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Introduction: Endoplasmic reticulum stress (ERS) is a prominent etiological factor in the pathogenesis of diabetes. Nevertheless, the mechanisms through which ERS contributes to the development of diabetes remain elusive. Methods: Transcriptional expression profiles from the Gene Expression Omnibus (GEO) datasets were analyzed and compared to obtain the differentially expressed genes (DEGs) in T2DM. Following the intersection with ERS associated genes, the ERS related T2DM DEGs were identified. Receiver operating characteristic (ROC) and Least Absolute Shrinkage and Selection Operator (LASSO) analysis were performed to screen out the ERS related biomarker genes and validate their diagnostic values. Gene expression level was detected by qPCR and Elisa assays in diabetic mice and patient serum samples. Results: By analyzing the transcriptional expression profiles of the GEO datasets, 49 T2DM-related DEGs were screened out in diabetic islets. RTN1, CLGN, PCSK1, IAPP, ILF2, IMPA1, CCDC47, and PTGES3 were identified as ERS-related DEGs in T2DM, which were revealed to be involved in protein folding, membrane composition, and metabolism regulation. ROC and LASSO analysis further screened out CLGN, ILF2, and IMPA1 as biomarker genes with high value and reliability for diagnostic purposes. These three genes were then demonstrated to be targeted by the transcription factors and miRNAs, including CEBPA, CEBPB, miR-197-5p, miR-6133, and others. Among these miRNAs, the expression of miR-197-5p, miR-320c, miR-1296-3P and miR-6133 was down-regulated, while that of miR-4462, miR-4476-5P and miR-7851-3P was up-regulated in diabetic samples. Small molecular drugs, including D002994, D001564, and others, were predicted to target these genes potentially. qPCR and Elisa analysis both validated the same expression alteration trend of the ERS-related biomarker genes in diabetic mice and T2DM patients. Discussion: These findings will offer innovative perspectives for clinical diagnosis and treatment strategies for T2DM. [ABSTRACT FROM AUTHOR]

Introduction: Immune dysregulation plays a major role in cancer progression. The quantification of lymphocytic spatial inflammation may enable spatial system biology, improve understanding of therapeutic resistance, and contribute to prognostic imaging biomarkers. Methods: In this paper, we propose a knowledge-guided deep learning framework to measure the lymphocytic spatial architecture on human H&E tissue, where the fidelity of training labels is maximized through single-cell resolution image registration of H&E to IHC. We demonstrate that such an approach enables pixel-perfect ground-truth labeling of lymphocytes on H&E as measured by IHC. We then experimentally validate our technique in a genetically engineered, immune-compromised Rag2 mouse model, where Rag2 knockout mice lacking mature lymphocytes are used as a negative experimental control. Such experimental validation moves beyond the classical statistical testing of deep learning models and demonstrates feasibility of more rigorous validation strategies that integrate computational science and basic science. Results: Using our developed approach, we automatically annotated more than 111,000 human nuclei (45,611 CD3/CD20 positive lymphocytes) on H&E images to develop our model, which achieved an AUC of 0.78 and 0.71 on internal hold-out testing data and external testing on an independent dataset, respectively. As a measure of the global spatial architecture of the lymphocytic microenvironment, the average structural similarity between predicted lymphocytic density maps and ground truth lymphocytic density maps was 0.86 ± 0.06 on testing data. On experimental mouse model validation, we measured a lymphocytic density of 96.5 ± %1% in a Rag2+/- control mouse, compared to an average of 16.2 ± %5% in Rag2-/- immune knockout mice (p<0.0001, ANOVA-test). Discussion: These results demonstrate that CD3/CD20 positive lymphocytes can be accurately detected and characterized on H&E by deep learning and generalized across species. Collectively, these data suggest that our understanding of complex biological systems may benefit from computationally-derived spatial analysis, as well as integration of computational science and basic science. [ABSTRACT FROM AUTHOR]

Reliable modelling of the solar potential of urban surfaces (i.e. roofs, facades and ground) in the built environment can contribute to boost the exploitation of solar energy. Empirical and quasi-physical models are combined into model chains for this scope. Among these models, the decomposition models are used to separate the direct from the diffuse solar irradiance. Such variables are rarely measured, thus making necessary their computation. Studies in literature pointed out that Yang4 is the best-performing decomposition model globally. However, in geographically limited applications, quasi-universal decomposition models like Yang4 and Engerer4 can be outperformed by local models (i.e. models parametrized with climate-specific data) such as Skartveit3 and Starke3. This makes necessary to perform local validation studies to verify the findings from worldwide validation studies. In this study, the four best-performing decomposition models are implemented in Python and experimentally validated against 1-min solar irradiance data (i.e. direct and diffuse irradiance) of Trondheim (Lat. 63°26′N, Norway). More than 1-year long data are considered. The study confirms that the Yang4 model performed the best for high-latitude applications, but Starke3 can achieve a level of performance close to Yang4. [ABSTRACT FROM AUTHOR]

To explore the potential mechanisms of Houttuynia cordata in the treatment of CRC using network pharmacology combined with experimental validation. The major active components of Houttuynia cordata were identified using the TCMSP database, and their related targets were mined. CRC-related target genes were obtained through the Genecards and OMIM databases. The R software Ven Diagram package was used for visualization of the intersection of drug and disease targets. The intersection target genes were subjected to GO function enrichment and KEGG pathway enrichment analysis using the R software clusterProfiler package. A "Drug - active component - target - Disease" network was constructed and analyzed using Cytoscape software. Intersection target genes were uploaded to the STRING database, and the resultant data were imported into Cytoscape software to construct a PPI network and filter core target genes. Expression analysis, diagnostic efficacy, and survival analysis were used to demonstrate the function and clinical value of the core target genes. The correlation between core genes in CRC samples and immune cell infiltration was analyzed using the R software and ssGSVA algorithm. Molecular docking validation of core active components with core target genes was performed using AutodockVina 1.2.2 software. Finally, the effects of quercetin and kaempferol, core active components of Houttuynia cordata, on the growth of HCT116 cells and the regulation of core target genes were validated through CCK8 assay, flow cytometry, and RT-qPCR. Seven effective active components and 147 component-related targets were selected, along with 3806 CRC-related target genes. GO analysis mainly involved biological processes such as epithelial cell proliferation, with KEGG pathway analysis focusing on pathways including AGE-RAGE signaling. Quercetin and kaempferol were identified as two core components, with IL1B, MMP9, CXCL8, and IL6 as four core target genes. Immune infiltration analysis showed that IL1B, MMP9, CXCL8, and IL6 primarily exert anti-CRC effects by promoting neutrophil activity. Molecular docking results indicated stable binding capacities of quercetin and kaempferol with IL1B, MMP9, CXCL8, and IL6. Experimental validation showed that quercetin and kaempferol could inhibit the viability of HCT116 cells in a dose-dependent manner, promote apoptosis, and downregulate the expression of IL1B, MMP9, CXCL8, and IL6 genes. Houttuynia cordata may exert therapeutic effects on CRC by modulating the immune microenvironment and anti-inflammatory responses, providing new research directions and theoretical guidance for the treatment of CRC with Houttuynia cordata. [ABSTRACT FROM AUTHOR]

Wave energy has the potential to provide a sustainable solution for global energy demands, particularly in coastal regions. This study explores the use of reinforcement learning (RL), specifically the Q-learning algorithm, to optimise the energy extraction capabilities of a wave energy converter (WEC) using a single-body point absorber with resistive control. Experimental validation demonstrated that Q-learning effectively optimises the power take-off (PTO) damping coefficient, leading to an energy output that closely aligns with theoretical predictions. The stability observed after approximately 40 episodes highlights the capability of Q-learning for real-time optimisation, even under irregular wave conditions. The results also showed an improvement in efficiency of 12% for the theoretical case and 11.3% for the experimental case from the initial to the optimised state, underscoring the effectiveness of the RL strategy. The simplicity of the resistive control strategy makes it a viable solution for practical engineering applications, reducing the complexity and cost of deployment. This study provides a significant step towards bridging the gap between the theoretical modelling and experimental implementation of RL-based WEC systems, contributing to the advancement of sustainable ocean energy technologies. [ABSTRACT FROM AUTHOR]

