Dynamic Structure Research Articles

“All-in-one” tea polyphenol-modified injectable hyaluronic acid-based hydrogel for diabetic wound healing

Refractory diabetic wounds are a devastating and rapidly growing clinical problem, which is associated with high incidence rates, mortality, and recurrence rates. Therapeutic angiogenesis in wound tissues is essential to the healing of diabetic wounds. However, the presence of excessive oxidative stress in diabetic wounds hinders angiogenesis, and conventional anti-oxidative approaches are inefficient to compensate for the systematically impaired angiogenesis. Here, a multifunctional supramolecular hyaluronic acid hydrogel dressing for diabetic wounds is successfully designed and constructed (GHPM). The GHPM hydrogel features outstanding properties, including excellent tissue adhesion, antibacterial ability, conductivity, and antioxidant properties. Based on the dynamic crosslinking structure, the GHPM hydrogel also presents adequate injectable and self-healing capabilities, which play a vital role in covering irregular or deep wounds. Additionally, diabetic wounds treated with GHPM hydrogel showed a significant acceleration of wound closure by preventing wound infection, reducing oxidative stress, and accelerating collagen deposition. More interestingly, the combination of electrical stimulation and GHPM hydrogel can effectively promote angiogenesis and neurogenesis, further accelerating diabetic wound healing in an all-around way. This advanced collaborative strategy opens a new avenue in treating diabetic wounds.

Differential interference with actin-binding protein function by acute Cytochalasin B.

Dynamic actin filament remodeling is crucial for a plethora of fundamental cell biological processes, ranging from cell division and migration to cell communication, intracellular trafficking or tissue development. Cytochalasin B and -D are fungal secondary metabolites frequently used for interference with such processes. Although generally assumed to block actin filament polymerization at their rapidly growing barbed ends and compete with regulators at these sites, our molecular understanding of their precise effects in dynamic actin structures is scarce. Here we combine live cell imaging and analysis of fluorescent actin-binding protein dynamics with acute treatment of lamellipodia in migrating cells with cytochalasin B. Our results show that in spite of an abrupt halt of lamellipodium protrusion, cytochalasin B affects various actin filament barbed end-binding proteins in a differential fashion. Cytochalasin B enhances instead of diminishes the accumulation of prominent barbed end-binding factors such as Ena/VASP family proteins and heterodimeric capping protein (CP) in the lamellipodium. Similar results were obtained with cytochalasin D. All these effects are highly specific, as cytochalasin-induced VASP accumulation requires the presence of CP, but not vice versa , and coincides with abrogation of both actin and VASP turnover. Cytochalasin B can also increase apparent barbed end interactions with the actin-binding β-tentacle of CP and partially mimic its Arp2/3 complex-promoting activity in the lamellipodium. In conclusion, our results reveal a new spectrum of cytochalasin activities on barbed end-binding factors, with important implications for the interpretation of their effects on dynamic actin structures.

Dynamically crosslinked poly(vinyl alcohol)/borax strain sensors for organ motion monitoring

Wearable electronic sensing devices can detect various physiological responses and subtle changes in the skin in real time for the early detection and treatment of potential health problems or diseases. Among them, flexible hydrogel-based sensors are attracting much attention because they can monitor human movements and physiological signals. However, developing hydrogel-based sensors with rapid self-healing, self-adhesion, excellent conductivity and sensitivity characteristics remains a challenge. In this study, a hydrogel with a dynamic reversible network structure was developed using poly(vinyl alcohol) (PVA), hyaluronic acid (HA), borax, and tannic acid (TA). Multiple hydrogen bonds resulting from abundant hydroxyl groups in the hydrogel composed of borax, PVA, and TA improved the self-healing ability of the hydrogel, and the conductivity of this system (∼0.62 S/m) was improved upon immersion in NaCl. The optimum hydrogel exhibited excellent elasticity (∼941 %), biocompatibility, and demonstrated adhesion to porcine skin (dry: 5.3 kPa; wet: 2 kPa) without external stimulation in air and underwater environments. In addition, the fabricated hydrogels exhibited excellent sensitivity (∼300 % strain, gauge factor (GF) = 2.86; 300–900 % strain, GF = 4.95), allowing them to detect and distinguish various large and small human movements. Hydrogels that exhibited stable electrical signals even after 500 cycles were obtained, and the PBHT-N hydrogels were implanted into rabbit hearts to verify their applicability as strain sensors for effective real-time heart rate monitoring during rapid body movement.

