Analysis Of Distribution Research Articles

Characterization of Corticotropin-releasing Hormone Receptors (CRHRs) and Binding Proteins (CRHBPs) in Nile Tilapia: Molecular Identification, Functional Analysis and Tissue Distribution

Corticotropin-releasing hormone (CRH) mediates various physiological/pathological roles such as stress and reproduction in vertebrates by specifically activating its receptors (CRHRs), and the regulation is intricately intertwined with the CRH binding protein (CRHBP). Although numerous research on mammalian CRHRs and CRHBP has been conducted, reports regarding the teleost CRHRs and CRHBP are limited. Herein, using Nile tilapia (ti-) as a model, we conducted the characterization, functional analysis, and examination of tissue distribution of tiCRHRs and tiCRHBPs. Our study showed that: (1) tiCRHR1a, tiCRHR1b and tiCRHR2 encoded proteins of 432, 436 and 414 amino acids (-aa), while tiCRHBP1 and tiCRHBP2 were predicated to generate a 323- and 322-aa precursor respectively; (2) All tiCRHRs could be activated by tiCRH and subsequently coupled to cAMP/PKA signaling pathways, while only tiCRHR1a and tiCRHR1b could trigger MAPK/ERK signaling cascade; (3) tiCRHBP1 and tiCRHBP2 could does-dependently suppress tiCRH-upregulated luciferase activity in HEK293 cells expressing tiCRHRs; (4) All tiCRHRs mRNA were considerably detected in the central nervous system (CNS), but they exhibited distinct expression pattern in examined peripheral tissues; (5) tiCRHBP1 exhibited an exclusive expression pattern in the pituitary, whereas tiCRHBP2 mRNA was abundantly expressed in the telencephalon. Collectively, our data will help to facilitate a better understanding of the members and functions of CRHRs and CRHBP in teleost.

Analysis of Distribution and Drug Susceptibility Test Results of Pathogenic Bacteria in Diabetic Foot Ulcers.

This study aimed to determine the pathogen distribution and drug susceptibility of diabetic foot wound secretions in a tertiary hospital in a coastal area of southeastern China to guide clinical antibiotic selection. A retrospective analysis was conducted on 212 patients with diabetic foot hospitalized at Xiamen Third Hospital from 2018 to 2023, and foot wound secretions were collected for microbial culture and drug susceptibility testing. Among 212 cases of patients with diabetic foot wound secretions, 163 cases (76.9%) were cultured with pathogenic bacteria, and a total of 207 strains of pathogenic bacteria were cultured, including 75 strains (36.23%) of Gram-positive (G+) bacteria, 118 strains of Gram-negative (G-) bacteria (57.00%), 14 strains of fungi (6.76%), 120 cases of single microorganism infection (73.62%), 43 cases of mixed infection (26.38%), and 15 strains of multidrug-resistant bacteria (7.25%). The top three pathogenic bacteria were Staphylococcus aureus, Klebsiella pneumoniae, and Pseudomonas aeruginosa. G+ bacteria were dominated by S.aureus. Drug susceptibility results showed that G+ bacteria were highly susceptible to vancomycin, linezolid, tigecycline, quinupristin/dalfopristin, rifampicin, and furotoxin, and somewhat resistant to penicillin, erythromycin, clindamycin, and cefoxitin. Among G- bacterial infections, Klebsiella pneumoniae, Pseudomonas aeruginosa, Escherichia coli, and Proteus were the major species. Drug susceptibility testing indicated that carbapenems such as imipenem and ertapenem were the most effective antibacterial drugs against G- strains, followed by amikacin, piperacillin, and tazabactams to which these bacteria were also relatively sensitive, while resistance to penicillins and first-generation cephalosporins increased significantly. We isolated one strain of pathogenic bacteria from a Wagner grade1 ulcer, which was G+ bacteria. In Wagner grade2 ulcers, the distribution of pathogenic bacteria was mainly G+ bacteria. In Wagner grade3 and 4 ulcers, the distribution of pathogenic bacteria was mainly G- bacteria, and the increased rate of mixed infection was mainly due to mixed infection of G+ and G-. Two strains of pathogenic bacteria were isolated at Wagner grade5, which were mixed infections of G+ and G-. Pathogenic bacteria in diabetic foot wounds are predominantly G- bacteria, followed by G+ bacteria. As the Wagner ulcer grade increases, the distribution of pathogenic bacteria changes from G+ bacteria to G- bacteria, and the mixed infection rate increases. G+ bacteria are highly susceptible to vancomycin, linezolid, tigecycline, quinupristin/dalfopristin, rifampicin, and furotoxin, and somewhat resistant to penicillin, erythromycin, clindamycin, and cefoxitin. G- bacteria are more sensitive to the antimicrobial drugs ertapenem, imipenem, amikacin, piperacillin tazobactam, and have high resistance to penicillin and first-generation cephalosporins.

