Search Results (84)

This study elucidates the role of the steroidogenic acute regulatory protein (StAR) in sex steroid hormone dynamics and the gonadal development of the commercially important marine bivalve ark shell Scapharca broughtonii. The sequence of the StAR gene was obtained and verified from the transcriptome of ark shell, then the tissue localization and expression pattern during the gonad development of the StAR gene were detected by in situ hybridization and quantitative real-time PCR, respectively. Additionally, the concentrations of three critical sex steroid hormones (progesterone, testosterone, and estradiol) were measured throughout gonadal development using enzyme-linked immunosorbent assay (ELISA). The results showed that the length of the coding region of StAR was 1446 bp, encoding 481 amino acids. The results of qRT-PCR showed that the expression of the StAR gene varied with gonadal development, increased from the early active stage to the development stage, and decreased from the mature stage to the spent stage. Notably, the expression level in ovaries was higher than that in testes, suggesting the potential involvement of StAR in sex differentiation and gonadal development. Additionally, the results indicated that progesterone, testosterone, and estradiol accounted for 80%, 10%, and 10% of the total hormone content in the gonads, respectively. Correlation analysis revealed a highly significant strong positive correlation between progesterone/estradiol levels and StAR gene expression, demonstrating that StAR serves as a key regulator in sex steroid hormone biosynthesis. These findings provide crucial molecular evidence for StAR-mediated steroidogenesis in bivalve reproduction, offering fundamental insights into invertebrate endocrinology. Full article

The Qinghai–Tibetan Plateau (QTP), often referred to as the “Third Pole” of the world, harbors alpine grassland ecosystems that play an essential role as global carbon sinks, helping to mitigate the pace of climate change. Nonetheless, alterations in natural environmental conditions coupled with escalating human activities have disrupted the seasonal growth cycles of grasslands, thereby intensifying degradation processes. To date, the key drivers and lifecycle dynamics of Grassland Depletion across the QTP remain contentious, limiting our comprehension of its ecological repercussions and regulatory mechanisms. This study comprehensively investigates grassland degradation on the Qinghai–Tibetan Plateau, analyzing its drivers and changes in ecological suitability during the growing season. By integrating natural factors (e.g., precipitation and temperature) and anthropogenic influences (e.g., population density and grazing intensity), it examines observational data from over 160 monitoring stations collected between the 1980s and 2020. The findings reveal three distinct phases of grassland degradation: an acute degradation phase in 1990 (GDI, Grassland Degradation Index = 2.53), a partial recovery phase from 1996 to 2005 (GDI < 2.0) during which the proportion of degraded grassland decreased from 71.85% in 1990 to 51.22% in 2005, and a renewed intensification of degradation after 2006 (GDI > 2.0), with degraded grassland areas reaching 56.39% by 2020. Among the influencing variables, precipitation emerged as the most significant driver, interacting closely with anthropogenic factors such as grazing practices and population distribution. Specifically, the combined impacts of precipitation with population density, grazing pressure, and elevation were particularly notable, yielding interaction q-values of 0.796, 0.767, and 0.752, respectively. Our findings reveal that while grasslands exhibit superior carbon sink potential relative to forests, their productivity and ecological functionality are undergoing considerable declines due to the compounded effects of multiple interacting factors. Consequently, the spatial distribution of ecologically suitable zones has contracted significantly, with the remaining high-suitability regions concentrating in the “twin-star” zones of Baingoin and Zanda grasslands, areas recognized as focal points for future ecosystem preservation. Furthermore, the effects of climate change and intensifying anthropogenic activity have driven the reduction in highly suitable grassland areas, shrinking from 41,232 km² in 1990 to 24,485 km² by 2020, with projections indicating a further decrease to only 2844 km² by 2060. This study sheds light on the intricate mechanisms behind Grassland Depletion, providing essential guidance for conservation efforts and ecological restoration on the QTP. Moreover, it offers theoretical underpinnings to support China’s carbon neutrality and peak carbon emission goals. Full article

Applying the holographic 2-flavor Einstein–Maxwell-dilaton model, the parameters of which are fixed by lattice QCD, we extract the equations of state for hot quark–gluon plasma around the critical point at $T=182$ MeV, and have corresponding quark star cores constructed. By further adding hadron shells, the mass range of the whole stars spans from 2 to 17 solar masses, with the maximum compactness around 0.22. This result allows them to be black hole mimickers and candidates for gap events. The I–Love–Q–C relations are also analyzed, which show consistency with the neutron star cases when the discontinuity at the quark–hadron interface is not large. Furthermore, we illustrate the full parameter maps of the energy density and pressure as functions of the temperature and chemical potential and discuss the constant thermal conductivity case supposing a heat source inside. Full article

