Search Results (1,451)

Equinin B (GQCQRKCLGHCSKKCPKHPQCRKRCIRRCFGYCL), a marine peptide from Actinia equina exhibits antibacterial activity against both Gram-positive and Gram-negative bacteria. To identify a smaller active region and explore tunable properties, three peptide fragments were synthesized: GQCQRKCLGHCS (EB1), KKCPKHPQCRK (EB2), and RCIRRCFGYCL (EB3), yielding peptides with key AMP-like properties, including the most positively charged and most hydrophobic regions. Only the 11-residue C-terminal fragment showed selective activity against Gram-positive bacteria, including Staphylococcus epidermidis, Bacillus subtilis, and Enterococcus hirae, while remaining inactive against Escherichia coli. Peptide modifications, achieved by replacing cysteine residues with arginine, generally did not enhance activity, but in the C-terminal fragment EB3 they reduced hemolytic activity and increased bacterial specificity. Membrane depolarization assays confirmed that the unmodified fragment EB3 strongly disrupts bacterial membranes, whereas the modified variant showed minimal depolarization, highlighting its markedly reduced membrane-disruptive potential. In silico modelling revealed that the EB3 can adopt multiple membrane-disruption modes, from transient shallow pores to carpet-like mechanisms, while the cysteine-to-arginine variant interacts mainly via partial insertion anchored by arginine residues. Phenylalanine appears to interact with the membrane, and reducing hydrophobicity by its removal abolished antibacterial activity. These findings highlight the 11-residue C-terminal fragment as a tunable, membrane-targeting motif with mechanistic novelty, offering a blueprint for developing safer, selective antimicrobial peptides with reduced cytotoxicity. Full article

Thrips are cosmopolitan agricultural pests and important vectors of plant viruses, and the increasing coexistence of multiple morphologically similar species has intensified the demand for species-specific molecular identification. However, traditional morphological identification and PCR assays using universal primers are often inadequate for mixed-species samples and field-adaptable application. In this study, we developed a species-specific molecular identification framework targeting a polymorphism-rich region of the mitochondrial cytochrome c oxidase subunit I (COI) gene, which is more time-efficient than sequencing-based COI DNA barcoding, for four economically important thrips species in southern China, including the globally invasive Frankliniella occidentalis. By aligning COI sequences, polymorphism-rich regions were identified and used to design four species-specific primer pairs, each containing a diagnostic 3′-terminal nucleotide. These primers were combined with a PBS-based DNA extraction workflow optimized for single-insect samples that minimizes dependence on column-based purification. The assay achieved a practical detection limit of 1 ng per reaction, demonstrated species-specific amplification, and maintained reproducible amplification at DNA inputs of ≥1 ng per reaction. Notably, PCR inhibition caused by crude extracts was effectively alleviated by fivefold dilution. Although the chemical identities of the inhibitors remain unknown, interspecific variation in inhibition strength was observed, with T. hawaiiensis exhibiting the strongest suppression, possibly due to differences in lysate composition. This integrated framework balances target specificity, operational simplicity, and dilution-mitigated inhibition, providing a field-adaptable tool for thrips species identification and invasive species monitoring. Moreover, it provides a species-specific molecular foundation for downstream integration with visual nucleic acid detection platforms, such as the CRISPR/Cas12a system, thereby facilitating the future development of portable molecular identification workflows for small agricultural pests. Full article

