Modeling Experiments Research Articles

Up IGF-I via High-toughness Adaptive Hydrogels for Remodeling Growth Plate of Children

Abstract The growth plate is crucial for skeletal growth in children, but research on repairing growth plate damage and restoring growth is limited. Here, a high-toughness adaptive dual-crosslinked hydrogel designed to mimic the growth plate's structure, supporting regeneration and bone growth. Composed of aldehyde-modified bacterial cellulose (DBNC), methacrylated gelatin (GelMA), and sodium alginate (Alg), the hydrogel is engineered through ionic bonding and Schiff base reactions, creating a macroporous structure. This structure can transform into a denser form by binding with calcium ions. In vitro, the loose macroporous structure of the hydrogels can promote chondrogenic differentiation, and when it forms a dense structure by binding with calcium ions, it also can activate relevant chondrogenic signaling pathways under the influence of IGF-1, further inhibiting osteogenesis. In vivo experiments in a rat model of growth plate injury demonstrated that the hydrogel promoted growth plate cartilage regeneration and minimized bone bridge formation by creating a hypoxic microenvironment that activates IGF-1-related pathways. This environment encourages chondrogenic differentiation while preventing the undesired formation of bone tissue within the growth plate area. Overall, the dual-crosslinked hydrogel not only mimics the growth plate's structure but also facilitates localized IGF-1 expression, effectively reshaping the growth plate's function. This approach represents a promising therapeutic strategy for treating growth plate injuries, potentially addressing challenges associated with skeletal growth restoration in pediatric patients.

Unstable relationship between tropical Indian Ocean SST and spring drought on the Loess Plateau modulated by interdecadal variability of ENSO

Abstract The Loess Plateau (LP) is recognized as a region highly vulnerable to climate change, particularly susceptible to spring droughts. Spring drought intensity is crucial as it significantly impacts crop growth and the occurrence of dust storms. However, the underlying mechanisms of spring drought in LP remain unclear. This study investigates the relationship between spring drought intensity in the LP and interannual sea surface temperature anomalies (SSTAs) in the tropical Indian Ocean (SST_TIO). We found that this relationship is negatively correlated but exhibits instability. It was significant during 1963–2001, a time characterized by homogeneous SST_TIO changes, and became insignificant during 2002–2021, during which SST_TIO changes were inhomogeneous. Homogeneous SST_TIO changes appear to stimulate atmospheric wave trains emanating from North Africa and the Arabian Peninsula, influencing precipitation patterns in the LP via the anomalous height in Northeast Asia. In contrast, inhomogeneous SST_TIO changes do not have this effect. Additionally, the impact of homogeneous SST_TIO changes on LP's spring precipitation during 1963–2001 was slightly enhanced by synergistic SSTAs in the tropical eastern Pacific-Atlantic oceans. sensitivity experiments of numerical model confirm the above physical processes. Moreover, these synergistic changes in the TIO and tropical Pacific-Atlantic are modulated by the interdecadal variability of the preceding winter El Niño-Southern Oscillation (ENSO). SSTAs in Indian Ocean exhibit more homogeneous distributions and a closer linkage with tropical Pacific-Atlantic during the periods with stronger ENSO variability. Conversely, when ENSO variability is weak, inhomogeneous SSTAs of Indian Ocean have a weaker relation with tropical Pacific-Atlantic regions.

The Optimization of the Rear Guide Vane of a Bulb Tubular Pump Based on Orthogonal Tests

Bulb tubular pumps have been widely used in hydraulic engineering because of their compact structure, easy maintenance, high adaptability, and other characteristics. In this paper, the performance optimization of the bulb tubular pump in the South-to-North water diversion project is studied, as well as the influence of the design of the rear guide vane structure on the hydraulic efficiency of the pump. This study takes a certain type of bulb tubular pump as its research object, optimizing the rear guide vane. Firstly, the accuracy of the numerical simulation method is verified using grid convergence analysis and model experimentation. The orthogonal experimental design method is used to optimize the design, and the range analysis results show that the blade wrap angle has the most significant influence on the hydraulic efficiency and head. Finally, the optimization results under a 0° impeller setting angle were verified by numerical analysis, and the hydraulic efficiency of the optimized pump was increased by 0.7%, 0.88%, and 1.1% under low flow, design flow, and high flow, respectively. By introducing entropy generation theory for inflow analysis, the reduction in energy loss in the pump is proven, thus verifying the effectiveness of the optimization. Through the optimization, the separation fluid phenomenon on the guide vane surface is improved, the vortex scale is reduced, and the flow field in the pump is improved to a certain extent.

