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Degradation by the 26 S proteasome is an intricately regulated process fine tuned by the precise nature of ubiquitin modifications attached to a protein substrate. By debranching ubiquitin chains composed of K48 linkages, the proteasome-associated ubiquitin C-terminal hydrolase UCHL5/UCH37 serves as a positive regulator of protein degradation. How UCH37 achieves specificity for K48 chains is unclear. Here, we use a combination of hydrogen-deuterium mass spectrometry, chemical crosslinking, small-angle X-ray scattering, nuclear magnetic resonance (NMR), molecular docking, and targeted mutagenesis to uncover a cryptic K48 ubiquitin (Ub) chain-specific binding site on the opposite face of UCH37 relative to the canonical S1 (cS1) ubiquitin-binding site. Biochemical assays demonstrate the K48 chain-specific binding site is required for chain debranching and proteasome-mediated degradation of proteins modified with branched chains. Using quantitative proteomics, translation shutoff experiments, and linkage-specific affinity tools, we then identify specific proteins whose degradation depends on the debranching activity of UCH37. Our findings suggest that UCH37 and potentially other DUBs could use more than one S1 site to perform different biochemical functions. [ABSTRACT FROM AUTHOR]

Energy transport within biological systems is critical for biological functions in living cells and for technological applications in molecular motors. Biological systems have very complex dynamics supporting a large number of biochemical and biophysical processes. In the current work, we study the energy transport along protein chains. We examine the influence of different factors such as temperature, salt concentration, and external mechanical drive on the energy flux through protein chains. We obtain that energy fluctuations around the average value for short chains are greater than for longer chains. In addition, the external mechanical load is the most effective agent on bioenergy transport along the studied protein systems. Our results can help design a functional nano-scaled molecular motor based on energy transport along protein chains. [ABSTRACT FROM AUTHOR]

Sulfur related prokaryotes residing in hot spring present good opportunity for exploring the limitless possibilities of integral ecosystem processes. Metagenomic analysis further expands the phylogenetic breadth of these extraordinary sulfur (S) metabolizing microorganisms as well as their complex metabolic networks and syntrophic interactions in environmental biosystems. Through this study, we explored and expanded the microbial genetic repertoire with focus on S cycling genes through metagenomic analysis of S contaminated hot spring, located at the Northern Himalayas. The analysis revealed rich diversity of microbial consortia with established roles in S cycling such as Pseudomonas , Thioalkalivibrio , Desulfovibrio , and Desulfobulbaceae (Proteobacteria). The major gene families inferred to be abundant across microbial mat, sediment, and water were assigned to Proteobacteria as reflected from the reads per kilobase (RPKs) categorized into translation and ribosomal structure and biogenesis. An analysis of sequence similarity showed conserved pattern of both dsrAB genes (n = 178) retrieved from all metagenomes while other S disproportionation proteins were diverged due to different structural and chemical substrates. The diversity of S oxidizing bacteria (SOB) and sulfate reducing bacteria (SRB) with conserved (r) dsrAB suggests for it to be an important adaptation for microbial fitness at this site. Here, (i) the oxidative and reductive dsr evolutionary time–scale phylogeny proved that the earliest (but not the first) dsrAB proteins belong to anaerobic Thiobacillus with other (rdsr) oxidizers, also we confirm that (ii) SRBs belongs to δ- Proteobacteria occurring independent lateral gene transfer (LGT) of dsr genes to different and few novel lineages. Further, the structural prediction of unassigned DsrAB proteins confirmed their relatedness with species of Desulfovibrio (TM score = 0.86, 0.98, 0.96) and Archaeoglobus fulgidus (TM score = 0.97, 0.98). We proposed that the genetic repertoire might provide the basis of studying time–scale evolution and horizontal gene transfer of these genes in biogeochemical S cycling. [ABSTRACT FROM AUTHOR]

Type III Secretion Systems (T3SS) deliver subunits from the bacterial cytosol to nascent cell surface flagella. Early flagellar subunits that form the rod and hook substructures are unchaperoned and contain their own export signals. A gate recognition motif (GRM) docks them at the FlhBc component of the FlhAB-FliPQR export gate, but the gate must then be opened and subunits must be unfolded to pass through the flagellar channel. This induced us to seek further signals on the subunits. Here, we identify a second signal at the extreme N-terminus of flagellar rod and hook subunits and determine that key to the signal is its hydrophobicity. We show that the two export signal elements are recognised separately and sequentially, as the N-terminal signal is recognised by the flagellar export machinery only after subunits have docked at FlhBC via the GRM. The position of the N-terminal hydrophobic signal in the subunit sequence relative to the GRM appeared to be important, as a FlgD deletion variant (FlgDshort), in which the distance between the N-terminal signal and the GRM was shortened, 'stalled' at the export machinery and was not exported. The attenuation of motility caused by FlgDshort was suppressed by mutations that destabilised the closed conformation of the FlhAB-FliPQR export gate, suggesting that the hydrophobic N-terminal signal might trigger opening of the flagellar export gate. [ABSTRACT FROM AUTHOR]

Among the most sought after breakthroughs nowadays to combat computational saturation in the electronic hardware realm, neuromorphic and cytomorphic mimetics of biological structures seem potentially promising. Biological circuits are distinguishable due to their minuscule dimensions and immensely low power consumption; yet they achieve extremely complex and magnificent tasks of life, such as, thinking, memorizing, decision making and self-regulating in response to the surroundings. Low power analog circuit solutions are edged over digital ones as they are inherently noisy and fuzzy like bio-systems. In this paper, an analog circuit equivalent for a well-known biological pathway, cyclic adenosine monophosphate (cAMP), has been proposed, exploiting the fabrication characteristics of an analog transistor. The work demonstrates an application of previously published research of the authors, where it was shown that a single transistor operating in analog mode can mimic some fundamental biological circuit processes like receptor-ligand binding, Michaelis Menten and Hill process reactions. Since biological pathways are chain connections of such reactions, same modular approach can be used to build electronic pathways using those basic transistor circuits. Although the idea of creating silicon life seems far-fetched at this stage, this work supplements the idea of cytomorphic chips which is already gaining interest of bio-engineering community. [ABSTRACT FROM AUTHOR]

