Resistance Model Research Articles

Frost resistance and damage evolution model of basalt fiber-reinforced recycled concrete based on recycled coarse aggregate strengthening and vibration mixing processes

A self-created grinder machine was utilized to clear the wrapped mortar from recycled coarse aggregates (RCA) in order to enhance the performance of basalt fiber-reinforced recycled aggregate concrete (BFRAC). In combination with the RCA strengthening and vibration mixing processes, the mechanical properties and freeze-thaw frost of BFRAC were tested to clarify the mechanism for improving the frost resistance under the synergistic effect of basalt fiber (BF) reinforcement and vibration mixing. Meanwhile, the impact of the production process and BF strengthening technique on RAC performance was explained from a microscopic standpoint using a scanning electron microscope (SEM) test, and aggregate-old mortar interface transition zones were significantly reduced. BF is beneficial in improving the mechanical properties and frost resistance of recycled aggregate concrete (RAC). Among them, the performance improvement effect of RAC is the most significant when using vibration mixing processes, adding BF with a length of 18 mm and a content of 0.2 %. It can increase the compressive strength of RAC by 19 % compared to ordinary mixing, the splitting tensile strength by 37.6 %, and the flexural strength by 34.4 %. A polynomial damage deterioration model was established with relative dynamic elastic modulus and compressive strength as damage variables. The results show that the model can accurately predict the degree of freeze-thaw damage of BFRAC. The research results have significant theoretical value for enhancing the frost resistance performance of RAC.

A multi-objective optimisation approach for the linear modelling of cerebral autoregulation system

Objective:Dynamic cerebral autoregulation (dCA) has been addressed through different approaches for discriminating between normal and impaired conditions based on spontaneous fluctuations in arterial blood pressure (ABP) and cerebral blood flow (CF). This work presents a novel multi-objective optimisation (MO) approach for finding good configurations of a cerebrovascular resistance-compliance model. Methods:Data from twenty-nine subjects under normo and hypercapnic (5% CO2 in air) conditions was used. Cerebrovascular resistance and vessel compliance models with ABP as input and CF velocity as output were fitted using a MO approach, considering fitting Pearson’s correlation and error. Results:MO approach finds better model configurations than the single-objective (SO) approach, especially for hypercapnic conditions. In addition, the Pareto-optimal front from the multi-objective approach enables new information on dCA, reflecting a higher contribution of myogenic mechanism for explaining dCA impairment.

Identification of Important Wetlands and Optimization of Landscape Patterns Based on Human Pressure Index: The Case of the Linghekou Wetland in China

The Linghekou wetland is a rich repository of ecological resources and serves as an important habitat for numerous rare and protected animals. However, due to a confluence of natural and anthropogenic factors, the ecological environment of the Linghekou wetland is facing a multitude of threats, including the reduction in wetland area, the degradation of wetland resources, and the instability of ecological structure. This paper employs an anthropogenic focus, utilizing the human pressure index (HPI), spatial autocorrelation, and cold and hot spot methods to identify crucial wetlands. These identified wetlands are then utilized as ecological source sites to optimize the landscape pattern of the Linghekou wetland, employing the minimum cumulative resistance (MCR) model. The final results indicated the identification of 6 ecological sources, 8 ecological corridors, and 42 ecological nodes. These were primarily concentrated in the southern region of the study area and were distributed in a reasonable manner. The method of identifying ecological sources when optimizing the landscape pattern with the MCR model was enriched by this approach. Additionally, the paper offers recommendations for the optimization of the landscape pattern of the Linghekou wetland and establishes a foundation for the protection and restoration of other similar wetlands.

