Bridge Interaction Research Articles

Hydrochar supported strategy for nZVI to remove bisphenol A and Cr(VI): Performance, synergetic mechanism, and life cycle assessment

To comprehensively overcome the shortcomings and extend the application of nanoscale zero-valent iron (nZVI), a promising hydrochar supported strategy was provided. nZVI/Eupatorium adenophorum hydrochar (nZVI/EaHC) composite was attained under relatively mild reaction condition, and life cycle assessment revealed that the greenhouse gases emission, ecotoxicity, and resource consumption of nZVI/EaHC fabrication processes largely reduced in comparison with nZVI and pyrolysis biochar supported nZVI (nZVI/EaBC). Moreover, nZVI/EaHC exhibited an outstanding potential in reduction and immobilization of Cr(VI) as well as degradation of bisphenol A (BPA) via Fenton-like system. The static experiment showed that the removal efficiency achieved 99.21 % within 1 h for Cr(VI) and 97.9 % within 1 min for BPA, which significantly exceeded the performance of nZVI/EaBC, accompanied by a significant detoxification to non-harmful level and mineralization of 87.9 % within 10 min. The dynamic continuous flow column experiment indicated that 90 % Cr(VI) was removed within 40 min and 90 % BPA within 180 min under ultra-low-dosage of catalyst and H2O2. Furthermore, hydrochar supported strategy may reduce the economic cost and avoid secondary pollution due to the outstanding stability under aerobic condition and recyclability in magnetic field. The synergetic mechanisms were further revealed, the abundant oxygen-containing functional groups on EaHC facilitated the generation of electron-rich/poor centers via chemical bond bridge (COFe) and Fe-π interaction, which further enhanced the electron transfer to reduce Cr(VI) or promote the production of multiple reactive species including OH, O2–, and 1O2 to degrade BPA, additionally, persistent free radicals on EaHC also contributed to the degradation of BPA. Therefore, this efficient, applicable, and sustainable strategy may have a greatly practical outlook on nZVI application together with a comprehensive control and utilization of biomass including invasive plants.

Cryo-EM reveals a phosphorylated R-domain envelops the NBD1 catalytic domain in an ABC transporter.

Many ATP-binding cassette transporters are regulated by phosphorylation on long and disordered loops which presents a challenge to visualize with structural methods. We have trapped an activated state of the regulatory domain (R-domain) of yeast cadmium factor 1 (Ycf1) by enzymatically enriching the phosphorylated state. A 3.23 Å cryo-EM structure reveals an R-domain structure with four phosphorylated residues and the position for the entire R-domain. The structure reveals key R-domain interactions including a bridging interaction between NBD1 and NBD2 and an interaction with the R-insertion, another regulatory region. We scanned these interactions by systematically replacing segments along the entire R-domain with scrambled combinations of alanine, glycine, and glutamine and probing function under cellular conditions that require the Ycf1 function. We find a close match with these interactions and interacting regions on our R-domain structure that points to the importance of most well-structured segments for function. We propose a model where the R-domain stabilizes a transport-competent state upon phosphorylation by enveloping NBD1 entirely.

Dynamic Intelligent Analysis of Single-Column Pier Bridges Considering Vehicle–Bridge Interaction

With its advantages of low engineering cost, minimal space occupancy, and aesthetically pleasing shape, the single-column pier bridge is frequently utilized in urban viaducts and interchange ramps. Due to structural peculiarities, the bridge subjected to eccentric loading, flexural and torsional interaction, and centrifugal force may undergo tipping accidents. To better comprehend the overturning resistance of the bridge, the vibration governing equation of the bridge (idealized as an orthotropic thin plate with point supports in the domain model) is established considering vehicle–bridge interaction. An approximate dynamic analysis formula is subsequently derived via a hybrid method using the grey wolf optimizer. Compared with the outcomes of finite element analysis, the maximal deviation arising from this derived analytical formula is approximately [Formula: see text]% with the greater discrepancy being observed in scenarios featuring minimal support reactions. Compared with the finite element method, the proposed method in this study has higher computational efficiency with precision. This analytical solution is then utilized in the parametric study to scrutinize the influences of span, road surface roughness, and vehicle velocity on a single-column pier bridge under four vehicles. The analysis findings indicate that the proposed approach is reasonably precise, remarkably efficient, and efficacious.

