Search Results (702)

As a global environmental problem, biological invasion poses a serious threat to natural ecosystems. To explore the influence mechanism of Alternanthera philoxeroides (Mart.) Griseb on the growth and development of landscape plants, this study systematically analyzed the effects of extracts from different organs (stems, leaves, and roots) of A. philoxeroides on the seed germination and seedling growth of Zinnia elegans Jacq. by combining the Petri dish filter paper method with a pot experiment to reveal the potential mechanism of allelopathy. The results showed that the aqueous extract of A. philoxeroides inhibited the seed germination and seedling growth of Z. elegans. The high concentration (100 mg·mL⁻¹) of stem and leaf extracts significantly reduced the germination rate (by 99.10% and 90.65%) and seedling morphological parameters. The allelopathic inhibition increased with an increase in concentration, and the inhibitory effect of stem and leaf extracts was significantly stronger than that of root extracts. Aqueous extracts from the roots, stems, and leaves of A. philoxeroides at three concentrations (25, 50, and 100 mg·mL⁻¹) induced oxidative stress in seedlings, as evidenced by the elevated malondialdehyde (MDA) content and dysregulated activities of antioxidant enzymes. Specifically, superoxide dismutase (SOD) and catalase (CAT) activities exhibited a concentration-dependent trend of initial induction followed by subsequent inhibition, while root activity was significantly suppressed (p < 0.05), ultimately impairing seedling growth. The aqueous extracts of A. philoxeroides showed a concentration-dependent inhibitory effect on the seed germination and seedling growth of Z. elegans. High concentrations of stem and leaf extracts exerted a significant inhibitory effect on seedling growth, and this growth suppression was attributed to the induction of oxidative stress by the extracts. This study elucidated the phytotoxicity degree and physiological response mechanisms underlying the biochemical allelopathy of A. philoxeroides on Z. elegans. The findings provide a theoretical foundation for the selection of horticultural plant cultivars resistant to allelopathic stress and the development of management strategies for invasive plants. Full article

Climate warming and drought often co-occur to form warm–dry climate patterns. However, systematic comparative studies of the responses of invasive plants from different families to their combined effects remain limited. We conducted a greenhouse experiment to investigate the interactive effects of warm (normal vs. warming) and drought (well-watered vs. drought) conditions on the growth, root traits, and competitive performance of 11 invasive plant species from three families (Amaranthaceae, Poaceae, and Asteraceae) growing in competition with native communities. Our results showed that warming did not significantly increase the total biomass of all invasive species combined but significantly promoted biomass accumulation in Poaceae and Asteraceae. Drought consistently reduced the biomass across all invasive species. Notably, a marginally significant interaction effect of warm and drought conditions on the biomass proportion of Amaranthaceae was detected. Specifically, under normal conditions, drought increased the biomass proportion of Amaranthaceae species, whereas under the warming treatment, drought decreased it. Furthermore, root traits of invasive species exhibited clear family level differentiation. Poaceae adopted an expansion strategy by increasing root length and root surface area under warming treatment, Amaranthaceae exhibited a contraction strategy by reducing root investment under drought treatment, and Asteraceae displayed an efficient strategy with increased specific root length under drought treatment. Except for the biomass proportion of Amaranthaceae, no significant interactive effects were found for most other parameters, indicating that the combined effects of warming and drought were primarily additive. Our results revealed that warm, dry climates influence invasive plants in a taxon-specific manner, with different families employing distinct root trait adjustment strategies in response to environmental stress. These findings highlight the importance of family level comparative studies for predicting invasion dynamics and developing targeted management strategies for future climate scenarios. Full article

Background: Guided endodontics (GE), introduced in 2016, is an innovative approach aimed at addressing the challenges faced in endodontic treatment, particularly in cases of pulp canal obliteration (PCO). Objectives: This narrative review aims to assess the efficacy and application of static guided endodontics to facilitate minimally invasive access to difficult-to-locate root canals during primary endodontic treatment of incisors and canines. Method: A search strategy of the literature was performed on PubMed until 18 November 2025. The review synthesizes findings from 28 studies, focusing on recent advancements, procedural planning, and clinical outcomes related to GE. Results: Key findings indicate that GE may improve the ability to locate and treat calcified canals, reduce complications associated with traditional methods. Radiographic assessments and clinical indicators demonstrate favorable short- to medium-term outcomes; however, there is an absence of standardized protocols for long-term follow-up. Conclusions: Recommendations for future research include the establishment of unified technical guidelines to enhance consistency and comparability of results across clinical settings. Overall, guided endodontics represents a promising advancement in improving the success of root canal therapy while preserving natural dentition. The primary goal of this article is to update the literature review on static guided endodontics in anterior teeth during primary endodontics. Full article