Mouse models for metabolic health research: molecular mechanism of exercise effects on health improvement through adipose tissue remodelling.

Exercise provides health benefits to multiple metabolic tissues through complex biological pathways and interactions between organs. However, investigating these complex mechanisms in humans is still limited, making mouse models extremely useful for exploring exercise-induced changes in whole-body metabolism and health. In this review, we focus on gaining a broader understanding of the metabolic phenotypes and molecular mechanisms induced by exercise in mouse models. We first discuss the differences in adaptations induced by aerobic and resistance exercise, and compare voluntary wheel running and forced treadmill exercise, the two main methods of aerobic exercise research in mice, to show the similarities and differences between the same aerobic exercise but different methods, and their impact on experimental outcomes. The effects of exercise on metabolic phenotypes, including alleviation of obesity and metabolic disorders, and the mechanisms involved in adipose tissue remodelling and browning are explored, as well as the role of the gut microbiota in mediating the physiological responses and metabolic effects of exercise. Understanding these molecular mechanisms and methodological aspects of exercise experiments in mouse models can serve as a valuable template for the design of future basic research in exercise physiology and will provide a strong scientific evidence base for optimizing the design of exercise intervention programmes for metabolic health.

An Integrated Stacking Ensemble Model for Natural Gas Purchase Prediction Incorporating Multiple Features

Accurate prediction of natural gas purchase volumes is crucial for both the economy and the environment. It not only facilitates the rational allocation of resources for companies but also helps to reduce operational costs. Although existing prediction methods have achieved some success in addressing the nonlinear relationships in natural gas purchases, there remains potential for further improvement. To address this issue, a stacking ensemble learning model was developed to enhance the ability to handle complex nonlinear problems. This model integrates diverse algorithms and incorporates weather factors, while regionalizing characteristics of natural gas usage, thereby achieving accurate forecasts of natural gas purchase volumes. We selected three distinctly different base models—Informer, multiple linear regression (MLR), and support vector regression (SVR)—for our research. By conducting four different feature combination experiments for each base model, including weather, time, regional, and usage features, we constructed 12 foundational models. Subsequently, we integrated these base models using a meta-learner to form the final stacking ensemble model. The experimental results indicate that the stacking ensemble model outperforms individual models across key metrics, including R2, MRE, and RMSE. Notably, the R2 values improved by 4–15% compared to the 12 base models. The model was subsequently applied to predict natural gas purchase volumes in Pi County, Chengdu, China. In November 2024, a side-by-side comparison of the predicted and actual data revealed a maximum error of just 5.39%. This exceptional accuracy effectively meets forecasting requirements, underscoring the model’s predictive strength in the energy sector.

A Method for Imaging the Ischemic Penumbra with MRI using IVIM.

