signaling

Supplementary Figure 1 from Activation of DNA Methyltransferase 1 by EBV LMP1 Involves c-Jun NH2-Terminal Kinase Signaling

Supplementary Figure 3 from Activation of DNA Methyltransferase 1 by EBV LMP1 Involves c-Jun NH2-Terminal Kinase Signaling

Supplementary Figure 5 from Activation of DNA Methyltransferase 1 by EBV LMP1 Involves c-Jun NH2-Terminal Kinase Signaling

EBV latent membrane protein 1 (LMP1) activates cellular DNA methyltransferases, resulting in hypermethylation and silencing of E-cadherin. However, the underlying mechanism remains to be elucidated. In this study, we show that LMP1 directly induces the dnmt1 promoter activity through its COOH-terminal activation region-2 YYD domain. Using (i) LMP1 mutants, (ii) dominant negative mutants c-jun NH2-terminal kinase (JNK)-DN, p38-DN, and constitutive active mutant IκB, as well as (iii) dsRNAs targeting c-Jun, JNK, and tumor necrosis factor receptor–associated death domain protein, and (iv) signal transduction inhibitors, we show that LMP1-mediated DNA methyltransferase-1 (DNMT1) activation involves JNK but not nuclear factor κB and p38/mitogen-activated protein kinase signaling. In addition, LMP1 is unable to activate dnmt1-P1 promoter with activator protein-1 (AP-1) site mutation. Chromatin immunoprecipitation assay results also confirm that LMP1 activates P1 promoter via the JNK-AP-1 pathway. Furthermore, chromatin immunoprecipitation assay data in LMP1-inducible cells disclose that LMP1 induces formation of a transcriptional repression complex, composed of DNMT1 and histone deacetylase, which locates on E-cadherin gene promoter. Treatment with JNK inhibitor, SP600125, prevents the formation of this repression complex. Statistical analyses of the immunohistochemical staining of 32 nasopharyngeal carcinoma (NPC) biopsies show LMP1 expression (18 of 32, 56.25%), DNMT1 expression (31 of 32, 97%), and phospho-c-Jun (27 of 32, 84.38%), suggesting that overexpression of these proteins is observed in NPC tumor. Overall, these results support a mechanistic link between JNK-AP-1 signaling and DNA methylation induced by the EBV oncogene product LMP1. (Cancer Res 2006; 66(24): 11668-76)

PurposeThe purpose of this paper is to propose a fractional order optimization method based on perturbation bound and gamma function of a DGM(r,1).Design/methodology/approachBy analyzing and minimizing perturbation bound, the sub-optimal solution on fractional order interval is obtained through offline solving without iterative calculation. By this method, an optimized fractional order non-equidistant ROGM (OFONEROGM) is applied in fitting and prediction water quality parameters for a surface water pollution monitoring system.FindingsThis method can narrow fractional order interval in this work. In a surface water pollution monitoring system, the fitting and prediction performances of OFONEROGM are demonstrated comparing with integer order non-equidistant ROGM (IONEROGM).Originality/valueA method of offline solving the sub-optimal solution on fractional order interval is proposed. It can narrow the optimized fractional order range of NEROGM without iterative calculation. A large number of calculations are eliminated. Besides that, optimized fractional order interval is only related to the number of original data, and convenient for practical application. In this work, an OFONEROGM is modeled for predicting water quality trend for preventing water pollution or stealing sewage discharge. It will provide guiding significance in water quality parameter fitting and predicting for water environment management.