Structural steel (E250 grade) is used in several engineering applications involving loadings from quasi-static to high strain rates (blast discs, explosion vents, etc.), which introduce large deformation, strain and strain rate hardening, thermal softening, and damage to the material. The material's dynamic constitutive behaviour can be aptly modelled by a visco-plasticity-based Johnson–Cook (J–C) strength model and damage initiation and complete failure by the J–C's damage model. In the latter, damage initiation is modelled through continuum damage mechanics and propagation by the fracture mechanics. This paper focuses on the determination of 10 different J–C's dynamic constitutive and damage model parameters for E250 structural steel by conducting several experiments involving tensile tests at different strain rates (0.0003–1.0 s-1), stress triaxialities (0.33–0.95), temperatures (30–800 °C), and SHPB experiments (at 3000 and 8000 s-1). It explains the processes and step-by-step procedures for extracting the model parameters from the experimental results. A different approach is followed in arriving at fracture strain for extracting damage model parameters to suit fracture mechanic-based damage evolution available in the existing FEA codes. The constitutive and damage model parameters thus determined are validated through numerical simulations and comparison with three independent experiments viz. i) experiment of a plain tensile specimen, ii) tensile experiment of a notched specimen, and iii) hydrostatic burst experiment of a flat burst disc. The responses and failure patterns from numerical simulations agreed very well in all three experiments, thereby validating the determined model parameters. The determined model parameters can be utilised directly in the commercially available nonlinear explicit FEA codes. [ABSTRACT FROM AUTHOR]

This study presents the validation of a dynamic test system to simulate a high‐speed train passing bridges under seismic excitation. The system comprises scaled models of a CRH380A high‐speed train and an 11‐span simply supported bridge on a shake table array. This innovative apparatus combines seismic loading with the moving train load to replicate train‐track‐bridge interaction (TTBI) during earthquakes. It allows investigation of various train speeds and seismic excitations, providing invaluable insights into TTBI. First, the detailed similarity design principle based on the equations of motion was discussed, and its applicability to the wheel‐rail contact relationship was verified. Then, the dynamic characteristics of the scaled model were identified, and the impact of the error between the scaled model and the theoretical model on the TTBI response was assessed. Furthermore, the comparison of the dynamic test model and the numerical simulation in acceleration responses validated the accuracy of the rigid‐flexible coupling model method for the actual TTBI system. Test cases without external excitation, with simple harmonic excitation and with seismic excitation were conducted on the dynamic test system. Results showed that the influence of track irregularity and running speed on train response aligns with the classical train‐bridge interaction theory. The successful implementation of this test system marks a significant advance in understanding TTBI mechanics and has significant implications for seismic safety enhancement of railway infrastructure. [ABSTRACT FROM AUTHOR]

This study conducted molding process research on castings of complex engine blocks with a new Al–Si–Cu aluminum alloy material. Numerical simulation and experimental validation were used to investigate the effects of different pouring system design schemes on the casting performance, defect formation and mechanical properties of aluminum alloy castings. Based on the casting structure and alloy casting properties, three types of casting systems (i.e., A, B, and C) were designed and analyzed by numerical simulation and testing. The study shows that the molding process of casting system scheme C is more optimal, the numerically simulated porosity is reduced by 4.13 and 1.9% compared with those of schemes A and B, respectively, the defect volume is reduced by 205.87 and 94.7 cm3 compared with those of schemes A and B, respectively, and the average cooling rate is improved by 47.6 and 26.5% compared with those of schemes A and B, respectively. After experimental verification, casting system C exhibited optimal mechanical properties, good CT scan and the microstructure of aluminum alloy analysis results, and numerical simulation results consistent with the actual trial production results, providing guidance for relevant theoretical research. [ABSTRACT FROM AUTHOR]

Biomaterials with osteoinductivity are widely used for bone defect repair due to their unique structures and functions. Machine learning (ML) is pivotal in analyzing osteoinductivity and accelerating new material design. However, challenges include creating a comprehensive database of osteoinductive materials and dealing with low-quality, disparate data. As a standard for evaluating the osteoinductivity of biomaterials, ectopic ossification has been used. This paper compiles research findings from the past thirty years, resulting in a robust database validated by experts. To tackle issues of limited data samples, missing data, and high-dimensional sparsity, a data enhancement strategy is developed. This approach achieved an area under the curve (AUC) of 0.921, a precision of 0.839, and a recall of 0.833. Model interpretation identified key factors such as porosity, bone morphogenetic protein-2 (BMP-2), and hydroxyapatite (HA) proportion as crucial determinants of outcomes. Optimizing pore structure and material composition through partial dependence plot (PDP) analysis led to a new bone area ratio of 14.7 ± 7 % in animal experiments, surpassing the database average of 10.97 %. This highlights the significant potential of ML in the development and design of osteoinductive materials. This study leverages machine learning to analyze osteoinductive biomaterials, addressing challenges in database creation and data quality. Our data enhancement strategy significantly improved model performance. By optimizing pore structure and material composition, we increased new bone formation rates, showcasing the vast potential of machine learning in biomaterial design. [Display omitted] [ABSTRACT FROM AUTHOR]

There are a series of problems in the maintenance of transmission towers. In this paper, based on the existing structure, a climbing robot that can be applied to the transmission tower is designed, and the reliability of the grasp is analyzed. Key parts are optimized with Ansys analysis software and planning for climbing gait is completed with Adams simulation software; Robot control system is designed based on hierarchical and decentralized control architecture and the paw position adjustment decisions are optimized, and the fuzzy control algorithm is used to realize the gait adjustment of the robot The experiment result shows, the robot can complete the task of climbing and crossing the obstacle of the steel surface of the tower angle. [ABSTRACT FROM AUTHOR]

Timely fault detection is essential to flight safety of tandem rotor helicopter. In this paper, a fault detection method is proposed based on state estimation and the deviation between the measured value and the estimated value. Firstly, a polyhedral linear parameter varying (LPV) model is established to solve the nonlinear coupling problem of the helicopter in different moving directions. Then, to obtain actuator fault information, a robust state observer is developed to generate the residual. Meanwhile, a mixed H − / H ∞ algorithm is designed to calculate observer gain by configuring performance parameters, which makes the residuals both sensitive to actuator faults and robust to external disturbances. Furthermore, a dynamic threshold method is introduced to evaluate the residual signal for actuator fault detection. Finally, based on the 3-dof helicopter platform, the effectiveness of the proposed method is verified through comparative simulation and experimental tests. [ABSTRACT FROM AUTHOR]

Hyperthermia induces slight temperature increase of 4–8 °C inside the tumor, making it more responsive to radiation and drugs, thereby improving the outcome of the oncological treatment. To verify the level of heat in the tumor and to avoid damage of the healthy tissue, methods for non-invasive temperature monitoring are needed. Temperature estimation by means of microwave imaging is of great interest among the scientific community. In this paper, we present the results of experiments based on ultra-wideband (UWB) M-sequence technology. Our temperature estimation approach uses temperature dependency of tissue dielectric properties and relation of UWB images to the reflection coefficient on the boundary between tissue types. The realistic measurement setup for neck cancer hyperthermia considers three antenna arrangements. Data are processed with Delay and Sum beamforming and Truncated Singular Value Decomposition. Two types of experiments are presented in this paper. In the first experiment, relative permittivity of subsequently replaced tumor mimicking material is estimated, and in the second experiment, real temperature change in the tumor imitate is monitored. The results showed that the presented approach allows for qualitative as well as quantitative permittivity and temperature estimation. The frequency range for temperature estimation, preferable antenna configurations, and limitations of the method are indicated. [ABSTRACT FROM AUTHOR]

The temperature distribution characteristics of dry-type distribution transformers reflect their overall performance and quality. Distribution transformer daily load changes dramatically, its temperature fluctuates within a certain range. However, most of the research results on transformer temperature rise focus on the steady-state temperature characteristics of transformers, and lack of research related to dynamic temperature rise characteristics. This paper carries out a multi-physics coupling simulation and experimental verification of the dynamic temperature rise relaxation characteristics. The simulation uses the “electromagnetic-flow-thermal” multi-physics coupling analysis method to simulate the steady-state temperature rise characteristics and dynamic temperature rise relaxation characteristics of windings under different load rates. Then, this paper also explores the correlation between the dynamic temperature rise relaxation characteristics and load rate at the typical positions of high-voltage windings and low-voltage windings. The results show that the temperature rise of the winding shows the law of increasing the saturation index function with the increase of the load application time at any load rate. A quantitative characterization model of dynamic temperature rise relaxation behavior at different positions of transformer windings is constructed. It is found that the steady-state temperature rise value of different parts of the winding increases regularly as a power function with the increase of load rate, while the constant value of dynamic temperature rise relaxation time in different parts of the winding decreases as a power function with the increase of load rate. The verification results of the quantitative characterization model of dynamic temperature rise relaxation behavior show that the maximum error of the measured and theoretical steady-state temperature rise value is only 1.56 K, and the maximum error of the constant value of dynamic temperature rise relaxation time is only 0.082 h. These findings provide valuable insights into the performance and quality of dry-type distribution transformers, and can help improve their design and operation for better efficiency and safety. [ABSTRACT FROM AUTHOR]

