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Abstract Ubiquitination is a posttranslational modification in eukaryotes that plays a significant role in the infection of intracellular microbial pathogens, such as Legionella pneumophila. While the Legionella-containing vacuole (LCV) is coated with ubiquitin (Ub), it avoids recognition by autophagy adaptors. Here, we report that the Sdc and Sde families of effectors work together to build ubiquitinated species around the LCV. The Sdc effectors catalyze canonical polyubiquitination directly on host targets or on phosphoribosyl-Ub conjugated to host targets by Sde. Remarkably, Ub moieties within poly-Ub chains are either modified with a phosphoribosyl group by PDE domain-containing effectors or covalently attached to other host substrates via Sde-mediated phosphoribosyl-ubiquitination. Furthermore, these modifications prevent the recognition by Ub adaptors and therefore exclude host autophagy adaptors from the LCV. In this work, we shed light on the nature of the poly-ubiquitinated species present at the surface of the LCV and provide a molecular mechanism for the avoidance of autophagy adaptors by the Ub-decorated LCV.

Abstract Background Artificial intelligence is a growing phenomenon that will soon facilitate wide-scale changes in many professions, and is expected to play an important role in the field of medical education. This study explored the realistic feelings and experiences of nursing undergraduates participating in different stages of artificial intelligence + project task driven learning, and provide a basis for artificial intelligence participation in nursing teaching. Methods We conducted face-to-face semi-structured interviews with nursing undergraduates participating in Nursing Research Course which adopts artificial intelligence + project task driven learning from a medical university in Ningxia from September to November 2023, to understand their experience of using artificial intelligence for learning and the emotional changes at different stages. The interview guide included items about their personal experience and feelings of completing project tasks through dialogue with artificial intelligence, and suggestions for course content. Thematic analysis was used to analyze interview data. This study followed the COREQ checklist. Results According to the interview data, three themes were summarized. Undergraduate nursing students have different experiences in participating in artificial intelligence + project task driven learning at different stages, mainly manifested as diverse emotional experiences under initial knowledge deficiency, the individual growth supported by external forces during the adaptation period, and the expectations and suggestions after the birth of the results in the end period. Conclusions Nursing undergraduates can actively adapt to the integration of artificial intelligence into nursing teaching, dynamically observe students’ learning experience, strengthen positive guidance, and provide support for personalized teaching models, better leveraging the advantages of artificial intelligence participation in teaching.

In response to the challenge that traditional convolutional neural networks face in effectively capturing the posture and spatial relationships of plant disease lesions on leaves, leading to issues of low recognition accuracy and poor robustness, this paper proposes a plant leaf disease image classification method that integrates capsule networks and residual networks. Firstly, by optimizing and refining the traditional residual network (ResNet), the initial convolutional layer of ResNet is enhanced by replacing its kernel with a concatenation of $3\times 3$ small convolutional kernels, aiming to more effectively extract features of plant leaf lesions. Subsequently, a channel attention mechanism is introduced into the residual block to heighten the model’s focus on crucial features. Finally, the improved ResNet is effectively integrated with the capsule network (CapsNet). The initial pooling layer of ResNet is removed to reduce the loss of positional information. The output of the third residual module of ResNet is then connected with CapsNet, fully leveraging the strengths of both networks to enhance the model’s robustness. Train and test the model on the PlantVillage, AI Challenger 2018, and Tomato Leaf Disease datasets and conduct comparative experiments with other typical classification models. The proposed SE-SK-CapResNet model has demonstrated a remarkable ability to accurately recognize diseased leaves, achieving an accuracy rate of 98.58%, 95.08%, and 97.19%, respectively. Furthermore, this model has exhibited superior performance in image rotation transformations and classification compared to traditional network models. These experimental results suggest that the SE-SK-CapResNet model is a promising solution for the detection of diseased leaves in the field of agriculture.

