Subsequent Simulations Research Articles

Ply-ply friction behavior between unidirectional thermoplastic prepreg plies during thermoforming: Characterization and modeling

The ply-ply friction behavior of unidirectional carbon fiber reinforced polyphenylene sulfide (UD CF/PPS) prepreg in thermoforming was investigated through an improved pull-through testing system. The effects of temperature, normal force and slipping velocity were considered in testing. The results indicated the existence of three key mechanisms underlying slipping: namely the resin shear, fiber–fiber contact and fiber-resin interaction. A three-stage division of the experimental curve was proposed, and several factors were defined to establish a quantitative definition of the ply-ply friction behavior. The results showed that the influence of slipping velocity is particularly evident. Its post-yield stress (12.8 kPa), steady-state CoF (0.118) and residual stress (0.705 kPa) were the highest, exhibiting the largest changes of 957.9 %, 736.9 % and 47.2 %, respectively. This indicated the strong contribution of resin in ply-ply friction. In addition, the Stribeck analysis also suggested the dominance of hydrodynamic lubrication condition in slipping. Based on the experimental results, a simple phenomenological model was proposed based on experimental curves to accurately describe the effects of processing parameters. This work presents a comprehensive characterization of the ply-ply friction behavior of UD CF/PPS prepreg in thermoforming, providing a substantial experimental foundation for the subsequent simulation research.

Simulation inversion analysis of simultaneous commutation failure of Zhaoyi and Yindong DC

Abstract Aim at the three times simultaneous commutation failure of two Multi-outfeed and Multi-infeed DC Systems in a Similar Path of Ningxia, the Ningxia power grid model is built in Power System Analysis Software Package (PSASP) with actual parameters, and the accident inversion simulation is carried out based on the operation state of the power grid before the fault. Based on the inversion simulation, the simulation results were compared with the measured PMU data. The results showed that the trend of simulation and the measured curve is consistent, and the simulation was slightly more serious than the actual fault, but the overall error was less than 10%, which verified the accuracy of the simulation model and method, and provided a basis for the subsequent simulation analysis of the power grid operation mode.

A Study on the Mid-frequency Tire-Sourced Cabin Noise in Electric Vehicles

ABSTRACT This study investigates and provides a framework for addressing a reported tire- sourced cabin noise in the mid-frequency range of 300–500 Hz for an electric vehicle (EV). Noise, vibration, and harshness (NVH) of EVs present new challenges compared with internal combustion engine vehicles because of significant design changes between the two vehicle types. In turn, the tire–road interaction noise becomes a more significant source of cabin noise in EVs. In this regard, some prominent EV manufacturers recently reported relatively high measured cabin noise, particularly in the mid-frequency range of 300–500 Hz. Identifying the root cause(s) of noise in that range is a challenging task, as both tire structure–borne and airborne sources are contributors in that frequency range of elevated noise. The current work presents the results of an experimental modal analysis to provide insight into some potential sources of the reported noise for an all-season tire/wheel assembly designed for an EV. The subsequent parametric simulations, conducted via the tire–vehicle finite element model, evaluate some of the mitigation solutions for the reported noise.

Binding of a Drug (Colchicine) to L-Asparaginase Enzyme Using Multispectroscopic, Thermodynamics, and Simulation Studies: Possible Implication in Acute Lymphoblastic Leukemia Treatment.