As a quarantine pest of conifer, Sirex noctilio has caused widespread harm around the world. It is expected that the molecular mechanism of protein–ligand binding can be elucidated to carry out the pest control. Through studies of SnocOBP12–ligand hydrophobic binding and dynamics and responsible amino acid residues identification, we got some promising results. SnocOBP12 had a general and excellent affinity for host plant volatiles, and may be a key protein for S. noctilio to find host plants. Among the many odor molecules that are bound to SnocOBP12, (−)-α-cedrene and (E)-β-farnesene from host plants and (−)-globuol from the symbiotic fungi of Sirex noctilio stood out and formed highly stable complexes with SnocOBP12. By the molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) method, the calculated free binding energy of the three complexes was −30.572 ± 0.101 kcal/mol, −28.349 ± 0.119 kcal/mol and −25.244 ± 0.152 kcal/mol, respectively. It was found that the van der Waals energy contributed to the stability of the complexes. Some key amino acid residues were also found: LEU74 and TYR109 were very important for SnocOBP12 to stably bind (−)-α-cedrene, while for (E)-β-farnesene, ILE6, MET10, and LEU74 were very important for the stable binding system. We discovered three potential ligands and analyzed the interaction pattern of the protein with them, this paper provides a favorable molecular basis for optimizing the attractant formulation. Investigation of the binding characteristics in the olfactory system at the molecular level is helpful to understand the behavior of S. noctilio and develop new methods for more effective and environmentally friendly pest control. [ABSTRACT FROM AUTHOR]

Functional and structural adaptation of common carotid artery could be one of the important causes of postflight orthostatic intolerance after microgravity exposure, the mechanisms of which remain unclear. Recent evidence indicates that long-term spaceflight increases carotid artery stiffness, which might present a high risk to astronaut health and postflight working ability. Studies have suggested that vascular calcification is a common pathological change in cardiovascular diseases that is mainly manifested as an increase in vascular stiffness. Therefore, this study investigated whether simulated microgravity induces calcification of common carotid artery and to elucidate the underlying mechanisms. Four-week-old hindlimb-unweighted (HU) rats were used to simulate the deconditioning effects of microgravity on cardiovascular system. We found that simulated microgravity induced vascular smooth muscle cell (VSMC) osteogenic differentiation and medial calcification, increased receptor activator of nuclear factor κB (NF-κB) ligand (RANKL) and RANK expression, and enhanced NF-κB activation in rat common carotid artery. In vitro activation of the RANK pathway with exogenous RANKL, a RANK ligand, increased RANK and osteoprotegerin (OPG) expression in HU rats. Moreover, the expression of osteogenic markers and activation of NF-κB in HU rats were further enhanced by exogenous RANKL but suppressed by the RANK inhibitor osteoprotegerin fusion protein (OPG-Fc). These results indicated that the OPG/RANKL/RANK system modulates VSMC osteogenic differentiation and medial calcification of common carotid artery in simulated microgravity rats by regulating the NF-kB pathway. [ABSTRACT FROM AUTHOR]

Concepts of a submerged floating tunnel (SFT) for novel sea-crossings have been researched in recent years. An SFT tube should be moored afloat by tensioned mooring systems to maintain the tube position under complex hydrodynamic loads. In-line force is amongst the dominant hydrodynamic parameters in the SFT cross-section design and the mooring system reliability evaluation. Selecting a suitable in-line force computation method is crucial to successful and accurate SFT cross-section optimization. The transition SST model is an effective turbulence transition prediction tool in the boundary layer computation subjected to tidal flow at both low and high Reynolds numbers. Two types of parametric Bézier curves applied in airfoil optimization are used to describe the SFT cross-section. We show that an SFT cross-section described by a leading-edge Bézier-PARSEC (BP) curve has better hydrodynamic performance than a trailing-edge BP curve of equal aspect ratio (AR). To avoid large flow separation, an AR not exceeding 0.47 is recommended. An SFT cross-section design should balance hydrodynamic performance and construction cost. The SFT cross-section with AR = 0.47 using the leading-edge BP curve with fixed clearance has a comparatively small in-line force and a minimum material cost. [ABSTRACT FROM AUTHOR]

This article studies the problem of cooperative substructure transportation using multiple modular robots in an on-orbit assembly mission. Two kinds of modular robots, termed as force and torque robots, are used to provide control forces and torque for the substructure, respectively. Using the framework of cooperative games, a set of Pareto optimal control problems are formulated to solve for the optimal control forces and torque of modular robots, such that they can cooperatively bring the substructure to dock with the main body of a large space structure. Additionally, an event-triggered coordinated compensatory control mechanism using the model predictive control principles is designed for modular robots, which guarantees that the substructure can follow the desired optimal trajectories with the computation and communication burden of modular robots being reduced. Numerical simulations demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The development of London's West India Docks, opened in 1802, made manifest the contemporary connections between culture, capitalism, and colonialism. A liminal space, the docks existed as a secure conduit for the importation of goods from the West Indies, most of which were produced by enslaved Africans. As such, they functioned as a threshold between the brutal realities of the plantation-based slave economy, and the polite world of the London merchant whose wealth derived from that economy. This collaborative article, which we wrote as two curators at the Museum of London, explores the lasting effects of that liminality, focusing on the aesthetic and spatial implications of the West India Docks's environment, and the ways in which these persist in influencing the site and its communities today. [ABSTRACT FROM AUTHOR]

Background: Cytokine storm (CS) is a systemic inflammatory syndrome and a major cause of multi-organ failure and even death in COVID-19 patients. With the increasing number of COVID-19 patients, there is an urgent need to develop effective therapeutic strategies for CS. Baicalin is an anti-inflammatory and antiviral traditional Chinese medicine. In the present study, we aimed to evaluate the therapeutic mechanism of baicalin against CS through network analysis and experimental validation, and to detect key targets of CS that may bind closely to baicalin through molecular docking. Method: Access to potential targets of baicalin and CS in public databases. We constructed the protein-protein interaction (PPI) network of baicalin and CS by Cytoscape 9.0 software and performed network topology analysis of the potential targets. Then, the hub target was identified by molecular docking technique and validated in the CS model. Finally, GO and KEGG pathway functional enrichment analysis of common targets were confirmed using R language, and the location of overlapping targets in key pathways was queried via KEGG Mapper. Result: A total of 86 overlapping targets of baicalin and CS were identified, among which MAPK14, IL2, FGF2, CASP3, PTGS2, PIK3CA, EGFR, and TNF were the core targets. Moreover, it was found that baicalin bound most closely to TNF through molecular docking, and demonstrated that baicalin can effectively inhibit the elevation of TNF-α in vitro and in vivo. Furthermore, bioenrichment analysis revealed that the TNF signaling pathway and IL-17 signaling pathway may be potential key pathways for baicalin to treat CS. Conclusion: Based on this study, baicalin was identified as a potential drug for the alleviation of CS, and the possible key targets and pathways of baicalin for the treatment of CS were elucidated to reveal the main pharmacological mechanisms. [ABSTRACT FROM AUTHOR]

