Search Results (810)

The gut microbiota of macaques, highly homologous to humans in biological characteristics and metabolic functions, serves as an ideal model for studying the mechanisms of human intestinal diseases and therapeutic approaches. A comprehensive characterization of the macaque gut microbiota provides unique insights into human health and disease. This study employs metagenomic sequencing to assess the gut microbiota of wild M. mulatta brevicaudus across various ages, sexes, and physiological states. The results revealed that the dominant bacterial species in various age groups included Segatella copri and Bifidobacterium adolescentis. The predominant bacterial species in various sexes included Alistipes senegalensis and Parabacteroides (specifically Parabacteroides merdae, Parabacteroides johnsonii, and Parabacteroides sp. CT06). The dominant species during lactation and non-lactation periods were identified as Alistipes indistinctus and Capnocytophaga haemolytica. Functional analysis revealed significant enrichment in pathways such as global and overview maps, carbohydrate metabolism and amino acid metabolism. This study enhances our understanding of how age, sex, and physiological states shape the gut microbiota in M. mulatta brevicaudus, offering a foundation for future research on (1) host–microbiome interactions in primate evolution, and (2) translational applications in human health, such as microbiome-based therapies for metabolic or immune-related disorders. Full article

Background/Objectives: Fear detection through EEG signals has gained increasing attention due to its applications in affective computing, mental health monitoring, and intelligent safety systems. This systematic review aimed to identify the most effective methods, algorithms, and configurations reported in the literature for detecting fear from EEG signals using artificial intelligence (AI). Methods: Following the PRISMA 2020 methodology, a structured search was conducted using the string (“fear detection” AND “artificial intelligence” OR “machine learning” AND NOT “fnirs OR mri OR ct OR pet OR image”). After applying inclusion and exclusion criteria, 11 relevant studies were selected. Results: The review examined key methodological aspects such as algorithms (e.g., SVM, CNN, Decision Trees), EEG devices (Emotiv, Biosemi), experimental paradigms (videos, interactive games), dominant brainwave bands (beta, gamma, alpha), and electrode placement. Non-linear models, particularly when combined with immersive stimulation, achieved the highest classification accuracy (up to 92%). Beta and gamma frequencies were consistently associated with fear states, while frontotemporal electrode positioning and proprietary datasets further enhanced model performance. Conclusions: EEG-based fear detection using AI demonstrates high potential and rapid growth, offering significant interdisciplinary applications in healthcare, safety systems, and affective computing. Full article

Enhanced Geothermal Systems (EGS) require thermochemically stable proppant materials capable of sustaining fracture conductivity under harsh subsurface conditions. This study systematically investigates the response of commercial proppants to coupled thermo-hydro-chemical (THC) effects, focusing on chemical stability and microstructural evolution. Four proppant types were evaluated: an ultra-low-density ceramic (ULD), a resin-coated sand (RCS), and two quartz-based silica sands. Experiments were conducted under simulated EGS conditions at 130 °C with daily thermal cycling over a 25-day period, using diluted site-specific Utah FORGE geothermal fluids. Static batch reactions were followed by comprehensive multi-modal characterization, including scanning electron microscopy with energy-dispersive spectroscopy (SEM-EDS), X-ray diffraction (XRD), and micro-computed tomography (micro-CT). Proppants were tested in both granular and powdered forms to evaluate surface area effects and potential long-term reactivity. Results indicate that ULD proppants experienced notable resin degradation and secondary mineral precipitation within internal pore networks, evidenced by a 30.4% reduction in intragranular porosity (from CT analysis) and diminished amorphous peaks in the XRD spectra. RCS proppants exhibited a significant loss of surface carbon content from 72.98% to 53.05%, consistent with resin breakdown observed via SEM imaging. While the quartz-based sand proppants remained morphologically intact at the macro-scale, SEM-EDS revealed localized surface alteration and mineral precipitation. The brown sand proppant, in particular, showed the most extensive surface precipitation, with a 15.2% increase in newly detected mineral phases. These findings advance understanding of proppant–fluid interactions under low-temperature EGS conditions and underscore the importance of selecting proppants based on thermo-chemical compatibility. The results also highlight the need for continued development of chemically resilient proppant formulations tailored for long-term geothermal applications. Full article