In acute ischemic stroke, the amount of "local" CBF distal to the occlusion, i.e. all blood flow within a region whether supplied antegrade or delayed and dispersed through the collateral network, may contain valuable information regarding infarct growth rate and treatment response. DSC CBF using a local arterial input function (AIF) is one method of quantifying local CBF (local-qCBF) and correlates with collaterals. Similarly, intravoxel incoherent motion MRI (IVIM) is "local", with excitation and readout in the same plane, and a potential alternative way to measure local-qCBF. The purpose of this work was to compare IVIM local-qCBF against DSC local-qCBF in the ischemic penumbra, compare measurement of perfusion-diffusion mismatch (PWI/DWI), and examine if local-qCBF may improve prediction of final infarct. Eight experiments in a pre-clinical canine model of middle cerebral artery occlusion were performed; native collateral circulation was quantified via x-ray DSA 30 minutes post-occlusion, and collateralization was subsequently enhanced in a subset of experiments with simultaneous pressor and vasodilator. IVIM and DSC MRI were acquired 2.5hr post-occlusion. IVIM was post-processed to return local-qCBF from fD*, water transport time (WTT) from D*, diffusion from D, and the PWI/DWI mismatch. These were compared with DSC parameters processed first with a standard global-AIF and then with a local-AIF. These DSC parameters included time-to-maximum, local MTT, standard-qCBF, local-qCBF and PWI/DWI mismatch. Infarct volume was measured with DWI at 2.5hrs and 4hrs post-occlusion. 2.5hr post-occlusion, IVIM local-qCBF in the non-infarcted ipsilateral territory strongly correlated with DSC local-qCBF (slope=1.00, R2=0.69, Lin's CCC=0.71). Correlation was weaker between IVIM local-qCBF and DSC standard-qCBF (R2=0.13). DSC localqCBF and IVIM local-qCBF in the non-infarcted ipsilateral territory both returned strong prediction of final infarct volume (R2=0.78, R2=0.61 respectively). DSC standard-qCBF was a weaker predictor (R2=0.12). The hypoperfused lesion from DSC local-qCBF and from IVIM local-qCBF both predicted final infarct volume with good sensitivity and correlation (slope=2.08, R2=0.67, slope=2.50, R2=0.68 respectively). The IVIM PWI/DWI ratio was correlated with infarct growth (R2=0.70) and WTT correlated with DSC MTT (R2=0.60). Non-contrast IVIM measurement of local-qCBF and PWI/DWI mismatch may include collateral circulation and improve prediction of infarct growth. AIF: arterial input function, IVIM: intravoxel incoherent motion, qCBF: quantitative cerebral blood flow, WTT: water transport time, MCAO: middle cerebral artery occlusion, MD: mean diffusivity.

The Role of Atmospheric Composition in Defining the Habitable Zone Limits and Supporting E. coli Growth.

Studying exoplanet atmospheres is essential for assessing their potential to host liquid water and their capacity to support life (their habitability). Each atmosphere uniquely influences the likelihood of surface liquid water, defining the habitable zone (HZ)-the region around a star where liquid water can exist. However, being within the HZ does not guarantee habitability, as life requires more than just liquid water. In this study, we adopted a two-pronged approach. First, we estimated the surface conditions of planets near the HZ's inner edge under various atmospheric compositions. By utilizing a 3D climate model, we refined the inner boundaries of the HZ for planets with atmospheres dominated by H2 and CO2 for the first time. Second, we investigated microbial survival in these environments, conducting laboratory experiments on the growth and survival of E. coli K-12, focusing on the impact of different gas compositions. This innovative combination of climate modeling and biological experiments bridges theoretical climate predictions with biological outcomes. Our findings indicate that atmospheric composition significantly affects bacterial growth patterns, highlighting the importance of considering diverse atmospheres in evaluating exoplanet habitability and advancing the search for life beyond Earth.

Modeling and Evaluation of Attention Mechanism Neural Network Based on Industrial Time Series Data

Chemical process control systems are complex, and modeling the controlled object is the first task in automatic control and optimal design. Most chemical process modeling experiments require test signals to be applied to the process, which may lead to production interruptions or cause safety accidents. Therefore, this paper proposes an improved transformer model based on a self-attention mechanism for modeling industrial processes. Then, an evaluation mechanism based on root mean square error (RMSE) and Kullback–Leibler divergence (KLD) metrics is designed to obtain more appropriate model parameters. The Variational Auto-Encoder (VAE) network is used to compute the associated KLD. Finally, a real nonlinear dynamic process in the petrochemical industry is modeled and evaluated using the proposed methodology to predict the time series data of the process. This study demonstrates the validity of the proposed transformer model and illustrates the versatility of using an integrated modeling, evaluation, and prediction scheme for nonlinear dynamic processes in process industries. The scheme is of great importance for the field of industrial soft measurements as well as for deep learning-based time series prediction. In addition, the issue of a suitable time domain for the prediction is discussed.

Learning Outcomes: How is the Experimentation of the AIR Learning Model?

