Effect of fly ash and curing temperature on the properties of magnesium phosphate repair mortar.

This article is aimed at discussing the combined effect of mineral admixture and servicing temperature, especially in cold environment, on the properties of magnesium phosphate repair mortar (MPM). The influence mechanism of fly ash content on the microstructure and performance of MPM were firstly investigated, and then the evolution rules in properties of fly ash modified MPM cured at - 20 °C, 0 °C, 20 °C and 40 °C were further revealed. The results show that the incorporation of fly ash has no significant effect on the setting time and fluidity of MPM. When MPM is modified with 10 wt% and 15 wt% fly ash, its mechanical properties, adhesive strength, water resistance, and volume stability are effectively improved. Fly ash reduces the crystallinity and continuity of struvite enriched in hardened MPM, and its particles are embedded among struvite and unreacted MgO. The compressive strength of MPM-10 cured for various ages increases with the elevating of curing temperature, while the flexural strength, interfacial bonding strength, strength retention and linear shrinkage exhibits the opposite laws. When cured at 0 °C and - 20 °C, MPM-10 still has good early strength, water resistance and interfacial bonding properties, which indicates that MPM-10 provides with an ability of emergency repair of cracked components served in cold environments.

Evaluation of DNA-protein complex structures using the deep learning method.

Biological processes such as transcription, repair, and regulation require interactions between DNA and proteins. To unravel their functions, it is imperative to determine the high-resolution structures of DNA-protein complexes. However, experimental methods for this purpose are costly and technically demanding. Consequently, there is an urgent need for computational techniques to identify the structures of DNA-protein complexes. Despite technological advancements, accurately identifying DNA-protein complexes through computational methods still poses a challenge. Our team has developed a cutting-edge deep-learning approach called DDPScore that assesses DNA-protein complex structures. DDPScore utilizes a 4D convolutional neural network to overcome limited training data. This approach effectively captures local and global features while comprehensively considering the conformational changes arising from the flexibility during the DNA-protein docking process. DDPScore consistently outperformed the available methods in comprehensive DNA-protein complex docking evaluations, even for the flexible docking challenges. DDPScore has a wide range of applications in predicting and designing structures of DNA-protein complexes.

Dynamic geometry design of cyclic peptide architectures for RNA structure.

Designing inhibitors for RNA is still challenging due to the bottleneck of maintaining the binding interaction of inhibitor-RNA accompanied by subtle RNA flexibility. Thus, the current approach usually needs to screen thousands of candidate inhibitors for binding. Here, we propose a dynamic geometry design approach to enrich the hits with only a tiny pool of designed geometrically compatible scaffold candidates. First, our method uses graph-based tree decomposition to explore the complementarity rigid binding cyclic peptide and design the amino acid side chain length and charge to fit the RNA pocket. Then, we perform an energy-based dynamical network algorithm to optimize the inhibitor-RNA hydrogen bonds. Dynamic geometry-guided design yields successful inhibitors with low micromolar binding affinity scaffolds and experimentally competes with the natural RNA chaperone. The results indicate that the dynamic geometry method yields higher efficiency and accuracy than traditional methods. The strategy could be further optimized to design the length and chirality by adopting nonstandard amino acids and facilitating RNA engineering for biological or medical applications.

Interfacial Bond-Slip Model for CFRP Plate Externally Bonded to Corroded Steel Plate.