Organisational Dynamics and Local Government Autonomy in Nigeria. An Interrogation

This research paper attempt to investigate the critical relationship between the interplay of organizational dynamics and perceptions of local government autonomy in Nigeria political system. A comprehensive analysis of grade level distribution, departmental structure, and length of service among respondents forms the fulcrum of this study. The study unveils the diverse tapestry of influences shaping attitudes towards local government autonomy in Kogi State, Nigeria. Key findings highlight the pivotal role of mid-level professionals (grade levels 11 to 13), the varied priorities across departments, and the dynamic evolution of perceptions over time. Informed by these insights, our recommendations emphasized tailored strategies, leadership empowerment, and continuous engagement to foster an organizational environment that values and champions local government autonomy in Nigeria. This research contributes to a deeper understanding of the organizational intricacies influencing local governance and offers practical insights for policymakers and administrators seeking to enhance local government autonomy in Nigeria political systems.

Structural Analysis of Thermal Diffusion and Non-Uniform Temperature Distribution along the Sidewall Thickness of STS316L during Gas Tungsten Arc Butt Welding

This study investigated how welding affects the thermal deformation of square cells produced for casks, which are dry storage containers for spent nuclear fuel. We aimed to minimize structural deformation by utilizing STS316L as the material for the square cells. We explored a method of subdividing the square cells and joining them through butt welding. Keeping the upper plate thickness constant, GTA butt welding was conducted while varying the column’s wall thickness, followed by measurement with a laser vision sensor. The heat conduction and thermal strain were then calculated using a finite element analysis (FEM). Both experimental and analytical results confirmed that there was significant thermal deformation in the cases of thick-walled columns due to variations in heat conduction distribution, with the resulting deformation patterns depending on thickness.

THÌ and LÀ Constructions in Vietnamese: A Study on Argument Structures

This study aims to shed light on the argument structure of the Vietnamese particles THÌ and LÀ, which function as markers of focused constituents and topic-comment structures, respectively. The research objectives are to identify the syntactic and semantic properties of constructions involving THÌ and LÀ, and to analyze their argument structures within the theoretical frameworks of construction grammar. Specifically, the constructional approach (Goldberg 1995, 2006) and radical construction grammar (Croft 2001) will be employed. The methodology involves collecting a corpus of naturally occurring data from various written sources. The data will undergo qualitative analysis to identify argument structure patterns associated with THÌ and LÀ constructions, as well as quantitative analysis of frequency and distribution. The expected findings will provide insights into the argument structures of these Vietnamese constructions, elucidating how focused constituents and topic-comment structures are marked. The study will evaluate the applicability of the chosen theoretical frameworks in accounting for the observed patterns. The findings have potential applications in natural language processing tasks requiring accurate recognition and interpretation of focused constituents and topic-comment structures, such as information extraction, machine translation, and language generation. Furthermore, the study may inform language teaching and acquisition by shedding light on the usage patterns of THÌ and LÀ in Vietnamese. The analysis is expected to contribute to a deeper understanding of argument structures in Vietnamese and potentially motivate extensions or modifications to the theoretical frameworks.

Data-driven analysis of annual rain distributions

Rainfall is an important component of the climate system, and its statistical properties are vital for prediction purposes. In this study, we have developed a statistical method for constructing the distribution of annual precipitation. The method is based on the convolution of the measured monthly rainfall distributions and does not depend on any presumed annual rainfall distribution. Using a simple statistical model, we demonstrate that our approach allows for a better prediction of extremely dry or wet years with a recurrence time several times longer than the original time series. The method that has been proposed can be utilized for other climate variables as well. Published by the American Physical Society 2024

Unveiling dissociation mechanisms and binding patterns in the UHRF1-DPPA3 complex via multi-replica molecular dynamics simulations.