In lunar exploration missions, rovers must navigate multiple waypoints within strict time constraints while avoiding dynamic obstacles, demanding real-time, collision-free path planning. This paper proposes a digital twin-enhanced hierarchical planning method, A*-D3QN-Opt (A-Star-Dueling Double Deep Q-Network-Optimized). The framework combines the A* algorithm for global optimal paths in static environments with an improved D3QN (Dueling Double Deep Q-Network) for dynamic obstacle avoidance. A multi-dimensional reward function balances path efficiency, safety, energy, and time, while priority experience replay accelerates training convergence. A high-fidelity digital twin simulation environment integrates a YOLOv5-based multimodal perception system for real-time obstacle detection and distance estimation. Experimental validation across low-, medium-, and high-complexity scenarios demonstrates superior performance: the method achieves shorter paths, zero collisions in dynamic settings, and 30% faster convergence than baseline D3QN. Results confirm its ability to harmonize optimality, safety, and real-time adaptability under dynamic constraints, offering critical support for autonomous navigation in lunar missions like Chang’e and future deep space exploration, thereby reducing operational risks and enhancing mission efficiency. Full article

Background: Preeclampsia (PE) is a pregnancy-specific disorder and a leading cause of maternal and fetal morbidity and mortality. Impaired trophoblast invasion is a hallmark of PE, and alternative splicing (AS) is crucial for trophoblast differentiation and placental development. However, the exact mechanisms of AS in PE remain poorly understood. Methods: To elucidate AS-mediated regulatory pathways in PE, a total of 38 fresh-frozen placental samples, including 13 pre-eclampsia samples and 25 normal control samples, were collected from Renmin Hospital of Wuhan University between 1 February and 30 July 2022. We performed transcriptome sequencing of seven PE and seven normal placentas to identify differentially spliced events. After quality control and adapter trimming, raw sequencing reads were aligned to the human reference genome using STAR. Differential exon usage was analyzed using DEXSeq (version 1.36.0), and exons with an adjusted p-value < 0.05 and a fold change greater than 2 or less than 0.5 were considered significantly differentially spliced. Functional assays, including CCK8, colony formation, and cell cycle analyses, were conducted to assess trophoblast proliferation, whereas wound healing and Transwell assays were used to evaluate trophoblast migration and invasion using the HTR-8/SVneo cell line. RNA immunoprecipitation sequencing (RIP-seq) and RNA stability assays were employed to investigate mRNA interactions and stability. Results: Insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3) emerged as a key RNA-binding protein associated with alternative splicing regulation, intersecting both AS-related candidate genes and known splicing factors, although it is not a classical splicing factor itself. IGF2BP3 overexpression markedly enhanced HTR-8/SVneo trophoblast proliferation, migration, and invasion while suppressing ROS activation. RNA-seq, RIP-seq, and RNA stability assays revealed that IGF2BP3 directly interacts with and enhances the stability of PDE3A mRNA. Functional rescue experiments confirmed that PDE3A knockdown partially abrogated IGF2BP3-mediated trophoblast progression. Furthermore, miR-196a-5p was identified as a negative regulator of IGF2BP3 via miRNA inhibitor/mimic transfection, qRT-PCR, and functional assays, confirming that miR-196a-5p overexpression downregulates IGF2BP3, thereby impairing trophoblast migration and proliferation. Notably, restoring IGF2BP3 expression reversed these inhibitory effects. Conclusions: Our findings reveal a previously unrecognized regulatory axis in PE in which miR-196a-5p suppresses IGF2BP3 expression, leading to PDE3A mRNA destabilization and impaired trophoblast function. This study offers mechanistic insights into PE pathogenesis and identifies IGF2BP3 as a potential therapeutic target. Full article