The compressibility of bank soils is a critical consideration in t riverbank protection project, construction. In the Inner Mongolia section of the Yellow River, a seasonal frozen soil region, the impact of F-T cycles on soil compressibility cannot be overlooked. This study, based on F-T cycle tests, conducted orthogonal consolidation tests on embankment sandy silt from the Inner Mongolia section of the Yellow River, considering varying initial w and ρd. It investigated the effects of different initial w, ρd, and F-T cycles on soil compressibility, ranked and assessed the significance of influencing factors, and established a predictive model for the compressibility of Inner Mongolia section Yellow River embankment sandy silt. The results show that: the embankment sandy silt is medium-high compression soil, with a between 0.1 and 0.74 MPa−1, Es between 2.65 and 18.47 MPa, and Cc between 0.04 and 0.24 MPa. The greater the ρd of soil, the smaller the initial w, the smaller the a and Cc, and the greater the Es of soil. The F-T effect affects soil compressibility, and soil a, Es and Cc are linearly related to the number of F-T cycles. The ranking of factors influencing soil compressibility is ρd > w > F-T cycles. The initial ρd and w are decisive factors affecting soil compressibility, while the impact of F-T cycles is relatively minor. Additionally, a regression predictive model based on the initial ρd and w of the soil demonstrates good performance in predicting soil compression indices. This model can be utilized for predicting the compressibility indices of embankment soil in the Inner Mongolia section of the Yellow River.

ObjectiveThe purpose of this study was to build nomograms for predicting the survival of individual advanced pleural mesothelioma (MPM) patients using the Surveillance, Epidemiology, and End Results (SEER) database.MethodsThe 1251 patients enrolled from the SEER database were randomized (in a 7:3 ratio) to a training cohort and an internal validation cohort. Eighty patients were enrolled from the Harbin Medical University Cancer Hospital as the external validation cohort. Nomograms were constructed from variables screened by univariate or multivariate Cox regression analyses and evaluated by consistency indices (C-index), calibration plots, and receiver operating characteristic (ROC) curves. Patients from the SEER database who received chemotherapy alone and chemoradiotherapy were statistically paired using propensity score matching of the two groups and performed subgroup analysis in the screened variables.ResultsThe nomograms are well-structured and well-validated prognostic maps constructed from four variables: gender, histology, AJCC stage, and treatment. All individuals were allocated into high-risk versus low-risk groups based on the median risk score of the training cohort, with the high-risk group having worse OS and CSS in all three cohorts (P

Nedd4/Rsp5 family E3 ligases mediate numerous cellular processes, many of which require the E3 ligase to interact with PY motif containing adaptor proteins. Several arrestin-related trafficking adaptors (ARTs) of Rsp5 were self-ubiquitinated for activation, but the regulation mechanism remains elusive. Remarkably, we demonstrate that Art1, Art4, and Art5 undergo K63-linked di-ubiquitination by Rsp5. This modification enhances the plasma membrane recruitment of Rsp5 by Art1 or Art5 upon substrate induction, required for cargo protein ubiquitination. In agreement with these observations, we find that di-ubiquitin strengthens the interaction between the pombe orthologs of Rsp5 and Art1, Pub1, and Any1. Furthermore, we discover that the homologous to E6AP C-terminus (HECT) domain exosite protects the K63-linked di-ubiquitin on the adaptors from cleavage by the deubiquitination enzyme Ubp2. Together, our study uncovers a novel ubiquitination modification implemented by Rsp5 adaptor proteins, underscoring the regulatory mechanism of how adaptor proteins control the recruitment, and activity of Rsp5 for the turnover of membrane proteins.

Abstract Due to the unguaranteed connectivity, wireless sensor networks based on delay tolerant network (DTN) are typically characterized by the opportunistic forwarding mechanism in transmission. Such a mechanism requires nodes to participate in forwarding messages actively. However, when the mechanism is used in the real world, selfish nodes will exhibit some non-cooperation behaviors. Therefore, some incentive mechanism may be designed to encourage selfish nodes. In order to solve the selfishness problem, we propose a fair credit-based incentive mechanism for routing in DTN-based sensor networks. In this mechanism, when a source node sends messages to its destination, each relay node will be rewarded with some credits. The accumulated credits are then used to evaluate the level of cooperation in the network. The selfish nodes with few credits are not able to get enough service from other nodes. With the fair incentive, all participating relays will get equal rewards by the trusted third party. In order to evaluate the proposed mechanism, we also perform some simulation, and the results demonstrate that the method can be used to support efficient routing for DTN-based sensor networks.