Ubiquitin-like with PHD and RING finger domain containing protein 1 (UHRF1) is responsible for preserving the stability of genomic methylation through the recruitment of DNA methyltransferase 1 (DNMT1). However, the interaction between Developmental pluripotency associated 3 (DPPA3) and the pre-PHD-PHD (PPHD) domain of UHRF1 hinders the nuclear localization of UHRF1. This disruption has implications for potential cancer treatment strategies. Drugs that mimic the binding pattern between DPPA3 and PPHD could offer a promising approach to cancer treatment. Our study reveals that DPPA3 undergoes dissociation from the C-terminal through three different modes of helix unfolding. Furthermore, we have identified key residue pairs involved in this dissociation process and potential drug-targeting residues. These findings offer valuable insights into the dissociation mechanism of DPPA3 from PPHD and have the potential to inform the design of novel drugs targeting UHRF1 for cancer therapy. To comprehend the dissociation process and binding patterns of PPHD-DPPA3, we employed enhanced sampling techniques, including steered molecular dynamics (SMD) and conventional molecular dynamics (cMD). Additionally, we utilized self-organizing maps (SOM) and time-resolved force distribution analysis (TRFDA) methodologies. The Gromacs software was used for performing molecular dynamics simulations, and the AMBER FF14SB force field was applied to the protein.

Analysis of the Polarization Distribution and Spin Angular Momentum of the Interference Field Obtained by Co-Planar Beams with Linear and Circular Polarization

Interference of two and four light beams with linear or circular polarization is studied analytically and numerically based on the Richards–Wolf formalism. We consider such characteristics of the interference fields as the distribution of intensity, polarization, and spin angular momentum density. The generation of light fields with 1D and 2D periodic structure of both intensity and polarization is demonstrated. We can control the periodic structure both by changing the polarization state of the interfering beams and by changing the numerical aperture of focusing. We consider examples with a basic configuration, as well as those with a certain symmetry in the polarization state of the interfering beams. In some cases, increasing the numerical aperture of the focusing system significantly affects the generated distributions of both intensity and polarization. Experimental results, obtained using a polarization video camera, are in good agreement with the simulation results. The considered light fields can be used in laser processing of thin films of photosensitive (as well as polarization-sensitive) materials in order to create arrays of various ordered nano- and microstructures.

Physicochemical Properties and Fine Structure of Starch in Jinong Xiangruan 1 and DGR1 Soft Rice Varieties Cultivated in Different Regions of China

Rice, a staple food for billions around the globe, is cultivated in numerous forms. Among them, soft rice is well known, which is characterized by its tender, creamy consistency and desirable texture. In this study, we examined the physicochemical properties and fine structure of starch from two soft rice varieties, Jinong Xiangruan 1 and DGR1, cultivated in different regions in China (Baodi District, Tianjin City; Liaoning Province; and Fengyang City, Anhui Province). The aim was to understand how amylopectin content (AC) influences rice quality. This research aims to bridge the knowledge gap regarding the role of amylopectin in determining rice’s adhesive consistency and viscosity. Significant regional differences were observed in yield components such as the number of grains per panicle, seed setting rates and 1000-grain weight, with Liaoning generally showing higher performance metrics compared to other regions. Physicochemical analysis highlighted that though glue consistency and taste values showed little regional variation, AC significantly influenced rice hardness and viscosity. Rapid Visco Analyzer (RVA) profile analysis further demonstrated distinct differences in viscosity characteristics, underscoring the regional impacts on starch behavior. Additionally, molecular weight distribution and amylopectin chain length analysis, conducted via SEC-MALLS-RI and ICS ion chromatography, revealed notable differences in starch composition across varieties and locations. The findings suggest that environmental conditions play a crucial role in defining starch characteristics and, consequently, the eating quality of rice. This provides valuable insights for breeding high-quality japonica rice with broad adaptability.

Comparative analysis of key fiber characteristics in white Pima cotton (Gossypium barbadense L.): Native accessions from the Peruvian Amazon

AbstractThe fiber quality of cotton (Gossypium barbadense L.) native to the Peruvian Amazon region is one of the most versatile and essential natural fibers in the Peruvian textile industry. There is little information about the fiber quality traits of cotton genotypes native to the Peruvian Amazon region. This study investigated the fiber quality traits of Peruvian Pima cotton accessions native to the Amazon region of the La Convención Province, Cusco, Peru, to determine the lines with the greatest potential for improving fiber quality in cotton genetic breeding programs. A total of 14 cotton accessions with white fiber color, being 12 accessions of G. barbadense L. (Pima cotton) and two accessions of Gossypium sp. (unknown cotton), were analyzed. The fiber properties determined using the high volume instrument method included seven characteristics. All fiber properties were classified into five quality classes. The data on fiber quality properties were subjected to distribution, correlation, and canonical variable analysis. The results of fiber quality properties showed that the two accessions of Gossypium sp. (unknown cotton) can be promising options to be used as high‐quality fiber progenies in crop genetic breeding programs or can be cultivated by regional farmers for the purpose of producing cotton with high fiber quality. Future investigations could utilize other methods of fiber quality analysis and compare the fiber quality of these cotton accessions native to the Peruvian Amazon region with other cotton species grown worldwide to improve the understanding of Pima cotton fiber quality and its applicability in different contexts of the textile industries.