Abiotic and biotic environments influence a myriad of plant-related processes, including growth, development, and the establishment and maintenance of interaction(s) with microbes. As a driver of this signaling between plants and microbes, the role of plant hormones in both surveillance and signaling has emerged as a point of intersection between plant-abiotic and -biotic responses. In the current study, we elucidate a role for NON-RACE-SPECIFIC DISEASE RESISTANCE1 (NDR1) by exploiting effector-triggered immunity (ETI) to define the regulation of plant host immunity in response to both pathogen infection and elevated temperature. We generated time-series RNA sequencing data of WT Col-0, a NDR1 overexpression line, as well as ndr1 and ics1-2 mutant plants under elevated temperature. Not surprisingly, the NDR1-overexpression line showed genotype-specific gene expression changes related to defense response and immune system function. Interestingly, overexpression of NDR1 revealed a role for NDR1 in immune system function; specifically, we describe a mechanism that intersects with Pseudomonas syringae, type-III effector translocation, R-protein signaling complex stabilization, and sustained levels of SA at elevated temperature during ETI. The results described herein support a role for NDR1 in maintaining cell signaling during simultaneous exposure to elevated temperature and avirulent pathogen stressors.One-sentence summaryNDR1 is required for Pst-AvrRpt2 triggered ETI at elevated temperature.

Phosphorus-carbon anode materials for alkali-metal ion storage in rechargeable batteries can simultaneously achieve high-energy density and fast charging. The P-C-bonded structure in the phosphorus-carbon materials has been observed and acknowledged to be a critical structural feature that renders improved cycling stability and rate performance. However, the underlying mechanisms, especially the role played by P-C bonds, remain elusive. By combining computational simulations and spectroscopic characterizations, we reveal that the stability of P-C bonds is critical to the electrochemical performance. In the discharge process, P-P bonds are fragile, while the bonding state of the P-C bonds is almost unchanged since electrons were mainly received by the P atoms to form lone pairs. The preserved P-C clusters can effectively serve as a reunion center for the recovery of P-P bonds in the recharging process, leading to a moderate energy change and improved cycling reversibility and structural stability of the phosphorous for electrochemical energy storage.

In this study, we focus on the quality of street space which has attracted high attentions. We discover associations between the quality of street space and built environment attributes through an ordered logistic model using massive street view pictures (SVPs) and data on street location, form, function and attributes. Before ascertain which built environment factors influence the quality of street space, we checked the concordance of the experts’ scores, as well as correlations between different dimensions through Kappa analysis and drew the distribution map of street space quality.We found that the value of intersection over union is 85.61% for scoring the street space quality by different people. The spatial quality of more than 75% streets are in the middle level with no obvious polarisation observed in the central area of Qingdao. In addition, for street quality index, all variables are statistically significant. The sequence is as follows: near-line rate > D/H ratio > slope > length of street > distance to administrative center > POIs diversity. The D/H ratio, near-line rate, slope length of street, distance to administrative center and POIs diversity have various associations on every dimension of street quality. They can prove useful for drafting more appropriate policy measures aimed at improving street quality.

The eukaryotic cytoskeleton plays essential roles in cell signaling and trafficking, broadly associated with immunity and diseases in humans and plants. To date, most studies describing cytoskeleton dynamics and function rely on qualitative/quantitative analyses of cytoskeletal images. While state-of-the-art, these approaches face general challenges: the diversity among filaments causes considerable inaccuracy, and the widely adopted image projection leads to bias and information loss. To solve these issues, we developed the Implicit Laplacian of Enhanced Edge (ILEE), an unguided, high-performance approach for 2D/3D-based quantification of cytoskeletal status and organization. Using ILEE, we constructed a Python library to enable automated cytoskeletal image analysis, providing biologically interpretable indices measuring the density, bundling, segmentation, branching, and directionality of the cytoskeleton. Our data demonstrated that ILEE resolves the defects of traditional approaches, enables the detection of novel cytoskeletal features, and yields data with superior accuracy, stability, and robustness. The ILEE toolbox is available for public use through PyPI and Google Colab.