Contrasting behavior of urea in strengthening and weakening confinement effects on polymer collapse.

Biomolecules inhabit a crowded living cell that is packed with high concentrations of cosolutes and macromolecules that result in restricted, confined volumes for biomolecular dynamics. To understand the impact of crowding on the biomolecular structure, the combined effects of the cosolutes (such as urea) and confinement need to be accounted for. This study involves examining these effects on the collapse equilibria of three model 32-mer polymers, which are simplified models of hydrophobic, charge-neutral, and uncharged hydrophilic polymers, using molecular dynamics simulations. The introduction of confinement promotes the collapse of all three polymers. Interestingly, addition of urea weakens the collapse of the confined hydrophobic polymer, leading to non-additive effects, whereas for the hydrophilic polymers, urea enhances the confinement effects by enhancing polymer collapse (or decreasing the polymer unfolding), thereby exhibiting an additive effect. The unfavorable dehydration energy opposes collapse in the confined hydrophobic and charge-neutral polymers under the influence of urea. However, the collapse is driven mainly by the favorable change in polymer-solvent entropy. The confined hydrophilic polymer, which tends to unfold in bulk water, is seen to have reduced unfolding in the presence of urea due to the stabilizing of the collapsed state by urea via cohesive bridging interactions. Therefore, there is a complex balance of competing factors, such as polymer chemistry and polymer-water and polymer-cosolute interactions, beyond volume exclusion effects, which determine the collapse equilibria under confinement. The results have implications to understand the altering of the free energy landscape of proteins in the confined living cell environment.

Development of tripeptide-cyclotriphosphazene derivatives: In vitro cytotoxicity, genotoxicity studies and molecular docking analysis within ovarian and prostate cancer cell line receptors

Peptide-phosphazene compounds are important compounds of growing interest in biomedical research and have potential therapeutic effects. The tripeptide-cyclotriphosphazenes conjugates were synthesized and analyzed for their molecular docking analysis, visualizing their binding profiles within various cancer cell line receptors and tested in vitro cytotoxic and genotoxic properties. Determining in vitro cytotoxic studies of obtained compounds displayed cytotoxic effect against two selected human cancer cell lines, including ovarian (A2780) and prostate (PC-3), cancer cells. The compound DTAP demonstrated significantly higher efficacy at 100 µM in the PC-3 cancer cell line compared to the reference drug docetaxel at 50 µM. Among the tripeptide-phosphazene conjugtates, DTGG demonstrates the most promising anticancer activity with a logIC50 of 1.23 µM, forming five hydrogen bonds and a favorable salt bridge interaction, along with several hydrophobic interactions, thereby stabilizing its binding within the human ovarian tumor domain based on molecular docking analysis. The derivative DTGP emerges as the most potent among the DTG derivatives, achieving a ΔG model value of −108 kcal/mol, primarily due to a π-cationic interaction with the LYS204 amino acid in chain C, which significantly enhances its binding affinity. Additionally, DNA damage studies on human ovarian and prostate cancer cell lines determined that cell death due to DNA damage was the basis of the decrease in cell viability. These results support the evaluation of the compounds as potential drug candidates.

Molecular Dynamics (MD) Simulations Provide Insights into the Activation Mechanisms of 5-HT2A Receptors

Recent breakthroughs in the determination of atomic resolution 3-D cryo-electron microscopy structures of membrane proteins present an unprecedented opportunity for drug discovery. Structure-based drug discovery utilizing in silico methods enables the study of dynamic connectivity of stable conformations induced by the drug in achieving its effect. With the ever-expanding computational power, simulations of this type reveal protein dynamics in the nano-, micro-, and even millisecond time scales. In the present study, aiming to characterize the protein dynamics of the 5HT2A receptor stimulated by ligands (agonist/antagonist), we performed 1 µs MD simulations on 5HT2A/DOI (agonist), 5HT2A/GSK215083 (antagonist), and 5HT2A (APO, no ligand) systems. The crystal structure of 5HT2A/zotepine (antagonist) (PDB: 6A94) was used to set up the simulation systems in a lipid bilayer environment. We found the monitoring of the ionic lock residue pair (R3.50-E6.30) of 5HT2A in MD simulations to be a good approximation of the effects of agonists (ionic lock breakage) or antagonists (ionic lock formation) on receptor activation. We further performed analyses of the MD trajectories, including Principal Component Analysis (PCA), hydrogen bond, salt bridge, and hydrophobic interaction network analyses, and correlation between residues to identify key elements of receptor activation. Our results suggest that in order to trigger receptor activation, DOI must interact with 5HT2A through residues V5.39, G5.42, S5.43, and S5.46 on TM5, inducing significant conformational changes in the backbone angles of G5.42 and S5.43. DOI also interacted with residues W6.48 (toggle switch) and F6.51 on TM6, causing major conformational shifts in the backbone angles of F6.44 and V6.45. These structural changes were transmitted to the intracellular ends of TM5, TM6, and ICL3, resulting in the breaking of the ionic lock and subsequent G protein activation. The studies could be helpful in future design of selective agonists/antagonists for various serotonin receptors (5HT1A, 5HT2A, 5HT2B, 5HT2C, and 5HT7) involved in detrimental disorders, such as addiction and schizophrenia.