A method determining critical operating parameters for landing aircraft based on runway pavement skid resistance

ABSTRACT Poor skid resistance of airport pavement is the critical cause of runway excursion accidents. While the current determination methods of skid resistance are limited to the independent operating parameters and the discontinuously monitoring the skid resistance, the empirically calculating critical operating parameters. In this study, an aircraft tire-fluid-airport pavement skid resistance model was developed using numerical simulation technology. The wide-body aircraft B777 was taken as an example, the available skid number (SN) was used to continuously track the skid resistance of pavement under various landing conditions. The combined effects of groove type, water film thickness and landing weight on the pavement skid resistance performance were evaluated when the pavement reached the maintenance threshold state. Results show that the skid resistance of the ungrooved pavement was subpar according to FAA. The skid resistance was positively connected with the grooved size and landing weight but negatively correlated with the water film thickness. Under certain operating conditions, the FAA maintenance threshold groove still meets the requirements for aircraft landing safety throughout the whole range of landing speeds. A real-time determination method of pavement skid resistance was proposed. It can guide pavement maintenance management departments to avoid runway excursion accidents.

Patterns of riparian forest disturbance caused by tree dislodging on a subtropical river during large floods

AbstractRiparian forests contribute to the resilience and biocomplexity of floodplains but may be catastrophically impacted by large floods. Forest disturbances will expose floodplains to stripping and pulses of large wood recruitment to the floodplain and channel. The widespread uprooting of trees follows hydrodynamic loading from floodwaters and the associated moments of these forces about the tree bases. A tree will uproot when the drag moment exceeds the anchorage resistance capacity. Alternatively, trunks will rupture when the tensile stresses caused by bending exceed the tensile strength of the outer trunk fibres. The likelihood and pattern of trees dislodging during floods on a subtropical river was investigated by developing a tree stability model. The modeling framework included development of a drag moment model and testing several potential formulations for anchorage resistance. Model parameters were calibrated to data collected in experiments and from observations in aerial photographs before and after a large flood in 2011. The prediction accuracy for the adopted tree stability model was 78%. Results from design flood simulations suggest that less than a third of the forest will dislodge even during the largest floods conceivable. This remarkable stability moderates the quantity of large wood recruited from riparian forests during extreme floods, which can impact infrastructure such as bridges and culverts downstream. Low rates of wood recruitment from dislodged floodplain trees in extreme floods suggests bank erosion is the dominant source of wood recruitment in these catchments.

BET inhibition sensitizes innate checkpoint inhibitor resistant melanoma to anti-CTLA-4 treatment.

Approximately 50% of melanoma patients fail to respond to immune checkpoint blockade (ICB), and acquired resistance hampers long-term survival in about half of initially responding patients. Whether targeting BET reader proteins, implicated in epigenetic dysregulation, can enhance ICB response rates and durability, remains to be determined. Here we show elevated BET proteins correlate with poor survival and ICB responses in melanoma patients. The BET inhibitor IBET151, combined with anti-CTLA-4, overcame innate ICB resistance however, sequential BET inhibition failed against acquired resistance in mouse models. Combination treatment response in the innate resistance model induced changes in tumor-infiltrating immune cells, reducing myeloid-derived suppressor cells (MDSCs). CD4+ and CD8+ T cells showed decreased expression of inhibitory receptors, with reduced TIM3, LAG3, and BTLA checkpoint expression. In human PBMCs invitro, BET inhibition reduced expression of immune checkpoints in CD4+ and CD8+ T cells, restoring effector cytokines and downregulating the transcriptional driver TOX. BET proteins in melanoma may play an oncogenic role by inducing immune suppression and driving T cell dysfunction. The study demonstrates an effective combination for innately unresponsive melanoma patients to checkpoint inhibitor immunotherapy, yet highlights BET inhibitors' limitations in an acquired resistance context.