Machine learning algorithms are commonly employed for classification and interpretation of high-dimensional data. The classification task is often broken down into two separate procedures, and different methods are applied to achieve accurate results and produce interpretable outcomes. First, an effective subset of high-dimensional features must be extracted and then the selected subset will be used to train a classifier. Gradient Boosted Trees (GBT) is an ensemble model and, particularly due to their robustness, ability to model complex nonlinear interactions, and feature interpretability, they are well suited for complex applications. XGBoost (eXtreme Gradient Boosting) is a high-performance implementation of GBT that incorporates regularization, parallel computation, and efficient tree pruning that makes it a suitable efficient, interpretable, and scalable classifier with potential applications to medical data analysis. In this study, a Monte Carlo Gradient Boosted Trees (MCGBT) model is proposed for both feature reduction and classification. The proposed MCGBT method was applied to a lung cancer dataset for feature identification and classification. The dataset contains 107 radiomics which are quantitative imaging biomarkers extracted from CT scans. A reduced set of 12 radiomics were identified, and patients were classified into different cancer stages. Cancer staging accuracy of 90.3% across 100 independent runs was achieved which was on par with that obtained using the full set of 107 radiomics, enabling lean and deployable classifiers. Full article

Background/Objectives: Truncating mutations in PALB2, a critical component of the BRCA1-PALB2-BRCA2 homologous recombination repair complex, are associated with increased risk and aggressiveness of breast cancer. The consequences of PALB2 truncation on the expression, localization, and functional dynamics of the scaffold protein IQGAP1 were investigated in this study based on two cases of truncated PALB2 human breast invasive ductal carcinoma (IDC), specifically, c.1240C>T (p.Arg414*) and c.2257C>T (p.Arg753*). Methods: Using confocal microscopy, we examined co-expression patterns of IQGAP1 with PALB2, PCNA, CK7, and β-tubulin in tumor tissues from both control cancer and PALB2-mutated cases. Results: In PALB2-truncated tumors, IQGAP1 exhibited enhanced peripheral and plasma membrane localization with elevated co-localization levels compared to controls, suggesting altered cytoskeletal organization. PALB2 truncation increased nuclear and cytoplasmic N-terminal PALB2 immunoreactivity, indicating the presence of truncated isoforms disrupting the homologous recombination repair system. Co-expression analyses with PCNA revealed an inverse expression pattern between IQGAP1 and proliferation markers, suggesting S-phase cell cycle-dependent heterogeneity. Furthermore, the loss of IQGAP1 dominance over CK7 and β-tubulin in mutant tumors, along with persistent intercellular spacing, implied a loss of cell–cell cohesion and the acquisition of invasive traits. Conclusions: These data support a model where PALB2 truncation triggers a reorganization of IQGAP1 that disrupts its canonical structural functions and facilitates tumor progression via enhanced motility and impaired cell–cell interaction. IQGAP1 thus serves as both a functional effector and potential biomarker in PALB2-mutated IDC, opening novel paths for diagnosis and targeted therapeutic intervention. Full article

This research is focused on exploring the importance of STEM (Science, Technology, Engineering, and Mathematics) education in the development of critical competencies among secondary school students in the 21st century. This was aimed to assess the impact of STEM-based activities on students’ creative and computational thinking skills. A quasi-experimental design that included 77 secondary school students from public and private schools in Bandar Lampung, Indonesia, who participated in STEM interventions for over 5 weeks, was adopted. Data were collected through creative thinking tests and questionnaires on CT and STEM attitudes. The results showed that students who participated in STEM activities exhibited significantly higher creative thinking scores compared to peers taught with the traditional curriculum. Specifically, the experimental group showed a progressive increase in weekly test scores, suggesting that STEM methods improved students’ performance over time. Structural equation modeling (SEM) disclosed strong positive associations between attitudes towards STEM, CT, and creativity. The implications of these results outlined the need to integrate STEM education into curricula to foster essential skills for future challenges. This research contributes to the understanding of effective educational strategies and also advocates for a shift towards more interactive and integrative methods in secondary education to meet the demands of the contemporary workforce. Full article