Flaviviruses comprise a genus of viruses that pose a significant burden on human health worldwide. Transmission by both mosquito and tick vectors, and broad host tropism contribute to the presence of flaviviruses globally. Like all viruses, they require utilization of host molecular machinery to facilitate their replication through physical interactions. Their RNA genomes are translated using host ribosomes, synthesizing viral proteins that cooperate with each other and host proteins to reshape the host cell into a factory for virus replication. Thus, dissecting the physical interactions between viral proteins and their host protein targets is essential in our comprehension of how flaviviruses replicate and how they alter host cell behavior. Beyond replication, even single interactions can contribute to immune evasion and pathogenesis, providing potential avenues for therapeutic intervention. Here, we review protein interactions between flavivirus and host proteins that contribute to virus replication, immune evasion, and disease. [ABSTRACT FROM AUTHOR]

Docks are a widespread problem in intensively managed grassland, requiring repeated pesticide applications for control purposes. New European Union pesticide regulations aim to restrict pesticide use. This necessitates improved efficiency of pesticide use including the most effective time to apply them during the target weed's lifecycle. The experimental site (52°21 N, 7°18 W) was reseeded with perennial ryegrass in October 2009. A plot (5 m × 10 m) experiment was laid down in a randomized complete block design with nine treatments and eight replicates. Four herbicides licensed for use in new leys (NLH) were each applied in April 2010. Four herbicides licensed for use in established grassland (EGH) were each applied 2 years later in April 2012. The ninth treatment was an untreated control. Dock numbers were measured over 5 years (2010–2014) and herbage production over 3 years (2012–2014). Across all treatments, dock numbers were relatively low until the fourth year during which there was more than a three‐fold increase due to clonal propagation. NLH gave more (p <.001) effective and enduring control than EGH. EGH varied in their effectiveness with (p <.001) recovery of individually marked docks that were 'apparently dead' following EGH application. In 2014 dock herbage dry‐matter (DM) production (t ha−1) was 3.41 in the control compared with 0.55 for NLH and 1.38 for EGH. Across all treatments in 2014 grass DM production declined with increasing dock herbage DM production (t ha−1): grass = 11.17 – 1.047 × dock (R2 =.73; p <.001). More eco‐efficient control of docks was achieved by herbicide application to new leys. [ABSTRACT FROM AUTHOR]

For the purpose of discovering potential inhibitors of β-amyloid (BACE1), which is a crucial element in Alzheimer's disease (AD) pathogenesis, an in silico study of naturally occurring compounds was performed using precise computational approaches. Autodock4 package was preliminary used to predict the binding affinities to BACE1 of more than four thousand compounds presented in the Vietnamese plants (VIETHERB) database. Based on docking results, twenty top-lead compounds having the largest docking energy to BACE1 were rigorously examined using steered molecular dynamics (SMD) simulations. Interestingly, SMD results found that the binding affinity values of three compounds, including myricetin 3-O-(3''-galloylrhamnopyranoside), quercetin 3-O-neohesperidoside, and hydroxysafflor yellow A, are remarkably higher than that of the well-known BACE1 inhibitor, 23I, and these compounds can thus be considered the promising candidates for inhibitors of BACE1. [ABSTRACT FROM AUTHOR]

Exosomes as nanosized membrane vesicles, could targeted deliver therapeutic agents by modification with target ligands. Exosome-derived non-coding RNAs play a vital role in the development of tumors. Previous evidences reveal that long non-coding RNA maternally expressed gene 3 (lncRNA MEG3) has anti-tumor properties. Whereas, the inhibitory effects of exosome-derived lncRNA MEG3 in osteosarcoma (OS) remain largely unknown. In this study, we utilize the engineering technology to combine exosome and lncRNA for tumor-targeting therapy of OS. We elucidated the anti-OS effects of lncRNA MEG3, and then prepared the c(RGDyK)-modified and MEG3-loaded exosomes (cRGD-Exo-MEG3). The engineered exosomes cRGD-Exo-MEG3 could deliver more efficiently to OS cells both in vitro and in vivo. In this way, cRGD-Exo-MEG3 facilitate the anti-OS effects of MEG3 significantly, with the help of enhanced tumor-targeting therapy. This study elucidates that engineered exosomes as targeted lncRNA MEG3 delivery vehicles have potentially therapeutic effects for OS. [Display omitted] • This study utilizes the engineering technology to combine exosome and lncRNA for tumor-targeting therapy of osteosarcoma. • The engineered exosomes cRGD-Exo-MEG3 could deliver more efficiently to osteosarcoma cells both in vitro and in vivo. • Engineered exosomes as targeted lncRNA MEG3 delivery vehicles have potentially therapeutic effects for osteosarcoma. [ABSTRACT FROM AUTHOR]

Shopping malls are densely located in major cities such as Singapore and Hong Kong. Tenants in these shopping malls generate a large number of freight orders to their contracted logistics service providers, who independently plan their own delivery schedules. These uncoordinated deliveries and limited docking capacity jointly cause congestion at the shopping malls. A delivery coordination platform centrally plans the vehicle routes for the logistics service providers and simultaneously schedules the dock time slots at the shopping malls for the delivery orders. Vehicle routing and dock scheduling decisions need to be made jointly against the backdrop of travel time and service time uncertainty and subject to practical operations rules. We model this problem as a two-stage stochastic mixed integer program, develop an adaptive large neighborhood search algorithm that approximates the second stage recourse function using various sample sizes, and examine the associated in-sample and out-of-sample stability. Our numerical study on a testbed of instances based on real data in Singapore demonstrates the value of coordination and the value of stochastic solutions. [ABSTRACT FROM AUTHOR]