Empowering E-mobility: Day-ahead dynamic time of use tariff for electric vehicle charging

The greenhouse gases and preservation of the environment have been the most prioritized concern in many countries and international organizations, leading to set aims and initiatives for lowering the dependency on fossil fuels and minimizing carbon emissions. As a part of many initiatives, great emphasis is given to promoting electric vehicles (EVs) over their traditional carbon fuel-based counterpart. To support large-scale EV adoption, a dynamic tariff scheme is required that addresses complex issues like user comfort, savings, and utility revenue. In this research work, a dynamic pricing scheme is modeled for the centralized EV charging stations (EVCS) on a residential feeder. This pricing scheme integrates the existing static time of use (ToU) pricing to an hourly dynamic ToU tariff that varies according to the demand level in the residential feeder. The proposed tariff plan provides a day-ahead dynamic structure with a probable price variation range to aid the EV owners and the day-ahead charging mechanism to schedule the EVs beforehand. The developed scheme calculates the returns and adjusts the tariff including the demand charge and the recovery component on a daily, monthly, and yearly basis for the unsatisfactory investment revenue. Also, user convenience is ensured by setting the minimum possible tariff as well as satisfying the minimum revenue target with the integration of particle swarm optimization (PSO) in designing the pricing structure. The simulation results demonstrate the effectiveness of the proposed dynamic pricing scheme maintaining a trade-off between the interests of all parties involved. Moreover, the simulation outcome of the test case indicates that EV owners can save more than 32 % on charging bills if they plan correctly. On the other hand, the utility can earn more than 2.4 times the existing rate during the peak time of the residential feeder.

Self-diffusion is temperature independent on active membranes.

Molecular transport maintains cellular structures and functions. For example, lipid and protein diffusion sculpts the dynamic shapes and structures on the cell membrane that perform essential cellular functions, such as cell signaling. Temperature variations in thermal equilibrium rapidly change molecular transport properties. The coefficient of lipid self-diffusion increases exponentially with temperature in thermal equilibrium, for example. Hence, maintaining cellular homeostasis through molecular transport is hard in thermal equilibrium in the noisy cellular environment, where temperatures can fluctuate widely due to local heat generation. In this paper, using both molecular and lattice-based modeling of membrane transport, we show that the presence of active transport originating from the cell's cytoskeleton can make the self-diffusion of the molecules on the membrane robust to temperature fluctuations. The resultant temperature-independence of self-diffusion keeps the precision of cellular signaling invariant over a broad range of ambient temperatures, allowing cells to make robust decisions. We have also found that the Kawasaki algorithm, the widely used model of lipid transport on lattices, predicts incorrect temperature dependence of lipid self-diffusion in equilibrium. We propose a new algorithm that correctly captures the equilibrium properties of lipid self-diffusion and reproduces experimental observations.

Mesoscopic structure graphs for interpreting uncertainty in non-linear embeddings

Probabilistic-based non-linear dimensionality reduction (PB-NL-DR) methods, such as t-SNE and UMAP, are effective in unfolding complex high-dimensional manifolds, allowing users to explore and understand the structural patterns of data. However, due to the trade-off between global and local structure preservation and the randomness during computation, these methods may introduce false neighborhood relationships, known as distortion errors and misleading visualizations. To address this issue, we first conduct a detailed survey to illustrate the design space of prior layout enrichment visualizations for interpreting DR results, and then propose a node-link visualization technique, ManiGraph. This technique rethinks the neighborhood fidelity between the high- and low-dimensional spaces by constructing dynamic mesoscopic structure graphs and measuring region-adapted trustworthiness. ManiGraph also addresses the overplotting issue in scatterplot visualization for large-scale datasets and supports examining in unsupervised scenarios. We demonstrate the effectiveness of ManiGraph in different analytical cases, including generic machine learning using 3D toy data illustrations and fashion-MNIST, a computational biology study using a single-cell RNA sequencing dataset, and a deep learning-enabled colorectal cancer study with histopathology-MNIST.