Background/Objectives: Dental cavity preparation is a critical procedure in restorative dentistry that involves the removal of decayed tissue while preserving a healthy tooth structure. Excessive stress during tooth preparation leads to enamel cracking, dentin damage, and long term compressive pulp health. This study employed finite element analysis (FEA) to investigate the stress distribution in dental structures during cavity preparation using round diamond burs of varying diameters and depths of cut (DOC). Methods: A three-dimensional human maxillary first molar was generated from computed tomography (CT) scan data using 3D Slicer, Fusion 360, and ANSYS Space Claim 2024 R-2. Finite element analysis (FEA) was conducted using ANSYS Workbench 2024. Round diamond burs with diameters of 1, 2, and 3 mm were modeled. Cutting simulations were performed for DOC of 1 mm and 2 mm. The burs were treated as rigid bodies, whereas the dental structures were modeled as deformable bodies using the Cowper–Symonds model. Results: The simulations revealed that larger bur diameters and deeper cuts led to higher stress magnitudes, particularly in the enamel and dentin. The maximum von Mises stress was reached at 136.98 MPa, and dentin 140.33 MPa. Smaller burs (≤2 mm) and lower depths of cut (≤1 mm) produced lower stress values and were optimal for minimizing dental structural damage. Pulpal stress remained low but showed an increasing trend with increased DOC and bur size. Conclusions: This study provides clinically relevant guidance for reducing mechanical damage during cavity preparation by recommending the use of smaller burs and controlled cutting depths. The originality of this study lies in its integration of CT-based anatomy with dynamic FEA modeling, enabling a realistic simulation of tool–tissue interaction in dentistry. These insights can inform bur selection, cutting protocols, and future experimental validations. Full article

This study investigated the radiation attenuation characteristics of commonly used dental implant materials across an energy spectrum relevant to dental radiology. Two titanium implants were examined, with densities of 4.428 g/cm³ and 4.51 g/cm³, respectively. The first consisted of 90.39% titanium, 5.40% aluminum, and 4.21% vanadium, while the second comprised 58% titanium, 33% oxygen, 7% iron, 1% carbon, and 1% nitrogen. The third material was a zirconia implant (5Y form) composed of 94.75% zirconium dioxide, 5.00% yttrium oxide, and 0.25% aluminum oxide, exhibiting a higher density of 6.05 g/cm³. Monte Carlo simulations (MCNP6) and XCOM data were utilized to estimate photon source parameters, geometric configuration, and interactions with biological materials to calculate the half-value layer, mean free path, and tenth-value layer at varying photon energies. The results indicated that titanium alloys are well suited for low-energy imaging modalities such as CBCT and panoramic radiography due to their reduced artifact production. While zirconia implants demonstrated superior attenuation at higher energies (e.g., CT), their higher density may induce beam-hardening artifacts in low-energy systems. Future research should validate these simulation results through in vitro and clinical imaging and further explore the correlation between material-specific attenuation and CBCT image artifacts. Full article