The purpose of this study is to establish the interfacial bond-slip model for CFRP plate externally bonded to corroded steel plate. The present bond-slip models for CFRP materials bonded to uncorroded steel plate were first reviewed. Thirty-four double-lap joints were tested to investigate the effect of corrosion duration and adhesive thickness on the bond behavior between CFRP plates and corroded steel plates, and the bond-slip curves for the bonding interface with different adhesive thickness and corrosion duration were obtained combined with the CFRP plate strain distribution data. A new bond-slip model for CFRP plate externally bonded to corroded steel plate was proposed, and the expression of the characteristic parameters, which included the maximum bond resistance τf, the relative slip at the peak bond stress s1, the fitting parameter α, and the interfacial fracture energy Gf, were also developed based on the careful regression analysis of the present data. The influence of the corrosion duration and construction adhesive thickness on the bond-slip relationship were accounted together and expressed as a new parameter; that is, the effective adhesive thickness teff. The comparison between the predicted values and experimental results indicated that the proposed bond-slip model can be applied to reproduce the structural response of the CFRP plate-corroded steel plate double-lap joint with reasonable accuracy. The outcome of this study can provide meaningful references and essential data for the reliable application of CFRP strengthening systems in the performance improvement of corroded steel structures.

Fatigue Crack Propagation Prediction of Corroded Steel Plate Strengthened with Carbon Fiber Reinforced Polymer (CFRP) Plates.

The purpose of this study is to investigate the mechanism of improving fatigue performance and the estimation model of fatigue life for corroded steel plate strengthened with CFRP plates. A new two-stage fatigue crack propagation prediction model for the corroded steel plate strengthened with CFRP plates was proposed; moreover, the identification of critical rust pits and the equivalent method of initial cracks, and the calculation method of stress intensity factor (SIF) values at the crack tip were established. The accuracy of the proposed model was verified by comparing the predicted and tested fatigue life of the corroded steel plate strengthened with CFRP plates. Finally, the proposed two-stage crack propagation model was applied to carry out a parameter analysis to investigate the effect of weight loss rate, equivalent initial crack size, adhesive thickness, CFRP stiffness and CFRP prestress level on the fatigue crack propagation of the corroded steel plate strengthened with CFRP plates. Results showed that the maximum depth and the average width of the rust pits were suggested to be taken as the equivalent dimensions of the initial semi-elliptical surface crack for the fatigue crack propagation prediction of corroded steel plate strengthened with CFRP plates. Increasing the weight loss rate of the corroded steel plate, the initial crack size or the adhesive thickness would accelerate the crack growth and reduce the fatigue life, whereas increasing the stiffness or prestress level of the CFRP plate would significantly reduce the crack growth rate and increase the fatigue life. The smaller the initial crack size, the more sensitive the crack propagation life was to the variation of equivalent initial crack size. The influence of adhesive thickness on the fatigue life was limited and convergent, and the application of prestressing could significantly improve the utilization rate of CFRP materials and the fatigue strengthening effect of the corroded steel plate.

Stress Concentration Analysis of the Corroded Steel Plate Strengthened with Carbon Fiber Reinforced Polymer (CFRP) Plates.

The purpose of this study is to investigate the stress concentration of a corroded steel plate strengthened with carbon fiber reinforced polymer (CFRP) plates. An accelerated corrosion experiment was first executed to acquire corroded steel plates, and then surface profile measurements were conducted to obtain 3D coordinate data of the corroded steel surface. Finite element models considering the surface morphology of the corroded steel plate and the interfacial bonding properties between the CFRP plate and the corroded steel plate were established to investigate the stress concentration of the corroded steel plate strengthened with and without CFRP plates. The reliability of the numerical modeling method was verified based on a mesh convergence analysis and a comparison of the fatigue test, 3D morphology scanning, and numerical analysis results. Specimens with five levels of corrosion damage, six kinds of CFRP-strengthening stiffness, five kinds of adhesive thickness, and five levels of CFRP prestress were numerically modeled. The primary indications consist of features of stress distribution, and the stress concentration factors Kt and Ktg were analyzed. Results showed that the features of stress distribution and the stress concentration factor Kt of the corroded steel plate strengthened with and without CFRP plates are only related to the shape, size, and position of rust pits, but not to the degree of uniform corrosion or the reinforcement parameters. The value of Kt for the corroded steel plate with a corrosion duration of 6~18 months and a weight loss rate of 9.16~21.78% was approximately 1.199~1.345. The converted stress concentration factor Ktg has more practical significance than the stress concentration factor Kt in describing the influence of corrosion and CFRP reinforcement on the peak tensile stress of the corroded steel plate. The value of Ktg increased linearly with the increase of the weight loss rate of the corroded steel plate and decreased appreciably with the increase of the strengthening stiffness and prestress level of the CFRP plates, and it presented a very small increasing trend with the increase of the adhesive thickness.