The research aims to elucidate how drug interactions affect the activity of L-asparaginase (L-ASNase), an essential enzyme in cancer treatment, especially for acute lymphoblastic leukemia (ALL). Understanding these interactions is crucial for optimizing treatment effectiveness and reducing adverse effects. This study explores the intricate molecular interactions and structural dynamics of L-ASNase upon binding with colchicine. Fluorescence quenching experiments were conducted at various temperatures (298, 303, and 310 K), revealing notable interactions between L-ASNase and colchicine. These interactions were characterized by a reduction in fluorescence intensity and a blue shift in emission maxima. Additional analyses, including the determination of Stern-Volmer quenching constants (KSV), bimolecular quenching rate constants (kq), and thermodynamic parameters, indicated a static quenching mechanism with moderate binding affinities (Ka: 1.40-2.71 × 104 M-1) across different temperatures. Thermodynamic study suggested positive enthalpy and entropy changes (ΔH° = -10.26 kcal mol-1; ΔS° = -14.19 cal mol-1 K-1), suggesting a spontaneous reaction with negative ΔG° values (-5.86 to -6.03 kcal mol-1). FRET measurements supported optimal distances (r and Ro) for FRET occurrence, reinforcing the static quenching mechanism. Molecular docking further supported these findings, revealing a 1:1 stoichiometric binding ratio for L-ASNase:colchicine and elucidating specific binding orientations and interactions critical for complex stability. Subsequent molecular dynamics simulations spanning 100 ns underscored the stability of the L-ASNase-colchicine complex, with minimal deviations observed in key structural parameters such as RMSD, RMSF, Rg, and SASA. Additionally, spectroscopic analyses, including circular dichroism (CD), synchronous fluorescence, and 3D fluorescence provided insights into the conformational changes and alterations in the microenvironment of aromatic amino acid residues in L-ASNase upon colchicine binding. Moreover, L-ASNase activity was slightly reduced by 25% in the presence of colchicine. This comprehensive investigation sheds light on the molecular intricacies of the L-ASNase-colchicine complex, advancing our understanding of drug-target interactions and offering potential avenues for therapeutic applications.

The rotational disruption of porous dust aggregates from ab initio kinematic calculations

The size of dust grains in the interstellar medium follows a distribution where most of the dust mass is made up of smaller grains. However, the redistribution from larger grains towards smaller sizes, especially by means of rotational disruption, is still poorly understood. We aim to study the dynamics of porous grain aggregates undergoing an accelerated rotation, namely, a spin-up process that rapidly increases the angular velocity of the aggregate. In particular, we aim to determine the deformation of the grains and the maximal angular velocity up to the rotational disruption event by caused by centrifugal forces. We precalculated the porous grain aggregate by means of ballistic aggregation analogous to the interstellar dust as input for subsequent numerical simulations. We performed three-dimensional (3D) N-body simulations, mimicking the radiative torque spin-up process up to the point where the grain aggregates become rotationally disrupted. Our simulations results are in agreement with theoretical models predicting a characteristic angular velocity, $ disr $, on the order of $ rad\ $, where grains become rotationally disrupted. In contrast to theoretical predictions, we show that for large porous grain aggregates ($ nm $), the $ disr $ values do not strictly decline. Instead, they reach a lower asymptotic value. Hence, such grains can withstand an accelerated rotation more efficiently up to a factor of 10 because the displacement of mass by centrifugal forces and the subsequent mechanical deformation supports the buildup of new connections within the aggregate. Furthermore, we report that the rapid rotation of grains deforms an ensemble with initially 50:50 prolate and oblate shapes, respectively, preferentially into oblate shapes. Finally, we present a best-fit formula to predict the average rotational disruption of an ensemble of porous dust aggregates dependent on the internal grain structure, total number of monomers, and applied material properties.

A Novel A105Y Mutant of CYP17A1 Exhibits Almost Perfect Regioselectivity in the Production of 17α-Hydroxyprogesterone.