This study examines how the experimentation of the Auditory, Intellectually, Repetition (AIR) learning model impacts students' learning outcomes in the Islamic Cultural History (SKI) subject at MTs Negeri 1 Bandar Lampung. The research is motivated by students' learning outcomes that have not met the Minimum Competency Criteria (KKM), which may be due to limitations in teaching methods and the influence of other external factors. This study employs a quantitative approach, with the population consisting of all eighth-grade students. The sample includes class VIII(A) as the experimental group and class VIII(B) as the control group. The data were analyzed using an independent t-test, yielding a final significance value of 0.070. This indicates that there is no statistically significant difference between the experimental and control groups. These results suggest that the AIR learning model does not produce significantly different learning outcomes compared to conventional teaching methods in this context. Therefore, further research is needed to optimize the application of the AIR learning model in the Islamic Cultural History (SKI) subject.

Biomimetic bioreactor for potentiated uricase replacement therapy in hyperuricemia and gout.

Uricase replacement therapy is a promising approach for managing hyperuricemia and gout but is hindered by challenges such as short blood circulation time, reduced catalytic activity, and excessive hydrogen peroxide (H2O2) production. These limitations necessitate innovative strategies to enhance therapeutic efficacy and safety. We designed and synthesized RBC@SeMSN@Uri, a red blood cell-coated biomimetic self-cascade bioreactor, which encapsulates uricase (Uri) and a selenium-based nano-scavenger (SeMSN) within RBC membranes. This design aims to reduce immunogenicity, extend systemic circulation, and maintain enzymatic activity. In vitro assays were conducted to evaluate biocompatibility, anti-inflammatory effects, and oxidative stress protection. In vivo experiments in hyperuricemia and gout models assessed therapeutic efficacy, biodistribution, and biosafety. RBC@SeMSN@Uri effectively degraded uric acid (UA) into allantoin and converted H2O2 into water, preventing oxidative damage and inflammation. In vitro assays demonstrated excellent biocompatibility and reduced H2O2-induced inflammatory responses compared to free uricase. In vivo, the bioreactor prolonged circulation time, significantly reduced uric acid levels, alleviated kidney damage, and mitigated symptoms of hyperuricemia and gout. It also targeted inflamed joints, reducing swelling and inflammation in gouty arthritis models. This study presents RBC@SeMSN@Uri as a novel biomimetic strategy for enzyme replacement therapy in hyperuricemia and gout. By integrating uricase and selenium-based nano-scavenger within RBC membranes, the bioreactor addresses key limitations of traditional therapies, offering enhanced stability, reduced immunogenicity, and superior therapeutic efficacy. This platform holds potential for broader applications in protein or antibody delivery for enzyme replacement therapies in other diseases.

Potential Diagnostic Biomarkers in Heart Failure: Suppressed Immune-Associated Genes Identified by Bioinformatic Analysis and Machine Learning

Heart failure (HF) threatens tens of millions of people’s health worldwide, which is the terminal stage in the development of majority cardiovascular diseases. Recently, an increasing number of studies have demonstrated that bioinformatics and machine learning (ML) algorithms can offer new insights into the diagnosing and treating HF. To further discover HF diagnostic genes, we utilized least absolute shrinkage and selection operator (LASSO) and Support Vector Machine (SVM) to identify novel immune-related genes. The HF dataset was obtained from the gene expression omnibus (GEO) database and three candidate genes (LCN6, MUC4, and TNFRSF13C) were finally screened. In addition, the myocardial infarction (MI) modeling experiments on mice were performed to validate the expression of LCN6, MUC4, and TNFRSF13C on experimental HF mice. Altogether, these three candidate genes are promising targets for the prediction of HF with immunological perspective.

Spatiotemporal modeling and projection framework of rainfall-induced landslide risk under climate change

Global warming is expected to exacerbate extreme rainfall events, potentially increasing the risk of landslides. While landslides have been extensively studied, much of the focus has been on developing static frameworks for landslide susceptibility, with relatively little exploration of spatiotemporal modeling. Furthermore, previous studies have often overlooked the spatiotemporal impacts of climate change and dynamic socio-economic factors on landslide susceptibility and risk. This has resulted in a lack of understanding of how landslide risk will evolve in the future. Consequently, this study proposes a modeling approach to simulate the dynamics of landslide susceptibility and exposure population over the next 80 years. The approach involves a series of novel modeling experiments using rainfall-induced landslide data collected over the past decade in Jiangxi Province, using a GAMs that considers the effects of spatial relationships and spatio-temporal cross-validation, with an AUC of 0.885 and an error rate of 15.32%, and combining with the CMIP6 precipitation data to the direct effect of climate change on landslide susceptibility. In addition, a dynamic risk prediction model combining static and dynamic populations was developed to provide a more comprehensive understanding of future landslide impacts. This research framework serves as a scientific foundation and valuable reference for comprehending the effects of climate change on landslide hazards and their management in urban planning and risk mitigation. It aims to inform the development of more effective strategies to mitigate potential losses from future landslide risks.