Classification of the morphology of red blood cells (RBCs) plays an extremely important role in evaluating the quality of long-term stored blood, as RBC storage lesions such as transformation of discocytes to echinocytes and then to spherocytes may cause adverse clinical effects. Most RBC segmentation and classification methods, limited by interference of staining procedures and poor details, are based on traditional bright field microscopy. In the present study, quantitative phase imaging (QPI) technology was combined with deep learning for automatic classification of RBC morphology. QPI can be used to observe unstained RBCs with high spatial resolution and phase information. In deep learning based on phase information, boundary curvature is used to reduce inadequate learning for preliminary screening of the three shapes of unstained RBCs. The model accuracy was 97.3% for the stacked sparse autoencoder plus Softmax classifier. Compared with the traditional convolutional neural network, the developed method showed a lower misclassification rate and less processing time, especially for RBCs with more discocytes. This method has potential applications in automatically evaluating the quality of long-term stored blood and real-time diagnosis of RBC-related diseases.

Electric taxis have been adopted as a new energy public transportation tool as opposed to traditional taxis in modern city. Designing an efficient swapping station deployment scheme has become an important issue to improve the endurance capability of electric taxis. In this study, based on real operation trajectory data from 3997 taxis in Suzhou city, the battery swapping demand of taxis based on urban traffic flow is obtained to construct a network coverage deployment model under rule constraints, where the main optimization goal is to minimize the number of swapping stations and load balancing. According to this model, a traffic drive planning algorithm based on computational geometry is presented. The experimental results illustrate that the deployment scheme obtained by the proposed algorithm is significantly optimized in terms of the deployment cost and service load and has a lower algorithm time complexity than the typical unified deployment scheme. Therefore, the proposed method can be applied to improve the operating efficiency of the urban electric taxi system.

Glutamylation is a posttranslational modification where the amino group of a free glutamate amino acid is conjugated to the carboxyl group of a glutamate side chain within a target protein. SidJ is a Legionella kinase-like protein that has recently been identified to perform protein polyglutamylation of the Legionella SdeA Phosphoribosyl-Ubiquitin (PR-Ub) ligase to inhibit SdeA’s activity. The attachment of multiple glutamate amino acids to the catalytic glutamate residue of SdeA by SidJ inhibits SdeA’s modification of ubiquitin (Ub) and ligation activity. In this protocol, we will discuss a SidJ non-radioactive, in vitro glutamylation assay using its substrate SdeA. This will also include a second reaction to assay the inhibition of SdeA by using both modification of free Ub and ligation of ADP-ribosylated Ubiquitin (ADPR-Ub) to SdeA’s substrate Rab33b. Prior to the identification and publication of SdeA’s activity, no SdeA inhibition assays existed. Our group and others have demonstrated various methods to display inhibition of SdeA’s activity. The alternatives include measurement of ADP-ribosylation of Ub using radioactive NAD, NAD hydrolysis, and Western blot analysis of HA-Ub ligation by SdeA. This protocol will describe the inhibition of both ubiquitin modification and the PR-Ub ligation by SdeA using inexpensive standard gels and Coomassie staining.

The Legionella effector protein SidJ has recently been identified to perform polyglutamylation on another Legionella effector, SdeA, ablating SdeA’s activity. SidJ is a kinase-like protein that requires the small eukaryotic protein calmodulin to perform glutamylation. Glutamylation is a relatively uncommon type of post-translational modification, where the amino group of a free glutamate amino acid is covalently linked to the γ-carboxyl group of a glutamate sidechain in a substrate protein. This protocol describes the SidJ glutamylation reaction using radioactive [U-14C] glutamate and its substrate SdeA, the separation of proteins by gel electrophoresis, preparation of gels for radioactive exposure, and relative quantification of glutamylation activity. This procedure is useful for the identification of substrates for glutamylation, characterization of substrate and glutamylase activities due to mutations, and identification of proteins with glutamylation activity. Some studies have assayed glutamylation with the use of [3H] glutamate (Regnard et al., 1998) and the use of the GT335 antibody (Wolff et al., 1992). However, the use of [U-14C] glutamate requires a shorter radioactive exposure time with no dependence on antibody specificity.