Comparative analysis of infected cassava root transcriptomics reveals candidate genes for root rot disease resistance

Cassava root-rot incited by soil-borne pathogens is one of the major diseases that reduces root yield. Although the use of resistant cultivars is the most effective method of management, the genetic basis for root-rot resistance remains poorly understood. Therefore, our work analyzed the transcriptome of two contrasting genotypes (BRS Kiriris/resistant and BGM-1345/susceptible) using RNA-Seq to understand the molecular response and identify candidate genes for resistance. Cassava seedlings (resistant and susceptible to root-rot) were both planted in infested and sterilized soil and samples from Initial-time and Final-time periods, pooled. Two controls were used: (i) seedlings collected before planting in infested soil (absolute control) and, (ii) plants grown in sterilized soil (mock treatments). For the differentially expressed genes (DEGs) analysis 23.912 were expressed in the resistant genotype, where 10.307 were differentially expressed in the control treatment, 15 DEGs in the Initial Time-period and 366 DEGs in the Final Time-period. Eighteen candidate genes from the resistant genotype were related to plant defense, such as the MLP-like protein 31 and the peroxidase A2-like gene. This is the first model of resistance at the transcriptional level proposed for the cassava × root-rot pathosystem. Gene validation will contribute to screening for resistance of germplasm, segregating populations and/or use in gene editing in the pursuit to develop most promising cassava clones with resistance to root-rot.

A convex level-set method with multiplicative-additive model for image segmentation

The existing active contour models (ACMs) based on bias field (BF) correction mostly rely on a single BF assumption and lack in-depth discussion on the convexity of the energy functional, often leading to the problem of local minima. To address this issue, this paper introduces a dual BF and proposes a convex level-set (LS) method based on multiplicative-additive (MA) model to achieve global minima. Firstly, a MA model is adopted as the fidelity term, and a kernel function is introduced to adjust the size of the intensity inhomogeneous neighborhood, enhancing the adaptability to intensity inhomogeneity. Then, the convex LS function is embedded in the variational framework to ensure convexity of each variable in the energy functional. This transformation turns the segmentation problem into a convex optimization problem. By introducing the total variation regularization term to smooth the LS function, the model's resistance to noise is effectively enhanced. Finally, by minimizing the proposed energy functional, image segmentation and BF correction are successfully achieved. Experimental results validate the global minima property of our model, while also demonstrating good flexibility in the initial contour. The proposed model achieves superior segmentation results compared to other classical ACMs on various types of images.

Developing predictive models for HIV Drug resistance: A genomic and AI approach

This paper proposes a novel approach to combating HIV drug resistance through the development of predictive models leveraging genomic data and artificial intelligence (AI). With the increasing prevalence of drug-resistant strains of HIV, there is a critical need for innovative strategies to predict and manage resistance mutations, thereby optimizing treatment outcomes and prolonging the efficacy of antiretroviral therapy (ART). Drawing on advances in genomics and AI, this study outlines a conceptual framework for the development of predictive models that can identify potential drug-resistance mutations in HIV genomes and inform clinical decision-making. The proposed framework integrates genomic data from HIV-infected individuals with AI algorithms capable of learning complex patterns within the data. By analyzing genomic sequences obtained from HIV-positive patients, the models aim to identify genetic variations associated with drug resistance, predict the likelihood of resistance development, and guide the selection of appropriate treatment regimens. This approach holds promise for personalized medicine in HIV care, enabling clinicians to tailor therapy based on an individual's genetic profile and risk of resistance. Key components of the conceptual framework include data preprocessing to extract relevant genomic features, model training using machine learning techniques such as deep learning and ensemble methods, and validation of predictive performance through cross-validation and independent testing. Furthermore, the integration of clinical data, such as treatment history and viral load measurements, enhances the predictive accuracy of the models and provides valuable insights into treatment response dynamics.The development of predictive models for HIV drug resistance represents a paradigm shift in HIV care, offering a proactive approach to treatment management and surveillance. By leveraging genomic and AI technologies, healthcare providers can anticipate and address emerging resistance mutations before they compromise treatment efficacy. Ultimately, the implementation of predictive models holds the potential to improve patient outcomes, reduce the transmission of drug-resistant HIV strains, and advance the global fight against HIV/AIDS. Keywords: Developing, Predictive Models, HIV Drug Resistance, Genomic, AI Approach.