Revealing the Effect of Dynamic Structural Evolution on Triple Junction Deformation Mechanism: Molecular Dynamics Simulations and an Energetic Model

Abstract Triple junction (TJ) migration is a plastic deformation mechanism in polycrystalline metals mediated by the interplay between neighboring grain boundaries (GBs). Compared with GB migration, the dynamic change of TJ structure during migration and its impact on subsequent TJ behavior is often overlooked. In this study, we explore the effect of dynamic TJ structure evolution on TJ deformation mechanism in a face-centered cubic metal Au model using molecular dynamics simulations. Our analysis reveals that the dislocation accumulation at TJ due to inconsistent disconnection nucleation from neighboring GBs can influence the stick-slip behavior of TJ migration. With the dynamic change of TJ structure, the velocity of TJ migration is gradually reduced, leading to a transition from TJ migration to dislocation emission from TJ. We have developed an energetic model to evaluate the critical stresses required for TJ migration and dislocation emission, providing an explanation of the competition between TJ migration and dislocation emission. Our findings deepen the understanding of TJ-governed plastic deformation mechanisms in polycrystalline materials.

Interferometric Radars for Bridge Monitoring: Comparison among X-Bands, Ku-Bands, and W-Bands

Interferometric radars are widely used sensors for structural health monitoring. They are able to perform dynamic measurements of displacement with sub-millimeter precision. Today, the Ku-band is the most common, due to the spread of commercial systems operating in this band. At the same time, the W-band sensors are gaining ever more interest. Other popular systems work in the X-band. Since the characteristics of the measurements dramatically depend on the operative frequency, it is essential to highlight their differences. For instance, higher frequency allows for high displacement resolution, but it is more subject to phase wrapping and decorrelation effects. In this paper, a direct comparison between radars operating in X, Ku, and W-band for bridge monitoring is carried out. The radars provide frequency-modulated continuous-wave signals. Experimental campaigns were performed both in controlled and realistic scenarios (a stayed bridge). The results of the experiments demonstrate that all the three sensors are suitable for performing dynamic structure monitoring despite their differences. It is worth noting that this comparative analysis has highlighted the role of amplitude variation in phase/displacement measurement. Regarding this point, the three different bands exhibit significant differences.

Soliton and lump and travelling wave solutions of the (3 + 1) dimensional KPB like equation with analysis of chaotic behaviors

Nonlinear evolution equations (NLEEs) have a wide range of applications in various fields, including physics, engineering, biology, economics, and more. These equations are used to describe complex systems that change over time, where the state or behavior of the system not only depends on the current situation, but may also be related to the past. A deep understanding of the solutions to NLEEs is of great significance for predicting and controlling the behavior of complex systems. The (3 + 1)-dimensional Kadomtsev-Petviashvili-Boussinesq-like (KPB-like) equation represents a partial differential equation that describes nonlinear wave phenomena in multi-dimensional spaces. This model is commonly employed in fields such as fluid dynamics, plasma physics, and nonlinear optics to study wave behaviors. This paper investigates the KPB-like equations, which have meaningful physical implications in describing nonlinear wave phenomena. Hirota bilinear method is employed to derive the bilinear form for the KPB-like equation and 1-soliton, 2-soliton, lump, and travelling wave solutions are studied to this kind of nonlinear model. In addition, the chaotic behaviors of soliton and lump solutions are explored via applying the Duffing chaotic system. To have a better understanding of dynamic structures, 3D, line, density and contour map plots of begotten results are displayed. Our results indicate the directness and effectiveness of the applied method for analyzing high-dimensional differential equations that arise in nonlinear science.