Hypertension has become a major contributor to the morbidity and mortality of cardiovascular diseases worldwide. Despite the evidence of the anti‐hypertensive effect of gastrodia‐uncaria granules (GUG) in hypertensive patients, little is known about its potential therapeutic targets as well as the underlying mechanism. GUG components were sourced from TCMSP and HERB, with bioactive ingredients screened. Hypertension‐related targets were gathered from DisGeNET, OMIM, GeneCards, CTD, and GEO. The STRING database constructed a protein–protein interaction network, visualized by Cytoscape 3.7.1. Core targets were analyzed via GO and KEGG using R package ClusterProfiler. Molecular docking with AutodockVina 1.2.2 revealed favorable binding affinities. In vivo studies on hypertensive mice and rats validated network pharmacology findings. GUG yielded 228 active ingredients and 1190 targets, intersecting with 373 hypertension‐related genes. PPI network analysis identified five core genes: AKT1, TNF‐α, GAPDH, IL‐6, and ALB. Top enriched GO terms and KEGG pathways associated with the anti‐hypertensive properties of GUG were documented. Molecular docking indicated stable binding of core components to targets. In vivo study showed that GUG could improve vascular relaxation, alleviate vascular remodeling, and lower blood pressure in hypertensive animal models possibly through inhibiting inflammatory factors such as AKT1, mTOR, and CCND1. Integrated network pharmacology and in vivo experiment showed that GUG may exert anti‐hypertensive effects by inhibiting inflammation response, which provides some clues for understanding the effect and mechanisms of GUG in the treatment of hypertension. [ABSTRACT FROM AUTHOR]

Shrimp and shelled pteropods are ecologically important organisms that can produce significant amounts of water column backscatter. Few studies have experimentally measured both target strength (TS) and scattering model inputs for individual shrimp and shelled pteropods, especially from the meso- and bathypelagic. We captured animals from net trawls throughout the northeast Pacific and northwest Atlantic continental shelves between 2016 and 2020. We measured morphology, density and sound speed contrasts, and broadband TS (35–75, 110–230 kHz) from tethered individuals at sea and on land in scientific aquaria. Experimentally measured TS was used to test scattering model performance. Differences in measured mean length-to-radius ratios and density contrasts of epipelagic shrimp (10–13 and 1.02–1.03) were statistically greater than for mesopelagic species (8–9 and 1.04–1.05). Differences between predicted and measured shrimp TS averaged over measurement bandwidths were <2 dB, which is similar to previous studies. Conversely, pteropod TS model predictions differed from measurements by >4 dB, with species with elongated shapes having larger differences, likely due to shell shape and uncertainty surrounding material properties. Widely used physics-based acoustic scattering models may significantly underestimate uncertainty in TS predictions for these animals. [ABSTRACT FROM AUTHOR]

Chemotherapy-induced diarrhea (CID) is a potentially serious side effect that often occurs during anticancer therapy and is caused by the toxic effects of chemotherapeutic drugs on the gastrointestinal tract, resulting in increased frequency of bowel movements and fluid contents. Among these agents, irinotecan (CPT-11) is most commonly associated with CID. Hesperidin (HPD), a flavonoid glycoside found predominantly in citrus fruits, has anti-oxidation properties and anti-inflammation properties that may benefit CID management. Nevertheless, its potential mechanism is still uncertain. In this study, we firstly evaluated the pharmacodynamics of HPD for the treatment of CID in a mouse model, then used network pharmacology and molecular docking methods to excavate the mechanism of HPD in relieving CID, and finally further proved the predicted mechanism through molecular biology experiments. The results demonstrate that HPD significantly alleviated diarrhea, weight loss, colonic pathological damage, oxidative stress, and inflammation in CID mice. In addition, 74 potential targets for HPD intervention in CID were verified by network pharmacology, with the top 10 key targets being AKT1, CASP3, ALB, EGFR, HSP90AA1, MMP9, ESR1, ANXA5, PPARG, and IGF1. The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that the PI3K–Akt pathway, FoxO pathway, MAPK pathway, TNF pathway, and Ras pathway were most relevant to the HPD potential treatment of CID genes. The molecular docking results showed that HPD had good binding to seven apoptosis-related targets, including AKT1, ANXA5, CASP3, HSP90AA1, IGF1, MMP9, and PPARG. Moreover, we verified apoptosis by TdT-mediated dUTP nick-end labeling (TUNEL) staining and immunohistochemistry, and the hypothesis about the proteins above was further verified by Western blotting in vivo experiments. Overall, this study elucidates the potential and underlying mechanisms of HPD in alleviating CID. [ABSTRACT FROM AUTHOR]

In this paper, we demonstrate the use of machine learning to optimize the continuous flow process of a crucial intermediate in the production of Nemonoxacin. Our focus is to achieve the good yield and enantioselectivity in the construction of chiral methyl group utilize the initial 29 experimental datasets and consider six important variables. Employing Single-Objective Bayesian optimization (SOBO), we achieved an impressive predicted yield of up to 89.7%, which is consistent with the experimental results, with a yield of 89.5%. Additionally, A Multi-Objective Bayesian Optimization (MOBO) algorithm, namely qNEHVI, to strike a balance between yield and enantioselectivity in the continuous flow system is applied. The algorithm's prediction, with a yield of 81.8% and enantioselectivity of 97.85%, was experimentally validated, yielding 83.8% and 97.2%, respectively. This study effectively demonstrates that Bayesian optimization is a powerful tool for optimizing the continuous process in the production of active pharmaceutical ingredients (APIs). [ABSTRACT FROM AUTHOR]

Understanding the flow dynamics of non-Newtonian fluids is crucial in various engineering, industrial, and biomedical applications. However, the existing generalized Reynolds number formulations for non-Newtonian fluids have limited applicability due to their dependencies on their specific viscosity models. In this study, we propose a new viscosity-model-independent generalized Reynolds number formulation for laminar pipe flow. The proposed method is based on the direct adaptation of the measurement principles of rotational viscometers for wall shear rate estimation. We assess the accuracy of this proposed formulation for power-law and Carreau-Yasuda viscosity models through robust friction factor experiments. The experimental results demonstrate the applicability and effectiveness of the proposed viscosity-model-independent Reynolds number, as the measured friction factor data align closely with our Reynolds number predictions. Furthermore, we compare the accuracy of our Reynolds number formulation against established generalized Reynolds formulations for pure shear-thinning (Carreau-Yasuda) and viscoplastic (Herschel-Bulkley-extended) models. The results of the comparative analysis confirm the reliability and robustness of this generalized Reynolds number in characterizing and interpreting flow behavior in systems with visco-inelastic non-Newtonian fluids. This unified generalized Reynolds number formulation presents new and significant opportunities for precise pipe flow characterization and interpretation as it is applicable to any visco-inelastic (time-independent) viscosity model without requiring additional derivations. [ABSTRACT FROM AUTHOR]

In response to limitations in vibration suppression performance of traditional linear tuned mass damper due to energy threshold constraints and narrow vibration bands, this study proposes a magnetic tri-stable NES (MTNES) formed by combining a linear spring and magnets. Compared to the conventional nonlinear energy sink (NES), the magnetic tri-stable NES (MTNES) incorporates magnetism to enhance the nonlinear stiffness. Firstly, the mechanism of the MTNES is introduced in this study, which reveals the existence of the three stable points in the system. Subsequently, the equations of motion of the coupled system with MTNES attached to the cantilever beam are derived, and the optimal parameter combination for MTNES is determined using a global optimization method. Furthermore, the influence of MTNES parameter variations on vibration suppression efficiency is studied through parameter analysis. Then, the restoring force of the MTNES is simplified into polynomial form, and the system response is analyzed using the harmonic balance method and Runge–Kutta method. Finally, experimental studies on the coupled system are conducted. The results indicate that MTNES can effectively suppress the resonance of the host structure within a wide frequency band, with the highest vibration suppression rate of up to 66% under strong modulated response. Additionally, the results of numerical calculations and theoretical analysis are in good agreement with that of the experiment. [ABSTRACT FROM AUTHOR]