Collaborative Cross mice have diverse phenotypic responses to infection with Methicillin-resistant Staphylococcus aureus USA300.

Staphylococcus aureus (S. aureus) is an opportunistic pathogen causing diseases ranging from mild skin infections to life threatening conditions, including endocarditis, pneumonia, and sepsis. To identify host genes modulating this host-pathogen interaction, we infected 25 Collaborative Cross (CC) mouse strains with methicillin-resistant S. aureus (MRSA) and monitored disease progression for seven days using a surgically implanted telemetry system. CC strains varied widely in their response to intravenous MRSA infection. We identified eight 'susceptible' CC strains with high bacterial load, tissue damage, and reduced survival. Among the surviving strains, six with minimal colonization were classified as 'resistant', while the remaining six tolerated higher organ colonization ('tolerant'). The kidney was the most heavily colonized organ, but liver, spleen and lung colonization were better correlated with reduced survival. Resistant strains had higher pre-infection circulating neutrophils and lower post-infection tissue damage compared to susceptible and tolerant strains. We identified four CC strains with sexual dimorphism: all females survived the study period while all males met our euthanasia criteria earlier. In these CC strains, males had more baseline circulating monocytes and red blood cells. We identified several CC strains that may be useful as new models for endocarditis, myocarditis, pneumonia, and resistance to MRSA infection. Quantitative Trait Locus (QTL) analysis identified two significant loci, on Chromosomes 18 and 3, involved in early susceptibility and late survival after infection. We prioritized Npc1 and Ifi44l genes as the strongest candidates influencing survival using variant analysis and mRNA expression data from kidneys within these intervals.

EXPERIMENTAL AND NUMERICAL STUDY OF INCREASED CORE SURFACE AREA ON THE PERFORMANCE OF ADDITIVELY MANUFACTURED HONEYCOMB SANDWICH STRUCTURES

Abstract Sandwich composite structures have an efficient structural design that provides high bending stiffness and strength at low weight. However, these structures are plagued with weak core-to-facesheet bond strength. In this work, the effect of increasing the contact area between the composite facesheet and honeycomb core was studied. Sandwich panels were manufactured using two different honeycomb structures, a regular and a modified honeycomb, and their respective bond strengths were evaluated using the flatwise tension test (ASTM C297). The honeycombs were additively manufactured using selective laser melting (SLM) process. The modified honeycomb was designed to have a larger surface area while retaining the same relative density as the regular honeycomb. The facesheets were made out of carbon-fiber, while the core was additively manufactured using 304L stainless steel powder. Impact specimens were manufactured and tested for impact resistance. A finite element model was created to study the integrity of the sandwich structures subjected to localized impact damage. The finite element model of the damage resistance due to impact showed a good agreement with the experimental results. Samples with increased contact area showed higher impact resistance. The average impact strength of the modified samples was 41.3% higher than the average impact strength of the regular samples. Flatwise tension results showed that by increasing the contact area between the core and the facesheet the core-to-facesheet bond strength increased.

Slurry Erosion Resistance, Morphology, and Machine Learning Modeling of Plasma-Sprayed Si3N4+TiC+VC and CrNi based Ceramic Coatings

This study presents a comprehensive analysis of the morphology, mechanical properties, erosion resistance, and machine learning modeling of Si3N4+TiC+VC and CrNi based ceramic coatings deposited via plasma spraying. The cross-sectional morphology analysis revealed good mechanical interlocking between the coatings and the substrate, with pores predominantly observed in the Si3N4+TiC+VC coating. The coating thicknesses were measured as follows: 260 μm for Si3N4+TiC+VC, 243 μm for Si3N4+TiC+VC blended with CrNi, and 232 μm for pure CrNi coating. Mechanical characterization showed that microhardness values ranged from 1933 HV for Si3N4+TiC+VC coating to 499 HV for pure CrNi coatings. Slurry erosion tests demonstrated that pure Si3N4+TiC+VC coating exhibited superior erosion resistance at 90º impingement angle compared to other coatings. Additionally, a rigorous evaluation of over 20 machine learning regression models revealed that Gaussian Process Regressors and Artificial Neural Network (ANN) with a layer size of 20, displayed satisfactory performance in modeling mass loss prediction. The erosion mechanisms observed in the coatings provided valuable insights into their response to slurry erosion, highlighting the influence of coating composition and impingement angles. The findings underscore the potential of Si3N4+TiC+VC ceramic coatings to enhance the erosion resistance of stainless steel, offering promising applications in various industries.