Unravelling heterogenous adsorption performance of hydrochar particle and key properties in heavy metal immobilization relative to corresponding residual bulk hydrochar

Immobilization performance of released hydrochar particle (HP) to metal is largely unknown and hinder accurate estimation to immobilization effect in hydrochar application. Herein, HPs derived from typical biomass, food waste (FW), and blue algae (BA), were collected to investigate their adsorption abilities, mechanisms towards typical Cd(II) relative to residual bulk hydrochar (BH) and unravel corresponding properties of this heterogeneity. The results were: 1) the micro-sized HP with poor porous structure, less O-containing functional groups (OFGs) and negative surface charge induced inferior adsorption capacities (0.65-0.81 times) but quicker adsorption rate (3.09-10.08 times) towards Cd(II) compared with BH, 2) cation bridge interaction in coagulation and settling processes unexpectedly facilitated adsorption performance of micro-sized and negative charged FWHPs added with counterions, 3) HP facilitated its electrostatic attraction with Cd(II) rather than common pore filling and surface complexation, especially bare aromatic structure in HP formed another cation-π interaction with Cd(II) highlighted by density functional theory (DFT) method. The special coagulation process and cation-π interaction of HP will facilitate its vertical co-migration ability but weaken immobilization stability towards metals. The distinct heterogeneities of adsorption ability of HP and BH and underlying key properties provide an in-depth understanding of hydrochar application for remediation of metal contaminants in soil/water environment.

Data-Driven Relationship for Reduction Factor of Ballasted Railway Bridge Deflections Due to Load Distribution Within Track

Increasing the operating speed of the trains on modern networks necessitates performing dynamic analyses to assess the performance of bridges under passage of trains. The detailed investigation of their responses requires constructing complex computational models capable to take the train–track–bridge interaction effects into account. Such models have successfully been developed; however, employing those elaborated models for practical engineering applications, or to perform studies that require a large number of analyses may become infeasible. Among such situations are conducting probabilistic investigations, screening of entire networks, or sensitivity analyses. These concerns have been addressed by employing simplified models mostly relying on moving load modeling strategy which disregards the train–track–bridge interaction effects. Those neglected contributions can be compensated by implementing additional correction factors. The distribution of loads within track is one of those disregarded effects where a reduction factor is recommended by design guidelines to take its contribution into account. It has been shown that the existing relationship for these reduction factors delivers an acceptable performance for vertical accelerations, while showing a less favorable performance for displacements. Then, a data-driven strategy is adopted in this study to propose easy-to-apply relationships for reduction factors of deflections, due to load distribution within the track. In this context, three different distributive lengths of triangular load footprints have been considered, namely 2.0, 2.5 and 3.0[Formula: see text]m. The procedure employed has trained and tested for more than 1[Formula: see text]200 train configurations, comprising conventional, articulated and regular vehicles, and including several tens of thousand data points for each distributive length. The performance observed in the new models revealed a considerable improvement with respect to the existing relationship.

Phosphopeptide-bridged NH2-TiO2-mediated carbon dots self-enhancing and electrochemiluminescence microsensors for label-free protein kinase A detection.