Chimeric antigen receptor (CAR) T cell therapy has demonstrated clinical success in hematologic malignancies but has limited efficacy in solid tumors due to tumor microenvironment (TME) barriers that impede CAR T cell recognition, infiltration, and sustained function. Traditional 2D assays inadequately recapitulate these constraints, necessitating improved in vitro models. This study validated a 3D tumor spheroid platform using an agarose microwell system to generate uniform B7-H3-positive spheroids from multiple solid tumor cell lines, enabling the evaluation of CAR T cell activity. TME-relevant immune modulation under 3D conditions was analyzed by flow cytometry for B7-H3, MHC I/II, and antigen processing machinery (APM), followed by co-culture with B7-H3 CAR T cells to assess cytotoxicity, spheroid integrity, tumor viability, and CAR T cell activation, exhaustion, and cytokine production. Two human cancer-cell-line-derived spheroids, DU 145 (prostate cancer) and SUM159 (breast cancer), retained B7-H3 expression, while MC38 (mouse colon cancer)-derived spheroids served as a B7-H3 negative control. Under 3D culture conditions, DU 145 and SUM159 spheroids acquire TME-like immune evasion characteristics and specifically downregulated MHC-I and APM (TAP1, TAP2, LMP7) with concurrent upregulation of MHC-II and calreticulin. Co-culture showed effective spheroid infiltration, cytotoxicity, and structural disruption, with infiltrating CAR T cells displaying higher CD4⁺ fraction, activation, exhaustion, effector/terminal differentiation, and IFN-γ/TNF-α production. This 3D platform recapitulates critical TME constraints and provides a cost-effective, feasible preclinical tool to assess CAR T therapies beyond conventional 2D assays. Full article

Feed formulation is a typical multi-objective optimization problem that aims to minimize cost while satisfying multiple nutritional constraints. However, existing methods often suffer from limitations in handling nonlinear constraints, high-dimensional decision spaces, and solution feasibility. To address these challenges, this study proposes a multi-objective feed formulation method based on an improved Non-dominated Sorting Genetic Algorithm II (NSGA-II). A hybrid Dirichlet–Latin Hypercube Sampling (Dirichlet-LHS) strategy is introduced to generate an initial population with high feasibility and diversity, together with an iterative normalization-based dynamic repair operator to efficiently handle ingredient proportion and nutritional constraints. In addition, an adaptive termination mechanism based on the hypervolume improvement rate (Hypervolume Termination, HVT) is designed to avoid redundant computation while ensuring effective convergence of the Pareto front. Experimental results demonstrate that the Dirichlet–LHS strategy outperforms random sampling, Dirichlet sampling, and Latin hypercube sampling in terms of hypervolume and solution diversity. Under identical nutritional constraints, the improved NSGA-II reduces formulation cost by 1.52% compared with multi-objective Bayesian optimization and by 2.17% relative to conventional feed formulation methods. In a practical application to meat sheep diet formulation, the optimized feed cost is reduced to 1162.23 CNY per ton, achieving a 4.83% cost reduction with only a 1.09 s increase in computation time. These results indicate that the proposed method effectively addresses strongly constrained multi-objective feed formulation problems and provides reliable technical support for precision feeding in intelligent livestock production. Full article

Fluorite, a key accessory mineral associated with rare earth element (REE) deposits, exerts a significant influence on REE migration and precipitation through complexation, adsorption, and lattice substitution within fluorine-bearing fluid systems. It therefore provides a valuable archive for constraining REE enrichment processes. The Weishan alkaline–carbonatite-related REE deposit, the third-largest LREE deposit in China, is formed through a multistage magmatic–hydrothermal evolution of the carbonatite system. However, limited mineralogical constraints on REE enrichment and precipitation have hindered a comprehensive understanding of its metallogenic processes and exploration potential. Here, cathodoluminescence imaging and LA-ICP-MS trace element analyses were conducted on fluorite of multiple generations from the Weishan deposit to constrain the physicochemical conditions of mobility and precipitation mechanisms of this REE deposit. Four generations of fluorite are recognized, recording progressive evolution of the ore-forming fluids. Type I fluorite, which coexists with bastnäsite and calcite, is LREE-enriched and exhibits negative Eu anomalies, indicating precipitation from high-temperature, weakly acidic, and reducing fluids. Type II fluorite occurs as overgrowths on Type I, while Type III fluorite replaces Type II fluorite, with both displaying LREE depletion and MREE-Y enrichment, consistent with cooling during continued hydrothermal evolution. Type IV fluorite, which is interstitial between calcite grains and associated with mica, is formed under low-temperature, oxidizing conditions, reflecting REE exhaustion and the terminal stage of fluorite precipitation. Systematic shifts in REE patterns among the four generations track progressive cooling of the system. The decreasing trend in La/Ho and Tb/La further suggests that these fluorites record dissolution–reprecipitation events and associated element remobilization during fluid evolution. Full article