Evaluation of the airflow distribution of a vertical air ventilation system in a car cabin using PIV measurements and CFD simulations

The main goal of a ventilation system in the car cabin in general is to guarantee an adequate thermal comfort for all passengers and to enable a good air quality with sufficient air supply into the cabin. Quantifying the indoor air distribution is essential to provide the necessary thermal comfort and the required air quality. The aim of this study is therefore to analyze the subsequent airflow distribution of the vertical air ventilation system presented as a possible solution for future cars with modern interior designs. With the vertical air ventilation concept, air vents are located at the ceiling and floor area of the car cabin, as ceiling and floor regions enable a large-area influx of air into the car cabin and allow accessibility to passengers in every seating position. For the analysis of the airflow distribution of the ventilation system, Particle Image Velocimetry (PIV) measurements have been performed with a test vehicle in a climate chamber under specific conditions. Two different thermal manikins, one heated and the other unheated, have been used in the experiments. The results of the comparison between the two thermal manikins reflect a relatively low to medium impact of the human thermal natural convection on the airflow pattern around the manikin in the different air distribution modes of the vertical air ventilation system. Using the same ventilation settings, numerical simulations have been performed. The results of the numerical simulations are analyzed and compared with the results of the PIV measurements. The developed numerical model shows a good agreement with the experiments. It can hence be used for example in further studies to evaluate the thermal comfort or the air quality of the vertical airflow system as a new ventilation concept for future car interior designs.

Theoretical and experimental comparison of gear systems: Planetary mechanical transmission and coaxial magnetic gear

Gear systems in today’s industry are one of the critical pillars providing power transformation and matching speed and torque to application requirements. Reliability, high efficiency, and low operating costs are desirable due to the prevalence of gearboxes. This paper provides a comparative analysis of selected mechanical and magnetic gears, using a specific example to point out the advantages and disadvantages of contactless power conversion. After determining the essence of the operation of the magnetic gear on the base model, two magnetic gear optimization cases are presented, testifying to the application potential. An analysis of the stress distribution in the area of the teeth of the mechanical gearbox and the most stressed element of the magnetic gear - the modulator, was carried out. The effects of temperature and load on losses were measured and simulated, and ultimately, the efficiency characteristics of the two gears were also compared.

Application of laboratory micro X-ray fluorescence devices for X-ray topography

It is demonstrated that high-resolution energy-dispersive X-ray fluorescence mapping devices based on a micro-focused beam are not restricted to high-speed analyses of element distributions or to the detection of different grains, twins and subgrains in crystalline materials but can also be used for the detection of dislocations in high-quality single crystals. Si single crystals with low dislocation densities were selected as model materials to visualize the position of dislocations by the spatially resolved measurement of Bragg-peak intensity fluctuations. These originate from the most distorted planes caused by the stress fields of dislocations. The results obtained by this approach are compared with laboratory-based Lang X-ray topographs. The presented methodology yields comparable results and it is of particular interest in the field of crystal growth, where fast chemical and microstructural characterization feedback loops are indispensable for short and efficient development times. The beam divergence was reduced via an aperture management system to facilitate the visualization of dislocations for virtually as-grown, non-polished and non-planar samples with a very pronounced surface profile.

Estimating and Rewarding the Value of Healthcare Interventions Beyond the Healthcare Sector: A Conceptual Framework.