Backgrounds: The ossification of the ligamentum flavum (OLF) is one of the major causes of thoracic myelopathy. Previous studies indicated there might be a potential link between metabolic disorder and pathogenesis of OLF. The aim of this study was to determine the potential role of metabolic disorder in the pathogenesis of OLF using the strict bioinformatic workflow for metabolism‐related genes and experimental validation. Methods: A series of bioinformatic approaches based on metabolism‐related genes were conducted to compare the metabolism score between OLF tissues and normal ligamentum flavum (LF) tissues using the single sample gene set enrichment analysis. The OLF‐related and metabolism‐related differentially expressed genes (OMDEGs) were screened out, and the biological functions of OMDEGs were explored, including the Gene Ontology enrichment analysis, Kyoto Encyclopedia of Genes and Genomes enrichment analysis, and protein–protein interaction. The competing endogenous RNA (ceRNA) network based on pairs of miRNA‐hub OMDEGs was constructed. The correlation analysis was conducted to explore the potential relationship between metabolic disorder and immunity abnormality in OLF. In the end, the cell experiments were performed to validate the roles of GBE1 and TNF‐α in the osteogenic differentiation of LF cells. Results: There was a significant difference of metabolism score between OLF tissues and normal LF tissues. Forty‐nine OMDEGs were screened out and their biological functions were determined. The ceRNA network containing three hub OMDEGs and five differentially expressed miRNAs (DEmiRNAs) was built. The correlation analysis between hub OMDEGs and OLF‐related infiltrating immune cells indicated that metabolic disorder might contribute to the OLF via altering the local immune status of LF tissues. The cell experiments determined the important roles of GBE1 expression and TNF‐α in the osteogenic differentiation of LF cells. Conclusions: This research, for the first time, preliminarily illustrated the vital role of metabolic disorder in the pathogenesis of OLF using strict bioinformatic algorithms and experimental validation for metabolism‐related genes, which could provide new insights for investigating disease mechanism and screening effective therapeutic targets of OLF in the future. [ABSTRACT FROM AUTHOR]

The purpose of this study is to investigate the ingredients and mechanisms through which Dalbergiae Odoriferae Lignum (DOL) reduces adriamycin-induced cardiotoxicity. DOL's ingredients and drug targets were acquired from Traditional Chinese Medicine System Pharmacology Database and Analysis Platform (TCMSP), and adriamycin-induced cardiotoxicity disease targets were gathered from GeneCards and National Center for Biotechnology Information (NCBI). The therapeutic targets of DOL against adriamycin-induced cardiotoxicity were identified by intersecting drug and disease targets. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) were conducted using R. Subsequently, core targets were determined and used for molecular docking with DOL ingredients. In vitro and in vivo experiments validated DOL's primary ingredients against adriamycin-induced cardiotoxicity efficacy. Western blot and immunohistochemistry verified its impact on target protein. After intersecting 530 drug targets and 51 disease targets, 19 therapeutic targets for DOL alleviated adriamycin-induced cardiotoxicity were received. Molecular docking demonstrated that DOL primary ingredient formononetin had a robust binding affinity for nitric oxide synthase 3 (NOS3). Experimental results showed that formononetin effectively mitigated adriamycin-induced cardiotoxicity. Additionally, western blot and immunohistochemistry showed that formononetin improved NOS3 expression. The network pharmacology and experimentation suggest that the primary ingredient of DOL, formononetin, may target NOS3 to act as a therapeutic agent for adriamycin-induced cardiotoxicity. [ABSTRACT FROM AUTHOR]

The mechanism of MaiFuSheng (MFS) on inhibiting Nonalcoholic Fatty Liver Disease (NAFLD) were investigated based on the exploration of chemical compositions, the techniques of network pharmacology and molecular docking, and the validation using NAFLD mice model. The components of MFS were identified through UPLC-Zeno TOF-MS/MS. The Swiss Bioinformatics Research Platform were applied to obtain active components and potential targets of MFS. The DisGeNet and OMIM databases were used to screen disease targets of NAFLD. The intersection between disease targets and potential targets of MFS were obtained from Venn diagram, which were analyzed by constructing cross-target protein-protein interaction (PPI) network. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were conducted on Metascape database. The molecular docking about core targets and active components of MFS were carried out. Using high-fat diet (HFD)-induced C57BL/6J mice as NAFLD animal model to validate key targets. A total of 130 compounds were recognized, 54 active constituents and 176 potential targets of NAFLD were collected. The molecular docking experiments for the top 10 components with the targets are based on the degree value. We found docking models with the best binding energy for TNF-α with Quercetin, IL-17 with Asiatic acid, and IL-1β with Quercetin. We applied qPCR technique to detect above inflammation and lipid metabolism related indicators. Enrichment analysis demonstrated that MFS protects NAFLD via biological processes such as fatty acid transformation and positive regulation of lipid metabolism, as well as signaling pathways such as AGE-RAGE, HIF-1, and IL-17. Compared to the control groups, the model group's ALT, TG, and LDL-C indicators increased, whereas HDL-C indicators dropped (P<0.05) . MFS and Simvastatin treatment groups significantly reduced body weight, liver weight, and fat weight compared to the model groups (P<0.05). Higher doses resulted in significant reductions in serum levels and expression of TNF-α, IL-1β, and IL-17 (P<0.01). Compared to the control groups, the MFS treatment groups can minimize liver lipid accumulation by modulating the expression of lipid metabolism-related genes and improving hepatic fat breakdown. [ABSTRACT FROM AUTHOR]

Active combustion control (ACC) technology is an effective measure for suppressing the combustion oscillation of aero-engines. The magnetostrictive actuator is the most suitable choice for the ACC actuator due to its excellent high-frequency characteristics and high-temperature resistance. In order for the magnetostrictive actuator to produce high-frequency displacement, the constant current driver must have sufficient power, which results in a larger mass of the driver. A solution is to use multi-channel and low-power constant current driver. Therefore, the coil of the magnetostrictive actuator is axially dispersed and driven by two four-channel servo amplifiers. The driver's mass is significantly reduced while maintaining the same electromagnetic conversion effect. In addition, an analytical model of a discrete coil magnetostrictive actuator is established, and a series of experiments are conducted. The maximum hysteresis error of output displacement at 200 Hz is reduced by 15.2%. Furthermore, under PID closed-loop control, the root mean square (RMS) error is less than 2% when tracking a 10 Hz sinusoidal displacement with coil switching drive. [ABSTRACT FROM AUTHOR]

Abstract Hypertension has become a major contributor to the morbidity and mortality of cardiovascular diseases worldwide. Despite the evidence of the anti‐hypertensive effect of gastrodia‐uncaria granules (GUG) in hypertensive patients, little is known about its potential therapeutic targets as well as the underlying mechanism. GUG components were sourced from TCMSP and HERB, with bioactive ingredients screened. Hypertension‐related targets were gathered from DisGeNET, OMIM, GeneCards, CTD, and GEO. The STRING database constructed a protein–protein interaction network, visualized by Cytoscape 3.7.1. Core targets were analyzed via GO and KEGG using R package ClusterProfiler. Molecular docking with AutodockVina 1.2.2 revealed favorable binding affinities. In vivo studies on hypertensive mice and rats validated network pharmacology findings. GUG yielded 228 active ingredients and 1190 targets, intersecting with 373 hypertension‐related genes. PPI network analysis identified five core genes: AKT1, TNF‐α, GAPDH, IL‐6, and ALB. Top enriched GO terms and KEGG pathways associated with the anti‐hypertensive properties of GUG were documented. Molecular docking indicated stable binding of core components to targets. In vivo study showed that GUG could improve vascular relaxation, alleviate vascular remodeling, and lower blood pressure in hypertensive animal models possibly through inhibiting inflammatory factors such as AKT1, mTOR, and CCND1. Integrated network pharmacology and in vivo experiment showed that GUG may exert anti‐hypertensive effects by inhibiting inflammation response, which provides some clues for understanding the effect and mechanisms of GUG in the treatment of hypertension.