The poly(A) tail on viral mRNAs plays an important role in gene expression, given the role of the 3′ mRNA tail in mRNA stability and translation. Viruses have developed several strategies to maintain the integrity of their poly(A) tails. These include attracting stabilizing proteins through elements in the 3′ untranslated regions of their mRNA, remodeling their poly(A) tails using terminal nucleotidyl transferases, and blocking deadenylase access to the terminal 3′ end of their poly(A) tails using protein–protein interactions or through triple helical RNA structures. Collectively, the presence of these multiple strategies illustrates the vital overall need for viruses to maintain and preserve their poly(A) tails, highlighting a potential avenue for broad-spectrum antiviral development. In addition, poly(A) tail preservation strategies used by viruses may also be applied to RNA vaccines and therapeutics. Full article

Partial demagnetization of multiple in-wheel motors changes torque distribution characteristics and can reduce vehicle stability, which poses a challenge for in-wheel motor drive electric vehicles (IWMDEVs) to maintain a balance between safety and efficiency. To address this issue, a hierarchical multi-objective adaptive fault-tolerant control (FTC) strategy based on wheel terminal torque compensation is developed. In the upper layer, a nonlinear model predictive controller (NMPC) generates the desired total driving force and corrective yaw moment according to vehicle dynamics and driving conditions. The lower layer employs a quadratic programming (QP) scheme to allocate the wheel torques under actuator and tire constraints. Two adaptive coefficients—the stability–efficiency weighting factor and the current compensation factor—are updated through a randomized ensembled double Q-learning (REDQ) algorithm, enabling the controller to adaptively balance yaw stability preservation and energy optimization under different fault scenarios. The proposed method is implemented and verified in a CarSim–Simulink–Python co-simulation environment. The simulation results show that the controller effectively improves yaw and lateral stability while reducing energy consumption, validating the feasibility and effectiveness of the proposed strategy. This approach offers a promising solution to achieve reliable and energy-efficient control of IWMDEVs. Full article

Glucose-dependent insulinotropic polypeptide (GIP) was the first incretin hormone identified, best known for promoting glucose-stimulated insulin secretion. Increasing evidence has expanded its physiological relevance beyond glucose metabolism, revealing a significant role for GIP in the gut–bone axis. In vitro studies demonstrate that GIP inhibits osteoclast differentiation and activity while promoting osteoblastic bone formation. Findings from genetic animal models and human variant analyses further support the essential role of endogenous GIP signaling in maintaining bone mass and quality. Exogenous administration of GIP suppresses the bone-resorption marker C-terminal telopeptide of type I collagen (CTX) and increases the bone-formation marker procollagen type I N-terminal propeptide (P1NP) in healthy individuals, reflecting an acute shift toward reduced bone resorption and enhanced bone formation. Moreover, GIP confers protection against bone deterioration in multiple pathological conditions, including postmenopausal osteoporosis, inflammatory bone loss, obesity, and diabetes, etc., suggesting therapeutic potential beyond physiological contexts. Recent evidence also shows that GIP attenuates orthodontic tooth movement by limiting mechanically induced osteoclast activity, highlighting its broader skeletal actions. In this review, we summarize recent advances regarding the role of GIP in bone metabolism, integrating evidence from cellular studies, animal models and human investigations, and discuss future directions for GIP-based interventions. Full article