Estimation of Bond Strength and Effective Bond Length for the Double Strap Joint between Carbon Fiber Reinforced Polymer (CFRP) Plate and Corroded Steel Plate.

In this paper, we examine the development of the estimation models of bond strength and effective bond length for a double strap joint between carbon fiber reinforced polymer (CFRP) plate and corroded steel plate. The experimental study on the bond behavior between CFRP plate and corroded steel plate is summarized first and the analytical interfacial bond-slip model for CFRP plate externally bonded to corroded steel plate is proposed. Based on the theoretical stress analysis for the CFRP plate-corroded steel plate double-lap joint, the piecewise expressions of the interfacial shear stress and the normal peel stress of the interface between CFRP plate and corroded steel plate were established. The estimation models of the bond strength and the effective bond length for the double strap joint between the CFRP plate and the corroded steel plate were consequently developed on the basis of interfacial stress distribution equations and the stress boundary conditions. The comparison between the predicted and experimental results indicated that the proposed models could be adopted to predict the bond strength and effective bond length for the CFRP plates externally bonded to corroded steel substrates with reasonable accuracy. The proposed estimation models are expected to provide meaningful references and essential data for the reliable application of CFRP strengthening system to the performance improvement of corroded steel structures.

Updated Pharmacological Effects, Molecular Mechanisms, and Therapeutic Potential of Natural Product Geniposide.

At present, the potential of natural products in new drug development has attracted more and more scientists' attention, and natural products have become an important source for the treatment of various diseases or important lead compounds. Geniposide, as a novel iridoid glycoside compound, is an active natural product isolated from the herb Gardenia jasminoides Ellis (GJ) for the first time; it is also the main active component of GJ. Recent studies have found that geniposide has multiple pharmacological effects and biological activities, including hepatoprotective activity, an anti-osteoporosis effect, an antitumor effect, an anti-diabetic effect, ananti-myocardial dysfunction effect, a neuroprotective effect, and other protective effects. In this study, the latest research progress of the natural product geniposide is systematically described, and the pharmacological effects, pharmacokinetics, and toxicity of geniposide are also summarized and discussed comprehensively. We also emphasize the major pathways modulated by geniposide, offering new insights into the pharmacological effects of geniposide as a promising drug candidate for multiple disorders.

Enantioselective Reduction of α,ß-Unsaturated Ketones and Aryl Ketones by Perakine Reductase.

This report describes the enantioselective reduction of structurally diverse α,ß-unsaturated ketones and aryl ketones by perakine reductase (PR) from Rauvolfia. This enzymatic reduction produces α-chiral allylic and aryl alcohols with excellent enantioselectivity and most of the products in satisfactory yields. Furthermore, the work demonstrates 1 mmol scale reactions for product delivery without any detrimental effect on yield and enantioselectivity. The catalytic mechanism, determined by 3D-structure-based modeling of PR and ligand complexes, is also described.

Effect of external periodic signals and electromagnetic radiation on autaptic regulation of neuronal firing.