Summary: Legionella pneumophila is an intracellular pathogen that requires nutrients from the host for its replication. It has been shown that replicating L. pneumophila prefers amino acids as main sources of carbon and energy. The homeostasis of amino acids in eukaryotic cells is regulated by the transcription factor EB (TFEB), which translocates into the nucleus and activates genes for autophagy and lysosomal biogenesis. Here we show that the Legionella effector SetA causes a robust nuclear translocation of TFEB when exogenously expressed in mammalian cells and that the translocation is dependent on the glucosyltransferase activity of SetA. We further show that SetA directly glucosylates TFEB at multiple sites. Our findings of TFEB glucosylation by SetA may suggest an alternative strategy for exploiting host nutrients in addition to the control of host mTORC1 signaling by L. pneumophila. Our results provide further insight into the molecular mechanism of the delicate TFEB nuclear shuttling.

Pseudokinases are considered to be the inactive counterparts of conventional protein kinases and comprise approximately 10% of the human and mouse kinomes. Here, we report the crystal structure of the Legionella pneumophila effector protein, SidJ, in complex with the eukaryotic Ca2+-binding regulator, calmodulin (CaM). The structure reveals that SidJ contains a protein kinase-like fold domain, which retains a majority of the characteristic kinase catalytic motifs. However, SidJ fails to demonstrate kinase activity. Instead, mass spectrometry and in vitro biochemical analyses demonstrate that SidJ modifies another Legionella effector SdeA, an unconventional phosphoribosyl ubiquitin ligase, by adding glutamate molecules to a specific residue of SdeA in a CaM-dependent manner. Furthermore, we show that SidJ-mediated polyglutamylation suppresses the ADP-ribosylation activity. Our work further implies that some pseudokinases may possess ATP-dependent activities other than conventional phosphorylation.

The causative agent of Legionnaires’ disease, Legionella pneumophila, delivers more than 330 virulent effectors to its host to establish an intracellular membrane-bound organelle called the Legionella containing vacuole. Among the army of Legionella effectors, SidC and its paralog SdcA have been identified as novel bacterial ubiquitin (Ub) E3 ligases. To gain insight into the molecular mechanism of SidC/SdcA as Ub ligases, we determined the crystal structures of a binary complex of the N-terminal catalytic SNL domain of SdcA with its cognate E2 UbcH5C and a ternary complex consisting of the SNL domain of SidC with the Ub-linked E2 UbcH7. These two structures reveal the molecular determinants governing the Ub transfer cascade catalyzed by SidC. Together, our data support a common mechanism in the Ub transfer cascade in which the donor Ub is immobilized with its C-terminal tail locked in an extended conformation, priming the donor Ub for catalysis.

Many applications of Internet of Things (IoT) have been implemented based on unreliable wireless or mobile networks like the delay tolerant network (DTN). Therefore, it is an important issue for IoT applications to achieve efficient data transmission in DTN. In order to improve delivery rate and optimize delivery delay with low overhead in DTN for IoT applications, we propose a new routing protocol, called Scheduling-Probabilistic Routing Protocol using History of Encounters and Transitivity (PROPHET). In this protocol, we calculate the delivery predictability according to the encountering frequency among nodes. Two scheduling mechanisms are proposed to extend the traditional PROPHET protocol and improve performance in both storage and transmission in DTN. In order to evaluate the proposed routing protocol, we perform simulations and compare it with other routing protocols in an Opportunistic Network Environment (ONE) simulator. The results demonstrate that the proposed Scheduling-PROPHET can achieve better performances in several key aspects compared with the existing protocols.

The endosomal sorting complexes required for transport (ESCRTs) constitute hetero-oligomeric machines that catalyze multiple topologically similar membrane-remodeling processes. Although ESCRT-III subunits polymerize into spirals, how individual ESCRT-III subunits are activated and assembled together into a membrane-deforming filament remains unknown. Here, we determine X-ray crystal structures of the most abundant ESCRT-III subunit Snf7 in its active conformation. Using pulsed dipolar electron spin resonance spectroscopy (PDS), we show that Snf7 activation requires a prominent conformational rearrangement to expose protein-membrane and protein-protein interfaces. This promotes the assembly of Snf7 arrays with ~30 Å periodicity into a membrane-sculpting filament. Using a combination of biochemical and genetic approaches, both in vitro and in vivo, we demonstrate that mutations on these protein interfaces halt Snf7 assembly and block ESCRT function. The architecture of the activated and membrane-bound Snf7 polymer provides crucial insights into the spatially unique ESCRT-III-mediated membrane remodeling.

