Search Results (205)

Callicarpa peichieniana is an important traditional Chinese medicinal plant with pharmacological benefits for digestive system diseases and wounds, as well as high ornamental value. The goal of this study is to establish an effective in vitro regeneration system in order to satisfy the expanding market demand. Extracts from algae can enhance the proliferation and rooting effect of adventitious buds and can improve the survival rate of transplantation. This study developed an in vitro regeneration system using apical bud explants of C. peichieniana associated with Chlorella sorokiniana (an alga species). Inter simple sequence repeat (ISSR) molecular markers confirmed the genetic fidelity of the regenerated plantlets. The highest number of adventitious buds (5.00 buds) was induced from the apical buds with 0.5 mg/L 6-BA in a Murashige and Skoog (MS) medium, and the highest proliferation coefficient (5.83) was achieved with 2.0 mg/L 6-BA. A rooting rate of 100% was achieved by using 0.1 mg/L NAA, MS with 50% macroelements, and 20 g/L sucrose, averaging 6.36 roots per explant and a root length of 1.32 cm. In all micropropagation stages, C. sorokiniana coexisted and proliferated alongside C. peichieniana materials. ISSR showed that the genetic fidelity of C. peichieniana regenerated plants was 95.45%. Coconut coir/perlite = 1∶1 (v/v) was identified as the optimal transplantation substrate, achieving a 100% survival rate. The “C. peichieniana–C. sorokiniana association” in vitro regeneration system established in this study not only enables the mass production of high-quality regenerated plantlets but provides new ideas and demonstrations for culturing multiple species in the same in vitro system. Full article

In closed Brayton cycle power generation systems, sudden load disturbances can induce a compressor surge in turbine–alternator–compressor systems, posing significant risks to dynamic stability and operational reliability. To address this challenge, this study proposes a PID control strategy optimized via a genetic algorithm. A high-fidelity dynamic model of the turbine–alternator–compressor system under closed Brayton cycle conditions is developed in Simulink, incorporating surge boundaries derived from performance maps. Control parameters are tuned using a weighted multi-objective fitness function that integrates overshoot, rise time, and the integral of absolute error. Simulation results demonstrate that the proposed control scheme markedly enhances system responsiveness—achieving approximately a 70% improvement in rotational speed regulation—and effectively maintains the operating point outside the surge region. The proposed framework provides a practical and robust approach for improving the dynamic stability and reliability of closed Brayton cycle power generation systems. Full article

Reduced chemical kinetic mechanisms are essential for enabling the use of complex fuels in 3D CFD combustion simulations. This study presents the development and optimization of a compact mechanism capable of accurately modeling ethanol–gasoline blends, including Brazilian Type-C gasoline (27% ethanol by volume) and up to pure ethanol (E100). An initial mechanism was constructed using the Directed Relation Graph with Error Propagation (DRGEP) method applied to detailed mechanisms selected for each surrogate component. The resulting mechanism was then refined through three global iterations of a genetic algorithm targeting ignition delay time (IDT) and laminar flame speed (LFS) performance. Five candidate versions (Mec1 to Mec5), each containing 179 species and 771 reactions, were generated. Mec4 was identified as the optimal configuration based on quantitative error analysis across all tested conditions and blend ratios. The final mechanism offers a balance between predictive accuracy and computational feasibility, making it well-suited for high-fidelity simulations in complex geometries involving multi-component ethanol–gasoline fuels. Full article