17α-Hydroxyprogesterone (17α-OHP) is a steroid hormone with significant biological activity that can be obtained by catalyzing progesterone (PROG), the main product of sitosterol, through CYP17A1. However, increasing the catalytic specificity of HCYP17A1 for C17 hydroxylation of progesterone (PROG) poses a formidable challenge due to the close proximity of the C16 and C17 positions. In this study, a rational design was utilized to alter the spatial configuration of the substrate channel, leading to the complete abolition of its 16-hydroxylation activity. Subsequent molecular dynamics simulations revealed that the A105Y mutation heightened the rigidity of the G95-I112 region of CYP17A1, consequently regulating the direction of the entry of PROG into the catalytic pocket. Moreover, the establishment of hydrogen bonding between Y105 and R239, coupled with Pi-stacking of A105Y with F114, effectively immobilizes the substrate PROG in a fixed position, explaining the practically perfect regioselectivity observed in A105Y. Finally, a multifaceted enzymatic cascade system, incorporating A105Y, cytochrome P450 reductase (CPR), and glucose-6-phosphate dehydrogenase (ZWF) for NADPH cofactor regeneration, was constructed in Pichia pastoris GS115. The resulting biocatalyst produced 106 ± 3.2 mg L-1 17α-OHP, a 4.6-fold increase compared with A105Y alone. Thus, this study provides valuable insights for improving the regioselectivity and activity of P450 enzymes.

6-hydroxy-3-succinoylsemialdehyde-pyridine as a potential inhibitor of schizophrenia-associated enzyme

Schizophrenia’s cognitive deficits limit quality of life. Current drugs are ineffective. This study investigates 6-hydroxy-3-succinoylsemialdehyde-pyridine (6H3SAP), a nicotine derivative, as a potential inhibitor of KATII, an enzyme in the kynurenine pathway linked to cognitive dysfunction. Molecular docking was employed to assess the binding affinity of 6H3SAP to the KATII enzyme. The results indicated that 6H3SAP interacted with the KATII active site, demonstrating a binding affinity comparable to nicotine (previously suggested as a potential KATII blocker) but lower than NS1502, a well-established KATII inhibitor. Subsequent molecular dynamics simulations provided further insights into the interaction details between 6H3SAP and KATII. These simulations revealed the formation of stable interactions between 6H3SAP and key amino acid residues within the KATII binding pocket. Though promising, further research is needed to assess 6H3SAP’s efficacy and safety. Surprisingly, the molecular dynamics data also proposed that the nicotine-KATII tie is weak.

Process time distribution simulation in robotic assembly line balancing

Feedback control systems utilised in car body construction cause process time variance when compensating for external disturbances. By considering these in robotic assembly line balancing, the risk of cycle time violations can be controlled. This requires knowledge of the underlying process time distributions, which are not known in advance. Therefore, a simulation method is proposed to assess the impact of varying process time distributions on the balancing of robotic assembly lines. The initial step involves acquiring the process times of existing production processes. In the subsequent simulation, these are randomly and repeatedly selected as substitutes for the process times in the balancing of a new robotic assembly line. The impact of process time distribution variations on the result is investigated, and a single solution can be selected. The proposed method is evaluated based on the balancing of a robotic assembly line for a body-in-white rear compartment. Results are compared to normally distributed process times, which is a common assumption for modelling uncertain process times. Both approaches are evaluated utilising actual process time distributions. It is demonstrated that the proposed method yields fewer and less severe underestimations of cycle times, thereby reducing the number of uncontrolled violations of cycle times.

Investigating the Inhibitory Potential of Flavonoids against Aldose Reductase: Insights from Molecular Docking, Dynamics Simulations, and gmx_MMPBSA Analysis.

Diabetes mellitus (DM) is a complex metabolic disorder characterized by chronic hyperglycemia, with aldose reductase playing a critical role in the pathophysiology of diabetic complications. This study aimed to investigate the efficacy of flavonoid compounds as potential aldose reductase inhibitors using a combination of molecular docking and molecular dynamics (MD) simulations. The three-dimensional structures of representative flavonoid compounds were obtained from PubChem, minimized, and docked against aldose reductase using Discovery Studio's CDocker module. The top 10 compounds Daidzein, Quercetin, Kaempferol, Butin, Genistein, Sterubin, Baicalein, Pulchellidin, Wogonin, and Biochanin_A were selected based on their lowest docking energy values for further analysis. Subsequent MD simulations over 100 ns revealed that Daidzein and Quercetin maintained the highest stability, forming multiple conventional hydrogen bonds and strong hydrophobic interactions, consistent with their favorable interaction energies and stable RMSD values. Comparative analysis of hydrogen bond interactions and RMSD profiles underscored the ligand stability. MMPBSA analysis further confirmed the significant binding affinities of Daidzein and Quercetin, highlighting their potential as aldose reductase inhibitors. This study highlights the potential of flavonoids as aldose reductase inhibitors, offering insights into their binding interactions and stability, which could contribute to developing novel therapeutics for DM complications.