The unattended nature of wireless sensor networks makes them very vulnerable to malicious attacks. Therefore, how to preserve secure data collection is an important issue to wireless sensor networks. In this paper, we propose a novel approach of secure data collection for wireless sensor networks. We explore secret sharing and multipath routing to achieve secure data collection in wireless sensor network with compromised nodes. We present a novel tracing-feedback mechanism, which makes full use of the routing functionality of wireless sensor networks, to improve the quality of data collection. The major advantage of the approach is that the secure paths are constructed as a by-product of data collection. The process of secure routing causes little overhead to the sensor nodes in the network. Compared with existing works, the algorithms of the proposed approach are easy to implement and execute in resource-constrained wireless sensor networks. According to the result of a simulation experiment, the performance of the approach is better than the recent approaches with a similar purpose.

Invertases are essential enzymes that irreversibly catalyze the cleavage of sucrose into glucose and fructose. Cell wall invertase (CWI) and vacuolar invertase (VI) are glycosylated proteins and exert fundamental roles in plant growth as well as in response to environmental cues. As yet, comprehensive insight into invertase encoding genes are lacking in Glycine max. In the present study, the systematic survey of gene structures, coding regions, regulatory elements, conserved motifs, and phylogenies resulted in the identification of thirty–two putative invertase genes in soybean genome. Concomitantly, impacts on gene expression, enzyme activities, proteins, and soluble sugar accumulation were explored in specific tissues upon stress perturbation. In combination with the observation of subcellular compartmentation of the fluorescent fusion protein that indeed exported to apoplast, heterologous expression, and purification in using Pichia pastoris system revealed that GmCWI4 was a typical extracellular invertase. We postulated that GmCWI4 may play regulatory roles and be involved in pathogenic fungi defense. The experimental evaluation of physiological significance via phenotypic analysis of mutants under stress exposure has been initiated. Moreover, our paper provides theoretical basis for elucidating molecular mechanisms of invertase in association with inhibitors underlying the stress regime, and will contribute to the improvement of plant performance to a diverse range of stressors.

The opportunistic intracellular pathogen Legionella pneumophila is the causative agent of Legionnaires' disease. L. pneumophila delivers nearly 300 effector proteins into host cells for the establishment of a replication-permissive compartment known as the Legionella-containing vacuole (LCV). SidC and its paralog SdcA are two effectors that have been shown to anchor on the LCV via binding to phosphatidylinositol-4-phosphate [PI(4)P] to facilitate the recruitment of ER proteins to the LCV. We recently reported that the N-terminal SNL (SidC N-terminal E3 Ligase) domain of SidC is a ubiquitin E3 ligase, and its activity is required for the recruitment of ER proteins to the LCV. Here we report the crystal structure of SidC (1-871). The structure reveals that SidC contains four domains that are packed into an arch-like shape. The P4C domain (PI(4)P binding of SidC) comprises a four α-helix bundle and covers the ubiquitin ligase catalytic site of the SNL domain. Strikingly, a pocket with characteristic positive electrostatic potentials is formed at one end of this bundle. Liposome binding assays of the P4C domain further identified the determinants of phosphoinositide recognition and membrane interaction. Interestingly, we also found that binding with PI(4)P stimulates the E3 ligase activity, presumably due to a conformational switch induced by PI(4)P from a closed form to an open active form. Mutations of key residues involved in PI(4)P binding significantly reduced the association of SidC with the LCV and abolished its activity in the recruitment of ER proteins and ubiquitin signals, highlighting that PI(4)P-mediated targeting of SidC is critical to its function in the remodeling of the bacterial phagosome membrane. Finally, a GFP-fusion with the P4C domain was demonstrated to be specifically localized to PI(4)P-enriched compartments in mammalian cells. This domain shows the potential to be developed into a sensitive and accurate PI(4)P probe in living cells.

The unattended nature of wireless sensor networks makes them very vulnerable to an adversary's malicious attack. In this paper, we propose to apply game theory into solving the network security problem of wireless network. We explore game theory algorithms to model situation for wireless network with malicious nodes and investigate the attack and detection problem by modeling it as pairwise simultaneous game and spatial structured game. We consider the relationship between the nodes in a wireless sensor network to formulate the game and give the game theory algorithms in detail. We also evaluate the approach with a simulation experiment and analyze the simulation results in detail. We argue that the approach is able to support secure end-to-end communication in wireless sensor networks.