This study aims to develop an encrypted motion-copying system using homomorphic encryption for secure motion preservation and reproduction. A novel concept of encrypted motion-copying systems is introduced, realizing the preservation, edition, and reproduction of the motion over encrypted data. The developed motion-copying system uses the conventional encrypted four-channel bilateral control system with robotic arms to save the leader's motion by a human operator in the ciphertext in a memory. The follower's control system reproduces the motion using the encrypted data loaded from the secure memory. Additionally, the developed system enables us to directly edit the motion data preserved in the memory without decryption using homomorphic operation. Finally, this study demonstrates the effectiveness of the developed encrypted motion-copying system in free motion, object contact, and spatial scaling scenarios.

Rongrong Zhang,1,&ast; Wenjun Xu,1,&ast; Hongquan Wei,1,&ast; Boshi Li,1 Yaoxing Wang,1 Xueqing He,1 Jun Cao,1 Xinyu He,1 Mingxiang Xu,1,2 Wenjie Lu,1 Youzhi Xu1 1College of Basic Medicine, Anhui Medical University, Hefei, 230032, People’s Republic of China; 2Center for Scientific Research, Anhui Medical University, Hefei, 230032, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Youzhi Xu; Wenjie Lu, Email xuyouzhi@ahmu.edu.cn; wenjie63136@163.comPurpose: Currently, there is still no clear treatment for polycystic ovary syndrome (PCOS). YJKL has better therapeutic effects and lower toxic side effects for PCOS type infertility. This study aims to clarify the potential mechanism of YJKL Decoction in the treatment of PCOS based on network pharmacology and experiments verification.Patients and Methods: Network pharmacology and experimental validation approach were used to investigate the bioactive ingredients, critical targets and potential mechanisms of YJKL Decoction against PCOS. Firstly, we use network pharmacology methods to collect core targets, and then validate their effects on diseases through experiments.Results: Five core targets were screened, Threonine kinase 1 (AKT1), Cellular tumor antigen p53 (TP53), Tumor necrosis factor (TNF), Albumin (ALB) and Vascular endothelial growthfactor A (VEGFA). KEGG analysis showed that YJKL treatment for PCOS mainly include AGE-RAGE signaling pathway in diabetic complications, TNF signaling pathway and HIF-1 signaling pathway. The molecular docking results showed that compounds have higher affinity with targets. Finally, experimental results had shown that YJKL Decoction had an better therapeutic effects in the treatment of PCOS.Conclusion: Based on a systematic network pharmacology approach and experimental verification, our results comprehensively illustrated the active ingredients, potential targets, and molecular mechanism of YJKL for application to PCOS and helps to illustrate mechanism of action on a comprehensive level.Keywords: traditional Chinese Medicine, YJKL, polycystic ovary syndrome, PCOS, molecular docking, experimental validation

This paper presents a computational framework for drop time assessment of a control element assembly (CEA) under fuel assembly (FA) deformations. The proposed framework consists of three key components: 1) finite element modeling of CEA, 2) fluid-structure interaction to compute drag force, and 3) modeling of frictional contact between CEA and FA. Specially, to accommodate the large motion of CEA, beam elements based on absolute nodal coordinate formulation (ANCF) are adopted. The continuity equation is utilized to calculate the drag force, considering flow changes in the cross-sectional area during the CEA drop. Lastly, beam-inside-beam frictional contact model is employed to capture practical contact conditions between CEA and FA. The proposed framework is validated through experiments under two scenarios: free falls of CEA within FA, encompassing undeformed and deformed scenarios. The experimental validation of the framework demonstrated that the drop time of CEA can be accurately predicted under the complex coupling effects of fluid and frictional contact. The drop times of the S-shaped deformation case is longer than those of the C-shaped deformation case, affirming the time delay due to frictional force. The validation confirms the potential applicability to access the safety and reliability of nuclear power plants under extreme conditions.

Reactivity worth of fuel rods at the JSI TRIGA research reactor was measured. Differently burned fuel rods were chosen to validate fuel burnup calculations. Two methods of measuring reactivity worth of fuel rods are used, traditional method is compared to newly introduced method using fuel rods swapping. Connection between both methods is described theoretically and the theory is validated experimentally. Fuel rod worth calculated using the newly introduced fuel rod swap method was within 1σ of worth measured using the traditional method. In addition to the recently performed experiments, weekly measurements of reactor core reactivity throughout the operational history are used for validation. The measured data were used to validate the fuel burnup and core criticality calculations. Fuel burnup calculations are performed using three different computer codes: the deterministic TRIGLAV, the Monte Carlo Serpent-2, and the hybrid RAPID. Great agreement was observed for Serpent-2 and RAPID by simulating fuel rod worth and its burnup, indicating that the fuel burnup and criticality calculations are accurate and that reactivity changes due to small burnup differences on the order of 10 pcm can be accurately simulated. In addition it was shown using ex-core detectors and large fission chamber that detector response changes due to fuel swapping are evident for fuel rod burnup differences of 20 MWd/kg. Fuel burnup calculations were further validated on excess reactivity measurements for three mixed TRIGA cores. The calculated burnup reactivity coefficient ΔρBU using Serpent-2 and RAPID was within 1σ of the measurements, showing both codes are capable of calculating burnup for different TRIGA fuel types.

Abstract Objective To evaluate the anti-tumor effector of Liuwei Dihuang Decoction (LWDHD) in prostate cancer (PCa) and explore the potential mechanism using experimental validation, network pharmacology, bioinformatics analysis, and molecular docking. Methods CCK test, Clone formation assay and wound-healing assays were used to determine the effect of LWDHD on prostate cancer growth and metastasis. The active ingredients and targets of LWDHD were obtained from the TCMSP database, and the relevant targets were selected by GeneCards, OMIM and DisGeNET databases for PCa. The cross-targets of drugs and disease were imported into the STRING database to construct protein interactions. The network was also visualized using Cytoscape software and core targets are screened using the Network Analyzer plug-in. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were analyzed using R software. TCGA database was used to analyze the correlation of bioinformatics genes. AutoDock vina was used to predict the molecular docking and binding ability of active ingredients to key targets. Through WB and q-PCR experiments, the above gene targets were detected to verify the effect of LWDHD on PCa. Results CCK and scratch tests confirmed that LWDHD could inhibit the proliferation, invasion and migration of prostate cancer cells. Clone formation experiments showed that LWDHD inhibited the long-term proliferative capacity of PC3 cells. LWDHD and PCa had a total of 99 common targets, establishing a “drug-ingredient-common target” network. Through GO and KEGG enrichment analysis, PI3K/AKT, MAPK, TP53 pathway, MYC, TNF pathway and other signaling pathways were found. Bioinformatics analysis showed that MYC gene was highly expressed and CCND1 and MAPK1 were low expressed in prostate cancer tissues. In addition, TP53, AKT1, MYC, TNF and CCND1 were positively correlated with MAPK1, among which AKT1 and CCND1 were most closely correlated with MAPK1. Molecular docking results showed that quercetin, kaempferol, β-sitosterol and other main active ingredients of LWDHD treatment for PCa were combined with core proteins MAPK1 and AKT1 well. WB and q-PCR results showed that LWDHD inhibited the expression of PI3K and AKT in PC3 cells. Conclusion The mechanism of LWDHD therapy for PCa is a multi-target and multi-pathway complex process, which may be related to the biological processes mediated by MAPK1 and AKT1 pathways, such as cell proliferation and inhibition of metastasis, and the regulation of signaling pathways. The PI3K/AKT signaling pathway may be a central pathway of LWDHD to inhibit prostate cancer proliferation.