We developed SMART v1.0 (http://smart.omicstudio.cloud), the first database for small molecules with functional implications in plants. The SMART database is devoted to providing and managing small molecules and their associated structural data, chemoinformatic data, protein targets, pathways and induced phenotype/function information. Currently, SMART v1.0 encompasses 1218 unique small molecules which are involved in multiple biological pathways. SMART v1.0 is featured with user-friendly interfaces, through which pathway-centered visualization of small molecules can be efficiently performed, and multiple types of searches (i.e., text search, structure similarity search and sequence similarity search) can be conveniently conducted. SMART v1.0 is also specifically designed to be a small molecule-sharing database, allowing users to release their newly discovered small molecules to public via the Contribute webpage. The SMART database will facilitate the comprehensive understanding of small molecules in complex biological processes in plants. [ABSTRACT FROM AUTHOR]

The assembly and signaling properties of cilia rely on intraflagellar transport (IFT) trains moving proteins into, within, and out of cilia. A flurry of near-atomic models of the multiprotein complexes that make up IFT trains has revealed new conformational changes, which may underlie the switch between anterograde and retrograde intraflagellar transport. [ABSTRACT FROM AUTHOR]

To investigate the deformation and stability of the rock surrounding a tunnel excavated through layered rock, a three-dimensional numerical simulation was conducted to compare and analyze the right line of the YD2K100+560–630 two-stage docking cross-section of the Yuelongmen Tunnel using a ubiquitous joint model. Based on 3-D numerical simulations, the following conclusions were drawn: (1) The excavation on the construction entrance side significantly disturbed the construction exit side, and the exit side was more disturbed in the steeply dipping layer than in the gently dipping layer. (2) The influence of the dip angle of the laminae on the uplift of the tunnel invert was greater than the influence on the tunnel vault settlement when the laminae were oriented perpendicular to the trend of the tunnel and two-stage docking excavation was used. (3) When two-stage excavation was applied to gently inclined laminated rock, there was an obvious disturbance to both the top of the tunnel (less than one time the diameter of the through face; and to the bottom of the tunnel within 0.5 time the diameter of the through face on the side with the stopping construction exit side during the tunnelling process. When tunnel excavation was conducted against the trend of the layer, there was obvious disturbance to the top of the tunnel within 0.5 time the diameter of the through face and to the bottom of the tunnel within one time the diameter of the entrance face) on the construction exit side during the tunnelling process due to the presence of laminae. The excavation on the construction entrance side significantly disturbed the construction exit side. When docking and penetrating layered rock tunnels, priority should be given to docking and penetrating in the direction corresponding to the layers, and temporary support on the exit side should be strengthened to ensure the deformation stability of the surrounding rock mass. [ABSTRACT FROM AUTHOR]

Intracellular trafficking through the secretory organelles depends on transient interactions between cargo proteins and transport machinery. Cytosolic coat protein complexes capture specific luminal cargo proteins for incorporation into transport vesicles by interacting with them indirectly through a transmembrane adaptor or cargo receptor. Due to their transient nature, it is difficult to study these specific ternary protein interactions just using conventional native co-immunoprecipitation. To overcome this technical challenge, we have applied a crosslinking assay to stabilize the transient and/or weak protein interactions. Here, we describe a protocol of protein crosslinking and co-immunoprecipitation, which was employed to prove the indirect interaction in the endoplasmic reticulum of a luminal secretory protein with a selective subunit of the cytosolic COPII coat through a specific transmembrane cargo receptor. This method can be extended to address other transient ternary interactions between cytosolic proteins and luminal or extracellular proteins through a transmembrane receptor within the endomembrane system. [ABSTRACT FROM AUTHOR]

Nucleosomes are recognized as key regulators of transcription. However, the relationship between slow nucleosome unwrapping dynamics and bulk transcriptional properties has not been thoroughly explored. Here, an agent-based model that we call the dynamic defect Totally Asymmetric Simple Exclusion Process (ddTASEP) was constructed to investigate the effects of nucleosome-induced pausing on transcriptional dynamics. Pausing due to slow nucleosome dynamics induced RNAPII convoy formation, which would cooperatively prevent nucleosome rebinding leading to bursts of transcription. The mean first passage time (MFPT) and the variance of first passage time (VFPT) were analytically expressed in terms of the nucleosome rate constants, allowing for the direct quantification of the effects of nucleosome-induced pausing on pioneering polymerase dynamics. The mean first passage elongation rate γ(hc, ho) is inversely proportional to the MFPT and can be considered to be a new axis of the ddTASEP phase diagram, orthogonal to the classical αβ-plane (where α and β are the initiation and termination rates). Subsequently, we showed that, for β = 1, there is a novel jamming transition in the αγ-plane that separates the ddTASEP dynamics into initiation-limited and nucleosome pausing-limited regions. We propose analytical estimates for the RNAPII density ρ, average elongation rate v, and transcription flux J and verified them numerically. We demonstrate that the intra-burst RNAPII waiting times tin follow the time-headway distribution of a max flux TASEP and that the average inter-burst interval tIBI¯ correlates with the index of dispersion De. In the limit γ→0, the average burst size reaches a maximum set by the closing rate hc. When α≪1, the burst sizes are geometrically distributed, allowing large bursts even while the average burst size NB¯ is small. Last, preliminary results on the relative effects of static and dynamic defects are presented to show that dynamic defects can induce equal or greater pausing than static bottle necks. Author summary: To perform specific functions, cells must express specific genes by copying the information in DNA into RNA via transcription. Structural proteins called nucleosomes are spaced every 200 base pairs along the length of a strand of DNA and play a crucial function in the regulation of gene activity by tightly binding DNA strands and condensing them into heterochromatin, preventing transcription by RNA polymerase II (RNAPII). Even on active genes where nucleosomes are loosely attached to DNA strands, the wrapping and unwrapping of nucleosomes pause transcription as RNAPII passes by. Previous mathematical models of transcription have compared this biological process to traffic on a one lane highway without obstructions. In contrast, our proposed model simulates transcription like traffic in a grid system where nucleosomes can be thought of as pedestrians or other vehicles crossing the road at regularly spaced intersections. Just as side street traffic and pedestrian crossings can cause cars to form convoys and cause jams limiting the max speed in an area, nucleosomes can cause RNAPII to form convoys that lead to bursts of mRNA production and limit the average polymerase flux through the gene. [ABSTRACT FROM AUTHOR]