An improved Hindmarsh-Rose (HR) neuron model, where the memristor is a bridge between membrane potential and magnetic flux, can be used to investigate the effect of periodic signals on autaptic regulation of neurons under electromagnetic radiation. Based on the improved HR model driven by periodic high-low-frequency current and electromagnetic radiation, the responses of electrical autaptic regulation with diverse high-low-frequency signals are investigated using bifurcation analysis. It is found that the electrical modes of neurons are determined by the selecting parameters of both periodic high and low-frequency current and electromagnetic radiation, and the Hamiltonian energy depends on the neuronal firing modes. The effects of Gaussian white noise on the membrane potential are discussed using numerical simulations. It is demonstrated that external high-low-frequency stimulus plays a significant role in the autaptic regulation of neural firing mode, and the electrical mode of neurons can be affected by the angular frequency of both high-low-frequency forcing current and electromagnetic radiation. The mechanism of neuronal firing regulated by high-low-frequency signal and electromagnetic radiation discussed here could be applied to research neuronal networks and synchronisation modes.

Network of Conformational Transitions Revealed by Molecular Dynamics Simulations of the Carbonic Anhydrase II Apo-Enzyme.

Human carbonic anhydrase II (HCA II) is an enzyme that catalyzes the reversible hydration of CO2 into bicarbonate (HCO3-) and a proton (H+) as well as other reactions at an extremely high rate. This enzyme plays fundamental roles in human physiology/pathology, such as controlling the pH level in cells and so on. However, the binding mechanism between apo-HCA II and CO2 or other ligands as well as related conformational changes remains poorly understood, and atomic investigation into it could promote our understanding of related internal physiological/pathological mechanisms. In this study, long-time atomic molecular dynamics simulations as well as the clustering and free-energy analysis were performed to reveal the dynamics of apo-HCA II as well as the mechanism upon ligand binding. Our simulations indicate that the crystallographic B-factors considerably underestimate the loop dynamics: multiple conformations can be adopted by loops 1 and 2, especially for loop 1 because loop 1 is one side of the binding pocket, and its left-to-right movement can compress or extend the binding pocket, leading to one inactive (closed) state, three intermediate (semiopen) states, and one active (open) state; CO2 cannot get into the binding pocket of the inactive state but can get into those of intermediate and active states. The coexistence of multiple conformational states proposes a possible conformational selection model for the binding mechanism between apo-HCA II and CO2 or other ligands, revising our previous view of its functional mechanism of conformational change upon ligand binding and offering valuable structural insights into the workings of HCA II.

Fluctuation and noise propagation in phenotypic transition cascades of clonal populations.

Quantitative modeling of fluctuations of each phenotype is a crucial step towards a fundamental understanding of noise propagation through various phenotypic transition cascades. The theoretical formulas for noise propagation in various phenotypic transition cascades are derived by using the linear noise approximation of master equation and the logarithmic gain. By virtue of the theoretical formulas, we study the noise propagation in bidirectional and unidirectional phenotypic transition cascades, respectively. It is found that noise propagation in these two phenotypic transition cascades evidently differs: In the bidirectional cascade, a systemic random environment is provided by a correlated global component. The total noise of each phenotype is mainly determined by the intrinsic noise and the transmitted noise from other phenotypes. The intrinsic noise enlarged by interconversion through an added part shows a novel noise propagation mechanism. However, in the unidirectional cascade, the random environment of each downstream phenotype is provided by upstream phenotypes. The total noise of each downstream phenotype is mainly determined by the transmitted noises from upstream phenotypes. The intrinsic noise and the conversion noise can propagate in both bidirectional and unidirectional phenotypic transition cascades.

[Ammonium Adsorption Characteristics in Aqueous Solution by Dairy Manure Biochar].

The adsorption characteristics of ammonium from aqueous solution onto biochar derived from dairy manure were investigated as a function of parameters such as solution pH, particle size, adsorbent dosage, temperature and competitive cations. The results indicated that the effects of other cations on the adsorption of ammonium followed the order of preference Na > Ca2+ at identical mass concentrations. It was observed that pH played an important role in the ammonium adsorption and the optimal pH values ranged between 5 and 8. The kinetic data fitted the pseudo-second-order model (R2 = 0.967 3) but showed very poor fits for the pseudo-first-order model (R2 = 0.765 9) and the Elovich model (R2 = 0.724 9). The results from the Intra-particle model also showed that there were two separate stages in sorption process, which were external diffusion and the diffusion of inter-particle. Adsorption isotherms for dairy manure biochar were fitted the Freundlich model (R2 = 0.976 2) more effectively than other models. Thermodynamics parameters such as free energy (ΔGθ), enthalpy (ΔHθ), and entropy (ΔSθ) were also determined, which indicated that the adsorption was a spontaneous and endothermic process.