In silico modelling of stroke volume, cardiac output and systemic vascular resistance in cardiovascular safety pharmacology studies by telemetry

The principle of proportionality of the systolic area of the central aortic pressure to stroke volume (SV) has been long known. The aim of the present work was to evaluate an in silico solution derived from this principle for modelling SV (iSV model) in cardiovascular safety pharmacology studies by telemetry. Blood pressure was measured in the abdominal aorta in accordance with standard practice. Central aortic pressure was modelled from the abdominal aortic pressure waveform using the N-point moving average (NPMA) method for beat-to-beat estimation of SV. First, the iSV was compared to the SV measured by ultrasonic flowmetry in the ascending aorta (uSV) after various pharmacological challenges in beagle dogs anaesthetised with etomidate/fentanyl. The iSV showed minimal bias (0.2 mL i.e. 2%) and excellent agreement with uSV. Then, previous telemetry studies including reference vasoactive and inotropic compounds were retrospectively reanalysed to model drug effects on stroke volume (iSV), cardiac output (iCO) and systemic vascular resistance (iSVR). Among them, the examples of nicardipine and isoprenaline highlight risks of erroneous or biased estimation of drug effects from the abdominal aortic pressure due to pulse pressure amplification. Furthermore, the examples of verapamil, quinidine and moxifloxacin show that iSV, iCO and iSVR are earlier biomarkers than blood pressure itself for predicting drug effect on blood pressure. This in silico modelling approach included in vivo telemetry safety pharmacology studies can be considered as a New Approach Methodology (NAM) that provides valuable additional information and contribute to improving non-clinical translational research to the clinic.

Quercetin decreases fructose drinking in model of fructose-induced insulin resistance. Unexpected uric acid and TBARS lowering effect of methyl cellulose vehicle and fructose combination.

The aim of this study was to improve insulin sensitivity in fructose-treated animals by ingestion of flavonoid quercetin. Several signs of insulin resistance have been developed in rats by drinking 10% fructose solution for 9 weeks. The effect of 6-week-gavage-administrated quercetin (20 mg/kg/day in 1% methyl cellulose solution) was monitored. Rats of the control groups received methyl cellulose vehicle as well. The most striking result of the quercetin treatment was the normalization of the fructose solution drinking to the level of drinking water intake. In addition, quercetin supplementation considerably decreased the plasma glucose and Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) index in rats consuming fructose. Surprisingly, fructose ingestion did not elevate plasma uric acid, thiobarbituric acid reactive substances, nitrotyrosine, or advanced glycation end products fluorescence. Instead, a reduction of the above parameters was observed. In summary, these results indicate that quercetin supplementation reduces fructose drinking and decreases plasma glucose and the HOMA-IR index. Furthermore, methyl cellulose, in combination with fructose, causes uric acid - lowering, antioxidant and anti-glycation effects. Thus, methyl cellulose possibly shifts fructose metabolism in favor of the utilization of antioxidant features of fructose. Our results call for using methyl cellulose in sweetened beverages and other sweetened food.