Interactive Structural Analysis of KH3-4 Didomains of IGF2BPs with Preferred RNA Motif Having m6A Through Dynamics Simulation Studies.

m6A modification is the most common internal modification of messenger RNA in eukaryotes, and the disorder of m6A can trigger cancer progression. The GGACU is considered the most frequent consensus sequence of target transcripts which have a GGAC m6A core motif. Newly identified m6A 'readers' insulin-like growth factor 2 mRNA-binding proteins modulate gene expression by binding to the m6A binding sites of target mRNAs, thereby affecting various cancer-related processes. The dynamic impact of the methylation at m6A within the GGAC motif on human IGF2BPs has not been investigated at the structural level. In this study, through in silico analysis, we mapped IGF2BPs binding sites for the GGm6AC RNA core motif of target mRNAs. Subsequent molecular dynamics simulation analysis at 400 ns revealed that only the KH4 domain of IGF2BP1, containing the 503GKGG506 motif and its periphery residues, was involved in the interaction with the GGm6AC backbone. Meanwhile, the methyl group of m6A is accommodated by a shallow hydrophobic cradle formed by hydrophobic residues. Interestingly, in IGF2BP2 and IGF2BP3 complexes, the RNA was observed to shift from the KH4 domain to the KH3 domain in the simulation at 400 ns, indicating a distinct dynamic behavior. This suggests a conformational stabilization upon binding, likely essential for the functional interactions involving the KH3-4 domains. These findings highlight the potential of targeting IGF2BPs' interactions with m6A modifications for the development of novel oncological therapies.

Simulation of lunar soil compressive strength performance test based on grey correlation analysis

Detecting water ice in the permanent shadow area of the lunar south pole is an important task of China's Chang'e-7. For this purpose, a simulation study was carried out under the earth environment, and a test sample of polar water-containing simulated lunar soil was prepared. The mechanical properties of the lunar soil simulant were tested under ultra-low temperature conditions, and the changes in water content, relative density, temperature, loading rate, and base material ratio with compressive strength were analyzed. The results show that the compressive strength of the frozen lunar soil simulant increases with the increase of water content, increases with the increase of density, and increases with the decrease of temperature. It is less affected by the change of loading rate. The order of compressive strength affected by different base material ratios is: 100%anorthosite, <90%anorthosite, +10%basalt <70%, +30%anorthosite <100%, basalt, lunar soil simulant. Finally, the correlation between the basic physical properties of lunar soil simulant such as water content, relative density, temperature, loading rate, and ratio and compressive strength is explored through grey correlation analysis. The correlation order is: water content> density> temperature> ratio> loading rate. This paper prepared and tested the mechanical properties of hydrated lunar soil, and proposed a more systematic and standardized implementation plan. It serves as the basis for studying the properties of hydrated lunar soil in the polar region, and provides a theoretical basis and reference for subsequent lunar soil simulation research.

Research on the Robustness of Command and Control Networks under Cascading Failures

The current analysis of cascading failures in command and control networks pays little attention to their roles and mechanisms, resulting in challenges in quantifying survivability evaluation metrics and limiting practical application. To address these issues, this paper designs a command and control network model with a recovery strategy to improve the scientific evaluation of critical nodes and enhance the reliability of subsequent cascading failure simulations. Two capacity parameters are introduced to analyze the nonlinear behavior between network node load and capacity, and an optimal recovery strategy is proposed. This strategy prioritizes the recovery of critical nodes, thereby minimizing the overall probability of network failure. Simulations were conducted under both random failure and deliberate attack scenarios, comparing the proposed strategy with random recovery and betweenness-priority recovery strategies to identify the optimal recovery approach. The experiments showed that the optimal recovery strategy significantly enhanced the network’s survivability and recovery efficiency, allowing for the restoration of basic network functions in the shortest possible time and reducing the impact of cascading failures. By integrating the operability and uncertainty of real-world command and control networks, this method improved the network’s recovery capability and overall stability in the face of cascading failures through scientific evaluation and strategy optimization.