A novel electrochemiluminescence (ECL) method was developed for determination of protein kinase A (PKA) ultra-sensitively based on amidated nano-titanium (NH2-TiO2) embellished carbon dots (Mg@N-CDs) fluorescent probe, which integrated the target recognition and ECL signal enhancement. The Cys-labeled kemptides were employed to build a serine-rich synthetic substrate-heptapeptide (Cys-kemptide) on the Au-electrode surface. Then, the PKA-induced biosensor was triggered as a signal switch to introduce the large amounts of TiO2 decorated Mg@N-CD nanohybrid (Ti@NMg-CDs) into AuE/Cys-phosphopeptides for signal output. In particular, the presence of PKA could induce the formation of Cys-phosphopeptides by the catalytic reaction between specific substrate (kemptide) and PKA, which acts as an initiator to link the Ti@NMg-CDs according to the bridge interactions Ti-O-P. In this way, multiple Cys-phosphopeptides were adsorbed onto a single Ti@NMg-CDs, and the Ti@NMg-CDs not only provided high specific selectivity but also large surface area, as well as unprecedented high ECL efficiency. Using this PKA-induced enhanced sensor, the limit of detection of the PKA was 4.89 × 10-4 U/mL (S/N = 3). The proposed ECL biosensor was also universally applicable for the screening of PKA inhibitors and determining of other kinases activity. Our sensing system has excellent performance of specificity and the screening of kinase inhibitors, as well as it will inspire future effort in clinical diagnostics and new drug discovery.

Physically Guided Estimation of Vehicle Loading-Induced Low-Frequency Bridge Responses with BP-ANN

The intersectional relationship in bridge health monitoring refers to the mapping function that correlates bridge responses across different locations. This relationship is pivotal for estimating structural responses, which are then instrumental in assessing a bridge’s service status and identifying potential damage. The current research landscape is heavily focused on high-frequency responses, especially those associated with single-mode vibration. When it comes to low-frequency responses triggered by multi-mode vehicle loading, a prevalent strategy is to regard these low-frequency responses as “quasi-static” and subsequently apply time-series prediction techniques to simulate the intersectional relationship. However, these methods are contingent upon data regarding external loading, such as traffic conditions and air temperatures. This necessitates the collection of long-term monitoring data to account for fluctuations in traffic and temperature, a task that can be quite daunting in real-world engineering contexts. To address this challenge, our study shifts the analytical perspective from a static analysis to a dynamic analysis. By delving into the physical features of bridge responses of the vehicle–bridge interaction (VBI) system, we identify that the intersectional relationship should be inherently time-independent. The perceived time lag in quasi-static responses is, in essence, a result of low-frequency vibrations that are aligned with driving force modes. We specifically derive the intersectional relationship for low-frequency bridge responses within the VBI system and determine it to be a time-invariant transfer matrix associated with multiple mode shapes. Drawing on these physical insights, we adopt a time-independent machine learning method, the backpropagation–artificial neural network (BP-ANN), to simulate the intersectional relationship. To train the network, monitoring data from various cross-sections were input, with the responses at a particular section designated as the output. The trained network is now capable of estimating responses even in scenarios where time-related traffic conditions and temperatures deviate from those present in the training data set. To substantiate the time-independent nature of the derived intersectional relationship, finite element models were developed. The proposed method was further validated through the in-field monitoring of a continuous highway bridge. We anticipate that this method will be highly effective in estimating low-frequency responses under a variety of unknown traffic and air temperature conditions, offering significant convenience for practical engineering applications.

Asphaltene-Silica Interactions in Salinity Water and Their Ion Dependence

Summary The adsorption of asphaltene on the pore surface not only forms a dense adsorption film but also induces a transition in sandstone wettability to more hydrophobic, which poses challenges to oil displacement, especially in unconventional reservoirs. The asphaltene adsorption exhibits a strong ion dependence, especially toward high ion concentration and high-valence cations, and the mechanism is not yet entirely understood. In this work, atomic force microscopy (AFM), coreflooding experiments, and the self-priming rate method were used to investigate the impacts of ion concentration and types in connate water on the adsorption of asphaltene. Enhanced asphaltene adsorption is observed in the presence of ions, leading to a more pronounced hydrophobic character in the cores saturated by high-salinity water. Then, we proceed with a consideration of the attraction force law between asphaltene and rock. The attraction showed an exponential decay with respect to distance and is in accordance with the hydrated ion bridge interaction. Furthermore, the attraction intensified notably in CaCl2 solution compared to that in NaCl solution and was enhanced progressively with increasing ionic concentration. Therefore, the adsorption amount of asphaltene and ultimately the wettability of the rock are affected by ion concentration and valence in formation water. Our findings hold significant implications for enhancing oil recovery in unconventional reservoirs under high-salinity conditions.