Finite element method (FEM) analysis of heat transfer by natural convection in a circular cavity containing a corrugated hollow cylinder

PurposeThe purpose of this study is to analyze the free convection phenomena arising from a temperature disparity between a cold circular cylinder and a heated corrugated cylinder.Design/methodology/approachNumerical simulations were used to analyze the convection patterns. The inner cylinder, made of a thermally conductive solid material, was heated through its inner surface, while the space between the cylinders was filled with air. The governing equations for velocity, pressure and temperature were solved using a Galerkin finite element method-based solver for partial differential equations.FindingsThe study explored various parameters affecting the dynamic and thermal structure of the flow, including the Rayleigh number (103 ≤ Ra ≤ 106), the number of corrugations of the inner cylinder (3 ≤ N ≤ 18), the thermal conductivity of the hollow cylinder (1 ≤ K ≤ 200) and the angle of inclination of the inner cylinder (0° ≤ φ ≤ 90°). Results indicated a notable sensitivity of flow intensity to changes in the Rayleigh number and the inner cylinder’s inclination angle φ. Particularly, for Ra = 106, the average heat transfer rate increased by 203% with a K ratio increment from 1 to 100 but decreased by 16.3% as the number of corrugations increased from 3 to 18.Originality/valueThis research contributes to understanding the complex interplay between geometry, thermal properties and flow dynamics in natural convection systems involving cylindrical geometries. The findings offer useful insights for improving the transfer of heat procedures in real-world situations.

An adaptive and multi-path greedy perimeter stateless routing protocol in flying ad hoc networks

In recent years, flying ad hoc networks (FANET), formed from unmanned aerial vehicles (UAVs), have absorbed the attention of academic and industrial research communities due to their many applications in military and civilian fields. FANETs benefit from unique features, including highly moving UAVs and dynamic topological structure. Therefore, most existing routing protocols, such as the greedy perimeter stateless routing (GPSR), are not compatible with the FANET environment and its specific features. To improve the performance of GPSR in FANET, it is important to address several challenges, namely the selection of the right period for broadcasting hello messages in the network, the selection of the right criteria for selecting the next-hop node, and the improvement of reliability in the data transfer process. In this paper, an adaptive and multi-path greedy perimeter stateless routing (AM-GPSR) protocol is suggested in FANETs. It includes two new strategies, namely adaptive hello strategy and multi-path greedy forwarding strategy. The adaptive hello strategy defines a special hello broadcast period for each UAV according to its speed and error between two estimated and actual positions. Furthermore, the greedy forwarding strategy carries out a filtering operation on candidate nodes and eliminates border UAVs and those that are far from the destination. Then, candidate UAVs are prioritized based on the time to reach the destination and buffer capacity, and UAVs with higher priorities are chosen to send data packets. Finally, AM-GPSR applies a greedy multi-path forwarding strategy to increase reliability in the data transmission process. Lastly, the simulation of AM-GPSR is done via the network simulator version 2 (NS2) to evaluate its performance. This evaluation process includes two different scenarios, i.e. change in the speed of UAVs and change in their communication range. In this process, AM-GPSR is compared with three other methods, namely the aerial greedy geographic routing (AGGR) protocol, the geolocation assisted aeronautical routing protocol (AeroRP), and GPSR. This comparison shows the successful performance of AM-GPSR in terms of delivery success rate, throughput, and delay. Although the control overhead of the proposed method is more than that of AGGR.

Lightweight, ultra-compressed, and environmentally friendly wood/TPU aerogel sensor based on optimized performance of dynamic 3D pore structure

Although bio-based sensing materials have a wide range of applications in the field of pressure detection, they still need to improve their sensitivity, detection limit and hysteresis. This paper studied the relationship between the 3D pore structure and sensing performance under dynamics. Using Balsa wood as the substrate, CWA/TPU aerogel and its sensor were prepared with lightweight, compressibility, highly sensitivity, wide-detection, and low-hysteresis. Meanwhile, the brittleness problem of the carbonized aerogel was solved by uniformly attaching TPU to the aerogel interface. In this paper, the 3D structure of CWA/TPU aerogel during compression was reconstructed by Micro-XCT technology, and the results show that the sensitivity of the bio-based carbonized material is directly proportional to the porosity and inversely proportional to the aspect ratio. This CWA/TPU aerogel pressure sensor has a high sensitivity of 76.18 kPa−1 in a wide detection limit of 0.6 Pa–100 kPa, 90 % supercompression strain, ±7.4 % low hysteresis and outstanding stability over 10,000 cycles. And the sensor can detect different ranges of pressure strains and has great potential for future applications in physiological signal monitoring, action recognition, and sports training.