Bike sharing service (BSS) networks have been proliferating all over the globe thanks to their success as the first/last-mile connectivity inside a smart city. Their (re)configuration — i.e., station (re)placement and dock resizing — has thus become increasingly important for BSS providers and smart city planners. Instead of using conventional labor-intensive manual surveys, we propose a novel information fusion framework called CBikes that (re)configures the BSS network by jointly fusing crowdsourced station suggestions from online websites and the usage history of bike stations. Using comprehensive real data analyses, we identify and exploit important global trip patterns to (re)configure the BSS network while mitigating the local biases of individual feedbacks. Specifically, crowdsourced feedbacks, station usage, cost and other constraints are fused into a joint optimization of BSS network configuration. We also model the spatial distributions of station usage to account for and estimate the unexplored regions without historical usage information. We further design a semidefinite programming transformation to solve the bike station (re)placement problem efficiently and effectively. Our extensive data analytics and evaluation have shown CBikes’ effectiveness and accuracy in (re)placing stations and resizing docks based on three large BSS systems (with $>$ > 900 stations) in Chicago, Twin Cities (Minneapolis–Saint Paul), and Los Angeles. [ABSTRACT FROM AUTHOR]

Summary: In this article, a novel cable‐drogue docking system is proposed between an autonomous underwater vehicle (AUV) and one mobile underwater platform, to increase the docking safety and reduce the negative influences of turbulences around the platform shell on the AUV. The mathematical model of the cable‐drogue system and an radial basis function neural network (RBFNN)‐based Q‐learning proportional‐integral‐differential (PID) controller are developed for the system characteristics analysis and the stabilized control. First, the cable‐drogue's mathematical model is established as a link‐joint‐connected system, whose kinematic and dynamic equations are derived subjected to the hydrodynamic forces on system. One numerical solution procedure is also presented to obtain the motion state of the cable‐drogue system. Next, considering the current interferences on the cable‐drogue system, a cross rudder is added on the drogue to enhance the robustness. An RBFNN‐based Q‐learning PID controller is proposed to improve the control performances, in which the control parameters are adaptively optimized by an Q‐learning neural network. Finally, numerical simulations are made to study the steady‐state and dynamic characteristics of the cable‐drogue system in ocean environment, and to investigate the performances of both the traditional PID controller and the proposed RBFNN‐based Q‐learning PID controller in unknown dynamical system. Simulation results show the effectiveness of the kinematic and dynamic equations of the cable‐drogue system and the proposed controller in this article. [ABSTRACT FROM AUTHOR]

A thermodynamically consistent phase-field model is introduced for simulating motion and shape transformation of vesicles under flow conditions. In particular, a general slip boundary condition is used to describe the interaction between vesicles and the wall of the fluid domain in the absence of cell-wall adhesion introduced by ligand-receptor binding. A second-order accurate in both space and time C0 finite element method is proposed to solve the model governing equations. Various numerical tests confirm the convergence, energy stability, and conservation of mass and surface area of cells of the proposed scheme. Vesicles with different mechanical properties are also used to explain the pathological risk for patients with sickle cell disease. [ABSTRACT FROM AUTHOR]

The biological significance of proteins attracted the scientific community in exploring their characteristics. The studies shed light on the interaction patterns and functions of proteins in a living body. Due to their practical difficulties, reliable experimental techniques pave the way for introducing computational methods in the interaction prediction. Automated methods reduced the difficulties but could not yet replace experimental studies as the field is still evolving. Interaction prediction problem being critical needs highly accurate results, but none of the existing methods could offer reliable performance that can parallel with experimental results yet. This article aims to assess the existing computational docking algorithms, their challenges, and future scope. Blind docking techniques are quite helpful when no information other than the individual structures are available. As more and more complex structures are being added to different databases, information-driven approaches can be a good alternative. Artificial intelligence, ruling over the major fields, is expected to take over this domain very shortly. [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 (COVID-19) is causing major sanitary and socioeconomic issues, yet some locations are less impacted than others. While densely populated areas are likely to favor viral transmission, we hypothesize that other environmental factors could explain lower cases in some areas. We studied COVID-19 impact and population statistics in highly forested Mediterranean Italian regions versus some northern regions where the amount of trees per capita is much lower. We also evaluated the affinity of Mediterranean plant-emitted volatile organic compounds (VOCs) isoprene, α-pinene, linalool and limonene for COVID-19 protein targets by molecular docking modeling. Results show that while mean death number increased about 4 times from 2020 to 2021, the percentage of deaths per population (0.06–0.10%) was lower in the greener Mediterranean regions such as Sardinia, Calabria and Basilica versus northern regions with low forest coverage, such as Lombardy (0.33%) and Emilia Romagna (0.29%). Data also show that the pandemic severity cannot be explained solely by population density. Modeling reveals that plant organic compounds could bind and interfere with the complex formed by the receptor binding domain of the coronavirus spike protein with the human cell receptor. Overall, our findings are likely explained by sea proximity and mild climate, Mediterranean diet and the abundance of non-deciduous Mediterranean plants which emit immunomodulatory and antiviral compounds. Potential implications include 'forest bathing' as a therapeutic practice, designing nasal sprays containing plant volatile organic compounds, and preserving and increasing forest coverage. [ABSTRACT FROM AUTHOR]

In the present work, the molecules, (E)-1-(4,4″-difluoro-5′-methoxy-1,1′:3′,1″-terphenyl-4′-yl)-3-phenylprop-2-en-1-one (DFTP), (2E)-1-(4,4″-difluoro-5′-methoxy-1,1′:3′,1″-terphenyl-4′-yl)-3-(4-fluorophenyl)prop-2-en-1-one (TFTP), (2E)-3-(4-bromophenyl)-1-(4,4″-difluoro-5′-methoxy-1,1′:3′,1″-terphenyl-4′-yl)-prop-2-en-1-one (BFTP), and (E)-1-1(4,4″-difluoro-5′-methoxy-1,1′:3′-1″-terphenyl-4′-yl)-3-(4-methylphenyl)prop-2-en-1-one (FMTP) have been synthesized and vibrational wavenumbers and electronic properties have also been performed. The compound series shows good light harvesting properties and photovoltaic modeling shows that they can be used successfully in DSSCs as photo sensitizers. The NLO activity of the title compounds have been investigated and β and γ values varies in the order BFTP > FMTP > TFTP > DFTP. The consequences which were made by electron donor acceptor due to charge transfer mechanism have been scrutinized by the natural bond investigation. Molecular docking has been performed to understand the binding interactions of the analyzed ligands with tyrosine-protein kinase JAK2 and these compounds can be developed as anticancer agent. [ABSTRACT FROM AUTHOR]