Disruption of salt bridge interactions in the inter-domain cleft of the tubulin-like protein FtsZ of Escherichia coli makes cells sensitive to the cell division inhibitor PC190723.

FtsZ forms a ring-like assembly at the site of division in bacteria. It is the first protein involved in the formation of the divisome complex to split the cell into two halves, indicating its importance in bacterial cell division. FtsZ is an attractive target for developing new anti-microbial drugs to overcome the challenges of antibiotic resistance. The most potent inhibitor against FtsZ is PC190723, which is effective against all strains and species of Staphylococcus, including the methicillin- and multi-drug-resistant Staphylococcus aureus and strains of Bacillus. However, FtsZs from bacteria such as E. coli, Streptococcus, and Enterococcus were shown to be resistant to this inhibitor. In this study, we provide further evidence that the three pairwise bridging interactions, between residues S227 and G191, R307 and E198 and D299 and R202, between S7, S9, S10 β-strands and the H7 helix occlude the inhibitor from binding to E. coli FtsZ. We generated single, double and triple mutations to disrupt those bridges and tested the effectiveness of PC190723 directly on Z-ring assembly in vivo. Our results show that the disruption of S227-G191 and R307-E198 bridges render EcFtsZ highly sensitive to PC190723 for Z-ring assembly. Ectopic expression of the double mutants, FtsZ S227I R307V results in hypersensitivity of the susceptible E. coli imp4213 strain to PC190723. Our studies could further predict the effectiveness of PC190723 or its derivatives towards FtsZs of other bacterial genera.

Research on Influencing Factors of Cable Clamp Bolt Elastic Interaction in Cross-Ocean Suspension Bridges

Suspension bridges are the most common type of bridge used to cross the ocean. The cable clamps in suspension bridges clamp the main cables by bolt preload, but the elastic interaction of the bolts reduces the preload, which is detrimental to the force in suspension bridges. However, research on the factors influencing the elastic interaction of cable clamp bolts in suspension bridges is currently limited. This paper aims to explore the law of influence of external factors on the elastic interaction of bolts through a combined approach of theoretical analysis, full-scale experiment, and finite element simulation. The results indicate that the average preload loss was reduced by about 27% when the elastic modulus was increased by about 110%. The average preload loss was reduced by about 45% when the bolt center distance was increased by 75%. The number of bolts has a small effect on the elastic interaction, which can be ignored. When the preload of bolt installation was increased by 133%, the average preload loss was reduced by approximately 125%, which was almost a linear relationship. Tightening the bolt from the center bolt creates greater elastic interaction. The conclusions can provide suggestions for reducing the elastic interaction of bolts in the design and construction of suspension bridge cable clamps.

Vertical Track–Bridge Interaction in Railway Bridges with Ballast Superstructure: Experimental Analysis of Dynamic Stiffness and Damping Behavior

Realistic vibration predictions of railway bridges during high-speed train crossings require reliable dynamic input parameters for the applied calculation model. In particular, the dynamic stiffness and damping properties of the ballast superstructure for the mathematical consideration of the vertical track–bridge interaction (TBI) significantly influence the generated calculation results. However, due to a striking scattering of model-related characteristic values available in the literature, adequate and realistic consideration of the dynamic properties of the vertical TBI in vibration predictions is associated with considerable uncertainties. This uncertainness illustrates the need to determine experimental-based and reliable characteristic values. For targeted and isolated research of dynamic characteristics of vertical TBI, a unique large-scale test facility was developed at the Institute of Structural Engineering at TU Wien, which replicates a section of ballast superstructure on a railway bridge on a scale of 1:1 and excited to vertical movements. This paper presents the essential results and findings from the experiments, focusing on determining the ballast superstructure’s dynamic stiffness and damping characteristics, which can subsequently be implemented in practical applications for vibration predictions. As a result of the experiments, model-related dynamic stiffness and damping parameters are provided to describe the vertical TBI. In addition, the experiments are used to identify destabilization processes occurring in the ballast superstructure as a result of vertical vibrations. The investigations include the vertical TBI’s displacement and acceleration behavior and the track’s settlement behavior due to the entire structure’s vertical movements. These investigations allow for assessing the currently valid, internationally, and nationally normatively prescribed permissible accelerations for railway bridges due to train crossings. The conclusion is that short-term excessive vertical accelerations of the ballast superstructure caused by train passage do not destabilize the ballast bed or considerably change the track position.