As a tectonically stable and extensively superimposed basin situated in the North China Craton, the Ordos Basin hosts abundant reserves of oil, natural gas, and coal within its Paleozoic strata, rendering it a focal area in energy-related geological research. The basin’s evolutionary history provides a comprehensive record of key geological transitions—from an Early Paleozoic carbonate platform to Late Paleozoic marine–continental transitional deposits and ultimately to continental clastic sedimentation—largely governed by the regional tectonic dynamics associated with the North China Plate. This study presents a systematic review of the sedimentary and tectonic evolution of the Paleozoic sequence in the basin. Findings indicate that during the Early Paleozoic, the basin developed under a passive continental margin setting, characterized by widespread epicontinental marine carbonate deposition. By the Late Ordovician, subduction of the Qinqi Ocean triggered the Caledonian orogeny, resulting in regional uplift across the basin, widespread erosion, and a significant hiatus in Middle to Late Ordovician sedimentation, which facilitated the formation of paleo-weathered crust karst reservoirs. In the Late Paleozoic, the basin evolved into an intracratonic depression. From the Late Carboniferous to the Early Permian, the Hercynian tectonic event influenced the transformation from isolated rift basins to a broad epicontinental sea, leading to the deposition of critical coal-bearing strata within marine–continental transitional facies. Starting in the Middle Permian, the closure of surrounding oceanic domains induced widespread tectonic uplift, shifting the depositional environment to a terrestrial fluvial-lacustrine system and marking the termination of marine sedimentation in the region. Based on the comprehensive research findings, this study underscores that the superposition, inheritance, and interaction of multiple tectonic events are the primary controls on the paleogeographic architecture and sedimentary. Full article

In indoor environments where Global Navigation Satellite System (GNSS) signals are entirely blocked, wireless signals such as 5G and Ultra-Wideband (UWB) have become primary means for high-precision positioning. However, complex indoor structures lead to significant multipath effects, which severely constrain the improvement of positioning accuracy. Existing indoor positioning methods rarely link environmental semantic information (e.g., wall, column) to multipath error estimation, leading to inaccurate multipath correction—especially in complex scenes with multiple reflective objects. To address this issue, this paper proposes a LiDAR-assisted multipath estimation and positioning method. This method constructs a tightly coupled perception-positioning framework: first, a semantic-feature-based neural network for reflective surface detection is designed to accurately extract the geometric parameters of potential reflectors from LiDAR point clouds; subsequently, a unified factor graph model is established to multidimensionally associate and jointly infer terminal states, virtual anchor (VA) states, wireless signal measurements, and LiDAR-perceived reflector information, enabling dynamic discrimination and utilization of both line-of-sight (LOS) and non-line-of-sight (NLOS) paths. Experimental results demonstrate that the root mean square error (RMSE) of the proposed method is improved by 32.1% compared to traditional multipath compensation approaches. This research provides an effective solution for high-precision and robust positioning in complex indoor environments. Full article

Multi-revolution Lambert solvers are intended to find the elliptic transfer orbits that are traveled multiple times and connect two specified positions in prescribed time, under the assumption of considering natural (Keplerian) orbital motion in the presence of a single attracting body. This study proposes and tests a new, effective multi-revolution Lambert solver that employs the initial true anomaly, which identifies the initial position along the transfer ellipse, as the unknown variable. The related search interval is identified through closed-form expressions for upper and lower bounds. A simple numerical algorithm is developed and employed over the entire search interval to detect all Lambert solutions. The new multi-revolution solver proposed in this work is simple to understand and easy to implement and is successfully tested in several challenging scenarios (corresponding to some pathological cases reported in the recent scientific literature), as well as for the study of Earth–Mars interplanetary transfers. Comparison with alternative, up-to-date techniques points out that the new approach at hand is able to detect all the feasible transfer ellipses, in all cases, with very satisfactory accuracy in terms of final position error, even in challenging scenarios that include a huge number of revolutions or near-antipodal terminal positions. Full article