Fluctuations of cell population in a colonic crypt.

The number of stem cells in a colonic crypt is often very small, which leads to large intrinsic fluctuations in the cell population. Based on the model of cell population dynamics with linear feedback in a colonic crypt, we present a stochastic dynamics of the cell population [including stem cells (SCs), transit amplifying cells (TACs), and fully differentiated cells (FDCs)]. The Fano factor, covariance, and susceptibility formulas of the cell population around the steady state are derived by using the Langevin theory. In the range of physiologically reasonable parameter values, it is found that the stationary populations of TACs and FDCs exhibit an approximately threshold behavior as a function of the net growth rate of TACs, and the reproductions of TACs and FDCs can be classified into three regimens: controlled, crossover, and uncontrolled. With the increasing of the net growth rate of TACs, there is a maximum of the relative intrinsic fluctuations (i.e., the Fano factors) of TACs and FDCs in the crossover region. For a fixed differentiation rate and the net growth rate of SCs, the covariance of fluctuations between SCs and TACs has a maximum in the crossover region. However, the susceptibilities of both TACs and FDCs to the net growth rate of TACs have a minimum in the crossover region.

Robustness and backbone motif of a cancer network regulated by miR-17-92 cluster during the G1/S transition.

Based on interactions among transcription factors, oncogenes, tumor suppressors and microRNAs, a Boolean model of cancer network regulated by miR-17-92 cluster is constructed, and the network is associated with the control of G1/S transition in the mammalian cell cycle. The robustness properties of this regulatory network are investigated by virtue of the Boolean network theory. It is found that, during G1/S transition in the cell cycle process, the regulatory networks are robustly constructed, and the robustness property is largely preserved with respect to small perturbations to the network. By using the unique process-based approach, the structure of this network is analyzed. It is shown that the network can be decomposed into a backbone motif which provides the main biological functions, and a remaining motif which makes the regulatory system more stable. The critical role of miR-17-92 in suppressing the G1/S cell cycle checkpoint and increasing the uncontrolled proliferation of the cancer cells by targeting a genetic network of interacting proteins is displayed with our model.

Intrinsic noise in post-transcriptional gene regulation by small non-coding RNA.

Small non-coding RNA (sRNA) plays very important role in the post transcriptional regulation in various organisms. In complex regulatory networks, highly significant relative fluctuations in RNAs copy numbers can not be neglected due to very small copy number of individual RNA molecules. Here we consider two simple regulation schemes, where one is single target gene regulated by a sRNA and the other is two target mRNAs (mRNA(R) and mRNA(T)) regulated by one sRNA. The Fano factor (a measure of the relative size of the internal fluctuations) formulae of RNA molecules in the post transcriptional regulation are theoretically derived by using of the Langevin theory. For single target gene regulated by a sRNA, it is shown that the intrinsic noise of both mRNA and sRNA approaches the bare Poissonian limit in the regimen of both target RNA silencing and surviving. However, the strong anti-correlation between the fluctuations of two components result in a large intrinsic fluctuations in the level of RNA molecules in the regimen of crossover. For two target mRNAs regulated by one sRNA, in the regimen of crossover, it is found that, with the increasing of transcription rate of target mRNA(T), the maximal intrinsic fluctuation of RNA molecules is shifted from sRNA to target mRNA(R), and then to target mRNA(T). The intrinsic noise intensity of target mRNA(R) is determined by both the transcriptional rate of itself and that of sRNA, and independent of the transcriptional rate of the other target mRNA(T).