Analysis of damage models and mechanisms of mechanical sand concrete under composite salt freeze–thaw cycles

Mechanical sand concrete (MSC) deterioration in bridge engineering within cold-salt environments in the West was investigated. This study evaluated the salt-freezing resistance and damage models of granite mechanical sand concrete (GMSC) and tuff mechanical sand concrete (TMSC) under composite salt freezing-thaw cycles, using multiple indicators such as mass loss, relative dynamic elastic modulus, flexural strength, and compressive strength. A mechanistic study on the evolution of microscopic pores was conducted using nuclear magnetic resonance technology. The results showed that with an increase in composite salt freeze–thaw cycles, both TMSC and GMSC exhibited a decreasing trend in all indicators except for mass loss, which initially decreased and then increased. The relative dynamic modulus of elasticity decreased by 13.8 % and 17.4 % after 125 freeze–thaw cycles for TMSC and GMSC; compressive strength decreased to 36.16 MPa and 35.01 MPa; and flexural strength decreased to 4.977 MPa and 4.973 MPa, respectively. Combined with the T2 spectrum analysis of NMR, it can be seen that with the increase of the number of freeze-thaw cycles of the composite salt, the internal porosity of the TMSC structure increases from 1.91 % to 2.55 %, and the GMSC from 2.1 % to 2.86 %, and the harmful pore percentage increases by 1.73 times and 1.75 times, in turn, compared with that before the freeze-thaw.Thus, TMSC demonstrated superior salt-freezing resistance compared to GMSC. This study offers a reference and guidance for adopting MSC in cold and salty western regions.

Analysis of a Novel Method for Generating 3D Mesh at Contact Points in Packed Beds

This study comprehensively analyzes the impact of the novel HybridBridge method, developed by the authors, for generating a 3D mesh at contact points within packed beds within the effective thermal conductivity. It compares HybridBridge with alternative methodologies, highlights its superiority and outlines potential applications. The HybridBridge employs two independent geometry parameters to facilitate optimal flow mapping while maintaining physically accurate effective thermal conductivity and ensuring high mesh quality. A method is proposed to estimate the HybridBridge radius for a defined packed bed and cap height, enabling a presimulative determination of a suitable radius. Numerical analysis of a body-centered-cubic unit cell with varied HybridBridges is conducted alongside previous simulations involving a simple-cubic unit cell. Additionally, a physically based resistance model is introduced, delineating effective thermal conductivity as a function of the HybridBridge geometry and porosity. An equation for the HybridBridge radius, tailored to simulation parameters, is derived. Comparison with the unit cells and a randomly packed bed reveals an acceptable average deviation between the calculated and utilized radii, thereby streamlining and refining the implementation of the HybridBridge methodology.

Construction of Cultivated Land Ecological Network Based on Supply and Demand of Ecosystem Services and MCR Model: A Case Study of Shandong Province, China

The research on the ecological protection of cultivated land has gradually become a focus and frontier of cultivated land protection. Constructing an ecological network of a cultivated land system is important to improve the effect of cultivated land ecological protection. In this study, the supply-demand ratio of five ecosystem services was calculated from 2000 to 2020 in Shandong Province, a major grain-producing area in China. The morphological spatial pattern analysis (MSPA) model was used to construct the minimum cumulative resistance (MCR) model. The conclusions of the study are as follows: (1) the areas with a higher supply and demand ratio of various ecosystem services of cultivated land in Shandong Province are distributed in southern and southwestern areas. (2) The ecological source of cultivated land in Shandong Province has decreased by about 7000 km2 from 2000 to 2020, and the fragmentation trend is obvious. (3) The total length of the ecological corridors is 798.5 km2. The majority of these corridors are located in central and southern Shandong. The ideas and conclusions of this study are important for the formulation of ecological protection policies for regional cultivated land systems.