The unreliability and dynamics of mobile wireless sensor networks make it hard to perform end-to-end communications. This paper presents a novel source-initiated on-demand routing mechanism for efficient data transmission in mobile wireless sensor networks. It explores the Thorup-Zwick theory to achieve source-initiated on-demand routing with time efficiency. It is able to find out shortest routing path between source and target in a network and transfer data in linear time. The algorithm is easy to be implemented and performed in resource-constrained mobile wireless sensor networks. We also evaluate the approach by analyzing its cost in detail. It can be seen that the approach is efficient to support data transmission in mobile wireless sensor networks.

Intermolecular contacts between integrin LFA-1 (α(L)β(2)) and ICAM-1 derive solely from the integrin α(L) I domain and the first domain (D1) of ICAM-1. This study presents a crystal structure of the engineered complex of the α(L) I domain and ICAM-1 D1. Previously, we engineered the I domain for high affinity by point mutations that were identified by a directed evolution approach. In order to examine α(L) I domain allostery between the C-terminal α7-helix (allosteric site) and the metal-ion dependent adhesion site (active site), we have chosen a high affinity variant without mutations directly influencing either the position of the α7-helix or the active sites. In our crystal, the α(L) I domain was found to have a high affinity conformation to D1 with its α7-helix displaced downward away from the binding interface, recapitulating a current understanding of the allostery in the I domain and its linkage to neighboring domains of integrins in signaling. To enable soluble D1 of ICAM-1 to fold on its own, we also engineered D1 to be functional by mutations, which were found to be those that would convert hydrogen bond networks in the solvent-excluded core into vdW contacts. The backbone structure of the β-sandwich fold and the epitope for I domain binding of the engineered D1 were essentially identical to those of wild-type D1. Most deviations in engineered D1 were found in the loops at the N-terminal region that interacts with human rhinovirus (HRV). Structural deviation found in engineered D1 was overall in agreement with the function of engineered D1 observed previously, i.e., full capacity binding to α(L) I domain but reduced interaction with HRV.

Progranulin haplo-insufficiency is a main cause of frontotemporal lobar degeneration (FTLD) with TDP-43 aggregates. Previous studies have shown that sortilin regulates progranulin trafficking and is a main determinant of progranulin level in the brain. In this study, we mapped the binding site between progranulin and sortilin. Progranulin binds to the beta-propeller region of sortilin through its C-terminal tail. The C-terminal progranulin fragment is fully sufficient for sortilin binding and progranulin C-terminal peptide displaces progranulin binding to sortilin. Deletion of the last 3 residues of progranulin (QLL) abolishes its binding to sortilin and also sortilin dependent regulation of progranulin trafficking. Since progranulin haplo-insufficiency results in FTLD, these results may provide important insights into future studies of progranulin trafficking and signaling and progranulin based therapy for FTLD.

Wireless Sensor Networks (WSN) use many sensor nodes to monitor various environmental information in designated areas in real-time, which has broad application prospects in many fields and industries. Due to the sensor's physical fault or technical defect, there are some errors in the collected data; therefore, it is necessary to clean and repair the data before they are used. This paper proposes a high-dimensional sequential data cleaning algorithm for WSNs. The algorithm combines the correlation between different dimensions and the temporal correlation characteristics within the same dimension. Firstly, the data is preprocessed, and the abnormal dimension is determined by combining the prior knowledge and correlation calculation. Then, the algorithm of dynamic programming and speed constraint is used to determine the outliers and mark the abnormal dimensions. Finally, the autoregressive model with exogenous variables is used to repair outliers. Experiments are carried out on a real WSN dataset in this paper. The results show that the repair effect of the proposed algorithm is better than the single dimension benchmark algorithm. [ABSTRACT FROM AUTHOR]