Certificate-based multi-copy cloud storage auditing supporting data dynamics

With the advent of cloud computing, users are increasingly choosing to store their data on cloud. As a result, data integrity and availability have emerged as key concerns for data owners. Users expect to store multiple copies of their data to cloud and ensure the integrity of these data copies. Currently, numerous multi-copy cloud storage auditing schemes have been proposed. However, most of them depend on public key infrastructure, identity-based cryptography, or certificateless cryptography. These schemes encounter challenges such as complicated certificate management, key escrow, or the necessity for a secure channel for distributing keys, respectively. Furthermore, most of them are not resilient to copy-summation attack. To address the above problems, we propose a certificate-based multi-copy cloud storage auditing scheme supporting data dynamics. We design a novel dynamic structure named Leaves Merkle hash tree (LMHT) to achieve multi-copy dynamic updates. Different from traditional Merkle hash trees, LMHT has significant advantages in data deletion. In addition, the proposed scheme can resist copy-summation attack, in which cloud cannot pass the verification if it only stores summation of all copies without storing data blocks’ all copies. Security analysis and performance evaluation demonstrate that the proposed scheme is secure and efficient.

Rational Engineering of a β-Glucosidase (H0HC94) from Glycosyl Hydrolase Family I (GH1) to Improve Catalytic Performance on Cellobiose.

The conversion of lignocellulosic feedstocks by cellulases to glucose is a critical step in biofuel production. β-Glucosidases catalyze the final step in cellulose breakdown, producing glucose, and are often the rate-limiting step in biomass hydrolysis. The specific activity of most natural and engineered β-glucosidase is higher on the artificial substrate p-nitrophenyl β-d-glucopyranoside (pNPGlc) than on the natural substrate, cellobiose. We report an engineered β-glucosidase (Q319A H0HC94) with a 1.8-fold higher specific activity (366.3 ± 36 μmol/min/mg), a 1.5-fold increase in kcat (340.8 ± 27 s-1), and a 3-fold increase in catalytic efficiency (236.65 mM-1 s-1) over H0HC94 (WT) on cellobiose. Molecular dynamic simulations and protein structure network analysis indicate that the Q319A H0HC94 active site pocket is significantly remodeled compared to the WT, leading to changes in enzyme conformation, better accessibility of cellobiose inside the active site pocket, and higher enzymatic activity. This study shows the impact of rational engineering of a nonconserved residue to increase β-glucosidase substrate accessibility and catalytic efficiency by reducing crowding interaction between cellobiose and active site pocket residues near the gatekeeper region and increasing pocket volume and surface area. Thus, rational engineering of previously characterized enzymes could be an excellent strategy to improve cellulose hydrolysis.

Interval efficiency estimation using relational dynamic DEA approach: case of Indian banks

Data envelopment analysis (DEA) facilitates relative performance estimation of homogenous decision-making units (DMUs), whereas dynamic DEA pertains to intertemporal elements like carryovers for measuring DMUs’ efficiencies over time. To enhance DMU’s performance, there is a need to measure its efficiency with dynamic structure and further to determine input-output target points for making significant improvements in an inefficient DMU. Therefore, the present study proposes a relational dynamic DEA approach that comprises a dynamic structure in which periods are connected through good and bad links/carry-overs along with desirable and undesirable outputs and utilizes interval data. The system and period efficiency intervals are derived using a unique set of weights based on common weights methodology. Moreover, the relationship between the complement of the lower (upper) bound system and period efficiencies is established. Lastly, the input-output target points are suggested to improve DMUs in terms of upper-bound system efficiencies in a dynamic environment. To validate the usefulness of the proposed approach, a case study in Indian banks for the period 2017– 2021 is presented. This study investigates the impact of stressed assets (bad link/carryover) and loss due to non-performing assets (bad/undesirable output) on banks’ dynamic efficiency. The results are compared with the static structure. The findings, targets, and implications of the study can assist bank experts and policymakers in formulating policies/strategies for further improvements.