In this study, we present refined orbital and fundamental parameters of the Galactic B[e] supergiant binary system HD 327083 using the Bayesian Markov Chain Monte Carlo (MCMC) method applied to the radial velocities data of HD 327083. We found that the system is well described by a circular orbital model with the mass ratio of the components of $q=1.15\pm 0.07$. We modeled the evolutionary history of the system using MESA code. Initially, the system was formed by a binary with the orbital period of $Porb=108$ day, which contained stars with 13.00 $\pm 0.05$ ${\mathrm{M}}_{\odot }$ and $11.50\pm 0.05$ ${\mathrm{M}}_{\odot }$ masses. They had a relatively slow rotation ${\upsilon }_{rot}=0.40\pm 0.13{\upsilon }_{crit}$ and provided a strong stellar wind. The current system age is $13.6\pm 0.1$ Myr, and the state of the system corresponds to a close filling of the high massive component’s Roche lobe and a beginning of the mass transfer. The mass-transfer event will occur in a short interval of ≲0.1 Myr only. After that, the mass of the post-primary drops to ≈5 ${\mathrm{M}}_{\odot }$, the post-secondary mass grows until ≈20 ${\mathrm{M}}_{\odot }$, and the binary will convert to a detached system with a long orbital period of ≈700 days. Full article

Emphasising their connection with shell-like star-like curves, this work investigates a new subclass of star-like functions defined by $\mathfrak{q}$-Fibonacci numbers and $\mathfrak{q}$-polynomials. We study the geometric and analytic properties of this subclass, including the computation of intervals of univalence and nonunivalence for some functions. Moreover, we define a sufficient condition for functions in this subclass to satisfy the criteria of the famous class of analytic functions with positive real components. This work improves our understanding of the link between Fibonacci-type sequences and the geometric properties of analytic functions by using subordination ideas and the features of $\mathfrak{q}$-Fibonacci sequences. Emphasising the possibility for diverse research in combinatorial and analytical mathematics, the results offer fresh insights and support further study on the applications of calculus in geometric function theory. Full article

Insulin-like growth factors (IGFs) play crucial roles in the regulation of animal growth and reproduction. However, the functional and regulatory mechanisms underlying ovarian growth and oocyte maturation in teleosts remain unclear. In this study, the expression profiles of lncRNAs and mRNAs were analyzed in the ovaries of golden pompano (Trachinotus ovatus) treated with IGF1 and IGF2 proteins to gain insights into the role of these two IGF ligands in the regulation of ovarian development and maturation. A total of 1494 lncRNAs and 8728 mRNAs were differentially expressed following IGF1 treatment compared with the control group. A total of 101 lncRNAs and 377 mRNAs were differentially expressed after IGF2 treatment compared to those in the control group. The results revealed that KEGG pathways enriched by target genes of the DE lncRNAs overlapped significantly with those enriched by the DE mRNAs in both the IGF1 and IGF2 groups. The key overlapping enriched pathways included ECM receptor interaction, gap junction, Hedgehog signaling pathway, Ras signaling pathway, Rap1 signaling pathway, TGF beta signaling pathway, Wnt signaling pathway, GnRH signaling pathway, progesterone-mediated oocyte maturation, oocyte meiosis, cell cycle, and MAPK signaling pathway. The differentially expressed genes (DEGs) involved in ovarian development and oocyte maturation were cyp17a1, cyp19a1, star, hsd17b3, hsd17b7, adam23, slc26a6, htr2b, h2ax, nanos3, krt18, pgr, and inhbb, following IGF1 and IGF2 treatment. Furthermore, four lncRNAs (MSTRG.66521.1, MSTRG.49969.1, MSTRG.59923.1, and MSTRG.13767.1) for IGF1 and two (MSTRG.20896.2 and MSTRG.58123.2) for IGF2 within the lncRNA–mRNA network were found to target DEGs related to ovarian development and maturation. This suggests that IGFs may affect reproductive processes by regulating the expression of lncRNAs and mRNAs. RT-qPCR analysis revealed that these six lncRNAs showed high expression levels in the brain, pituitary, liver, and gonad tissues, indicating their potential involvement in regulating ovarian growth and development. This study elucidates the lncRNA–mRNA regulatory mechanism in response to IGF1 and IGF2 treatment during stage III of ovarian development in golden pompano, thereby deepening our understanding of its functional role. Full article