Jilei Li,1,&ast; Wenchao Dan,2,&ast; Chenchen Zhang,3 Nian Liu,3 Yichong Wang,1 Jixiang Liu,3 Shengsheng Zhang1 1Digestive Disease Center, Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, 100010, People’s Republic of China; 2Department of Dermatology, Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, 100010, People’s Republic of China; 3Beijing University of Chinese Medicine, Beijing, 100029, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Shengsheng Zhang, Digestive Disease Center, Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, 100010, Tel +8613801088329, Email zhangshengsheng@bjzhongyi.comPurpose: This study aimed to delineate the molecular processes underlying the therapeutic effects of berberine on UC by employing network pharmacology tactics, molecular docking, and dynamic simulations supported by empirical validations both in vivo and in vitro.Patients and Methods: We systematically screened potential targets and relevant pathways affected by berberine for UC treatment from comprehensive databases, including GeneCards, DisGeNET, and GEO. Molecular docking and simulation protocols were used to assess the interaction stability between berberine and its principal targets. The predictions were validated using both a DSS-induced UC mouse model and a lipopolysaccharide (LPS)-stimulated NCM460 cellular inflammation model.Results: Network pharmacology analysis revealed the regulatory effect of the TLR4/NF-κB/HIF-1α pathway in the ameliorative action of berberine in UC. Docking and simulation studies predicted the high-affinity interactions of berberine with pivotal targets: TLR4, NF-κB, HIF-1α, and the HIF inhibitor KC7F2. Moreover, in vivo analyses demonstrated that berberine attenuates clinical severity, as reflected by decreased disease activity index (DAI) scores, reduced weight loss, and mitigated intestinal inflammation in DSS-challenged mice. These outcomes include suppression of the proinflammatory cytokines IL-6 and TNF-α and downregulation of TLR4/NF-κB/HIF-1α mRNA and protein levels. Correspondingly, in vitro findings indicate that berberine decreases cellular inflammatory injury and suppresses TLR4/NF-κB/HIF-1α signaling, with notable effectiveness similar to that of the HIF-1α inhibitor KC7F2.Conclusion: Through network pharmacology analysis and experimental substantiation, this study confirmed that berberine enhances UC treatment outcomes by inhibiting the TLR4/NF-κB/HIF-1α axis, thereby mitigating inflammatory reactions and improving colonic pathology. Keywords: berberine, ulcerative colitis, TLR4/NF-κB/HIF-1α, network pharmacology, molecular docking, experimental validation, inhibitor

Rising energy prices have increased the popularity of many renewable energy sources including heat pumps. In the case of ground heat pumps research related to the analysis of the operation and selection of ground heat exchangers as a heat source are insufficient. With this in mind, on the operation of the horizontal slinky coil heat exchanger research work has been undertaken. As a research tool, the Computational Fluid Dynamics has been used. To check the adequacy of the CFD model, a validation of the model was carried out using the results of research on a real heat exchanger. Comparison was made: values of ground temperatures, outlet temperatures from the exchanger, and heat flux exchanged by the heat exchanger. In the opinion of the authors, the validation of the CFD model was successful.

Abstract Cryptosporidiosis is a worldwide zoonotic disease. Oxymatrine, an alkaloid extracted and isolated from the plant bitter ginseng, has been reported to have therapeutic effects on cryptosporidiosis. However, the underlying mechanism of its action remains unclear. In this study, we utilized network pharmacology and experimental validation to investigate the mechanism of oxymatrine in the treatment of cryptosporidiosis. First, the potential targets of drugs and diseases were predicted by TCMSP, Gene Cards, and other databases. Following the intersection of drug-disease targets, the DAVID database was used to implement the enrichment analysis of GO functions and KEGG pathways, and then the network diagram of "intersected target-KEGG" relationship was constructed. Autodock 4.2.6 software was used to carry out the molecular docking of core targets to drug components. Based on the establishment of a mouse model of cryptosporidiosis, the validity of the targets in the TNF/NF-κB signaling pathway was confirmed using Western blot analysis and Quantitative Rea-ltime-PCR. A total of 41 intersectional targets of oxymatrine and Cryptosporidium were generated from the results, and five core targets were screened out by network analysis, including RELA, AKT1, ESR1, TNF, and CASP3. The enrichment analysis showed that oxymatrine could regulate multiple gene targets, mediate TNF, Apoptpsis, IL-17, NF-κB and other signaling pathways. Molecular docking experiments revealed that oxymatrine was tightly bound to core targets with stable conformation. Furthermore, we found through animal experiments that oxymatrine could regulate the mRNA and protein expression of IL-6, NF-κB, and TNF-α in the intestinal tissues of post-infected mice through the TNF/NF-κB signaling pathway. Therefore, it can be concluded that oxymatrine can regulate the inflammatory factors TNF-α, NF-κB, and IL-6 through the TNF/NF-κB signaling pathway for the treatment of cryptosporidiosis. This prediction has also been validated by network pharmacology and animal experiments.

Agricultural greenhouses incorporate intricate systems to regulate the internal climate. Among the crucial climatic variables, indoor temperature and humidity take precedence in establishing an optimal environment for plant production and growth. The present research emphasizes the efficacy of employing intelligent control systems in the automation of the indoor climate for smart insulated greenhouses (SIGs), utilizing a fuzzy logic controller (FLC). This paper proposes the use of an FLC to reduce the energy consumption of a greenhouse. In the first step, a thermodynamic model is presented and experimentally validated based on thermal heat exchanges between the indoor and outdoor climatic variables. The outcomes show the effectiveness of the proposed model in controlling indoor air temperature and relative humidity with a low error percentage. Secondly, several fuzzy logic control models have been developed to regulate the indoor temperature and humidity for cold and hot periods. The results show the good performance of the proposed FLC model as highlighted by the statistical analysis. In fact, the root mean squared error (RMSE) is very small and equal to 0.69% for temperature and 0.23% for humidity, whereas the efficiency factor (EF) of the fuzzy logic control is equal to 99.35% for temperature control and 99.86% for humidity control.

Abstract Polysaccharopeptide (PSP) is a potential active component in traditional Chinese medicine because of its anticancer effects on a variety of cancer cells and as immune enhancers of the immune system. Previous studies on the role of PSP in breast cancer have been limited, and the mechanism has not been clarified. This study is based on network pharmacology and molecular docking technology to predict the possible target of PSP treatment of breast cancer, and use experiments to verify the effect and mechanism of PSP on breast cancer. In this study, 287 PSP targets were obtained using SwissTargetPrediction database and PharmMapper database, and 183 breast cancer targets were obtained using DisGenNET database. By intersections of PSP targets and breast cancer targets, a total of 10 intersections were obtained. GO functional enrichment, KEGG pathway enrichment and molecular docking of these 10 target genes were performed to obtain the potential targets of PSP on breast cancer. In vitro experiments, we found that PSP significantly inhibited the proliferation and induced apoptosis of breast cancer cell lines MDA-MB-231, SUM-159 and MCF-7. Western Blot results showed that PSP could down-regulate the expression of p-JAK2 and p-STAT3 proteins. Similarly, the results of in vivo experiments showed that PSP can directly inhibit the tumor of MDA-MB-231 tumor-bearing mice, and the mechanism of action is mainly to inhibit the JAK2-STAT3 pathway. The above results were consistent with the results of network pharmacology, which provides a scientific basis for the clinical application of PSP in breast cancer patients.

Abstract Background Traditional Chinese medicine (TCM) has been found widespread application in neoplasm treatment, yielding promising therapeutic candidates. Previous studies have revealed the anti-cancer properties of Brevilin A, a naturally occurring sesquiterpene lactone derived from Centipeda minima (L.) A.Br. (C. minima), a TCM herb, specifically against lung cancer. However, the underlying mechanisms of its effects remain elusive. This study employs network pharmacology and experimental analyses to unravel the molecular mechanisms of Brevilin A in lung cancer. Methods The Batman-TCM, Swiss Target Prediction, Pharmmapper, SuperPred, and BindingDB databases were screened to identify Brevilin A targets. Lung cancer-related targets were sourced from GEO, Genecards, OMIM, TTD, and Drugbank databases. Utilizing Cytoscape software, a protein-protein interaction (PPI) network was established. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene set enrichment analysis (GSEA), and gene-pathway correlation analysis were conducted using R software. To validate network pharmacology results, molecular docking, molecular dynamics simulations, and in vitro experiments were performed. Results We identified 599 Brevilin A-associated targets and 3864 lung cancer-related targets, with 155 overlapping genes considered as candidate targets for Brevilin A against lung cancer. The PPI network highlighted STAT3, TNF, HIF1A, PTEN, ESR1, and MTOR as potential therapeutic targets. GO and KEGG analyses revealed 2893 enriched GO terms and 157 enriched KEGG pathways, including the PI3K-Akt signaling pathway, FoxO signaling pathway, and HIF-1 signaling pathway. GSEA demonstrated a close association between hub genes and lung cancer. Gene-pathway correlation analysis indicated significant associations between hub genes and the cellular response to hypoxia pathway. Molecular docking and dynamics simulations confirmed Brevilin A’s interaction with PTEN and HIF1A, respectively. In vitro experiments demonstrated Brevilin A-induced dose- and time-dependent cell death in A549 cells. Notably, Brevilin A treatment significantly reduced HIF-1α mRNA expression while increasing PTEN mRNA levels. Conclusions This study demonstrates that Brevilin A exerts anti-cancer effects in treating lung cancer through a multi-target and multi-pathway manner, with the HIF pathway potentially being involved. These results lay a theoretical foundation for the prospective clinical application of Brevilin A.