The randomness and volatility of large-scale clean energy output represented by wind power and photovoltaic lead to difficulties in grid connection. The problems of abandoned wind, light, and water become increasingly prominent. The adjustment capacity of traditional thermal power is limited and it is difficult to ensure the consumption of high proportion clean energy. On this basis, the marginal benefit hedging rule in economics is introduced into the hydropower and photovoltaic joint operation system in this paper. A two-stage spatio-temporal hedging strategy is designed to solve the spatio-temporal conflict problem in the hydropower and photovoltaic joint system. The multi-objective joint dispatching model of hydropower and photovoltaic system considering system benefits, risks, and stability is established, which can be solved by a MOEA/D-GABS algorithm with selection strategy. The joint system scheduling schemes under different schemes are analyzed by case. The results demonstrate that, compared with the traditional multi-objective decision-making scheme, the flood control risk in each period of the reservoir in the proposed method is controlled to be no more than 1.63 × 10−3 (the flood control standard corresponding to the 50-year flood control risk is 0.006); the flood limit water level of the reservoir is increased from 583.00 m to 583.70 m, which improves the benefit of the reservoir; and the water utilization rate is effectively improved. On the other hand, compared with the traditional scheme, the proposed method reduces the peak valley difference of the combined system by 50.67% and 59.68% in typical sunny and cloudy scenarios, respectively, which greatly reduces the uncertainty of photovoltaic output, and the stability of the combined system is improved. It is shown that the proposed method can be used to guide the economic dispatch of a complementary system with hydropower as the regulating energy.

The origin of the herringbone reconstruction on Au(111) surface has never been explained properly at the atomic level because the large periodic length (~30 nm) does not allow ab initio simulations of the system and because of the lack of highly accurate empirical force field. We trained a machine learning force field with high accuracy to explore this reconstruction. Our study shows that the lattice deformation in Au deeper layers, which allows the effective relaxation of the densified and anisotropic top layer lattice, is critical for the herringbone reconstruction. The herringbone reconstruction is energetically more favorable than the stripe reconstruction only if the slab thickness exceeds 12 atomic layers. Furthermore, we reveal the high stability of herringbone reconstruction at high temperatures and that a slight strain of about ±0.2% can induce a transition from the herringbone pattern to the stripe pattern, and both agree well with the experimental observations.

Pattern-triggered immunity and effector-triggered immunity are two primary forms of innate immunity in land plants. The molecular components and connecting nodes of pattern-triggered immunity and effector-triggered immunity are not fully understood. Here, we report that the Arabidopsis calcium-dependent protein kinase CPK3 is a key regulator of both pattern-triggered immunity and effector-triggered immunity. In vitro and in vivo phosphorylation assays, coupled with genetic and cell biology-based analyses, show that actin-depolymerization factor 4 (ADF4) is a physiological substrate of CPK3, and that phosphorylation of ADF4 by CPK3 governs actin cytoskeletal organization associated with pattern-triggered immunity. CPK3 regulates stomatal closure induced by flg22 and is required for resistance to Pst DC3000. Our data further demonstrates that CPK3 is required for resistance to Pst DC3000 carrying the effector AvrPphB. These results suggest that CPK3 is a missing link between cytoskeleton organization, pattern-triggered immunity and effector-triggered immunity., Remodelling of the actin cytoskeleton occurs during plant immune responses to pathogens. Here Lu et al. show that this process requires the calcium-dependent kinase CPK3 which phosphorylates actin depolymerizing factor 4 and is required for both PAMP and effector-triggered immunity in Arabidopsis.

High-temperature reactions widely exist in nature. However, they are difficult to characterize either experimentally or computationally. The minimum energy path (MEP) model routinely used in comput...

The accuracy of correlation modeling for multiple wind farms will directly affect the assessment results of absorption capacity in electric utilities. Due to the rapid increase in installed capacity of wind power in recent years, there are often multiple wind farms with complex correlations in a region, and traditional correlation models are inaccurate and highly computational. In order to enhance the accuracy of correlation modeling for multiple wind farms, this paper combines the piecewise cloud representation and regular vine (R-vine) copulas for classification modeling purposes. The piecewise cloud representation is used to divide the multiple wind farms’ data into different categories, and the correlation models of different categories are established based on the R-vine copulas. A case of the SCADA system record data of 6 wind farms in Northwest China has been adopted to evaluate the effectiveness compared with its competitors. Case studies have demonstrated that the proposed method not only has good performances on modeling the correlation better than the traditional method but also has strong robustness, especially in the case that the correlation of different wind farms is inconsistent. Most importantly, this model is able to extract the correlations of different features in multiple wind farms’ data and then targeted modeling.