The cryopreservation of testicular tissues meets the demands for the germplasm preservation of humans and animals. Previously, we reported on the cryopreservation of bovine testicular tissues. To further evaluate the viability of these tissues, subcutaneous xenotransplantation of the frozen–thawed calf testicular tissues was performed with castrated nude mice as the recipients. After 28 days (D28), the survival and development of the grafts were examined. The grafts from 1-day-old (D1) calf testes were recovered and angiogenesis around the grafts was observed. Histologically, the seminiferous cords in the grafts were well maintained and capillaries in the interstitium were observed. Quantitative real-time PCR (qRT-PCR) analysis showed that the grafts expressed germline genes Gfrα-1, C-kit, and Sycp3 and somatic genes Sox9, Acta2, and Star. The expressions of C-kit, Sox9, Acta2, and Star were higher in 28D grafts than those in 1D and 30-day-old (30D) calf testicular controls. Together, we initially demonstrate that cryopreserved calf testicular tissues retain their viability and developmental capacity after xenotransplantation. Full article

Scan Quantum Mechanics (SQM) is a novel interpretation in which the superposition of states is only an approximate effective concept due to lack of time resolution. Quantum systems scan all possible states in the “apparent” superpositions and switch randomly and very rapidly among them. A crucial property that we postulate is quantum inertia $I_q$, that increases whenever a constituent is added, or the system is perturbed with all kinds of interactions. Once the quantum inertia reaches a critical value $I_{cr}$ for an observable, the switching among its eigenvalues stops and the corresponding superposition comes to an end. Consequently, increasing the quantum inertia of a quantum system by increasing its mass, its temperature, or the strength of the electric, magnetic and gravitational fields in its environment, can lead to the end of the superpositions for all the observables, the quantum system transmuting into a classical one, as a result. This process could be reversible, however, by decreasing the size of the system, its temperature, etc. SQM also implies a radiation mechanism from astrophysical objects with very strong gravitational fields that could contribute to neutron star formation. Future experiments might determine the critical quantum inertia $I_{cr}$ corresponding to different observables, which translates into critical masses, critical temperatures and critical electric, magnetic and gravitational fields. Full article

This comprehensive survey explored the evolving landscape of generative Artificial Intelligence (AI), with a specific focus on the recent technological breakthroughs and the gathering advancements toward possible Artificial General Intelligence (AGI). It critically examined the current state and future trajectory of generative AI, exploring how innovations in developing actionable and multimodal AI agents with the ability scale their “thinking” in solving complex reasoning tasks are reshaping research priorities and applications across various domains, while the survey also offers an impact analysis on the generative AI research taxonomy. This work has assessed the computational challenges, scalability, and real-world implications of these technologies while highlighting their potential in driving significant progress in fields like healthcare, finance, and education. Our study also addressed the emerging academic challenges posed by the proliferation of both AI-themed and AI-generated preprints, examining their impact on the peer-review process and scholarly communication. The study highlighted the importance of incorporating ethical and human-centric methods in AI development, ensuring alignment with societal norms and welfare, and outlined a strategy for future AI research that focuses on a balanced and conscientious use of generative AI as its capabilities continue to scale. Full article

This review provides an analysis of advancements in the design and performance assessment of Darrieus wind turbines over the past decade, with a focus on the contributions of computational fluid dynamics (CFD) to this field. The primary objective is to present insights from studies conducted between 2014 and 2024, emphasizing the enhancement of Darrieus wind turbine performance through various technological innovations. The research methodology employed for this review includes a critical analysis of published articles related to Darrieus turbines. The focus on the period from 2014 to 2024 was considered to highlight recent parametric CFD studies on Darrieus turbines, avoiding overlap with previously published reviews and maintaining originality relative to existing review works in the literature. By synthesizing a collection of articles, the review discusses a wide range of recent investigations utilizing CFD modeling techniques, including both 2D and 3D simulations. These studies predominantly utilize the “Ansys-Fluent” V12.0 and “STAR CCM+” V9.02 solvers to evaluate the aerodynamic performance of Darrieus rotors. Technological advancements focus on modifying the geometry of Darrieus, including alterations to blade profiles, chord length, rotor diameter, number of blades, turbine height, rotor solidity, and the integration of multiple rotors in various configurations. Additionally, the incorporation of flow deflectors, the use of advanced blade shapes, such as V-shaped or twisted blades, and the application of an opening ratio on the blades are explored to enhance rotor efficiency. The review highlights the significant impact of these geometric modifications on key performance metrics, particularly the moment and power coefficients. A dedicated section presents CFD-derived visualizations, including vorticity fields, turbulence contours illustrated through the Q-criterion, velocity vectors, and dynamic pressure contours. These visualizations provide a description of the flow structures around the modified Darrieus rotors. Moreover, the review includes an analysis of the dynamic performance curves of Darrieus, which show improvements resulting from the modifications of the baseline design. This analysis covers the evolution of pressure coefficients, moment coefficients, and the increased power output of Darrieus. Full article