In large indoor spaces such as complexes and logistics warehouses, sensor networks with automated mobile devices rely on high-accuracy indoor positioning systems. Due to the complexity of the indoor space structure, access point (AP) deployment is the key problem of indoor wireless location applications. The goal is to obtain an AP location scheme with high positioning accuracy and controllable deployment cost for any given indoor space structure, while the deployment algorithm itself has acceptable time overhead. This paper proposes a fast deployment algorithm based on graph theory. In this algorithm, the indoor plane space is modeled according to the coverage characteristics of wireless signals, and the problem is reduced into the k-coloring problem of weighted undirected graphs. Therefore, a graph coloring algorithm is proposed to obtain the deployment location of AP. Experimental results show that the proposed algorithm can achieve better positioning accuracy and cost deployment scheme in polynomial time compared with the existing greedy or heuristic algorithms. [ABSTRACT FROM AUTHOR]

Most bacteria surround themselves with a cell wall, a strong meshwork consisting primarily of the polymerized aminosugar peptidoglycan (PG). PG is essential for structural maintenance of bacterial cells, and thus for viability. PG is also constantly synthesized and turned over; the latter process is mediated by PG cleavage enzymes, for example, the endopeptidases (EPs). EPs themselves are essential for growth but also promote lethal cell wall degradation after exposure to antibiotics that inhibit PG synthases (e.g., β-lactams). Thus, EPs are attractive targets for novel antibiotics and their adjuvants. However, we have a poor understanding of how these enzymes are regulated in vivo, depriving us of novel pathways for the development of such antibiotics. Here, we have solved crystal structures of the LysM/M23 family peptidase ShyA, the primary EP of the cholera pathogen Vibrio cholerae. Our data suggest that ShyA assumes two drastically different conformations: a more open form that allows for substrate binding and a closed form, which we predicted to be catalytically inactive. Mutations expected to promote the open conformation caused enhanced activity in vitro and in vivo, and these results were recapitulated in EPs from the divergent pathogens Neisseria gonorrheae and Escherichia coli. Our results suggest that LysM/M23 EPs are regulated via release of the inhibitory Domain 1 from the M23 active site, likely through conformational rearrangement in vivo. [ABSTRACT FROM AUTHOR]

Posttranslational protein modification by ubiquitin (Ub) is a central eukaryotic mechanism that regulates a plethora of physiological processes. Recent studies unveiled an unconventional type of ubiquitination mediated by the SidE family of Legionella pneumophila effectors, such as SdeA, that catalyzes the conjugation of Ub to a serine residue of target proteins via a phosphoribosyl linker (hence named PR-ubiquitination). Comparable to the deubiquitinases in the canonical ubiquitination pathway, here we show that 2 paralogous Legionella effectors, Lpg2154 (DupA; deubiquitinase for PRubiquitination) and Lpg2509 (DupB), reverse PR-ubiquitination by specific removal of phosphoribosyl-Ub from substrates. Both DupA and DupB are fully capable of rescuing the Golgi fragmentation phenotype caused by exogenous expression of SdeA in mammalian cells. We further show that deletion of these 2 genes results in significant accumulation of PR-ubiquitinated species in host cells infected with Legionella. In addition, we have identified a list of specific PR-ubiquitinated host targets and show that DupA and DupB play a role in modulating the association of PR-ubiquitinated host targets with Legionella-containing vacuoles. Together, our data establish a complete PR-ubiquitination and deubiquitination cycle and demonstrate the intricate control that Legionella has over this unusual Ub-dependent posttranslational modification. [ABSTRACT FROM AUTHOR]

A modified low-cost unimorph deformable mirror (DM) driven only by positive voltages for atmospheric turbulence compensation is presented. The 214 patterned inner actuators generate convex deformations for aberration correction, while one outer ring actuator generates an overall concave bias. To evaluate the aberration correction capability of the proposed DM, the iterative reconstruction of Zernike aberrations and correction were performed in an adaptive optics test system. The experimental results indicate that the fabricated DM has an excellent aberration correction capability, particularly matching the first 20 term Zernike aberrations with the normalized residual root-mean-square (RMS) error <5%. Furthermore, the random atmospheric turbulence aberrations were simulated based on Karhunen-Loève coefficients and reconstructed using the fabricated DM. The simulative and experimental results show that the atmospheric turbulence aberrations can be steadily compensated with λ/40 (λ = 2.2 µm) RMS residual error, indicating the prospect for atmospheric applications. [ABSTRACT FROM AUTHOR]