Phase transformation lies at the heart of materials science because it allows for the control of structural phases of solids with desired properties. It has long been a challenge to manipulate phase transformations in crystals at the nanoscale with designed interfaces and compositions. Here in situ electron microscopy is employed to fabricate novel 2D phases with different stoichiometries in monolayer MoS

To control graphene growth on copper surfaces, we must understand the underlying growth mechanisms. Unfortunately, most high-resolution experimental characterization methods are not applicable under typical growth conditions, which makes theoretical simulations especially important in graphene growth mechanism studies. In this Feature Article, recent theoretical efforts in understanding graphene growth on copper surfaces are summarized. First-principles calculations indicate that methane decomposition on copper surfaces is very difficult. In contrast, dissociative adsorption of H2 is exothermic and H adatom can reach an equilibrium with gas-phase hydrogen quickly. Although thermodynamic analysis is useful in estimating the concentrations of different CxHy species on the surface, reliable steady-state concentrations can only be obtained after the full kinetic network is constructed by kinetic Monte Carlo simulations or other methods, since graphene growth is a nonequilibrium process. With thermodynamic and kinetic insights provided by first-principles calculations and simulations, a unified picture can be obtained to understand graphene growth on Cu surfaces.

Throughout their life span, plants confront an endless barrage of pathogens and pests. To successfully defend against biotic threats, plants have evolved a complex immune system responsible for surveillance, perception, and the activation of defense. Plant immunity requires multiple signaling processes, the outcome of which vary according to the lifestyle of the invading pathogen(s). In short, these processes require the activation of host perception, the regulation of numerous signaling cascades, and transcriptome reprograming, all of which are highly dynamic in terms of temporal and spatial scales. At the same time, the development of a single immune event is subjective to the development of plant immune system, which is co-regulated by numerous processes, including plant ontogenesis and the host microbiome. In total, insight into each of these processes provides a fuller understanding of the mechanisms that govern plant-pathogen interactions. In this review, we will discuss the "lifecycle" of plant immunity: the development of individual events of defense, including both local and distal processes, as well as the development and regulation of the overall immune system by ontogenesis regulatory genes and environmental microbiota. In total, we will integrate the output of recent discoveries and theories, together with several hypothetical models, to present a dynamic portrait of plant immunity.

Chromosome 17p13.3 microduplication syndrome is considered a multisystem disorder that results in a wide variety of clinical manifestations including dysmorphic facial characteristics, brain structural malformations, developmental restriction, growth restriction, and neurocognitive disorders. The two major classes of chromosome 17p13.3 microduplication, which have different clinical presentations, are associated with specific genetic regions. Among the various known phenotypes, scattered cases with congenital heart disease (CHD) have been reported for both classes of chromosome 17p13.3 microduplication syndrome. Unfortunately, there is insufficient understanding of the correlation between chromosome anomaly induced alterations in gene expression and aberrant cardiac development, and thus early diagnosis of CHD among patients with chromosome 17p13.3 microduplication is difficult without routine prenatal cardiac assessment. One such congenital heart anomalies known to affect a substantial number of newborns worldwide is ventricular septal defect (VSD), which has been found in 17p13.3 microduplication carriers, and seems to sometimes undergo spontaneous closure. We report an unprecedented case of moderate sized perimembranous-outlet VSD and congestive heart failure (CHF) in a Chinese Han male infant with a class II chromosome 17p13.3 microduplication. Despite the fact that cytogenic testing and fetal echocardiography confirmed a 249-Kb chromosome duplication within 17p13.3 that encompassed the PAFAH1B1 gene and showed the presence of VSD during prenatal period, this patient still developed a range of symptoms including sustained prolonged feeding, dyspnea, diaphoresis and retarded growth. A physical examination indicated hepatomegaly and a grade III/VI pan-systolic murmur along the left upper sternal border. Laboratory testing showed a high serum pro–B-type natriuretic peptide (pro-BNP). Imaging studies revealed cardiomegaly and a persistent VSD with related pulmonary stenosis. Since the clinical findings were compatible with CHF, we provided mainline treatment with digoxin, captopril, and furosemide, as well as fluid restriction. Despite sustained poor weight gain, the feeding behavior and the respiratory conditions of the patient improved gradually. This case report and literature review suggest that patients carrying chromosome 17p13.3 microduplication who have VSD may have an increased risk of developing CHF as young infants and hence a comprehensive cardiac evaluation is warranted to allow the early diagnosis and management of any severe heart anomalies.