The distribution of the magnetic field generated by an electromagnetic device can provide insights into their operational condition. This paper focuses on diagnosing electrolyzers through magneto-tomography, a method which involves mapping the magnetic field generated by electrical devices. Since current density and magnetic field are directly linked, this study can characterize the normal and abnormal operation of an electrolyzer. To achieve this, a two-dimensional (2-D) Biot–Savart model in polar coordinates is developed. To validate this model for electrolyzer diagnostics, an experimental setup was established to replicate the electrolyzer operation. The purely analytical model was successfully validated, with the average difference between the analytical results and experimental measurements established. The model validation is performed by comparing the experimental data to the theoretical results, and it is observed that the difference does not exceed 5%. [ABSTRACT FROM AUTHOR]

The prevalent numerical models for simulating axially finned heat exchangers with phase change materials (PCMs) and water as the heat transfer fluid rely on computational fluid dynamics (CFD) techniques, with a primary focus on phase change modeling. However, the computational demands of these models, incorporating phase change effects and resolving PCM movement in the liquid state, are substantial. From experiments suggesting that conduction in the solidified PCM around the finned tube dominates heat transfer during the heat discharge process, this article introduces a simplified CFD‐based model in which convective flow of the PCM is neglected. The model is experimentally validated using a 1‐m‐long axially finned heat exchanger prototype with four fins, recording temperatures under different water flow rates and orientations (horizontal and vertical). Results show that the proposed model predicts outlet water temperature satisfactorily, with absolute errors below 1.0°C and 2.2°C for the horizontal and vertical orientations, respectively. Additionally, the model can capture the temperature trend inside the PCM for the horizontal orientation. [ABSTRACT FROM AUTHOR]

This paper presents the results of an experimental investigation of the influence of electrode configuration on corona discharge and particle collection under ambient climatic conditions in Blade-to-Plane Electrostatic Precipitator (BP-ESP). In an experimental-scale electrostatic precipitator (BP-ESP), electrodes of different shapes (blade, saw blade with small tooth, and saw blade with large tooth) were tested. The experiments were performed with three types of dust particles having a mean size of about 5 µm, 10 µm, and 45 µm. An aerosol spectrometer was used to characterize the chemical composition of these dust particles injected into the ESP. Different DC-applied voltages have been taken into account for both positive and negative polarities. Results showed that a high current was generated with a saw blade electrode with large teeth which increased the particle collection efficiency, for both polarities. The negative corona discharge is overall more effective than the positive one for the different configurations of electrodes and dust particles used. [ABSTRACT FROM AUTHOR]

This paper deals with the synthesis and implementation of a controller for asymptotic tracking of the desired trajectory of a mobile robot. The mobile robot used for the experimental validation has eight motors with an inner control loop. Four steering actuators are controlled using position controllers and four driving actuators are controlled using velocity controllers. A complex robot kinematic model is converted into a control-oriented linear time-varying system, which is then used to design a time-varying control law that minimizes the quadratic optimality criterion. In contrast to conventional methodologies for solving the corresponding Riccati differential equations, a computational approach that explicitly determines the time-varying controller matrix by employing recurrent matrix computations is proposed. Mobile robot control inputs (linear velocity, steering angles and steering velocities) are forwarded to the steering and driving actuators with properly tuned position and velocity controllers using an inverse kinematic model of the mobile robot. The obtained control law is evaluated on an experimental set-up of a real mobile robot system. The controller is implemented using the Robot Operating System. [ABSTRACT FROM AUTHOR]

This study presents a novel conceptual laboratory‐scale double drum dryer (LDD) optimized for the efficient drying of wheat flour slurry into flakes. The research stems from the need to address the complexities of previous methodologies, lack of studies on industrial‐sized dryers, and high cost. The methodology involved designing dryer components, transmission system, creating engineering drawings, and simulating LDD with varied operating parameters. Verification was done using industrial double drum dryer (IGD) data and MATLAB simulations. Parameters were explored including temperature (120–140°C), drum dimension (0.1–0.7 m), and film thickness (0.3–0.6 mm). The design closely matched real‐world performance metrics with mean relative deviations of 2.67%, 3.30%, 10.12% for drum speed, water content, and throughput respectively. The predictive model outperformed the IGD, achieving a 9.13% increase in throughput. Optimal LDD parameters were identified 0.7 m length, 0.2 m diameter, 0.3 mm film thickness, 40% slurry TSS, 120°C temperature, and 4.47 rpm rotational speed, resulting in 3.00% water content and 132.78 kgh−1 throughput offering valuable insights for similar applications in the food industries. Practical applications: The research on the novel laboratory‐scale double drum dryer for drying wheat flour‐based slurry holds significant practical implications in the food industry. Firstly, the optimized design and simulation‐based approach offer a cost‐effective and efficient solution for small‐scale food processing businesses aiming to produce wheat flour flakes. By identifying optimal drying parameters, including temperature, drum dimensions, and film thickness, the research enables precise control over the drying process, leading to enhanced product quality and throughput. Moreover, the close agreement between simulation results and industrial observations validates the effectiveness of the proposed methodology, instilling confidence in its practical applicability. The development of a prototype based on these findings facilitates the adoption of this technology by small‐scale enterprises, empowering them to improve their production processes and competitiveness. Overall, this research contributes to advancing drying technology in the food industry, offering tangible benefits in terms of product quality, efficiency, and operational cost reduction. [ABSTRACT FROM AUTHOR]

Copyright of Traditional Chinese Drug Research & Clinical Pharmacology is the property of Traditional Chinese Drug Research & Clinical Pharmacology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

When structures are subjected to dynamic loading, such as that caused by an earthquake or working machinery, the rocking behavior of objects located on parts of the loaded structure plays an important role in addressing the protection and stability of non-structural components. In this work, the free rocking of a rigid block on a flexible beam and rigid base was investigated using numerical simulations. To this end, a numerical code based on the non-smooth contact dynamics method was developed for this particular problem, and numerical simulations are compared to experimental tests when a rigid base is considered. The purpose of the study was to investigate the predictive capabilities and limitations of the numerical model and address the effect of introducing beam flexibility on the rocking response. The investigated flexibilities were such that the beam deflection under the static weight of the block remains within the common limit of 1/250 of the beam span. For a rigid base, qualitatively good correlation with the experiments was obtained, and good convergence in terms of the time-step is displayed. With the increase in beam base flexibility, it was observed that the simulation results tend to become more sensitive to mesh density and time-step size. Furthermore, we identify a limited flexibility with respect to which unreliable predictions of the overall free rocking are obtained, which corresponds to the stiffness resulting in the beam deflection under the block weight of beam-span/2500. For stiffnesses higher than that, no significant effect of beam flexibility in comparison to the rigid base was noticed in terms of tilt angle and rocking duration, which indicates the adequacy of a rigid base approximation for beams with low flexibility. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Ordnance Equipment Engineering is the property of Chongqing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The demand for electric vehicle supply equipment (EVSE) is increasing because of the rapid shift toward electric transport. Introducing EVSE on a large scale into the power grid can increase power demand volatility, negatively affecting frequency stability. A viable solution to this challenge is the development of smart charging technologies capable of performing frequency regulation. This paper presents an experimental proof of concept for a new frequency regulation method for EVSE utilizing a distributed control architecture. The architecture dynamically adjusts the contribution of electric vehicles (EVs) to frequency regulation response based on the charging urgency assigned by the EV users. The method is demonstrated with two Renault ZOEs responding to frequency fluctuation with a combined power range of 6 kW in the frequency range of 50.1 to 49.9 Hz. The results confirm consistent power sharing and effective frequency regulation, with the system controlling the engagement of the EVs in frequency regulation based on priority. The delay and accuracy analyses reveal a fast and accurate response, with the cross-correlation indicating an 8.48 s delay and an average undershoot of 0.17 kW. In the conclusions, the paper discusses prospective improvements and outlines future research directions for integrating EVs as service providers. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the anti-tumor effector of Liuwei Dihuang Decoction (LWDHD) in prostate cancer (PCa) and explore the potential mechanism using experimental validation, network pharmacology, bioinformatics analysis, and molecular docking. Methods: CCK test, Clone formation assay and wound-healing assays were used to determine the effect of LWDHD on prostate cancer growth and metastasis. The active ingredients and targets of LWDHD were obtained from the TCMSP database, and the relevant targets were selected by GeneCards, OMIM and DisGeNET databases for PCa. The cross-targets of drugs and disease were imported into the STRING database to construct protein interactions. The network was also visualized using Cytoscape software and core targets are screened using the Network Analyzer plug-in. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were analyzed using R software. TCGA database was used to analyze the correlation of bioinformatics genes. AutoDock vina was used to predict the molecular docking and binding ability of active ingredients to key targets. Through WB and q-PCR experiments, the above gene targets were detected to verify the effect of LWDHD on PCa. Results: CCK and scratch tests confirmed that LWDHD could inhibit the proliferation, invasion and migration of prostate cancer cells. Clone formation experiments showed that LWDHD inhibited the long-term proliferative capacity of PC3 cells. LWDHD and PCa had a total of 99 common targets, establishing a "drug-ingredient-common target" network. Through GO and KEGG enrichment analysis, PI3K/AKT, MAPK, TP53 pathway, MYC, TNF pathway and other signaling pathways were found. Bioinformatics analysis showed that MYC gene was highly expressed and CCND1 and MAPK1 were low expressed in prostate cancer tissues. In addition, TP53, AKT1, MYC, TNF and CCND1 were positively correlated with MAPK1, among which AKT1 and CCND1 were most closely correlated with MAPK1. Molecular docking results showed that quercetin, kaempferol, β-sitosterol and other main active ingredients of LWDHD treatment for PCa were combined with core proteins MAPK1 and AKT1 well. WB and q-PCR results showed that LWDHD inhibited the expression of PI3K and AKT in PC3 cells. Conclusion: The mechanism of LWDHD therapy for PCa is a multi-target and multi-pathway complex process, which may be related to the biological processes mediated by MAPK1 and AKT1 pathways, such as cell proliferation and inhibition of metastasis, and the regulation of signaling pathways. The PI3K/AKT signaling pathway may be a central pathway of LWDHD to inhibit prostate cancer proliferation. [ABSTRACT FROM AUTHOR]