ABCG2 is a substantial member of the ABC transporter superfamily that plays a significant role in multidrug resistance in cancer. Until recently, the 3D structure of ABCG2 has not been resolved, which resulted in the limitation of developing potential ABCG2 inhibitors using structure‐based drug discovery. Herein, eMolecules, ChEMBL, and ChEBI databases, containing >25 million compounds, were virtually screened against the ABCG2 transporter in homodimer form. Performance of AutoDock4.2.6 software to predict inhibitor‐ABCG2 binding mode and affinity were validated on the basis of available experimental data. The explored databases were filtered based on docking scores. The most potent hits with binding affinities higher than that of experimental bound ligand (MZ29) were then selected and subjected to molecular mechanics minimization, followed by binding energy calculation using molecular mechanics‐generalized Born surface area (MM‐GBSA) approach. Furthermore, molecular dynamics simulations for 50 ns, followed by MM‐GBSA binding energy calculations, were performed for the promising compounds, unveiling eight potential inhibitors with binding affinities <−55.8 kcal/mol. Structural and energetic analyses demonstrated the stability of the eight identified inhibitors over the 50 ns MD simulation. This research sheds light on the potentiality of the identified ABCG2 inhibitors as a therapeutic approach to overcome multidrug resistance cancer therapy. [ABSTRACT FROM AUTHOR]

Autonomous aerial refueling (AAR) has generated great interest in recent years. However, much research has focused on the vision-based close docking stage; few studies have been conducted on the navigation algorithm for the rendezvous and following stages. High-precision relative navigation in following stage can provide favourable conditions for successful docking. Aiming at precise relative navigation in the complex high dynamic environment of aerial refueling rendezvous and following stages, a two-stage adaptive filtering architecture is exploited in this paper. An adaptive main Kalman filter (AKF) is realized for ambiguity eliminated GNSS/INS tightly coupled integrated system, and a robust adaptive subfilter is developed for GNSS individually. Particularly, aiming at the influence of pseudorange observation multipath outliers and state abnormal disturbances in unmanned air vehicle- (UAV-) tanker proximity, an INS-aided bifactor robust and classified factor adaptive filtering (IBRCAF) algorithm for single-frequency ambiguity resolution is proposed. Finally, the effectiveness of the algorithm is verified by the simulation experiments for UAV-tanker. The results indicate that the IBRCAF algorithm can efficiently suppress the influence of pseudorange multipath gross errors and abnormal state disturbances and greatly raise the success rate of ambiguity resolution, and the two-stage adaptive filtering algorithm of IBRCAF-AKF can significantly improve relative navigation performance and achieve centimeter-level accuracy. [ABSTRACT FROM AUTHOR]

Vacuolar acidification is essential for vacuoles in diverse physiological functions. However, its role in plant defense, and whether and how pathogens affect vacuolar acidification to promote infection remain unknown. Here, we show that Barley stripe mosaic virus (BSMV) replicase γa, but not its mutant γaR569A, directly blocks acidification of vacuolar lumen and suppresses autophagic degradation to promote viral infection in plants. These were achieved via molecular interaction between γa and V‐ATPase catalytic subunit B2 (VHA‐B2), leading to disruption of the interaction between VHA‐B2 and V‐ATPase catalytic subunit E (VHA‐E), which impairs the membrane localization of VHA‐B2 and suppresses V‐ATPase activity. Furthermore, a mutant virus BSMVR569A with the R569A point mutation possesses less viral pathogenicity. Interestingly, multiple viral infections block vacuolar acidification. These findings reveal that functional vacuolar acidification is required for plant antiviral defense and disruption of vacuolar acidification could be a general viral counter‐defense strategy employed by multiple viruses. Synopsis: A viral protein inhibits vacuolar acidification to facilitate viral infection by suppressing vacuolar H+‐ATPase activity via its interaction with the V‐ATPase subunit B2. Barley stripe mosaic virus (BSMV) γa protein blocks the acidification of vacuoles and the degradation of autophagic bodies.BSMV γa directly interacts with host vacuolar H+‐ATPase subunit B2 (VHA‐B2) to competitively disrupt the VHA‐B2‐VHA‐E interaction in plants.BSMV γa partially changes the subcellular localization of VHA‐B2 from membrane to cytosol and suppresses V‐ATPase activity.Disruption of vacuolar acidification could be a general viral counter‐defense strategy employed by multiple viruses [ABSTRACT FROM AUTHOR]

Motivation Antibodies are one of the most important classes of pharmaceuticals, with over 80 approved molecules currently in use against a wide variety of diseases. The drug discovery process for antibody therapeutic candidates however is time- and cost-intensive and heavily reliant on in vivo and in vitro high throughput screens. Here, we introduce a framework for structure-based deep learning for antibodies (DLAB) which can virtually screen putative binding antibodies against antigen targets of interest. DLAB is built to be able to predict antibody–antigen binding for antigens with no known antibody binders. Results We demonstrate that DLAB can be used both to improve antibody–antigen docking and structure-based virtual screening of antibody drug candidates. DLAB enables improved pose ranking for antibody docking experiments as well as selection of antibody–antigen pairings for which accurate poses are generated and correctly ranked. We also show that DLAB can identify binding antibodies against specific antigens in a case study. Our results demonstrate the promise of deep learning methods for structure-based virtual screening of antibodies. Availability and implementation The DLAB source code and pre-trained models are available at https://github.com/oxpig/dlab-public. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

In this paper, a circular objects detection method for Autonomous Underwater Vehicle (AUV) docking is proposed, based on the Dynamic Vision Sensor (DVS) and the Spiking Neural Network (SNN) framework. In contrast to the related work, the proposed method not only avoids motion blur caused by frame-based recognition during docking procedure but also reduces data redundancy with limited on-chip resources. First, four coplanar and rectangular constrained circular light sources are constructed as the docking landmark. By combining asynchronous Hough circle transform with the SNN model, the coordinates of landmarks in the image are detected. Second, a Perspective-4-Point (P4P) algorithm is utilized to calculate the relative pose between AUV and the landmark. In addition, a spatiotemporal filter is also used to eliminate noises generated by the background. Finally, experimental results are demonstrated from both software simulation and experimental pool, respectively, to verify the proposed method. It is concluded that the proposed method achieves better performance in accuracy and efficiency in underwater docking scenarios. [ABSTRACT FROM AUTHOR]