Simple Summary Reliable animal models of human malignancies are paramount for preclinical studies of novel treatment approaches. Here, we successfully developed a patient-derived xenograft (PDX) model of dedifferentiated endometrial carcinoma (DEC)–an uncommon uterine malignancy that is generally unresponsive to standard chemo- and radiotherapy. The murine model–termed PDX-mLung–was established through the implantation of lung metastatic lesions obtained from a woman with DEC. Histologic and molecular findings revealed that PDX-mLung was highly similar to the parent human malignant lesions (both primary DEC and lung metastases). Importantly, molecular analyses revealed that PDX-mLung exhibited druggable alterations including a FGFR2 mutation and CCNE2 amplification. The former was targeted with the FGFR inhibitor lenvatinib while the latter with the cell cycle inhibitor palbociclib. The combination of the two drugs exhibited synergistic therapeutic effects against in vivo tumor growth. Collectively, these data illustrate the value of PDX models for preclinical testing of new molecularly informed therapies in difficult-to-treat gynecologic malignancies. Our results may also prompt further clinical research to examine whether the combination of lenvatinib and palbociclib has potential to improve clinical outcomes of women with DEC. Abstract Conventional treatment of dedifferentiated endometrial carcinoma (DEC)–an uncommon and highly aggressive uterine malignancy–is beset by high failure rates. A line of research that holds promise to overcome these limitations is tailored treatments targeted on specific molecular alterations. However, suitable preclinical platforms to allow a reliable implementation of this approach are still lacking. Here, we developed a patient-derived xenograft (PDX) model for preclinical testing of investigational drugs informed by molecular data. The model–termed PDX-mLung was established in mice implanted with lung metastatic lesions obtained from a patient with DEC. Histologic and whole-exome genetic analyses revealed a high degree of identity between PDX-mLung and the patient’s parental lesions (both primary DEC and lung metastases). Interestingly, molecular analyses revealed that PDX-mLung harbored druggable alterations including a FGFR2 mutation and CCNE2 amplification. Targeted combined treatment with the FGFR inhibitor lenvatinib and the cell cycle inhibitor palbociclib was found to exert synergistic therapeutic effects against in vivo tumor growth. Based on the results of RNA sequencing, lenvatinib and palbociclib were found to exert anti-tumor effects by interfering interferon signaling and activating hormonal pathways, respectively. Collectively, these data provide proof-of-concept evidence on the value of PDX models for preclinical testing of molecularly informed drug therapy in difficult-to-treat human malignancies. Further clinical research is needed to examine more rigorously the potential usefulness of the lenvatinib and palbociclib combination in patients with DEC.

Chemical reactions on metal surfaces are important in various processes such as heterogeneous catalysis and nanostructure growth. At moderate or lower temperatures, these reactions generally follow the minimum energy path, and temperature effects can be reasonably described by a harmonic oscillator model. At a high temperature approaching the melting point of the substrate, general behaviors of surface reactions remain elusive. In this study, by taking hydrocarbon species adsorbed on Cu(111) as a model system and performing extensive molecular dynamics simulations powered by machine learning potentials, we identify several important high-temperature effects, including local chemical environment, surface atom mobility, and substrate thermal expansion. They affect different aspects of a high-temperature surface reaction in different ways. These results deepen our understanding of high-temperature reactions.