Evaluating healthcare interventions for their impacts beyond health outcomes may result in recognition of changes in human capital, income level, tax revenue, and government spending, which could affect economic growth and population health. In this paper, we document instances where current health technology assessment (HTA) practices fail to account for the impacts of healthcare interventions on broader society beyond the healthcare sector. We propose a novel conceptual framework, highlighting its three components (distributional cost-effectiveness analysis [DCEA], input-output model, and voting scheme) and their contributions to capturing the economic and societal ripple effects of healthcare interventions. This manuscript also outlines a case study in which the framework is applied to the reassessment of a previously evaluated digital health therapeutic for the treatment of opioid use disorder (OUD) compared with standard of care, demonstrating its practical application. The DCEA health value metric indicates that digital therapeutic is more equitable, favoring socioeconomically disadvantaged groups, while standard of care exacerbates health inequality by benefiting the already advantaged. Additionally, digital therapeutic shows potential for boosting productivity, raising income, and creating jobs, supporting its consideration by employer-sponsored health plans to optimize resource allocation for treating OUD. The conceptual framework provides insights for enhancing HTAs to incorporate the broader economic and societal impacts of healthcare interventions. By integrating DCEA, extended HTA analysis with input-output modeling, and a voting scheme, decision makers can make informed choices aligned with societal priorities, although further research and validation are necessary for practical implementation across diverse healthcare contexts.

Comprehensive Analysis of the Use of Web-GIS for Natural Hazard Management: A Systematic Review

This systematic review aims to synthesise Web-GIS evidence for managing natural hazards to share state-of-the-art practices and policies. A comprehensive search in SCOPUS, among other databases, identified 1775 articles published between 2014 and 2023. Following a selection process based on the PRISMA model, 65 articles met the inclusion criteria. The analysis revealed a growing trend over the past decade, with most research concentrated in the last three years. Eight crucial subtopics within the Web-GIS domain have emerged: Integrated Spatial Analysis and Modelling, Technologies and Infrastructure, Visualisation and User Interface Design, Decision Support Systems, Real-time Monitoring and Early Warning, Disaster Recovery and Resilience, Citizen and Social Media Integration, and Multi-Stakeholder Collaboration. A substantial contribution of the literature has been identified in Decision Support Systems and Integrated Spatial Analysis, reflecting their vital role in strategising and predicting hazard impacts. Furthermore, a geographical distribution analysis revealed significant Web-GIS applications in countries like Italy and China, alongside a deficit in low- and middle-income countries. It also highlights potential gaps in hazard studies, including the need to prioritise heatwave management in the face of climate change. This research calls for policymakers and practitioners to leverage evidence-informed decision making and foster community collaboration for enhanced natural disaster resilience.

Establishment of artificial intelligence model for precise histological subtyping of lung adenocarcinoma and its application to quantitative and spatial analysis.

The histological subtype of lung adenocarcinoma is a major prognostic factor. We developed a new artificial intelligence model to classify lung adenocarcinoma images into seven histological subtypes and adopted the model for whole-slide images to investigate the relationship between the distribution of histological subtypes and clinicopathological factors. Using histological subtype images, which are typical for pathologists, we trained and validated an artificial intelligence model. Then, the model was applied to whole-slide images of resected lung adenocarcinoma specimens from 147 cases. The model achieved an accuracy of 99.7% in training sets and 90.4% in validation sets consisting of typical tiles of histological subtyping for pathologists. When the model was applied to whole-slide images, the predominant subtype according to the artificial intelligence model classification matched that determined by pathologists in 75.5% of cases. The predominant subtype and tumor grade (using the WHO fourth and fifth classifications) determined by the artificial intelligence model resulted in similar recurrence-free survival curves to those determined by pathologists. Furthermore, we stratified the recurrence-free survival curves for patients with different proportions of high-grade components (solid, micropapillary and cribriform) according to the physical distribution of the high-grade component. The results suggested that tumors with centrally located high-grade components had a higher malignant potential (P<0.001 for 5-20% high-grade component). The new artificial intelligence model for histological subtyping of lung adenocarcinoma achieved high accuracy, and subtype quantification and subtype distribution analyses could be achieved. Artificial intelligence model therefore has potential for clinical application for both quantification and spatial analysis.

Enhanced electromagnetic wave absorption in ultrathin cement-based composites with integrated multi-dimensional carbon materials

The challenges posed by electromagnetic waves (EMW) cause significant interference in electronic device operation, jeopardizing information security and disturbing normal biological functions, which necessitate attention. Multi-scale carbon/cement-based composites were developed for EMW absorption by integrating multi-dimensional carbon materials, including carbon nanotubes (1D), graphene (2D), and modified carbon microspheres (3D). These composites demonstrate exceptional EMW absorption capabilities, with a minimum reflection loss (RLmin) of −44.32 dB and an effective absorption bandwidth (EAB) of 3.644 GHz at X band, merely having a thickness of 1.90 mm. Furthermore, the superior EMW absorption properties of these composites are confirmed through radar cross-section (RCS) simulation and electric field distribution analysis. A small house is constructed of designed three-layer multi-scale carbon/cement-based composites in which the actual EMW reflection losses are less than –10 dB within the whole test frequency range, and these composites can effectively obstruct 5 G mobile phone signals. Therefore, multi-scale carbon/cement-based composites could be promising candidates for effectively solving the increasingly serious problem of electromagnetic radiation pollution.