Hypolepis punctata, an aromatic fern with insect-resistant and ornamental potential. Up to date, no studies have reported its micropropagation, particularly using vegetative organs as explants. The optimized stolon sterilization (81.11%) employed 75% ethanol (30 s) and 15% sodium hypochlorite (12 min). The optimal conditions for GGB induction (75.56%) and proliferation (8.46 mm) were achieved using Murashige and Skoog (MS) medium + 2.0 mg/L 6-benzylaminopurine (BA) + 0.2 mg/L 1-naphthaleneacetic acid (NAA). The optimal plant growth regulator (PGR) formula for sporophyte regeneration was 0.5 mg/L BA + 0.1 mg/L NAA + 2 g/L activated charcoal (AC), achieving a 98.89% induction rate and 49.19 buds per explant. The 1/4 MS medium had the greatest promoting effect on biomass accumulation and leaf expansion. Optimal shoot elongation (97.78% success, 4.83 cm) was achieved in 1/4 MS + 0.5 mg/L BA + 0.1 mg/L NAA + 2 g/L AC, and optimized rooting (92.22%) was achieved using 1/4 MS + 0.5 mg/L indole-3-butyric acid (IBA) + 0.1 mg/L NAA + 2 g/L AC, producing 25.27 roots per plantlet. Crucially, ISSR analysis confirmed the genetic stability of all regenerants. This optimized protocol establishes a scalable micropropagation system, enhancing both commercial cultivation and genetic improvement potential in Hypolepis punctata. Full article

Cardiac physiology and pathology have been extensively explored at the transcriptional level. Still, they are less understood at the translational level, including three major knowledge gaps: pathophysiological impact, molecular mechanisms, and therapeutic implications of translational control in cardiac biology and heart disease. This review aims to provide a summary of the most recent key findings in this emerging field of translational control in heart health and disease, covering the physiological functions, disease pathogenesis, biochemical mechanisms, and development of potential RNA-based, translation-manipulating drugs. Translation of mRNA to protein is the final step in the central dogma for protein synthesis. Translation machinery includes a family of essential “housekeeping” factors and enzymes required for mRNA translation. These translation factors ensure the accurate processing of mRNA to protein according to the genetic code and maintain the optimal quality and quantity of cellular proteins for normal cardiac function. Translation factors also regulate the efficiency, speed, and fidelity of protein production and play a role in cardiac pathological remodeling under stress conditions. This review first introduces the techniques and methods used to study the translational regulation of gene expression in the cardiac system. We then summarize discoveries of a variety of pathophysiological functions and molecular mechanisms of translational control in cardiac health and disease, focusing on two primary symptoms, cardiac hypertrophy and fibrosis. In these sessions, we discuss the translational regulation directed by specific regulatory factors in cardiac physiology and how their genetic mutations, expression dysregulation, or functional alterations contribute to the etiology of heart disease. Notably, translational control exhibits extensive crosstalk with other processes, including transcriptional regulation, mitochondrial metabolism, and sarcomere homeostasis. Furthermore, recent findings have revealed the role of translational regulation in cardiomyocyte proliferation and heart regeneration, providing new approaches for creating regenerative medicine. Because transcript-specific translational regulation of both pathological and protective proteins occurs in heart disease, target-selective translation inhibitors and enhancers can be developed. These inhibitors and enhancers offer valuable insights into novel therapeutic targets and the development of RNA-based drugs for heart disease treatment. Full article

Rhaponticum carthamoides (Willd.) Iljin. (Leuzea carthamoides, Maral root), a medicinally valuable species listed in the Red Book of Kazakhstan, is known for its rich phytochemical profile. However, limited data exist on its microclonal propagation. This study aimed to optimize in vitro and medium-term storage conditions using biotechnological methods. Mature seeds collected from natural populations in the Kazakhstani Altai were germinated, and tissues from the seedlings were used as explants. Sterile shoots were cultured on Murashige and Skoog (MS) medium supplemented with 3.0 mg L⁻¹ −6-benzylaminopurine and 3.0 mg L⁻¹ kinetin. For shoot induction, MS medium supplemented with 0.5 mg L⁻¹ meta-Topolin and using stem apices as explants yielded optimal results. Medium-term storage with chlorocholine chloride at 0.1–0.4 g/L effectively preserved regenerative capacity for further rooting. After 12 months of storage, plantlets were transferred to half-strength MS medium with 3.0 g/L activated carbon and at 2.0 or 5.0 mg L⁻¹ indole-3-butyric acid for rooting. Regenerated plants were successfully acclimatized ex vitro. The 20-hydroxyecdysone content in field-grown plants post-storage reached 9.24 mg/mL, 2.4-fold higher than in wild plants. Inter simple sequence repeat analysis confirmed genetic stability. Our optimized protocol ensures high-yield metabolite production and genetic fidelity, enabling in vitro conservation, nursery-scale cultivation, and the restoration of R. carthamoides natural populations. Full article