With the wide deployment of renewable energies, future power grids become more vulnerable to extreme environments. This paper investigates enhancing the resilience of power systems with high penetrations of renewable energies under emergencies. The resilience enhancement firstly is defined as maintaining as much electric energy to critical loads in a fixed number of post-disaster periods by properly coordinating the available resources. Then, an optimal decision-making method is proposed to maximize the power supply of critical loads and to minimize the instability risks due to the randomness of the output power of renewable energies. The power consumption of loads, charging/discharging power of power storage plants, power generation of generators, and spinning reserve ratios of the renewable energy at each period are taken as decision variables. Constraints include spinning reserve, power flow constraints, and power consumption/generation limits. The interior-point algorithm is used to solve the formulated optimization problem. Numerical simulations verified the effectiveness and superiority of the proposed optimization method in boosting grid resilience after disasters. It is also found that a balance should be sought between decreasing stability risks and increasing the power supply benefit in extreme environments.

In Arabidopsis, basic helix–loop–helix transcription factors (TFs) MYC2, MYC3, and MYC4 are involved in many biological processes, such as defense against insects. We found that despite functional redundancy, MYC-related mutants displayed different resistance to cotton bollworm (Helicoverpa armigera). To screen out the most likely genes involved in defense against insects, we analyzed the correlation of gene expression with cotton bollworm resistance in wild-type (WT) and MYC-related mutants. In total, the expression of 94 genes in untreated plants and 545 genes in wounded plants were strongly correlated with insect resistance, and these genes were defined as MGAIs (MYC-related genes against insects). MYC3 had the greatest impact on the total expression of MGAIs. Gene ontology (GO) analysis revealed that besides the biosynthesis pathway of glucosinolates (GLSs), MGAIs, which are well-known defense compounds, were also enriched in flavonoid biosynthesis. Moreover, MYC3 dominantly affected the gene expression of flavonoid biosynthesis. Weighted gene co-expression network analysis (WGCNA) revealed that AAE18, which is involved in activating auxin precursor 2,4-dichlorophenoxybutyric acid (2,4-DB) and two other auxin response genes, was highly co-expressed with flavonoid biosynthesis genes. With wounding treatment, the WT plants exhibited better growth performance than chalcone synthase (CHS), which was defective in flavonoid biosynthesis. The data demonstrated dominant contributions of MYC3 to cotton bollworm resistance and imply that flavonoids might alleviate the growth inhibition caused by wounding in Arabidopsis.

NON-RACE-SPECIFIC DISEASE RISISTANCE1 (NDR1) is a key component of plant immune signaling, required for defense against the bacterial pathogen Pseudomonas syringae. Plant stress responses have overlapping molecular, physiological, and cell biology signatures, and given the central role of NDR1 during biotic stress perception and signaling, we hypothesized that NDR1 also functions in abiotic stress responses, including in a role that mediates signaling at the plasma membrane (PM) - cell wall (CW) continuum. Here, we demonstrate that NDR1 is required for the induction of drought stress responses in plants, a role that couples stress signaling in an abscisic acid-dependent manner. We show that NDR1 physically associates with the PM-localized H+-ATPases AHA1, AHA2, and AHA5 and is required for proper regulation of H+-ATPase activity and stomatal guard cell dynamics, providing a mechanistic function of NDR1 during drought responses. In the current study, we demonstrate that NDR1 functions in signaling processes associated with both biotic and abiotic stress response pathways, a function we hypothesize represents NDR1’s role in the maintenance of cellular homeostasis during stress. We propose a role for NDR1 as a core transducer of signaling between cell membrane processes and intercellular stress response activation.