Myo-inositol (MI) is recognized as a potential stress regulator capable of alleviating abiotic stress. The objective of this study is to analyze the role of MI in the salt stress response of Daucus carota L. and its potential mechanisms. “Hongxin Qicun” carrot seedlings were subjected to five treatments: control; salt stress (50 mM NaCl); and salt stress combined with 50, 100, or 200 μM of MI. Through an integrated approach combining physiological assays, non-invasive micro-test technology (NMT), and gene expression profiling, we found that salt stress severely inhibited seedling growth, disrupted K⁺/Na⁺ homeostasis, and triggered excessive H₂O₂ accumulation. Exogenous MI application mitigated these salt-induced damages, with 100 μM MI exerting the optimal effect. MI enhanced Na⁺ efflux and reduced K⁺ efflux in carrot roots under salt stress. Inhibitor experiments indicated that MI-promoted Na⁺ efflux relies on active transport via the plasma membrane (PM) Na⁺/H⁺ antiporter system, and qRT-PCR analysis showed that this response was accompanied by the upregulation of DcSOS1. Furthermore, MI contributes to K⁺ homeostasis by synergistically modulating PM H⁺-ATPase and high-affinity potassium transporters. The established proton gradient helps reduce salt-induced K⁺ loss through depolarization-activated potassium channels and non-selective cation channels. MI treatment decreased electrolyte leakage, malondialdehyde content, and H₂O₂ accumulation by enhancing the activities of the plant antioxidant defense system. Meanwhile, MI upregulated the expression of myo-inositol oxygenase (DcMIOXs) genes, which may contribute to osmotic balance maintenance and facilitate ROS scavenging. In conclusion, exogenous MI alleviates salt-induced physiological disorders in Daucus carota L. by coordinately regulating K⁺/Na⁺ and ROS homeostasis, with 100 μM identified as the optimal concentration for this effect. Full article

Respiration rate (RR) is a key physiological indicator of health, stress, and thermoregulatory load in dairy cattle, yet continuous RR monitoring under commercial farm conditions remains challenging. In this Technical Note, we present a non-invasive clip-on nose ring device for continuous respiration monitoring based on acoustic recording directly at the nostril. The device integrates a MEMS microphone, embedded electronics, battery, and removable storage in a sealed, mechanically robust housing suitable for real-world barn environments. The system was deployed on five dairy cows under commercial farm conditions, enabling repeated multi-day recordings over several weeks. The respiration rate was extracted offline from raw audio using a deterministic signal-processing pipeline based on multiscale periodicity detection. Algorithm-derived RR estimates were evaluated against manually annotated breath events. Using 10-min rolling median values, the algorithm achieved a mean absolute error (MAE) of 1.47 breaths per minute (bpm), a root mean square error (RMSE) of 1.92 bpm, and a high correlation with reference values (r = 0.98, R² = 0.96). In addition to short-term accuracy, the system enabled stable multi-day monitoring. Group-level analysis across all five animals revealed a clear diurnal respiration pattern over multiple consecutive days, with lower RR during nighttime and higher RR during daytime summer conditions, without signs of a baseline drift. These results demonstrate the feasibility of continuous, long-term respiration monitoring in dairy cattle using an audio-based clip-on nose ring device and provide a practical foundation for longitudinal (multi-day, within-animal) RR assessment under commercial farm conditions, with potential for future extensions towards advanced respiratory health monitoring. While the system demonstrated stable performance under summer farm conditions, validation under extreme heat-stress environments and larger animal cohorts is required for comprehensive population-level assessment. Full article

The carnauba palm trees in the Caatinga ecosystem, in Northeast Brazil, have been impacted by invasive species, particularly in areas subject to flooding. This study aimed to evaluate morphological, physiological, and nutritional responses of Copernicia prunifera (native) and Cryptostegia madagascariensis (invasive) seedlings exposed to flooding stress. The experiment was conducted in a randomized complete block design, with a split-plot arrangement and five replicates. The treatments were formed by two species and five periods of flood stress (0, 8, 12, 16, and 20 days). Flooding significantly reduced shoot dry mass in both species; however, the reduction was more pronounced in the invasive species (27%) compared to the native palm (20%). The invasive species showed strong use of resources, with higher values for leaf mineral nutrient, net photosynthesis, growth rate, and leaf area, regardless of the water regime. Under flooding, the invasive species produced adventitious roots, and the net photosynthetic rate was less impacted, despite greater sodium accumulation in the leaves. The results indicate that the characteristics of C. prunifera, such as slow growth rate, low specific leaf area, and morphological adaptations of the root system, may ensure greater stability in net carbon assimilation in the whole plant under flooding. However, the rapid growth and high absorption of soil resources of C. madagascariensis pose a significant threat to the establishment of C. prunifera seedlings, directly jeopardizing the long-term renewal of carnauba palm groves in the Caatinga ecosystem. Full article