Ajuga bracteosa is a herb with high medicinal value and a low range of distribution. It is used in several herbal and traditional medicines, including diabetes. In the present study, we designed the methodology for the micropropagation of A. bracteosa from internodal segments. The highest shoot multiplication was achieved on Murashige and Skoog (MS) medium supplemented with 6-benzyl-amino-purine (BAP) (5.0 µM) + indole-3-acetic acid (IAA) (1.5 µM) + adenine sulphate (ADS) (15.0 µM), which produced the maximum number of 20.45 ± 0.12 shoots/explants with 6.43 ± 0.006 cm shoot length. Rooting in the microshoots was attained on half-strength MS medium containing indole-3-butyric acid (IBA) (1.5 µM), with the highest root number of 16.44 ± 0.015 roots/shoot, and root length of 2.25 ± 0.011 cm. To assess genetic fidelity, SCoT marker analysis was performed on nine randomly selected in vitro regenerated plantlets and the mother plant, all of which exhibited monomorphic banding patterns, confirming genetic stability. Scanning electron microscopy (SEM) reveals normal stomatal structure in the regenerated plants post-acclimatization, indicating successful physiological recovery. Furthermore, Gas Chromatography–Mass Spectrometry (GC-MS) analysis confirms the presence of major phytocompounds in both the in vitro regenerated plants and the mother plant, supporting the conservation of phytochemical integrity. Given the restricted distribution and overharvesting pressure on this species, the established protocol provides an efficient strategy for rapid, large-scale, and genetically stable propagation to support conservation and pharmaceutical utilization. Full article

We investigated the dispersal ability of Euphydryas aurinia provincialis in a local-scale analysis within a single habitat patch of the Colfiorito highlands metapopulation. Our findings indicate that inside a single node, the organization of nesting patches can be conceptualized as a metapopulation itself, where reproductive sites, despite their spatial proximity, can act as either source or sink habitats depending on environmental conditions. We conducted fieldwork in six nesting patches inside a single node, capturing, marking, and recapturing individuals to assess their spatial distribution and movement tendencies at a large landscape scale. We found a high degree of site fidelity among individuals, with many recaptures occurring within the original marking site, but also a sex-based difference in movement patterns; females dispersed farther than males, likely driven by reproductive strategies, while males remained more localized, prioritizing mate-searching. Our findings suggest a complex dynamic in habitat connectivity: pastures and abandoned fields, despite being open, seem to act like sink areas, while breeding sites with shrub and tree cover act as source habitats, offering optimal conditions for reproduction. Individuals, especially females, from these source areas were later compelled to disperse into open habitats, highlighting a nuanced interaction between landscape structure and population dynamics. These results highlight the importance of maintaining habitat corridors to support metapopulation dynamics and prevent genetic isolation; the abandonment of traditional grazing practices is leading to the rapid closure of these source habitats, posing a severe risk of local extinction. Conservation efforts should prioritize the preservation of these source habitats to ensure the long-term viability of E. a. provincialis populations in fragmented landscapes. Full article

The architecture of rice tillers plays a pivotal role in yield potential, yet conventional phenotyping methods have struggled to capture these intricate three-dimensional (3D) structures with high fidelity. In this study, a 3D model reconstruction method was developed specifically for rice tillers to overcome the challenges posed by their slender, feature-poor morphology in multi-view stereo-based 3D reconstruction. By applying strategically designed colorful reference markers, high-resolution 3D tiller models of 231 rice landraces were reconstructed. Accurate phenotyping was achieved by introducing ScaleCalculator, a software tool that integrated depth images from a depth camera to calibrate the physical sizes of the 3D models. The high efficiency of the 3D model-based phenotyping pipeline was demonstrated by extracting the following seven key agronomic traits: flag leaf length, panicle length, first internode length below the panicle, stem length, flag leaf angle, second leaf angle from the panicle, and third leaf angle. Genome-wide association studies (GWAS) performed with these 3D traits identified numerous candidate genes, nine of which had been previously confirmed in the literature. This work provides a 3D phenomics solution tailored for slender organs and offers novel insights into the genetic regulation of complex morphological traits in rice. Full article