Background/Objectives: Hypertension is a major contributor to cardiovascular diseases and is often intensified by psychological stress, which can also affect bone metabolism. Although both conditions independently compromise bone health, their combined impact—particularly under acute and chronic stress—remains unclear. This pilot study aimed to assess the effects of such stressors on bone structure in spontaneously hypertensive rats (SHRs). Methods: Forty male rats, both normotensive and SHRs, were randomly assigned to control, acute stress, or chronic stress groups. Acute stress involves a single 2 h physical restraint. Chronic stress was induced over 10 days using alternating stressors: agitation, forced swimming, physical restraint, cold exposure, and water deprivation. Tibial bones were analyzed by microcomputed tomography (micro-CT), and histology was performed using Hematoxylin and Eosin and Masson’s Trichrome stains. Results: Micro-CT showed increased trabecular bone volume in normotensive rats under chronic stress, whereas SHRs displayed impaired remodeling under both stress types. Histological analysis revealed preserved connective tissue overall but evident changes in growth plate structure among stressed rats. SHRs exhibited exacerbated trabecular formation and cartilage abnormalities, including necrotic zones. Conclusions: Both acute and chronic stress, especially in the context of hypertension, negatively affect bone remodeling and maturation. Despite the absence of overt inflammation, structural bone changes were evident, indicating potential long-term risks. These findings highlight the importance of further studies on stress–hypertension interactions in bone health as well as the exploration of therapeutic approaches to mitigate skeletal damage under such conditions. Full article

Safflower (Carthamus tinctorius L.) is a plant in the family of Asteraceae, and the dried tubular flowers are used as medicine, which contain active ingredients such as safflower yellow pigment and safflower glycosides. They play important roles in many fields. NF-Y, as an important transcription factor in plants, regulates a variety of plant life activities. In this study, we identified and analysed 11 CtNF-Y gene family members from safflower for the first time. Their core motifs, which are conserved structural domains, gene structures, and cis-acting elements, are described in this study. In addition, there was good collinearity between safflower CtNF-Y and other species. Protein–protein interaction network analysis showed that the CtNF-YA1 and CtNF-YB subfamilies were the core proteins of the interaction network. Real-time quantitative PCR (qRT-PCR) studies showed that the expression level of the CtNF-Y gene was regulated by safflower flower colour and safflower flowering period. Subcellular localisation results showed that three CtNF-Y proteins were located in the nucleus, the cellular regulatory centre of the plant. This study will provide valuable insights into the selection of key candidate genes in the network of regulatory mechanisms for the formation of safflower flower colour and flowering time. Full article

This study centers on the adsorption–flotation coupling extraction of rubidium (Rb⁺) and cesium (Cs⁺) within a titanium silicate (CTS)–cetyltrimethylammonium bromide (CTAB) system, systematically investigating the impacts of pH, aeration rate, CTAB concentration, and flotation time on the extraction efficiency of these elements. Single-factor experiments revealed that the optimal flotation efficiency was achieved when the pH ranged from 6 to 10, the aeration rate was set at 1000 r/min, the CTAB concentration was 0.2 mmol/L, and the flotation duration was 18 min. Under these conditions, the adsorption capacities for Rb⁺ and Cs⁺ were recorded as 128.32 mg/g and 185.47 mg/g, respectively. Employing the response surface optimization method to analyze the interactive effects of these four factors, we found that their order of significance was as follows: pH > aeration rate > CTAB concentration > flotation time. The optimized parameters were determined as pH 8.64, bubble formation rate 1121 r/min, CTAB concentration 0.26 mmol/L, and flotation time 18.47 min. Under these refined conditions, the flotation efficiency for both CTS–Rb and CTS–Cs surpassed any single-factor experiment scenario, with the flotation efficiencies for Rb⁺ and Cs⁺ reaching 95.05% and 94.82%, respectively. This methodology effectively extracts Rb⁺ and Cs⁺ from low-concentration liquid systems, while addressing the challenges of solid–liquid separation for powdered adsorption materials. It holds significant theoretical and practical reference value for enhancing the separation processes of low-grade valuable components and boosting overall separation performance. Full article

Compact toroid (CT) injection, with its characteristics of high plasma density and extremely high injection velocity, is considered a highly promising method for core fueling in fusion reactors. Previous studies have lacked investigation into the transport process of CT within drift tubes. To investigate the dynamic processes of CT in drift tubes, this study developed a compressible magnetohydrodynamics (MHD) solver and a magnetic diffusion solver based on the OpenFOAM platform. They were integrated into a multi-region coupling framework to create a multi-region coupled MHD solver, mhdMRF, for simulating the dynamic behavior of CT in drift tubes and its interaction with finite-resistivity walls. The solver demonstrated excellent performance in simulations of the Orszag–Tang MHD vortex problem, the Brio–Wu shock tube problem, analytical verification of magnetic diffusion, and validation of internal coupling boundary conditions. Additionally, this work innovatively explored the effects of the geometric structure at the end of the inner electrode and finite-resistivity walls on the transport processes of CT. The results indicate that optimizing the geometric structure at the end of the inner electrode can significantly enhance the confinement performance and stability of CT transport. The resistivity of the wall profoundly influences the magnetic field structure and density distribution of CT. Full article