Endophytes are a type of microorganism that lives in harmony with plants, playing a significant role in promoting the growth of the host and enhancing the host’s stress resistance. Understanding the ecological functions of root endophytic fungi and screening functional strains can effectively alleviate the stress conditions of crops. In this study, endophyte 1R13 was isolated from the roots of rice. Through morphological observation and five-gene combined phylogenetic analysis, it was identified as Bussabanomyces oryzae (B. oryzae), which was proposed as a new species, Bussabanomyces oryzae nov. The colonization pattern of B. oryzae was mainly through invasion of the rice roots, entering the epidermal cells and then the cortical cells, and finally reaching the vascular bundle cells. In the co-culture assays with rice, B. oryzae can promote the growth of rice, increasing its growth volume by approximately 23% and its fresh weight by 52%. Meanwhile, it could enhance the stress resistance of rice, mainly manifested as increasing the ability of rice leaves to resist rice blast and improving the survival rate of transplanted seedlings in the field. Full article

We investigate the use of non-invasive, dual-wavelength (630 nm red/940 nm near-infrared) LED irradiation of the skull for relieving chronic neck and shoulder pain. A low-energy device was applied bilaterally for 15 min, with assessments of pain performed using the numeric rating scale (NRS), muscle relaxation assessed via infrared thermography, and autonomic function determined through heart-rate variability (HRV) analysis. The results demonstrated a mean NRS score reduction of 2.4 points, a 0.6 °C increase in cervical skin temperature, and a significant increase in HRV’s root mean square of successive differences, indicating improved autonomic regulation. This technique shows promise for effectively relaxing muscles, alleviating pain, and enhancing autonomic function. Full article

Markerless motion capture (MMC) provides a non-invasive alternative for motion analysis; however, its validity at the standard frame rate of 25 Hz commonly used in broadcast and surveillance applications remains to be established. This study evaluated the performance of a 25 Hz multi-camera MMC workflow using consumer-grade cameras for capturing basketball-specific movements. Three highly trained male athletes completed seven tasks, including sprinting and simulated sport-specific skills, while being synchronously recorded by six MMC cameras (DJI Action 5 Pro, 25 fps) and a 10-camera Vicon system (25 Hz). Kinematic data were processed using an RTMDet–RTMPose pipeline and low-pass filtered at 6 Hz. Waveform validity was assessed using Pearson’s correlation coefficient (r) and the root mean square error (RMSE). The displacement magnitudes of 12 joints showed excellent agreement (r = 0.916–0.994; median nRMSE = 0.54–1.32%), indicating robust trajectory reconstruction. In contrast, agreement decreased for derivative variables: velocity (r = 0.583–0.867) and acceleration (r = 0.232–0.677) were highly sensitive to the low sampling rate and numerical differentiation. Although a 25 Hz configuration is insufficient for high-precision impact analysis, it provides acceptable accuracy for macroscopic displacement tracking and external-load quantification in resource-constrained training environments. Future optimization should prioritize temporal synchronization to improve the reliability of derivative variables. Full article

Respiratory rate (RR) is a critical vital sign for the early detection of hypoxia and respiratory deterioration, yet its continuous monitoring remains challenging in clinical environments. Photoplethysmography (PPG) provides a non-invasive source of physiological information from which respiratory dynamics can be inferred. In this study, numerical physiological features derived from PPG data were used to comparatively evaluate multiple deep learning models for respiratory rate estimation. Fixed-length sliding windows were constructed from the dataset and used to train five neural network architectures: a Deep Feedforward Neural Network (DFNN), unidirectional and bidirectional Recurrent Neural Networks (RNN, Bi-RNN), and unidirectional and bidirectional Long Short-Term Memory networks (LSTM, Bi-LSTM). Model performance was assessed using mean absolute error (MAE), root mean squared error (RMSE), coefficient of determination (R²), and computational runtime. Results indicate that models incorporating temporal dependencies outperform the static feedforward baseline, achieving MAE values as low as 0.521 breaths/min, making them competitive with or lower than previously reported PPG-based approaches. These findings highlight the effectiveness of temporal deep learning models for respiratory rate estimation from PPG-derived numerical features and provide insight into accuracy–efficiency trade-offs relevant to real-time monitoring applications. Full article