Some empirical studies for the applications of fractional $ G $-Brownian motion in finance

<p>Since the fractional $ G $-Brownian motion (fGBm) generalizes the concepts of the standard Brownian motion, fractional Brownian motion, and $ G $-Brownian motion, while it can exhibit long-range dependence or antipersistence and feature the volatility uncertainty simultaneously, it can be a better alternative stochastic process in the financial applications. Thus, in this paper, some empirical studies for the financial applications of the fGBm were carried out, where the recent high-frequency data for some selected assets in the financial market are from the Oxford-Man Institute of Quantitative Finance Realized Library. There are two main empirical findings. One was that the H-$ G $-normal distributions associated with the fGBm are more suitable in describing the dynamics of daily returns and increments of log-volatility for these assets than the usual distributions, since they not only characterize the properties of skewness, excess kurtosis, and long-range dependence $ \left(\frac{1}{2} < H < 1\right) $ or antipersistence $ \left(0 < H < \frac{1}{2}\right) $, but also feature the volatility uncertainty. The other one was that the daily return and log-volatility both behave essentially as fGBm with different $ \underline{\sigma}^2 $ and $ \overline{\sigma}^2 $, but Hurst parameters $ H < \frac{1}{2} $, at any reasonable time scale. Then a generalized stochastic model for the dynamics of the assets called rough fractional stochastic volatility model driven by fGBm (RFSV-fGBm) was developed. Finally, some parameter estimates and numerical experiments for the RFSV-fGBm model were investigated and carried out.</p>

Binding mechanism of oligopeptides on solid surface: assessing the significance of single-molecule approach.

This paper addresses the complementarity and potential disparities between single-molecule and ensemble-average approaches to probe the binding mechanism of oligopeptides on inorganic solids. Specifically, we explore the peptide/gold interface owing to its significance in various topics and its suitability to perform experiments both in model and real conditions. Experimental results show that the studied peptide adopts a lying configuration upon adsorption on the gold surface and interacts through its peptidic links and deprotonated thiolate extremities, in agreement with theoretical predictions. Single-molecule force spectroscopy (SMFS) measurements revealed the existence of a wide panel of adhesion forces, resulting from the interaction between individual peptide moieties and the abundant surface sites. We therefore propose methodological developments for sorting the events of interest to understand the peptide adsorption mechanism. Thermodynamic and kinetic aspects of the peptide adsorption are probed using both static and dynamic force spectroscopy measurements. Specifically, we show the possibility of providing a reasonable estimate of the peptide free energy of adsorption ΔadsG° by exploring the fluctuations of the adhesion work, based on the Jarzynski equality, and by using a parametric Gamma estimator. The proposed approach offers a relevant method for studying the different factors influencing the peptide adsorption and evaluating their impact on ΔadsG° as an alternative to exploring adhesion forces that may lead to misinterpretations. This is illustrated by the comparison of the adsorption of two peptides with specific amino acids substitution. Our method provides insights into the overall mechanism by which peptides interact with the surface and allows an integration of the single-molecule versus ensemble-average points of view.

Impact of LITAF on Mitophagy and Neuronal Damage in Epilepsy via MCL-1 Ubiquitination.

This study aims to investigate how the E3 ubiquitin ligase LITAF influences mitochondrial autophagy by modulating MCL-1 ubiquitination, and its role in the development of epilepsy. Employing single-cell RNA sequencing (scRNA-seq) to analyze brain tissue from epilepsy patients, along with high-throughput transcriptomics, we identified changes in gene expression. This was complemented by invivo and invitro experiments, including protein-protein interaction (PPI) network analysis, western blotting, and behavioral assessments in mouse models. Neuronal cells in epilepsy patients exhibited significant gene expression alterations, with increased activity in apoptosis-related pathways and decreased activity in neurotransmitter-related pathways. LITAF was identified as a key upregulated factor, inhibiting mitochondrial autophagy by promoting MCL-1 ubiquitination, leading to increased neuronal damage. Knockdown experiments in mouse models further confirmed that LITAF facilitates MCL-1 ubiquitination, aggravating neuronal injury. Our findings demonstrate that LITAF regulates MCL-1 ubiquitination, significantly impacting mitochondrial autophagy and contributing to neuronal damage in epilepsy. Targeting LITAF and its downstream mechanisms may offer a promising therapeutic strategy for managing epilepsy.