Gynostemma pentaphyllum is commonly used to treat various tumors in China. The aim of the study is to explore the pharmacological mechanism of Gynostemma pentaphyllum in gastric cancer using joint network pharmacology, molecular docking and in vitro experimental verification. First, the active constituents and potential targets of Gynostemma pentaphyllum were screened from a public database and screening of core targets anti-gastric cancer using protein-protein interaction networks. The Cancer Genome Atlas and Human Protein Atlas databases were used to evaluate the messenger ribonucleic acid and protein expression of core target genes in normal gastric epithelium and gastric cancer tissues and their relationship with overall survival in gastric cancer. Functional and pathway enrichment analyses of the potential targets were performed using gene ontology and Kyoto encyclopedia of genes and genomes. Fifteen active components and all related targets of Gynostemma pentaphyllum were retrieved from the Traditional Chinese Medicine Systems Pharmacology database and 127 potential targets were identified by intersection with colorectal cancer-related targets. Protein-protein interaction network analysis showed that six target genes, AKT serine/threonine kinase 1, Jun proto-oncogene and B-cell lymphoma 2 proteins were key genes. Gene ontology enrichment analysis involved 1892 BP, 37 CC and 142 MF. Kyoto encyclopedia of genes and genomes enrichment analysis showed that the anti-cancer effects of Gynostemma pentaphyllum were mediated by advanced glycation end products-receptor for advanced glycation end products, interleukin-17, hypoxia inducible factor 1 and transforming growth factor signalling pathways. Molecular docking revealed that the three core target proteins stably bound to quercetin and rhamnazin. The results of the in vitro experiments showed that both quercetin and rhamnazin inhibited the activity of gastric cancer cells, up-regulated the messenger ribonucleic acid and protein AKT serine/threonine kinase 1 and down-regulated Jun proto-oncogene and B-cell lymphoma 2 protein activities at the specified concentrations. This study revealed the potential role of Gynostemma pentaphyllum in the treatment of gastric using network pharmacology, molecular docking and in vitro experiments. [ABSTRACT FROM AUTHOR]

Malaria is an infectious disease caused by Plasmodium spp. parasites, with widespread drug resistance to most antimalarial drugs. We report the development of two 3D-QSAR models based on comparative molecular field analysis (CoMFA), comparative molecular similarity index analysis (CoMSIA), and a 2D-QSAR model, using a database of 349 compounds with activity against the P. falciparum 3D7 strain. The models were validated internally and externally, complying with all metrics (q2 > 0.5, r2test > 0.6, r2m > 0.5, etc.). The final models have shown the following statistical values: r2test CoMFA = 0.878, r2test CoMSIA = 0.876, and r2test 2D-QSAR = 0.845. The models were experimentally tested through the synthesis and biological evaluation of ten quinoline derivatives against P. falciparum 3D7. The CoMSIA and 2D-QSAR models outperformed CoMFA in terms of better predictive capacity (MAE = 0.7006, 0.4849, and 1.2803, respectively). The physicochemical and pharmacokinetic properties of three selected quinoline derivatives were similar to chloroquine. Finally, the compounds showed low cytotoxicity (IC50 > 100 µM) on human HepG2 cells. These results suggest that the QSAR models accurately predict the toxicological profile, correlating well with experimental in vivo data. [ABSTRACT FROM AUTHOR]

Searching an optimal value of the neural emulator adaptive rate presents a great problem. Indeed, a new scheme of neural emulators based on the Particle Swarm Optimization (PSO) algorithm for nonlinear systems is adopted in this paper. The main goal of this approach consists in adjusting effectively the neural emulator adaptive rate in order to accelerate the convergence speed and to improve the precision degree. The obtained results are compared with those reached with an intelligent tuning strategy. An experimental validation of the new emulator adaptation is carried on chemical reactor. Efficiency of the proposed method is proved according to the obtained performances. [ABSTRACT FROM AUTHOR]

To examine the precise function of influenza A virus target genes (IATGs) in malignancy. Using multi-omics data from the TCGA and TCPA datasets, 33 tumor types were evaluated for IATGs. IATG expression in cancer cells was analyzed using transcriptome analysis. Copy number variation (CNV) was assessed using GISTICS 2.0. Spearman's analysis was used to correlate mRNA expression with methylation levels. GSEA was used for the enrichment analysis. Pearson's correlation analysis was used to examine the association between IATG mRNA expression and IC50. The ImmuCellAI algorithm was used to calculate the infiltration scores of 24 immune cell types. In 13 solid tumors, IATG mRNA levels were atypically expressed. Except for UCS, UVM, KICH, PCPG, THCA, CHOL, LAMI, and MESO, most cancers contained somatic IATG mutations. The main types of CNVs in IATGs are heterozygous amplifications and deletions. In most tumors, IATG mRNA expression is adversely associated with methylation. RT-PCR demonstrated that EGFR , ANXA5 , CACNA1C , CD209 , UVRAG were upregulated and CLEC4M was downregulated in KIRC cell lines, consistent with the TCGA and GTEx data. Genomic changes and clinical characteristics of IATGs were identified, which may offer fresh perspectives linking the influenza A virus to cancer. [ABSTRACT FROM AUTHOR]

This paper presents an innovative approach to characterize the boosting gain saturation phenomenon in DC–DC converters with variable duty cycles, a crucial component in energy management applications such as renewable energy systems and IoT devices. While existing literature predominantly relies on steady-state models to explain boosting gain behaviour, this study reveals discrepancies between theoretical predictions and experimental observations, particularly at high duty cycles. The research introduces an analytical model to accurately capture the boosting gain dynamics of a boost chopper converter, addressing the limitations of traditional steady-state analyses. Through experimental validation and numerical simulations using CAD tools, a significant boosting gain saturation of approximately 2.2 is empirically observed, highlighting the necessity for a transient model approach. By providing a comprehensive understanding of the boosting ratio constraints in practical boost converters, this work contributes to advancing the analytical modelling techniques in the field. The mathematical model’s validation through rigorous experimental measurements and simulation analyses underscores its reliability and applicability in real-world scenarios. The structured organization of the paper elucidates the development and verification process, culminating in insightful conclusions that underscore the significance of transient modelling in enhancing the performance and efficiency of DC–DC converters.Article Highlights: Novel transient model enhances DC–DC converter performance. Boosting gain saturation validated through experiments. Insights on boosting ratio constraints for practical applications [ABSTRACT FROM AUTHOR]