Within the framework of Rastall theory, we investigate the impact of charge on the structural development of different types of spherically symmetric anisotropic stars. To do so, we present modified field equations based upon the Finch–Skea metric potentials expressed in terms of three parameters $(A,B,C)$. These constants are determined using suitable matching conditions and observational data for compact objects which include Her X-1, SAX J 1808.4-3658, PSR J038-0842, LMC X-4 and SMC X-1. The equation of state offered by the $\mathbb{MIT}$ bag model for quark–gluon plasma is used to investigate the inner structure and other characteristics of these compact objects. For a fixed bag constant, $\mathcal{B}=60{\mathrm{MeV}/\mathrm{fm}}^3$, and two sets of the Rastall and charge parameters, $\zeta =0.255,0.259$ and $\tilde{\mathcal{Q}}=0.2,0.7$, respectively, we analyze the consistency of the matter variables in the model and other physical parameters such as energy conditions, stellar mass, compactness, and surface redshift. In addition, we assess the stability of the constructed model through two different approaches. It is found that the obtained model is physically viable and stable. Full article

Unmanned aerial vehicles (UAVs) have made significant advances in autonomous sensing, particularly in the field of precision agriculture. Effective path planning is critical for autonomous navigation in large orchards to ensure that UAVs are able to recognize the optimal route between the start and end points. When UAVs perform tasks such as crop protection, monitoring, and data collection in orchard environments, they must be able to adapt to dynamic conditions. To address these challenges, this study proposes an enhanced Q-learning algorithm designed to optimize UAV path planning by combining static and dynamic obstacle avoidance features. A shortest distance priority (SDP) strategy is integrated into the learning process to minimize the distance the UAV must travel to reach the target. In addition, the root mean square propagation (RMSP) method is used to dynamically adjust the learning rate according to gradient changes, which accelerates the learning process and improves path planning efficiency. In this study, firstly, the proposed method was compared with state-of-the-art path planning techniques (including A-star, Dijkstra, and traditional Q-learning) in terms of learning time and path length through a grid-based 2D simulation environment. The results showed that the proposed method significantly improved performance compared to existing methods. In addition, 3D simulation experiments were conducted in the AirSim virtual environment. Due to the complexity of the 3D state, a deep neural network was used to calculate the Q-value based on the proposed algorithm. The results indicate that the proposed method can achieve the shortest path planning and obstacle avoidance operations in an orchard 3D simulation environment. Therefore, drones equipped with this algorithm are expected to make outstanding contributions to the development of precision agriculture through intelligent navigation and obstacle avoidance. Full article

Sambucus sibirica, a deciduous shrub from the Adoxaceae family, is a traditional Kazakh medicine used in Xinjiang, China. Its branches, leaves, and fruits are used to treat fractures, rheumatoid arthritis, and nephritis. To advance research on S. sibirica, we conducted studies on its microscopic identification, chemical composition, and biological activity. The cross-sectional features of the branches, leaves, and fruits were observed under a microscope, revealing different types of ducts, cork cells, non-glandular hairs, oil droplets, stone cells, scale hairs, and star-shaped hairs in the S. sibirica powders. Fourier transform infrared spectroscopy (FTIR) was used to characterize the presence of specific chemical groups, revealing similarities and differences between different parts. Thin-layer chromatography (TLC) confirmed that chlorogenic acid was present in the branches, leaves, and fruits, whereas rutin was more prominent in the leaves. The total flavonoid contents were determined by a photocolorimetric approach and resulted in values of 7419.80, 5193.10, and 3629.10 μg·g⁻¹ (dry weight) for the leaves, branches, and fruits, respectively. Further qualitative and quantitative analyses via ultra-performance liquid chromatography coupled with triple quadrupole tandem mass spectrometry (UPLC-QqQ-MS/MS) identified rutin, chlorogenic acid, quercetin, isoquercetin, and astragalin, with contents ranging from 1.00 to 4535.60 μg·g⁻¹ (dry weight). Antioxidant tests revealed that the branches, leaves, and fruits of S. sibirica presented antioxidant properties, with the leaves demonstrating the highest activity, followed by the branches and fruits. These results align with the results of the quantitative analysis. This study provides valuable insights into the microscopic features, chemical composition, and antioxidant activity of S. sibirica, laying the foundation for its pharmacognosy research and quality standards and offering a reference for its future development and utilization. Full article