Structure based release kinetics analysis of doxazosin mesylate sustained-release tablets using micro-computed tomography

The structures of solid dosage forms determine their release behaviors and are critical attributes for the design and evaluation of the solid dosage forms. Here, the three-dimensional (3D) structures of doxazosin mesylate sustained-release tablets (DM SRT) as reference listed drug (RLD) and a generic preparation were parallelly assessed by micro-computed tomography (micro-CT). There were no significant differences observed in the release profiles between the RLD and the generic formulation in the conventional dissolution, but the generic preparation released slightly faster in media with ethanol for an alcohol-induced dose-dumping test. With their 3D structures obtained via micro-CT determination, the unique release behaviors of both RLD and the generic were investigated for samples from dissolution tests to reveal the effects of internal fine structure on the release kinetics. The structural parameters for both preparations were similar in conventional dissolution test, whilst the dissolutions in ethanol media of RLD were more or less distinguished from that of generic preparations, attributing to their static and dynamic structures. Furthermore, the findings revealed that the presence of ethanol accelerated the dissolution and induced changes in the internal structure of both the RLD and the generic preparations. Moreover, the structure parameters like volume and area of outer contour, remaining solid volume and cavity volume were not equivalent between the two formulations in 40 % ethanol. In conclusion, the structure data obtained from this study provided valuable insights into the diverse release behaviors observed in various modified-release formulations in drug development and quality control.

ACDRL: A constraint-guided dynamic reinforcement learning for index selection

Index selection aims to find the optimal index configuration for a certain workload. In recent years, the database committee has attempted to develop an intelligent index advisor for replacing database administrators (DBAs). Although some researches show that applying reinforcement learning (RL) to index selection is a significant and promising direction, many problems still exist in applying the RL agent to the index selection i.e. long training time, unstable performance, and limited state representation. To address these issues, we propose a constraint-guided dynamic RL for index selection. Specifically, our method has three major contributions: (i) To balance the space consumption and index configuration quality, we design a dynamic index state structure to avoid missing effective indexes in limited space consumption. (ii) To accelerate agent training, we design a constraint-guided method to largely reduce useless explorations. (iii) To keep the stability of the RL, we propose the trade-off strategy for value function design instead of using Q_network mindlessly. We test our ACDRL with two open-source benchmarks, TPC-H and TPC-DS. The experimental results show that our method outperforms state-of-the-art methods and could find the optimal index configurations with limited time consumption.

Modulation of dynamic DNA G-quadruplex structures in the hTERT promoter region by ligands.

Small molecules can inhibit cellular processes such as replication and transcription by binding to the promoter regions that are prone to form G-quadruplexes. However, since G-quadruplexes exist throughout the human genome, the G-quadruplex binders suffer from specificity issues. To tackle this problem, a G-quadruplex binder (Pyridostatin, or PDS) is conjugated with a ligand (Polyamide, or PA) that can specifically recognize DNA sequences flanking the G-quadruplex forming region. The binding mechanism of this hybrid ligand to the hTERT promoter region (hTERT 5-12) is then elucidated using optical tweezers. During mechanical unfolding processes, different intermediate structures of hTERT 5-12 in presence of PDS, PA, or PA-PDS conjugateare observed. These intermediate structures are consistent with two folding patterns of G-quadruplexes in the hTERT 5-12 fragment. While the duplex DNA binder PA facilitates the folding of a hairpin-G-quadruplex structure, the PDS assists the formation of two tandem G-quadruplexes. Both replication stop assay in vitro and dual luciferase assay in vivo established the effectiveness of the PA-PDS conjugate for hTERT 5-12 targeting. We expect such a ligand dependent folding dynamics will provide guidelines to the development of drugs that not only target hTERT expressions, but also other oncogenes via interactions with specific G-quadruplex structures formed in their promotor regions.

Stress less: Viral mastery of the RNA G-quadruplex

RNA G-quadruplexes are dynamically regulated during stress and infection. In this issue of Cell Host & Microbe, Schult etal.1 demonstrate that an RNA G-quadruplex conserved across orthoflaviviruses binds hnRNPH1 to mitigate the host stress response, highlighting the potential of this dynamic proviral RNA structure as a pan-flaviviral target.

An immersed boundary method for modeling fluid–solid–acoustic interactions involving dynamic structures

An immersed boundary method for modeling fluid–solid–acoustic interactions involving dynamic structures