Xanthomonas phaseoli pv. dieffenbachiae (Xpd), the causal agent of bacterial blight in Anthurium within the Araceae family, is listed as an EPPO A2 quarantine organism. Although the whole genome of Xpd has been sequenced, the molecular mechanisms underlying anthurium bacterial blight (ABB) remain unknown. Selecting an optimal reference gene is crucial for obtaining accurate and reliable gene expression profiles during the initial interactions between Xpd and Anthurium. The stability of four reference genes was evaluated by applying three statistical methods—BestKeeper, geNorm, and delta Ct (ΔCt)—using reverse-transcription quantitative PCR (RT-qPCR) data. The rpoD and gyrB genes exhibited the most consistent gene expression profiles, whereas atpD and thyA were less stable at four time points (0, 0.5, 1, and 2 h) during the interactions between Xpd and susceptible A. andreanum cultivar ‘Marian Seefurth.’ The suitability of these reference gene candidates was validated by normalizing the gene expression levels of four pathogenicity-related genes. The highly upregulated expression of gumD, which encodes xanthan biosynthesis glycosyltransferase, observed after 1 h of interaction, suggests it may be a key virulence determinant in the Xpd–Anthurium pathosystem. The stable reference genes identified here will facilitate more accurate and comprehensive gene expression studies in the Xpd–Anthurium pathosystem going forward. Full article

Plant roots influence various soil physical properties by altering the soil structure and pore configuration; however, a detailed understanding of these effects remains limited. In this study, we applied a relatively simple approach for segmenting plant roots and soil constituents using X-ray computed tomography (CT) images to evaluate root-induced changes in soil structure. The method combines manual initialization with a layer-wise automated region-growing approach, enabling the extraction of the root systems of soybean, Italian ryegrass, and Guinea grass. The method utilizes freely available software with a simple interface and does not require advanced image analysis skills, making it accessible to a wide range of researchers. The soil particles, pore water, and pore air were segmented using a Kriging-based thresholding technique. The segmented four-phase images allowed for the quantification of the volume fractions of soil constituents, pore size distributions, and coordination numbers. Furthermore, by separating the rhizosphere and bulk soil, we found that the root presence significantly reduced solid fractions and increased water content, particularly in the upper soil layers. Macropores and fine pores were observed near the roots, highlighting the complex structural impacts of root growth. While further validation is needed to assess the method’s applicability across different soil types and imaging conditions, it provides a practical basis for visualizing and quantifying root–soil interactions, and could contribute to advancing our understanding of how plant roots influence key soil hydraulic and thermal properties. Full article

Recent technological advances have expanded the use of 3D-printed polymer components across industries, including a growing interest in military applications. The effective defensive use of such materials depends on a thorough understanding of polymer properties, printing techniques, structural design, and influencing parameters. This paper analyzes the ballistic resistance of 3D-printed polymer structures against 9 × 19 mm projectiles. Cuboid targets with different infill patterns—cubic, grid, honeycomb, and gyroid—were fabricated and tested experimentally using live ammunition. Post-impact, CT scans were used to non-destructively measure projectile penetration depths. The honeycomb infill demonstrated superior bullet-stopping performance. Additionally, mechanical properties were experimentally determined and applied in FEM simulations, confirming the ability of commercial software to predict projectile–target interaction in complex geometries. A simplified analytical model also produced satisfactory agreement with experimental observations. The results contribute to a better understanding of impact behavior in 3D-printed polymer structures, supporting their potential application in defense systems. Full article