Giant goos–hanchen shift with heigh reflection base on guided mode resonance in trapezoidal hBN/dielectric metasurface

hBN is a natural hyperbolic van der Waals material that can enhance light–matter interactions. In this work, the maximum Goos-Hanchen(GH) shift has a magnitude of −4680 μm with high reflection using the central beam method in the trapezoidal dielectric/hBN grating (TDG) metasurface (MS) where the beam waist w0≥4λ. Analysis of the electromagnetic field distribution indicated that the amplified GH shift was a result of guided mode resonances excited in the waveguide dielectric layer. The frequency and magnitude of GH shifts can be effectively controlled by adjusting the height of the trapezoidal hBN, as well as by manipulating the widths of the top and bottom dielectric layers, the period of the TDG structure, and the height of the multi-layered structure. Moreover, an evaluation of the structure-sensing properties based on the GH shift was conducted. The enhanced and controllable GH shift exhibited by the TDG MS presents promising prospects for applications in optical sensors, optical switches, and optoelectronic detectors.

Spatiotemporal dynamic evolution and influencing factors of land use carbon emissions: evidence from Jiangsu Province, China

Land use/cover change has an important impact on global climate change and carbon cycle, and it has become another major source of carbon emission after energy consumption. Therefore, this study focuses on the main line of “land use carbon emissions-spatial and temporal patterns-influencing factors,” and selects 13 cities in Jiangsu Province as the research object. Based on the data of land use and energy consumption, combined with the method of land use carbon emissions and ArcGIS technology, this study conducted a quantitative analysis of the spatio-temporal distribution of carbon emissions in Jiangsu Province. The factors affecting the spatial distribution of carbon emissions from land use in Jiangsu Province were discussed by using Geographic detector. The results show that: 1) Carbon emissions in Jiangsu Province showed an overall growth trend, from 16215.44 ×104tC in 2010–23597.68 ×104tC in 2020, with an average annual growth rate of 4.55%, of which the construction land and watersheds had a greater impact on carbon sources and sinks, respectively. 2) During the period, there were significant differences in carbon emission levels among different cities in Jiangsu Province, and the land use carbon emission in Jiangsu Province showed a stable spatial pattern of “northwest—southeast.” The southern part of Jiangsu is always the hot area of carbon emission, while the cold spot area is mainly distributed in the northern and central parts of Jiangsu. 3) The interaction of factors such as economic development, industrial structure, energy intensity, land use and human activities is an important reason for the spatio-temporal differences of land use carbon emissions in Jiangsu Province. Among them, the level of urbanization, population size and economic aggregate have significant effects on carbon emissions.

Simultaneous integration of anti Si-poisoning and anti-fading properties on an innovative Al grain refiner via Nb-modified TiB2

Si-poisoning and fading effect of grain refiners deteriorate the refining effect of Al-Si alloys (Si≥3 wt%), further worsening the performance of alloys. In this work, an innovative Al-Nb-Ti-B with anti Si-poisoning and anti-fading properties was prepared by introducing synthetic TiB2 into Al-Nb melt. At the cooling rate of 1.4 K/s, the average grain size of Al-7Si alloys inoculated by this Al-Nb-Ti-B was refined to 326.05 μm, 40% reduction compared to 549.06 μm by commercial Al-5Ti-1B. The grain size remained at 421.95 μm even after 120 min holding time. Anti-fading mechanism was investigated by size distribution analysis of TiB2 nucleating particles. Anti Si-poisoning mechanism is attributed to Nb element which accumulates on the (01—10) surface of TiB2 and reduces the lattice misfit between TiB2 and α-Al. Atomic-scale microstructure analysis and first-principles calculations reveal that the Nb enrichment on TiB2 increases the chemical affinity of TiB2/Al interface and decreases the Si adsorption propensity. In brief, appropriate size distribution and unique Nb-rich layer contribute to the excellent grain refinement of TiB2 particles modified by Nb. These findings may shed new light on the realm of innovative aluminum grain refiners.