Despite considerable advances obtained by applying machine learning approaches in protein–ligand affinity predictions, the incorporation of receptor flexibility has remained an important bottleneck. While ensemble docking has been used widely as a solution to this problem, the optimum choice of receptor conformations is still an open question considering the issues related to the computational cost and false positive pose predictions. Here, a combination of ensemble learning and ensemble docking is suggested to rank different conformations of the target protein in light of their importance for the final accuracy of the model. Available X-ray structures of cyclin-dependent kinase 2 (CDK2) in complex with different ligands are used as an initial receptor ensemble, and its redundancy is removed through a graph-based redundancy removal, which is shown to be more efficient and less subjective than clustering-based representative selection methods. A set of ligands with available experimental affinity are docked to this nonredundant receptor ensemble, and the energetic features of the best scored poses are used in an ensemble learning procedure based on the random forest method. The importance of receptors is obtained through feature selection measures, and it is shown that a few of the most important conformations are sufficient to reach 1 kcal/mol accuracy in affinity prediction with considerable improvement of the early enrichment power of the models compared to the different ensemble docking without learning strategies. A clear strategy has been provided in which machine learning selects the most important experimental conformers of the receptor among a large set of protein–ligand complexes while simultaneously maintaining the final accuracy of affinity predictions at the highest level possible for available data. Our results could be informative for future attempts to design receptor-specific docking-rescoring strategies. [ABSTRACT FROM AUTHOR]

Gelsemium elegans (Gardner and Champ.) Benth. (Gelsemiaceae) (GEB) is a toxic plant indigenous to Southeast Asia especially China, and has long been used as Chinese folk medicine for the treatment of various types of pain, including neuropathic pain (NPP). Nevertheless, limited data are available on the understanding of the interactions between ingredients-targets-pathways. The present study integrated network pharmacology and experimental evidence to decipher molecular mechanisms of GEB against NPP. The candidate ingredients of GEB were collected from the published literature and online databases. Potentially active targets of GEB were predicted using the SwissTargetPrediction database. NPP-associated targets were retrieved from GeneCards, Therapeutic Target database, and DrugBank. Then the protein-protein interaction network was constructed. The DAVID database was applied to Gene Ontology and Kyoto Encyclopedia of Genes and Genome pathway enrichment analysis. Molecular docking was employed to validate the interaction between ingredients and targets. Subsequently, a 50 ns molecular dynamics simulation was performed to analyze the conformational stability of the protein-ligand complex. Furthermore, the potential anti-NPP mechanisms of GEB were evaluated in the rat chronic constriction injury model. A total of 47 alkaloids and 52 core targets were successfully identified for GEB in the treatment of NPP. Functional enrichment analysis showed that GEB was mainly involved in phosphorylation reactions and nitric oxide synthesis processes. It also participated in 73 pathways in the pathogenesis of NPP, including the neuroactive ligand-receptor interaction signaling pathway, calcium signaling pathway, and MAPK signaling pathway. Interestingly, 11-Hydroxyrankinidin well matched the active pockets of crucial targets, such as EGFR, JAK1, and AKT1. The 11-hydroxyrankinidin-EGFR complex was stable throughout the entire molecular dynamics simulation. Besides, the expression of EGFR and JAK1 could be regulated by koumine to achieve the anti-NPP action. These findings revealed the complex network relationship of GEB in the "multi-ingredient, multi-target, multi-pathway" mode, and explained the synergistic regulatory effect of each complex ingredient of GEB based on the holistic view of traditional Chinese medicine. The present study would provide a scientific approach and strategy for further studies of GEB in the treatment of NPP in the future. [ABSTRACT FROM AUTHOR]

Highlights: Extracellular vesicle (EV) multiplexing involves chemical, physical spatial, biological, or nanoparticle-based strategies. Multiplexing in EV biomarker development includes high-throughput screening as well as point-of-care testing platforms which to date have been applied mainly to EV surface proteins or internal cargo miRNAs. Multiplexed measurements at single-EV resolution are likely to revolutionize the applicability of EV analytes as biomarkers in complex and heterogeneous diseases. Extracellular vesicles (EVs) are cell-derived membranous particles that play a crucial role in molecular trafficking, intercellular transport and the egress of unwanted proteins. They have been implicated in many diseases including cancer and neurodegeneration. EVs are detected in all bodily fluids, and their protein and nucleic acid content offers a means of assessing the status of the cells from which they originated. As such, they provide opportunities in biomarker discovery for diagnosis, prognosis or the stratification of diseases as well as an objective monitoring of therapies. The simultaneous assaying of multiple EV-derived markers will be required for an impactful practical application, and multiplexing platforms have evolved with the potential to achieve this. Herein, we provide a comprehensive overview of the currently available multiplexing platforms for EV analysis, with a primary focus on miniaturized and integrated devices that offer potential step changes in analytical power, throughput and consistency. [ABSTRACT FROM AUTHOR]

Maneuvering a truck-trailer system while docking is extremely challenging. This article aims to alleviate this problem by presenting an enhanced path-following control framework for autonomous semi-trailer docking. In the proposed system, adaptive controllers that utilize gain scheduling are introduced for forward and reverse path-following tasks in docking maneuvers to increase the robustness and path-following performance. The system includes an improved pure pursuit controller with adaptive look-ahead distance for forward path following; a cascade controller of reverse pure pursuit and a gain-scheduled LQ control for reverse path-following. In the evaluation of the path-following performance of forward and reverse controllers, the closed-loop system of path-following controllers with the truck-trailer kinematic model is simulated in MATLAB/Simulink for various test cases, and the results are compared with those of other studies. Furthermore, different docking scenarios are generated via the cascade path planning algorithm for autonomous semitrailer docking. These are tested with a high degree semi-trailer model within the IPG TruckMaker simulation environment, and with a full truck-trailer vehicle in the test field. The results of both simulations and physical testing clearly demonstrate improvements in terms of the control problem formulation, i.e., the stabilized path-following is obtained with acceptable path-following errors. [ABSTRACT FROM AUTHOR]