Collisional and radiative data for tellurium ions in kilonovae modelling and laboratory benchmarks

ABSTRACT Tellurium is a primary candidate for the identification of the 2.1 $\, \mu$m emission line in kilonovae (KNe) spectra AT2017gfo and GRB230307A. Despite this, there is currently an insufficient amount of atomic data available for this species. We calculate the required atomic structure and collisional data, particularly the data required for accurate non-local-thermodynamic-equilibrium (NLTE) modelling of the low temperatures and densities in KNe. We use a multiconfigurational Dirac–Hartree–Fock method to produce optimized one-electron orbitals for Te i-iii. As a result energy levels and Einstein A-coefficients for Te i-iii have been calculated. These orbitals are then employed within Dirac R-matrix collision calculations to provide electron-impact-excitation collision strengths that were subsequently averaged according to a thermal Maxwellian distribution. Subsequent tardis simulations using this new atomic data reveal no significant changes to the synthetic spectra due to the very minor contribution of Te at early epochs. NLTE simulations with the colradpy package reveal optically thin spectra consistent with the increasing prominence of the Te iii 2.1 $\, \mu$m line as the KNe ejecta cools. This is reinforced by the estimation of luminosities at nebular KNe conditions. New line ratios for both observation and laboratory benchmarks of the atomic data are proposed.

Conformational and Solvent Effects on the Photoinduced Electron Transfer Dynamics of a Zinc Phthalocyanine-Benzoperylenetriimide Conjugate: A Nonadiabatic Dynamics Simulation.

Herein, we employed a combination of static electronic structure calculations and nonadiabatic dynamics simulations at linear-response time dependent density functional theory (LR-TDDFT) level with the optimally tuned range-separated hybrid (OT-RSH) functional to explore the ultrafast photoinduced dynamics of a zinc phthalocyanine-benzoperylenetriimide (ZnPc-BPTI) conjugate. Due to the flexibility of the linker, we identified two major conformations: the stacked conformation (ZnPc-BPTI-1) and the extended conformation (ZnPc-BPTI-2). Since the charge transfer states are much lower than the lowest local excitation in ZnPc-BPTI-1, which is contrary to ZnPc-BPTI-2, the ultrafast electron transfer (~3.6 ps) is only observed in the nonadiabatic simulations of ZnPc-BPTI-1 upon local excitation around the absorption maximum of ZnPc. However, when considering the solvent effects in benzonitrile: the lowest S1 states are both charge transfer states from ZnPc to BPTI for different conformers. Subsequent nonadiabatic dynamics simulations indicate that both conformers experience ultrafast electron transfer in benzonitrile with two time constants of 90 [100] fs and 1.40 [1.43] ps. Our present work not only agrees well with previous experimental study, but also points out the important role of conformational changes and solvent effects in regulating the photodynamics of organic donor-acceptor conjugates.

Binding of Peptides Containing D‐Amino Acids to the Tsg101 Tumor Susceptibility Protein

AbstractTsg101 is implicated in tumorigenesis and viral budding, and its inhibition through peptide binding is a potential therapeutic strategy. We utilized the crystal structure of the Tsg101‐PSAP complex from the protein databank in molecular dynamics studies on peptide‐Tsg101 interactions. To enhance peptide stability against enzymatic degradation, we designed peptides with L‐form terminal prolines and D‐form middle amino acids. These peptides also featured acetylated proline at the N‐terminus and amidated C‐terminus, increasing resistance to proteases. Virtual screening of 400 amino acid combinations identified promising peptide candidates and specific binding sites. Subsequent molecular dynamics simulations focused on the peptide PywP, which displayed strong binding stability at a novel Tsg101 site. Further simulations with variations of the D‐form amino acid ′w’ showed that 18 of 21 tested peptides, notably PyeP and PytP, remained firmly bound, highlighting their potential as Tsg101 inhibitors. These peptides also contain hydrophilic residues, potentially improving solubility and therapeutic delivery.