Dynamic strain aging and recrystallization mechanisms in laser powder bed melt printing of highly textured Hastelloy X

Hastelloy X (HX) is used in a wide range of aerospace applications due to its excellent high-temperature properties, Dynamic strain aging (DSA) and Dynamic recrystallization (DRX) are of great interest as they affect the mechanical behavior at high temperatures. In this study, the serrated flow behavior of highly textured Hastelloy X fabricated by laser powder bed fusion (LPBF) is investigated during uniaxial straining over a wide range of temperatures (20–800 °C) and strain rates (5×10−2 s−1 to 5×10−4 s−1). The alloy exhibits different types of tensile serrated flow in the temperature range of 200–600 °C. The alloy has been shown to have a very good tensile flow behavior. The presence of the Portevin-Le Chatelier effect (PLC) due to dynamic strain failure was observed at temperatures lower than 600 °C, respectively, with an average activation energy value of 45 kJ/mol calculated using the quasi-static aging (McCormick) model, and an average activation energy value calculated using the solute resistance (Cottrell) model of 41.8 kJ/mol, which is significantly lower than the 80–130 kJ/mol of conventionally fabricated HX. The effects of temperature and strain rate on fracture morphology and microstructure were analyzed by SEM, and the dynamic recrystallization behavior and nucleation mechanism were characterized by electron backscatter diffraction (EBSD). The changes in the content of recrystallized texture Cube and deformed texture Goss at different deformation temperatures are explained, and the dynamic recrystallization mode changes, from continuous dynamic recrystallization (CDRX) to discontinuous dynamic recrystallization (DDRX) as the deformation temperature increase. Verification of the different DRX mechanisms contributes to a comprehensive understanding of the microstructural evolution of the hot deformation of HX fabricated by LPBF.

Research on Material Viscoelasticity and Its Influence on Indentation Rolling Resistance

Viscoelastic materials are applied in several fields, and their relaxation characteristics are intricately related to the failure mechanism of sealing components and the generation of indentation rolling resistance in belt conveyors. Therefore, it is imperative to explore the relaxation characteristics of viscoelastic materials using characterization models. This article focuses on exploring these characterization models and the indentation rolling resistance of viscoelastic materials. The research comprises the following aspects: (1) A 2N + 2 element generalized Maxwell constitutive model is proposed for the relaxation behavior of viscoelastic materials to address the limitations of conventional relaxation models. (2) We conducted numerical calculations based on the relaxation modulus to solve the relaxation spectrum using several relaxation spectrum models. The findings showed that the model parameters were dependent on the testing time range. (3) The relationship between the indentation rolling resistance and relaxation model parameters was evaluated based on the theoretical foundation of the indentation rolling resistance calculation.

GPR30 selective agonist G-1 induced insulin resistance in ovariectomized mice on high fat diet and its mechanism

BackgroundPrevious in vivo and in vitro studies have demonstrated that estrogen receptor agonist G-1 regulates glucose and lipid metabolism. This study focused on the effects of G-1 on cardiometabolic syndrome and anti-obesity under a high fat diet (HFD). MethodsBilateral ovariectomized female mice were fed an HFD for 6 weeks, and treated them with G-1. A cardiomyocyte insulin resistance model was used to simulate the in vivo environment. The main outcome measures were blood glucose, body weight, and serum insulin levels to assess insulin resistance, while cardiac function and degree of fibrosis were assessed by cardiac ultrasound and pathological observations. We also examined the expression of p-AMPK, p-AKT, and GLUT4 in mice hearts and in vitro models to explore the mechanism by which G-1 regulates insulin signaling. ResultsG-1 reduced body weight in mice on an HFD, but simultaneously increased blood glucose and promoted insulin resistance, resulting in myocardial damage. This damage included disordered cardiomyocytes, massive accumulation of glycogen, extensive fibrosis of the heart, and thickening of the front and rear walls of the left ventricle. At the molecular level, G-1 enhances gluconeogenesis and promotes glucose production by increasing the activity of pyruvate carboxylase (PC) while inhibiting GLUT4 translocation via the AMPK/TBC1D1 pathway, thereby limiting glucose uptake. ConclusionDespite G-1's the potential efficacy in weight reduction, the concomitant induction of insulin resistance and cardiac impairment in conjunction with an HFD raises significant concerns. Therefore, comprehensive studies of its safety profile and effects under specific conditions are essential prior to clinical use.