The objective of this paper is to analyze the use of dock infrastructure and productivity at the port of Veracruz in Mexico for the period 2002-2020. With the use of proposed methodology by Mexican Institute of Transport (IMT), this article analyzes the port indicators for ship-port interface. The results indicate that there was an increase in the intensity of use and occupancy at the docks, this suggests that improved the port efficiency; in addition, there is an increase in the productivity of loading and unloading over the period analyzed. However, the port of Veracruz shows a stagnation in maritime transport connectivity and reached a saturation point during the years 2017 and 2018. Likewise, the ships spent between 35% and 45% of port turnaround times to non-productive activities, which is explained by congestion at the docks and users' decisions. [ABSTRACT FROM AUTHOR]

This study aimed to present a mathematical model to evaluate the operation of urban docks. To do this, the dock located in Tehran bazaar (Panzdah-e-Khordad St., between Pamanar intersection and Mostafa Khomeini intersection) has been selected as a case study sample. The proposed mathematical model is based on Queueing theory which with the necessary data, has undergone a three-step process. Finally, it examines the operation of dock based on the density rate parameter (p). In this research, the value of the density rate parameter (p) has been calculated by applying the mathematical model for the studied dock area, and the necessary analyzes have been performed according to the obtained value. Based on the analysis, the mean time to stop of freight vehicles is high according to the number of stations and it is necessary to manage this time, and the number of stations should be increased. In addition, since the dock is not separate from the traffic route of motor vehicles and motorcycles, and as a result of traffic problems in this area, it was concluded that the dock should be separated from vehicle traffic route. [ABSTRACT FROM AUTHOR]

• Comparative review of molecular docking scoring methods, with and without machine learning. • Analysis of most common data representation methods. • General trends for Deep Learning strategies on molecular docking. • An overview of popular datasets to improve your models. Artificial intelligence (AI) is often presented as a new Industrial Revolution. Many domains use AI, including molecular simulation for drug discovery. In this review, we provide an overview of ligand–protein molecular docking and how machine learning (ML), especially deep learning (DL), a subset of ML, is transforming the field by tackling the associated challenges. [ABSTRACT FROM AUTHOR]

• Targeting the WNT/β-catenin signaling pathway. • Novel approaches towards targeting the WNT/β-catenin pathway. • WNT/β-catenin Pathway Inhibitors in Clinical Development as cancer therapeutics. • Challenges in targeting the WNT/β-catenin signaling pathway. • Artificial intelligence and targeting WNT/β-catenin pathway. WNT/β-catenin signaling orchestrates various physiological processes, including embryonic development, growth, tissue homeostasis, and regeneration. Abnormal WNT/β-catenin signaling is associated with various cancers and its inhibition has shown effective antitumor responses. In this review, we discuss the pathway, potential targets for the development of WNT/β-catenin inhibitors, available inhibitors, and their specific molecular interactions with the target proteins. We also discuss inhibitors that are in clinical trials and describe potential new avenues for therapeutically targeting the WNT/β-catenin pathway. Furthermore, we introduce emerging strategies, including artificial intelligence (AI)-assisted tools and technology-based actionable approaches, to translate WNT/β-catenin inhibitors to the clinic for cancer therapy. [ABSTRACT FROM AUTHOR]

An example of a "best case scenario" for global logistics worker organizing is the International Dockworkers Council (IDC), an independent global union organization of workplace-level dockworker union activists that I have researched for the past decade. Keywords: global unions; dockworkers; logistics; structural power; internationalism EN global unions dockworkers logistics structural power internationalism 50 58 9 01/04/22 20220101 NES 220101 Graph: The Ever Given, part of the Evergreen fleet, in the Suez Canal.Herry Lawford, Flickr In March 2021, the massive container ship Ever Given, part of the Evergreen fleet, carrying eighteen thousand containers, ran aground, blocking the Suez Canal for six days.[4] The ship's cargo, valued at $1 billion,[5] included everything from apparel to electronics to furniture and agricultural commodities. Dockworker unions in both countries have become iconic symbols for the trade union movement and the left more broadly of what is possible when workers organize, and they have played a leading role in social and political movements in their countries since that time. Lessons on Intraorganizational Practices from the IDC In addition to providing lessons for the development of logistics worker-organizing strategy, the IDC's organizational model provides lessons on how to bring logistics workers together across disparate worksites - and even countries. [Extracted from the article]

Complexes of p24 proteins act as cargo receptors for the transport of COPII vesicles from the endoplasmic reticulum (ER). The major cargos of p24 complexes are hydrophilic proteins tethered to the ER membrane via a covalently attached glycosylphosphatidylinositol (GPI) or fatty acid. Each p24 complex is known to contain members from all four p24 subfamilies (p24α, p24β, p24γ and p24δ). However, it remains unclear how the cargo specificities of p24 complexes are influenced by member stoichiometry. Here, we report the subunit compositions of mammalian p24 complexes involved in the transport of GPI-anchored proteins and Wnt1. We show that at least one p24α is required for the formation of p24 complexes and that a p24 complex consisting of p24α2, p24β1, p24γ2 and p24δ1 is required for the efficient transport of GPI-anchored proteins. On the other hand, a p24 complex containing p24α2, p24α3, p24β1, p24γ and p24δ1 is involved in the transport of Wnt1. Further, interactions between p24α2 and p24α3 are critical for Wnt1 transport. Thus, p24α and p24γ subfamily members are important for cargo selectivity. Lastly, our data fit with an octamer, rather than a tetramer, model of p24 complexes, where each complex consists of two proteins from each p24 subfamily. [ABSTRACT FROM AUTHOR]

This article investigates the background, inception, design and construction of Brunel's tubular wrought-iron bridges, with a view to setting the Swivel Bridge in historical and technical context (Figure 1). [ABSTRACT FROM AUTHOR]

Isambard Kingdom Brunel designed a lock and 70 Tonne swing bridge of novel design in 1849, sited at the lowest vehicular crossing point on the River Avon in Bristol, at Cumberland Basin, the western entrance to the Floating Harbour. In the 1870's the bridge was shortened and relocated over a new entrance lock constructed where it served for well over 100 years. It still survives, lying derelict underneath the Plimsoll swinging road-bridge that superseded it in 1965. [ABSTRACT FROM AUTHOR]