Drive-By Identification of Joint Bridge Damage and Surface Roughness Based on Sensitivity Analysis of Residual Contact Point Deflections

Drive-by inspection of bridge damage using a passing vehicle’s dynamic response has great potential in bridge damage identification. Among the current drive-by methodologies, the methods based on bridge modeling have been proposed for the quantitative identification of bridge damage and bridge surface roughness. However, the coupling of bridge damage and unknown surface roughness increases the difficulty of the identification problem and most previous studies conduct the identification task of bridge damage or bridge surface roughness separately. In this paper, a novel method is proposed for the identification of joint bridge damage and bridge surface roughness based on the residual bridge deflections from the front and rear wheels contact points of an instrumented passing vehicle. The vehicle–bridge interaction is analyzed using a half-car model of a four degrees of freedom (4-DOF) with front and rear vehicle wheels. First, the vehicle–bridge unknown forces and displacement of the vehicle axles are identified by the generalized Kalman filter under unknown input (GKF-UI) proposed by the authors. The sensors can be installed conveniently on the vehicle body due to GKF-UI. Then, the residual bridge deflections from the front and rear vehicle wheels contact points are utilized to eliminate the effect of road surface roughness. Afterward, bridge structural damage is identified based on the sensitivity analysis of residual bridge deflections from the front and rear contact points with [Formula: see text]1-norm regularization. Finally, bridge road surface roughness is estimated based on the identified unknown forces and updated bridge model with damage. The results of numerical identification examples demonstrate the effectiveness of the proposed method for the identification of joint bridge damage and surface roughness.

MAGPIE: An interactive tool for visualizing and analyzing protein-ligand interactions.

Quantitative tools to compile and analyze biomolecular interactions among chemically diverse binding partners would improve therapeutic design and aid in studying molecular evolution. Here we present Mapping Areas of Genetic Parsimony In Epitopes (MAGPIE), a publicly available software package for simultaneously visualizing and analyzing thousands of interactions between a single protein or small molecule ligand (the "target") and all of its protein binding partners ("binders"). MAGPIE generates an interactive three-dimensional visualization from a set of protein complex structures that share the target ligand, as well as sequence logo-style amino acid frequency graphs that show all the amino acids from the set of protein binders that interact with user-defined target ligand positions or chemical groups. MAGPIE highlights all the salt bridge and hydrogen bond interactions made by the target in the visualization and as separate amino acid frequency graphs. Finally, MAGPIE collates the most common target-binder interactions as a list of "hotspots," which can be used to analyze trends or guide the de novo design of protein binders. As an example of the utility of the program, we used MAGPIE to probe how different antibody fragments bind a viral antigen; how a common metabolite binds diverse protein partners; and how two ligands bind orthologs of a well-conserved glycolytic enzyme for a detailed understanding of evolutionarily conserved interactions involved in its activation and inhibition. MAGPIE is implemented in Python 3 and freely available at https://github.com/glasgowlab/MAGPIE, along with sample datasets, usage examples, and helper scripts to prepare input structures.

The oncogenic fusion protein EML4-NTRK3 requires three salt bridges for stability and biological activity