A small cavity for detecting sound-induced flow.

A study is presented of a method for creating an acoustic flow sensor that is generally compatible with current silicon microfabrication processes. An aim of this effort is to obtain a design consisting of a minimal departure from the existing designs employed in mass-produced silicon microphones. Because the primary component in all of these microphones is the cavity behind the pressure-sensing diaphragm, we begin with a study of the acoustic particle velocity within a cavity in a planar surface. The sound within the cavity is caused by the external plane sound wave traveling parallel to the cavity's open surface. It is shown that with suitable dimensions of the cavity, the acoustic particle velocity simultaneously flows inward at one end and outward at the other end of the single open cavity surface. A simple analytical model is presented to estimate the required length and depth of the cavity such that the acoustic particle velocity into and out of the opening is a reasonable approximation to that of a plane traveling sound wave in the free field. Measurements of the acoustic particle velocity into and out of the cavity are in close agreement with both the simple model and a more detailed finite element model. Agreement between two dissimilar modeling approaches and experiments suggests that the dominant features of the system have been accounted for. By redirecting the acoustic particle velocity into and out of the cavity opening rather than the flow being parallel to the plane surface, this configuration greatly facilitates the design and fabrication of structures intended to sense the acoustic flow.

Differences in binding affinity among cell-cycle CDK and cyclin pairs.

The mammalian cell cycle is coordinated by primarily four cyclin-dependent kinases (CDKs), which are activated by a family of cyclin proteins to phosphorylate diverse protein effectors of cell growth and division. A wealth of qualitative protein interaction studies have supported a model in which different CDKs have specific cognate cyclin partners. However, there have been few quantitative measurements of binding kinetics and affinity to support our understanding of CDK-cyclin preferences and the structural origins of those preferences. We used a biolayer interferometry (BLI) assay to quantify association and dissociation rates and to determine binding constants for all pairings of the cell-cycle CDKs and cyclins. We found that the highest affinity interactions, including CDK1 for CycB, CDK2 for CycA and CycE, and CDK4 for CycD, involve complexes that are considered canonical and have most often been reported. Structural modeling and mutagenesis experiments demonstrate that specific sequence differences can explain preferential interactions in the case of CDK2 binding to CycA compared to CycD. Finally, we show that all the cell-cycle CDK-cyclin complexes are competent to catalyze ATP with only a few outliers with relatively high or low catalytic efficiency. The implications of these observations for the potential activation of noncanonical CDK-cyclin pairs in cancer cell proliferation are discussed.

Seismic Resilience of Geogrid Reinforced Concrete Earth-Retaining Wall of Various Incremental Panels Based on Physical and Numerical Modelling

The dynamic response for different earth-retaining walls having geogrid as a reinforcement, combined with cohesionless granular material for backfill to mitigate earth pressure, has been examined through scale-down shaking table experiments and full-scale 3D FE analysis, utilizing ABAQUS as the finite element software. The scale factor is 1/4th for scaled-down. This study included various physical modelling experiments using different geogrid-reinforced earth retaining (GRER) walls (1m height, 7.5cm, thickness, and length 1m). Additionally, comprehensive 3D finite element analysis were conducted with the configurations measuring (4m, height 0.3m, thickness, and length 4m). This study examines hollow prefabricated concrete panels with shear key (PC-W), stone masonry walls of gravity type (GM-W), and traditional reinforced concrete (RC-W) walls. It also presents comparative investigations, such as lateral horizontal displacement of the wall, lateral pressure to the backfill, backfill soil settlement, and settlement of the wall foundation of various (GRER) walls. The accuracy of the Finite Element simulation framework has also been assessed in the shaking table experiment, as well as the FE analyses. According to the results, a PC-W wall with a shear key is the most effective type because it shows more resistance toward displacement. As per the comparison of the test models, GRER walls’ seismic response was more affected by the earthquake waves from the far field having long-term high acceleration values. In contrast, seismic waves from the close field had a smaller impact on the walls’ seismic response. However, the geogrid could improve the GRER seismic resilience deformation. Geogrid layers may reduce backfill pressures and backfill settlements. The geogrids located in the central portion within the reinforced soil and the geogrid roots connected to the walls were essential to the seismic design of the geogrid-reinforced earth retaining wall. To evaluate the reliability of the findings, the models have a predicted R2 variance below 0.1, indicating a consistent relationship between these two variables.