This study addresses the critical need for accurate, continuous monitoring of surface water quality parameters (SWQPs) using remote sensing, overcoming limitations in existing models that often rely on pre-trained networks ill-suited for complex aquatic environments. We present a customized convolutional neural network (CNN) architecture, implemented in the MATLAB environment, designed to simultaneously predict optically active (Total Organic Carbon, TOC) and non-optically active (Dissolved Oxygen, DO) parameters from eighteen Sentinel-2 Level-2A satellite images, acquired between 2023 and 2024. Our approach integrates spatial and spectral data through a customized CNN with three convolutional layers and two dense layers, optimized via adaptive learning strategies, data augmentation, and rigorous regularization to enhance predictive performance and prevent overfitting. The models were trained and validated on fused datasets of satellite imagery and in situ measurements, organized into comprehensive four-dimensional arrays capturing spectral, spatial, and sample dimensions. The results demonstrated high accuracy, with coefficient of determination (R²) values exceeding 0.97 and low root mean square error (RMSE) across training, validation, and testing subsets. Spatial prediction maps generated at high resolution revealed realistic ecological and hydrological patterns consistent with known regional water quality dynamics in New Brunswick. Our contribution, accessible to users with MATLAB, lies in the development of a transparent, adaptable, and reproducible CNN framework tailored for multiparameter water quality estimation, which extends beyond traditional empirical, site-specific regression models by enabling non-invasive, cost-effective, and continuous monitoring from satellite platforms over a large, heterogeneous province-scale domain. Additionally, model interpretability was enhanced through SHapley Additive exPlanations (SHAP) analysis, which identified key spectral bands influencing predictions and provided ecological insights, offering guidance for future sensor design and data reduction strategies. This study addresses a significant research gap by providing a dual-parameter focused, end-to-end deep learning solution optimized for province-scale remote sensing data, facilitating more informed environmental management. This study can support water managers and agencies by providing province-wide DO and TOC maps derived from freely available Sentinel-2 imagery, reducing reliance on sparse field sampling alone and helping to identify areas of low oxygen or high organic carbon. Future work will extend this framework temporally and spatially and explore hybrid CNN architectures incorporating temporal dependencies for improved generalization and accuracy. Full article

Terahertz (THz) technology is finding increasingly widespread applications in biosensing, high-speed communication, and stealth materials. Meanwhile, graphene, as a quintessential two-dimensional material, has emerged as a core component of THz devices due to its unique optoelectronic properties. However, the precise and non-destructive characterization of the complex conductivity of graphene at the microscopic scale remains a formidable challenge. Conventional measurement methods often suffer from limitations associated with contact resistance or intricate sample preparation processes. In this paper, we propose a non-invasive parameter inversion method based on deep learning. We design a tri-layer graphene-silica-copper metasurface structure featuring a central cavity and establish a high-fidelity scattering model that incorporates physical effects such as edge diffraction and multi-mode resonance. Utilizing the Radar Cross Section (RCS) data generated by this model, we train a Deep Enhanced Conductivity Predictor (DECP) network integrated with a Convolutional Block Attention Module (CBAM). Experimental results demonstrate that the proposed network can accurately reconstruct the complex conductivity of graphene from far-field RCS data. The coefficients of determination (R²) for the prediction of both real and imaginary parts exceed 0.99, with a Root Mean Square Error (RMSE) as low as the order of 10⁻⁵. This study not only validates the effectiveness of data-driven approaches in material characterization but also provides a novel paradigm for the real-time monitoring and intelligent design of terahertz metasurfaces. Full article

Non-motor symptoms (NMSs) are highly prevalent in Parkinson’s Disease (PD) and contribute significantly to disease severity, progression, and diminished quality of life. NMSs are rooted in both physiological and psychological domains and include emotional dysfunction, autonomic dysregulation, cognitive impairment, pain exacerbation, and neural deficits. While pharmacological approaches are often employed for the alleviation of non-motor symptomology, modest efficacy and adverse side effects may limit their practical utility for individuals with PD, leaving the need for the identification of complementary approaches. Music interventions have emerged as potential adjunctive therapeutic approaches that may positively modulate NMSs in both physiological and psychological domains. Physiologically, music interventions have been shown to alter autonomic activity and pain/sensory perceptions and mediate neurotransmitter release related to arousal, physical effort, and stress. Psychologically, music interventions, both passive and active, have been shown to modulate emotional regulation, motivation, attention, and cognitive performance. Emerging evidence utilizing neuroimaging and behavioral techniques further supports this and suggests music-induced benefits even in the presence of advancing neurodegeneration. Overall, findings from this narrative review suggest music may serve as a potential non-invasive adjunctive therapeutic tool to counteract PD-induced NMSs by adaptively modulating physiological and psychological processes. This narrative review aims to gather current evidence on the physiological and psychological mechanisms underlying the benefits of music and proposes potential therapeutic translation for NMSs in PD. Furthermore, current difficulties, gaps in knowledge, and needs for future research are discussed with the goal of informing directions for clinical translation. Full article