Long-term transmission constrained unit commitment (LT-TCUC) is an important tool in generation expansion planning and has got much attention in recent years. When traditional Lagrangian relaxation (LR) and mixed integer programming (MIP) based methods are used to solve LT-TCUC problems, serious challenges related with the solution efficiency are encountered. This paper proposes a fast method for solving TCUC with long time horizon based on horizon splitting. The basic idea is to partition the whole horizon into several short time intervals, and then relax the coupling constraints between consecutive intervals (ramp rate constraints and minimum up/down time constraints). Sub-TCUC problem in each time interval is then solved independently (in parallel) with CPLEX and the solutions are further adjusted based on MIP to satisfy the relaxed coupling constraints. In this way, the feasibility of the solution is guaranteed and the solutions to the sub-TCUC problems are connected. Salient features of the method include that the solution efficiency is guaranteed and the solution quality can be estimated based on the optimality gap. The proposed method is tested on the modified IEEE 24-bus system, 118-bus systems, and a regional grid in China with one-month or one-year time horizon. Numerical results show that the solution method is efficient.

Approximately, 25% of nasopharyngeal carcinoma (NPC) patients develop recurrent disease. NPC may involve relatively few genomic alterations compared to other cancers due to its association with Epstein‐Barr virus (EBV). We envisioned that in‐depth sequencing of tumor tissues might provide new insights into the genetic alterations of this cancer. Thirty‐three NPC paired tumor/adjacent normal or peripheral blood mononuclear cell samples were deep‐sequenced (>1000×) with respect to a panel of 409 cancer‐related genes. Newly identified mutations and its correlation with clinical outcomes were evaluated. Profiling of somatic mutations and copy number variations (CNV) in NPC tumors identified alterations in RTK/RAS/PI3K, NOTCH, DNA repair, chromatin remodeling, cell cycle, NF‐κB, and TGF‐β pathways. In addition, patients harbored CNV among 409 cancer‐related genes and missense mutations in TGF‐β/SMAD signaling were associated with poor overall survival and poor recurrence‐free survival, respectively. The CNV events were correlated with plasma EBV copies, while mutations in TGFBR2 and SMAD4 abrogate SMAD‐dependent TGF‐β signaling. Functional analysis revealed that the new TGFBR2 kinase domain mutants were incapable of transducing the signal, leading to failure of phosphorylation of SMAD2/3 and activation of downstream TGF‐β‐mediated cell growth arrest. This study provides evidence supporting CNV and dysregulated TGF‐β signaling contributes to exacerbating the NPC pathogenesis.

Recently, a solid electrolyte material LiTa2PO8 (LTPO) with a high room-temperature ionic conductivity (1.6 mS/cm) has been reported in experiment. To understand its Li transport mechanism and find...

Summary Ralstonia solanacearum, one of the most destructive plant bacterial pathogens, delivers an array of effector proteins via its type III secretion system for pathogenesis. However, the biochemical functions of most of these proteins remain unclear. RipN is a type III effector with unknown function(s) from the pathogen R. solanacearum. Here, we demonstrate that RipN is a conserved type III effector found within the R. solanacearum species complex that contains a putative Nudix hydrolase domain and has ADP‐ribose/NADH pyrophosphorylase activity in vitro. Further analysis shows that RipN localizes to the endoplasmic reticulum (ER) and nucleus in Nicotiana tabacum leaf cells and Arabidopsis protoplasts, and truncation of the C‐terminus of RipN results in a loss of nuclear and ER targeting. Furthermore, the expression of RipN in Arabidopsis suppresses callose deposition and the transcription of pathogen‐associated molecular pattern (PAMP)‐triggered immunity (PTI) marker genes under flg22 treatment, and promotes bacterial growth in planta. In addition, the expression of RipN in plant cells alters NADH/NAD+, but not GSH/GSSG, ratios, and its Nudix hydrolase activity is indispensable for such biochemical function. These results suggest that RipN acts as a Nudix hydrolase, alters the NADH/NAD+ ratio of the plant and contributes to R. solanacearum virulence by suppression of PTI of the host.