Comparison of Point-of-Care Ultrasound Guidance and the Traditional Approach in Performing Simulated Emergent Cricothyroidotomy Among Emergency Medicine Physicians, Residents, and Students.

Objective Emergency cricothyroidotomy (EC) is a rare procedure used to establish airway access when both endotracheal intubation and bag-mask ventilation have failed. Point-of-care ultrasound (POCUS) has been proposed as an adjunct to aid in identifying anatomical landmarks. However, its impact on emergency physicians when performing EC remains unclear. This study compared emergency physician and student confidence, preference, and procedure time between POCUS and traditional palpation for EC. Methods Our study utilized a randomized controlled crossover design. Emergency medicine providers attended a didactic lecture demonstrating traditional palpation and POCUS techniques for EC. The participants were randomly allocated to two simulation groups. One group started with the palpation of landmarks, while the other group started with POCUS landmark identification. A randomized crossover design was employed, and in a subsequent simulation, the reverse technique was utilized. Time to anatomic landmark identification was recorded. Participants completed a survey assessing their confidence and preference. Procedure times and confidence level differences were examined via Wilcoxon signed-rank tests. Results Sixteen participants completed the survey and were included in the final analysis. All participants successfully performed EC with the two landmark identification techniques. There was no significant difference in self-reported confidence between POCUS and palpation (p = 0.17). Landmark identification by palpation was significantly faster than POCUS (p = 0.001). A total of 10 (63%) participants preferred palpation over POCUS. Conclusions Both POCUS and traditional palpation were effective in identifying anatomical landmarks for EC. Although palpation was significantly quicker, confidence and preference between the two techniques were similar. The results suggest that both approaches can benefit clinical practice, depending on the context and provider familiarity. Further studies with larger cohorts and real-world scenarios are recommended to explore the effectiveness and safety of POCUS in EC.

A reservoir computing approach in active noise control for vehicle applications

Reservoir Computing (RC) is an alternative approach to Recurrent Neural Networks (RNN) that can avoid some shortcomings of conventional gradient decent-training that are mainly related to high computational complexity and the reduced ability to "learn" long-range dependencies. In RC the input data are transformed into patterns in a high-dimensional space by an RNN called the "reservoir", which remains unchanged during training. The desired output signal is generated as a linear combination of the neuron's signals from the input-excited reservoir. The linear part of the RC architecture, which is called the "readout" can be trained with a simple learning algorithm such as linear regression. In this work an RC architecture is proposed for the attenuation of acoustic disturbances encountered in vehicle cabins such as aircrafts and yachts. At first, a dataset of acoustic pressure measurements from real-world cabins was used to generate the readout and reservoir layers. Subsequent computer simulations demonstrated that the proposed architecture can successfully attenuate such acoustic disturbances. Finally, the performance of RC in Active Noise Cancellation task was compared with both the linear FxLMS algorithm and a conventional RNN, showing that it has several advantages regarding acoustic pressure reduction combined with relatively low computational complexity.

High-order solitary waves, fission, hybrid waves and interaction solutions in the nonlinear dissipative (2+1)-dimensional Zabolotskaya-Khokhlov model

The Zabolotskaya-Khokhlov model (ZKm) is a widely used nonlinear model in the fields of sound, ultrasound, and shock waves. The aims of this paper stems from its examination and rectification of earlier results concerning the N-soliton solutions of nonlinear dissipative (2+1)-dimensional ZKm. By recognizing and incorporating the non-zero values of the dispersion coefficient , this study addresses a significant omission in current research. The findings enhance the comprehension of higher-order soliton behaviors, encompassing bifurcation solitons, higher-order breathers, rogue waves, periodic lumps, and their interactions, which are crucial for both theoretical studies and practical applications in areas like nonlinear optics and fluid dynamics. Subsequent detailed numerical simulations are conducted to elucidate the complex behaviors of the obtained solutions. This thorough exploration provides crucial insights into the intricate patterns exhibited by the nonlinear dissipative (2+1)-dimensional ZKm under different conditions, enhancing our understanding of the underlying physical phenomena.