Interface interaction mechanics analysis is of great significance for robot-assisted insertion surgery in minimally invasive surgery and therapy. Previous work indicates that the accurate modeling of soft tissue puncture forces plays a crucial role in surgical planning, robotic needle insertion, and biomechanical simulation, which can give insights useful for physicians to guide and operate assisted robots. The objective of this study is to develop a dynamic multi-component force model that integrates cutting force, stiffness resistance, and frictional interaction to characterize needle–soft tissue interaction during puncture. A dynamic force model is proposed, and a lateral periodic disturbance mechanism is introduced into the simulation framework in order to enhance the robustness and realism of the model under micro-manipulation scenarios. The model has been validated using a series of controlled puncture experiments on porcine liver and renal tissues under varying insertion angles (15°, 30°, 45°) and speeds (0.5 mm/s, 1.5 mm/s, 2.5 mm/s). Corresponding finite element simulations were also conducted using ANSYS software. The agreement between simulation and experiment has been quantitatively evaluated by comparing force–depth and force–time curves, and the statistical significance of the impact of angle and speed on puncture forces has been assessed using ANOVA and Tukey’s HSD tests. Quantitative comparison demonstrated strong consistency, with the optimal case reaching a coefficient of determination (R²) value of 0.96 and Root Mean Square Error (RMSE) below 0.13 N after incorporating a 0.05 mm lateral perturbation. Statistical analysis confirmed the impact of angle and speed on puncture force responses (p < 0.05). Furthermore, comparative analysis revealed that porcine liver exhibits more consistent biomechanical behavior than renal tissue, particularly under perturbation-enhanced simulation. This study successfully establishes a dynamic multi-component force model for soft tissue puncture, validated with high fidelity against experimental data. The incorporated lateral disturbance mechanism enhanced the model’s realism. This work can provide a reliable foundation for the future design of intelligent robot-assisted puncture systems and high-fidelity simulation-based training platforms. Full article

Exploring how nitrogen deposition alters the competitive interactions between invasive plants and native plants is critical for predicting the invasion trends of invasive plants and for formulating their control strategies. In this study, the invasive plant Solanum rostratum and its native congener S. nigrum were selected as research subjects, and three different nitrogen (N) concentration treatments (N1: 50 mg·kg⁻¹, N2: 100 mg·kg⁻¹, N3: 150 mg·kg⁻¹) were set up to compare the two species in terms of growth and development, leaf nutrient utilization strategies, stress tolerance, and rhizosphere microbial community differences under competitive conditions. The results showed that the biomass of S. rostratum was 1.4 to 2.3 times that of S. nigrum; the former had a lower root–shoot ratio and a larger crown width, enabling it to seize more living space and light resources. Across all nitrogen treatments, the net photosynthetic rate of S. rostratum leaves was significantly higher than that of S. nigrum, reflecting a stronger carbon sequestration capacity. With the increase in soil nitrogen concentration, the malondialdehyde content in S. rostratum leaves showed a decreasing trend; meanwhile, its leaf soluble sugar and catalase contents were 3.5 to 4.3 times and 1.5 to 2.5 times those of S. nigrum, respectively, indicating a lower oxidative stress level and higher stress tolerance in S. rostratum. The leaf C/P and C/N ratios of S. rostratum increased with the rise in soil N, demonstrating a higher nutrient use efficiency, while the decrease in leaf phosphorus (P) content might be attributed to the element dilution effect caused by the rapid plant growth. In addition, the diversity and stability of the rhizosphere microbial community of S. rostratum gradually increased with increasing soil N and were significantly higher than those of S. nigrum. The rhizosphere-recruited microbes of the genera Comamonas and Chryseobacterium may help promote its root nutrient absorption and thus enhance its competitive ability. Collectively, our findings reveal that under exogenous N application, S. rostratum gains a significant growth advantage over S. nigrum, which is attributed to its stronger capacities for carbon assimilation and spatial resource acquisition, a nutrient strategy characterized by low acquisition and high utilization, as well as a stable and diverse rhizosphere microbial community. Full article