Single-phase-to-ground faults occur frequently in distribution networks, while traditional localization methods have limitations such as insufficient feature extraction and poor topological adaptability. To address these issues, this paper proposes a two-stage localization method that integrates the Node Classification Matrix (NCM) and an Improved Binary Particle Swarm Optimization (IBPSO) algorithm. The NCM achieves rapid initial localization, and the IBPSO performs error correction. This paper employs an IEEE 33-node standard distribution network model to design simulations covering scenarios with varying fault locations, multiple fault resistances, and different numbers of node distortions for validation. The results demonstrate that the proposed method achieves a fault location accuracy of 96%, which is 19% higher than that of the NCM alone and 2% higher than that of the IBPSO alone. Moreover, it maintains an accuracy of over 95% under scenarios of 1–3 node distortions, topological switching, and high-impedance faults, and is compatible with existing Feeder Terminal Unit (FTU) devices. This method effectively balances localization speed and robustness, providing a reliable solution for the rapid fault isolation of distribution network. Full article

To alleviate communication pressure and terminal resource constraints in mobile edge computing (MEC) networks, this paper proposes a resource allocation optimization method for MEC systems that integrates data compression technology and non-orthogonal multiple access technology. This method considers practical constraints such as terminal device battery capacity and computational resource limitations. By jointly optimizing computational resource allocation, task offloading strategies, and data compression ratios, it constructs an optimization model aimed at minimizing the total task processing latency. Addressing the challenges stemming from the non-convex nature of the problem and the dynamic variations in channel conditions and task requirements, this paper proposes a softmax deep double deterministic policy gradient algorithm, where softmax operator function mitigates both overestimation and underestimation biases inherent in traditional reinforcement learning frameworks, enhancing convergence performance. Utilizing a deep reinforcement learning framework, the algorithm achieves joint decision-making optimization for computational resources, task offloading, and compression ratios, thereby minimizing the total task processing latency while satisfying transmit power and computational resource constraints. Simulation results demonstrate that the proposed scheme exhibits significant advantages over benchmark algorithms in terms of convergence speed and task processing latency. Full article

Mobile elements, particularly long terminal repeat retrotransposons (LTR-RTEs), are abundant and dynamic components of plant genomes. Although viral infections are known to transcriptionally activate retrotransposons, it remains unclear whether such virus-induced activation leads to their mobilization. To address this question, we examined LTR-RTE activation in Arabidopsis thaliana, Brassica napus, and Nicotiana benthamiana following infection with the RNA viruses Tobacco rattle virus (TRV), Potato virus X (PVX), and Tobacco ringspot virus (TRSV). Nanopore cDNA sequencing revealed virus-specific transcriptional responses, with PVX uniquely triggering a strong transcriptional burst of diverse LTR-RTE families in N. benthamiana. To test the role of viral suppressors of RNA silencing (VSRs) in this process, we analyzed extrachromosomal circular DNA (eccDNA) from plants infected with TRV expressing the VSR P19. This analysis identified eccDNA derived from Ty3/Gypsy Galadriel elements, demonstrating that viral infection can promote not only retrotransposon transcription but also eccDNA production, which may indicate the ability of LTR-RTEs to transpose. These findings clearly illustrate that plant–virus interactions can induce not only changes in gene transcription, but also the activation of multiple retrotransposons, highlighting a potential evolutionary interface linking antiviral defense and transposon regulation. Full article

In submerged tunnel construction, the installation accuracy of pre-embedded components directly impacts subsequent engineering quality and operational safety. However, current on-site construction still primarily relies on manual measurement and two-dimensional drawings for guidance, resulting in significant positioning errors, delayed information transmission, and inefficient installation inspections. To enhance the digitalization and intelligence of submerged tunnel construction, this paper proposes a BIM- and AR-based human–machine collaborative management method for pre-embedded components in submerged tunnel segments. This method establishes a site-wide panoramic model as its foundation, enabling intelligent matching of component model geometry and semantic information. It facilitates human–machine interaction applications such as AR-based visualization for positioning and verification of pre-embedded components, information querying, and progress simulation. Additionally, the system supports collaborative operations across multiple terminal devices, ensuring information consistency and task synchronization among diverse roles. Its application in the Mingzhu Bay Submerged Tunnel Project in Nansha, Guangzhou, validates the feasibility and practical utility of the proposed workflow in a pilot case, and indicates potential for further validation in broader construction settings. Full article