This research introduces an innovative passive vibration control methodology employing acoustic black hole (ABH) structures to mitigate vibration transmission in electric automotive steering machines—a prevalent issue adversely affecting driving comfort and vehicle safety. Leveraging the inherent bending wave manipulation properties of ABH configurations, we conceive an integrated vibration suppression framework synergizing advanced computational modeling with intelligent optimization algorithms. A high-fidelity finite element (FEM) model integrating ABH-attached steering machine system was developed and subjected to experimental validation via rigorous modal testing. To address computational challenges in design optimization, a hybrid modeling strategy integrating parametric design (using Latin Hypercube Sampling, LHS) with Kriging surrogate modeling is proposed. Systematic parameterization of ABH geometry and damping layer dimensions generated 40 training datasets and 12 validation datasets. Surrogate model verification confirms the model’s precise mapping of vibration characteristics across the design space. Subsequent multi-objective genetic algorithm optimization targeting RMS velocity suppression achieved substantial vibration attenuation (29.2%) compared to baseline parameters. The developed methodology provides automotive researchers and engineers with an efficient suitable design tool for vibration-sensitive automotive component design. Full article

Hydrogen is a promising zero-carbon fuel for internal combustion engines; however, the geometric optimization of injectors for low-pressure direct-injection (LPDI) systems under lean-burn conditions remains underexplored. This study presents a high-fidelity optimization framework that couples a validated computational fluid dynamics (CFD) combustion model with a surrogate-assisted multi-objective genetic algorithm (MOGA). The CFD model was validated using particle image velocimetry (PIV) data from non-reacting flow experiments conducted in an optically accessible research engine developed by Sandia National Laboratories, ensuring accurate prediction of in-cylinder flow structures. The optimization focused on two critical geometric parameters: injector hole count and injection angle. Partial indicated mean effective pressure (pIMEP) and in-cylinder NO_x emissions were selected as conflicting objectives to balance performance and emissions. Adaptive mesh refinement (AMR) was employed to resolve transient in-cylinder flow and combustion dynamics with high spatial accuracy. Among 22 evaluated configurations including both capped and uncapped designs, the injector featuring three holes at a 15.24° injection angle outperformed the baseline, delivering improved mixture uniformity, reduced knock tendency, and lower NO_x emissions. These results demonstrate the potential of geometry-based optimization for advancing hydrogen-fueled LPDI engines toward cleaner and more efficient combustion strategies. Full article

Rare genetic diseases are often caused by structural variants (SVs), such as insertions, deletions, duplications, inversions, and complex rearrangements. However, due to the technical limitations of short-read sequencing, these variants remain underdiagnosed. Long-read sequencing technologies, including Oxford Nanopore and Pacific Biosciences high-fidelity (HiFi), have recently advanced to the point that they can accurately find SVs throughout the genome, including in previously unreachable areas like repetitive sequences and segmental duplications. This study underscores the transformative role of long-read sequencing in diagnosing rare diseases, emphasizing the bioinformatics tools designed for detecting and interpreting structural variants (SVs). Comprehensive methods are reviewed, including methylation profiling, RNA-seq, phasing analysis, and long-read sequencing. The effectiveness and applications of well-known tools like Sniffles2, SVIM, and cuteSV are also assessed. Case studies illustrate how this technique has revealed new pathogenic pathways and solved cases that were previously undetected. Along with outlining potential future paths like telomere-to-telomere assemblies and pan-genome integration, we also address existing issues, including cost, clinical validation, and computational complexity. For uncommon genetic illnesses, long-read sequencing has the potential to completely change the molecular diagnostic picture as it approaches clinical adoption. Full article