Kinetic Monte Carlo modelling of nano-oxide precipitation and its associated stability under neutron irradiation for the Fe-Ti-Y-O system

While developing nuclear materials, predicting their behavior under long-term irradiation regimes spanning decades poses a significant challenge. We developed a novel Kinetic Monte Carlo (KMC) model to explore the precipitation behavior of Y-Ti-O oxides along grain boundaries within nanostructured ferritic alloys (NFA). This model also assessed the response of the oxides to neutron irradiation, even up simulated radiation damage levels in the desired long dpa range for reactor components. Our simulations investigated how temperature and grain boundary sinks influenced the oxide characteristics of a 12YWT-like alloy during heat treatments at 1023, 1123, and 1223 K. The oxide characteristics observed in our simulations were in good agreement with existing literature. Furthermore, the impact of grain boundaries on precipitation was found to be minimal. The resulting oxide configurations and positions were used in subsequent simulations that exposed them to simulated neutron irradiation to a total accumulated dose of 8 dpa at three temperatures: 673, 773, and 873 K, and at dose rates of 10−3, 10−4, and 10−5 dpa/s. This demonstrated the expected inverse relationship between oxide size and dose rate. In a long-term irradiation simulation at 873 K and 10−3 dpa/s was taken out to 66 dpa and found the oxides in the vicinity of the grain boundary were more susceptible to dissolution. Additionally, we conducted irradiation simulations of a 14YWT-like alloy to reproduce findings from neutron irradiation experiments. The larger oxides in the 14YWT-like alloy did not dissolve and displayed stability similar to the experimental results.

Clarifying therapeutic mechanisms of Guanxinshutong capsule for cardiac fibrosis treatment by network pharmacology, molecular docking, molecular dynamics simulation, and in vivo experiments

PurposeGuanxinshutong capsule (GXST) is a Chinese patent medicine used for the treatment of cardiac fibrosis (CF). Nevertheless, the precise mechanism of action of GXST remains unclear. In this study, we applied network pharmacology, molecular docking, molecular dynamics simulation, and in vivo experiments to assess the effects and mechanisms of GXST in the treatment of CF. MethodsThe TCMSP database provided the GXST targets and active substances. The GeneCards, OMIM, and TTD databases were searched for targets relevant to cardiac fibrosis. To filter core targets, a PPI network was set up. Metascape was utilized to conduct enrichment analysis for the KEGG and GO pathways. To evaluate the interaction between putative targets and active drugs, molecular docking was utilized. MDS was performed for the optimal complex of the core ligand protein identified through molecular docking. Induction of cardiac fibrosis in SD rats using isoproterenol, and the protective effects of GXST on the heart were evaluated using echocardiography, H&E staining, and Masson staining. ResultsThrough network pharmacology analysis, we have identified 83 active components and 73 key target proteins related to cardiac fibrosis from GXST. Subsequent molecular docking and molecular dynamics simulation results suggest that quercetin, luteolin, and kaempferol can inhibit cardiac fibrosis by regulating the expression of TNF-α, IL6, and IL1B proteins. These compounds and proteins may be key factors in the treatment of CF with GXST. Further, in vivo experiments demonstrate that GXST can alleviate myocardial injury and improve cardiac function in CF rats. ConclusionThis study successfully predicted the effective components, potential targets, and related pathways involved in treating CF by GXST. GXST can improve cardiac function and alleviate pathological damage in the hearts of SD rats. This provides a new strategy for future investigations into the mechanisms of GXST in the treatment of CF.