Aim of studyChromosomal translocations involving neurotrophic receptor tyrosine kinases (NTRKs) have been identified in 20 % of soft tissue sarcomas. This work focuses on the EML4-NTRK3 translocation identified in cases of Infantile Fibrosarcoma, which contains the coiled-coil multimerization domain of Echinoderm Microtubule-like protein 4 (EML4) fused with the tyrosine kinase domain of Neurotrophic Receptor Tyrosine Kinase 3 (NTRK3). The aim of the study was to test the importance of tyrosine kinase activity and multimerization for the oncogenic activity of EML4-NTRK3. MethodsThese studies examined EML4-NTRK3 proteins containing a kinase-dead or WT kinase domain, together with mutations in specific salt bridge residues within the coiled-coil domain. Biological activity was assayed using focus assays in NIH3T3 cells. The MAPK/ERK, JAK/STAT3 and PI3K/AKT pathways were analyzed for downstream activation of signaling pathways. Localization of EML4-NTRK3 proteins was examined by immunofluorescence microscopy, and the ability of the EML4 coiled-coil domain to drive protein multimerization was examined by biochemical assays. ResultsActivation of EML4-NTRK3 relies on both the tyrosine kinase activity of NTRK3 and salt-bridge stabilization within the coiled-coil domain of EML4. The tyrosine kinase activity of NTRK3 is essential for the biological activation of EML4-NTRK3. Furthermore, EML4-NTRK3 activates downstream signaling pathways MAPK/ERK, JAK/STAT3 and PKC/PLCγ. The disruption of three specific salt bridge interactions within the EML4 coiled-coil domain of EML4-NTRK3 blocks downstream activation, biological activity, and the ability to hetero-multimerize with EML4. We also demonstrate that EML4-NTRK3 is localized in the cytoplasm and fails to associate with microtubules. Concluding statementThese data suggest potential therapeutic strategies for Infantile Fibrosarcoma cases bearing EML4-NTRK3 fusion through inhibition of salt bridge interactions and disruption of multimerization.

A Numerical Investigation of Longitudinal Track–Bridge Interaction in Simply Supported Precast Concrete Girder Railway Bridges

A Numerical Investigation of Longitudinal Track–Bridge Interaction in Simply Supported Precast Concrete Girder Railway Bridges

Bridge damage identification based on synchronous statistical moment theory of vehicle–bridge interaction

AbstractConsidering the weak noise resistance and low identification efficiency of traditional bridge damage identification methods, a data‐driven approach based on synchronous statistical moment theory and vehicle–bridge interaction vibration theory is proposed. This method involves two main steps. First, a two‐axle test vehicle is used to collect acceleration response signals synchronously from adjacent designated measurement points while stationary. This operation is repeated to calculate the second‐order statistical moment curvature (SOSMC) difference of entire bridge points corresponding signals in different states. By comparing with the reference value, the preliminary damage location of the bridge can be obtained. Second, the first‐order modal shape curve is constructed using the second‐order statistical moment (SOSM). The refined identification of bridge damage is then based on an improved direct stiffness back calculation of the bridge's stiffness. This article proposes the synchronization theory for the first time and combines it with the statistical moment clustering method, forming an innovative approach to obtaining structural vibration modes. The effectiveness of this method has been well validated through numerical simulations with different parameters and on‐site bridge tests. The research results indicate that SOSMC indicators have better noise resistance and higher recognition efficiency in identifying damage locations, compared to modal curvature and flexibility curvature indicators. Additionally, compared to transfer rate and random subspace methods, the SOSM method results in smaller error and higher identification efficiency.

Exploring the Impact of C-Terminal Based Pentapeptides on the Disassembly of Aβ42 Fibrils.

An effective therapeutic strategy to suppress Alzheimer's disease (AD) progression is to disrupt β-sheet rich neurotoxic soluble amyloid-β (Aβ) aggregates. Previously, we identified new pentapeptides (RVVPI and RIAPA) with notably enhanced ability to block Aβ42 aggregation as compared to Aβ42 C-terminal derived peptide RIIGL using integrated computational protocol. In this work, the potential of RIIGL, RVVPI, and RIAPA for the structural destabilization of Aβ42 protofibril was assessed by molecular dynamics (MD) simulations and in vitro studies. The binding free energy analysis depicts that charged residues influence Aβ42 protofibril-pentapeptide interactions. Notably, RVVPI displays a more pronounced destabilization effect than other peptides due to higher conformational fluctuations, and disruption of salt bridge (K28-A42) interactions in Aβ42 protofibril. RVVPI exhibited highest inhibitory activity (Inhibition= 66.2%, IC50= 5.57 ± 0.83 µM) against Aβ42 aggregation consistent with computational results. Remarkably, RVVPI displayed ~4.5 fold lower IC50 value as compared to RIIGL. ThT and TEM studies highlighted the enhanced efficiency of RVVPI (62.4%) in the disassembly of pre-formed Aβ42 fibrils than RIIGL and RIAPA. The combined in silico and in vitro studies identified a new peptide, RVVPI, as an efficient inhibitor of Aβ42 fibrillation and disassembly of Aβ42 aggregates.