A standard approach to design begins with scaling up state-of-the-art machines to new target dimensions, moving towards larger rotors with lower specific energy to maximize revenue and enable power production in lower wind speed areas. This trend is particularly crucial in floating offshore wind in the Mediterranean Sea, where the high levelized cost of energy poses significant risks to the sustainability of investments in new projects. In this context, the conventional approach of scaling up machines designed for fixed foundations and strong offshore winds may not be optimal. Additionally, modern large-scale wind turbines for offshore applications face challenges in achieving high aerodynamic performance in thick root regions. This study proposes a holistic optimization framework that combines multi-fidelity analyses and tools to address the new challenges in wind turbine rotor design, accounting for the novel demands of this application. The method is based on a modular optimization framework for the aerodynamic design of a new wind turbine rotor, where the cost function block is defined with the aid of a model reduction strategy. The link between the full-order model required to evaluate the target rotor’s performance, the physical aspects of blade aerodynamics, and the optimization algorithm that needs several evaluations of the cost function is provided by the definition of a surrogate model (SM). An intelligent SM definition strategy is adopted to minimize the computational effort required to build a reliable model of the cost function. The strategy is based on the construction of a self-adaptive, automatic refinement of the training space, while the particular SM is defined by the use of stochastic radial basis functions. The goal of this paper is to describe the new aerodynamic design strategy, its performance, and results, presenting a case study of a 15 MW wind turbine blades optimized for specific deepwater sites in the Mediterranean Sea. Full article

In the severe environment of Hunshandake Sandy Land, the uncommon and indigenous Chinese tree species Picea mongolica is an important biological component. Conventional seed propagation in P. mongolica is constrained by low germination rates, prolonged breeding cycles, and hybrid offspring genetic instability, limiting efficient varietal improvement. In contrast, somatic embryogenesis (SE) offers superior propagation efficiency, exceptional germination synchrony, and strict genetic fidelity, enabling rapid mass production of elite regenerants. However, SE in P. mongolica is hampered by severe genotype dependence, poor mature embryo induction rates, and loss of embryogenic potential during long-term cultures, restricting the production of high-quality seedlings. In this study, we aimed to analyze the transcriptome and metabolome of three crucial phases of SE: mature somatic embryos (MSEs), globular somatic embryos (GSEs), and embryogenic calli (EC). Numerous differentially expressed genes (DEGs) were found, especially in pathways linked to ribosomal functions, flavonoid biosynthesis, and the metabolism of starch and sucrose. Additionally, 141 differentially accumulated metabolites (DAMs) belonging to flavonoids, organic acids, carbohydrates, lipids, amino acids, and other metabolites were identified. An integrated study of metabolomic and transcriptome data indicated considerable enrichment of DEGs and DAMs in starch and sucrose metabolism, as well as phenylpropanoid biosynthesis pathways, all of which are required for somatic embryo start and development. This study revealed a number of metabolites and genes linked with SE, offering important insights into the molecular mechanisms driving SE in P. mongolica and laying the groundwork for the development of an efficient SE system. Full article

An aircraft that has been carefully optimized for a single flight condition will tend to perform poorly at other flight conditions. For aircraft such as long-haul airliners, this is not necessarily a problem, since the cruise condition so heavily dominates a typical mission. However, other aircraft, such as Unmanned Aerial Vehicles (UAVs), may be expected to perform well at a wide range of flight conditions. Morphing systems may be a solution to this problem, as they allow the aircraft to adapt its shape to produce optimum performance at each flight condition. This study proposes an aerodynamic optimization framework for morphing airfoils by integrating Principal Component Analysis (PCA) for geometric dimensionality reduction and deep learning (DL) for surrogate modeling, alongside an optimization-guided data augmentation strategy. By employing PCA, the geometric dimensionality of airfoil surfaces is reduced from 24 to 18 design variables while preserving 100% shape fidelity, thus establishing a compressed morphing parameterization space. A Multi-Island Genetic Algorithm (MIGA) efficiently explores the reduced design space, while iterative retraining of the surrogate model enhances prediction accuracy, particularly in high-performance regions. Additionally, Shapley Additive Explanation (SHAP) analysis reveals interpretable correlations between principal component modes and aerodynamic performances. Experimental results show that the optimized airfoil achieves a 54.66% increase in low-speed cruise lift-to-drag ratio and 10.90% higher climb lift compared to the baseline. Overall, the proposed framework not only enhances the adaptability of morphing airfoils across various low-speed flight conditions but also facilitates targeted surrogate refinement and efficient data acquisition in high-performance regions. Full article