Outer membrane vesicles from genetically engineered Salmonella enterica serovar Typhimurium presenting Helicobacter pylori antigens UreB and CagA induce protection against Helicobacter pylori infection in mice

ABSTRACT Helicobacter pylori causes globally prevalent infections that are highly related to chronic gastritis and even development of gastric carcinomas. With the increase of antibiotic resistance, scientists have begun to search for better vaccine design strategies to eradicate H. pylori colonization. However, while current strategies prefer to formulate vaccines with a single H. pylori antigen, their potential has not yet been fully realized. Outer membrane vesicles (OMVs) are a potential platform since they could deliver multiple antigens. In this study, we engineered three crucial H. pylori antigen proteins (UreB, CagA, and VacA) onto the surface of OMVs derived from Salmonella enterica serovar Typhimurium (S. Typhimurium) mutant strains using the hemoglobin protease (Hbp) autotransporter system. In various knockout strategies, we found that OMVs isolated from the ΔrfbP ΔfliC ΔfljB ΔompA mutants could cause distinct increases in immunoglobulin G (IgG) and A (IgA) levels and effectively trigger T helper 1- and 17-biased cellular immune responses, which perform a vital role in protecting against H. pylori. Next, OMVs derived from ΔrfbP ΔfliC ΔfljB ΔompA mutants were used as a vector to deliver different combinations of H. pylori antigens. The antibody and cytokine levels and challenge experiments in mice model indicated that co-delivering UreB and CagA could protect against H. pylori and antigen-specific T cell responses. In summary, OMVs derived from the S. Typhimurium ΔrfbP ΔfliC ΔfljB ΔompA mutant strain as the vector while importing H. pylori UreB and CagA as antigenic proteins using the Hbp autotransporter system would greatly benefit controlling H. pylori infection.

Effects of Polyvinyl Alcohol – Hydroxyapatite Composite Ceramic on Calvarial Defects with Critical Size in Rat Models

Introduction: Biodegradable composite biomaterials are essential in healthcare, effectively tackling numerous complex challenges. Bone reconstruction is a surgical procedure aimed at remedying segmental bone loss, which is notably complicated and often fails to heal properly. A novel bone graft substitute incorporating polyvinyl alcohol (PVA) and synthetic hydroxyapatite (HA) has been developed and is tested in vivo in calvarial defect models of rat. The present study aimed to evaluate the bone regeneration potential of PVA – HA composite bone graft. Materials and methods: A total of 24 adult male Wistar rats aged 12-15 weeks with an average weight of 150 grams were used in the current study. A 4 mm full-thickness critical-size defect was created on the parietal bone and filled with the pre-sized graft material. Radiography, micro-computed tomography, scanning electron microscopy, histology, and serum biochemical parameters, including alkaline phosphatase and acid phosphatase activity, were utilized to evaluate the healing potential of the graft material. The animals were observed for twelve weeks. An immediate postoperative dorsoventral view of the skull was exposed at day zero and subsequent radiographs were taken periodically at weeks 2, 4, 8, and 12 in a group including 24 animals. Results: Immediate post-operative radiographs revealed the radiolucent nature of the graft material. Throughout the healing process, it was observed that the graft remained in position and was intact. The values of serum biochemical parameters alkaline phosphatase and acid phosphatase activity) were haphazard throughout the observation period. In the 8th week, signs of progressive degradation of the graft material and bone regeneration could be seen, particularly on radiography, micro-CT scanning electron microscopy, and histologic examination. Conclusion: It is concluded that the test graft material successfully accelerated bone regeneration and completely integrated with the host bone at week 12 of the experiment in the rat model.