Search Results (608)

CRISPR (clustered regularly interspaced short palindromic repeats)-Cas (CRISPR-associated protein) nucleases enable precise genome editing, but off-target cleavage remains a critical challenge. Here, we report the development of MAD7_HF, a high-fidelity variant of the MAD7 nuclease engineered through a bacterial screening system leveraging the DNA gyrase-targeting toxic gene ccdB. This system couples survival to efficient on-target cleavage and minimal off-target activity, mimicking the transient action required for high-precision editing. Through iterative selection and sequencing validation, we identified MAD7_HF, harboring three substitutions (R187C, S350T, K1019N) that enhanced discrimination between on- and off-target sites. In Escherichia coli assays, MAD7_HF exhibited a >20-fold reduction in off-target cleavage across multiple mismatch contexts while maintaining on-target efficiency comparable to wild-type MAD7. Structural modeling revealed that these mutations stabilize the guide RNA-DNA hybrid at on-target sites and weaken interactions with mismatched sequences. This work establishes a high-throughput bacterial screening strategy that allows the identification of Cas12a variants with improved specificity at a given target site, providing a useful framework for future efforts to develop precision genome-editing tools. Full article

Background. Automatic detection of Sit phases in people with Parkinson’s disease (PD) using a single body-worn sensor is crucial for enhancing long-term, home-based monitoring of mobility. Aim. The aim of this study was to enhance the accuracy of detecting and segmenting Sit phases in people with PD using a single SmartWatch worn at the ankle. Method. Twenty-two patients living with PD performed activities of daily living that incorporate repeated transitions to a seated position in a simulated free-living environment during 3 min, 4 min, and 5 min trials. Tri-axial accelerations and angular velocities of the right or left ankle were recorded at 50 Hz using a SmartWatch. Random forest algorithms were trained using raw and filtered data to automatically detect and segment Sit phases. Sensibility, specificity, and F-scores were calculated based on manual segmentation using the OptiTrack motion capture system. Results. Sensibility, specificity, and F-score achieved 78.3%, 93.8%, and 84.7% for Sit phase detection of the 3 min trial; 78.8%, 85.5%, and 80.6% for Sit phase detection of the 4 min trial; and 71.6%, 84.8%, and 75.6% for Sit phase detection of the 5 min trial. The median time difference between the manual and automatic segmentation was 0.95s, 0.89s, and 0.84s, respectively, for the 3 min, 4 min, and 5 min trial. Conclusion. This study demonstrates that a random forest algorithm can accurately detect and segment Sit phases in people with PD using data from a single ankle-worn SmartWatch. The algorithm’s performance was comparable to manual segmentation, while substantially reducing the time and effort required. These findings represent a meaningful step forward in enabling efficient, long-term, and home-based monitoring of mobility and symptom progression in people with PD. Full article

Background/Objectives: The recent development of four-dimensional X-ray velocimetry (4DXV) technology (three-dimensional space and time) provides a unique opportunity to obtain preclinical quantitative functional lung images. Only single-scan measurements in non-survival studies have been obtained to date; thus, methodologies enabling animal survival for repeated imaging to be accomplished over weeks or months from the same animal would establish new opportunities for the assessment of pathophysiology drivers and treatment response in advanced preclinical drug-screening efforts. Methods: An anesthesia protocol developed for animal recovery to allow for repetitive, longitudinal scanning of individual animals over time. Test–retest imaging scans from the lungs of healthy mice were performed over 8 weeks to assess the repeatability of scanner-derived quantitative imaging metrics and variability. Results: Using a murine model of fibroproliferative lung disease, this longitudinal scanning approach captured heterogeneous progressive changes in pulmonary function, enabling the visualization and quantitative measurement of averaged whole lung metrics and spatial/regional change. Radiation dosimetry studies evaluated the effects of imaging acquisition protocols on X-ray dosage to further adapt protocols for the minimization of radiation exposure during repeat imaging sessions using these newly developed image acquisition protocols. Conclusions: Overall, we have demonstrated that the 4DXV advanced imaging scanner allows for repeat measurements from the same animal over time to enable the high-resolution, noninvasive mapping of quantitative lung airflow dysfunction in mouse models with heterogeneous pulmonary disease. The animal anesthesia and image acquisition protocols described will serve as the foundation on which further applications of the 4DXV technology can be used to study a diverse array of murine pulmonary disease models. Together, 4DXV provides a novel and significant advancement for the longitudinal, noninvasive interrogation of pulmonary disease to assess spatial/regional disease initiation, progression, and response to therapeutic interventions. Full article

Cyperus esculentus is a very destructive perennial weed, rapidly propagating and spreading through large amounts of daughter tubers. Successful control relies on depleting the soil tuber bank. This study investigated the effect of different control measures, applied across several cropping systems, on tuber bank dynamics over time. Therefore, 52 infested fields were monitored over 3 consecutive years, with annual quantification of the C. esculentus tuber bank. In maize monocropping systems, substantial 3-year tuber bank reductions (>90%) are achievable with preplant incorporation of dimethenamid-P or S-metolachlor, followed by a post-emergence application of mesotrione and pyridate at the 4–5 leaf stage, combined with delayed sowing (after 20 May) or mechanical measures (e.g., hoeing, harrowing). On non-maize fields, effective strategies (median tuber bank reductions of 57–70%) include intensive black fallow with at least four control timings or winter cereal cropping followed by intensive control (at least three measures) during the stubble phase. Established, fertilized grasslands also offer moderate reductions (17–67%) via intensive grazing or mowing. These results demonstrate that significant C. esculentus reductions are possible across different crops, but control remains challenging, requiring intensive, repeated strategies over multiple years. Less intensive approaches may undermine previous efforts. Full article

High-precision spiral trajectory tracking for aquaculture net-cage inspection is hindered by uncertain hydrodynamics, strong coupling, and time-varying disturbances acting on an underactuated autonomous underwater vehicle. This paper adapts and validates a model–data-driven learning-aided adaptive robust control strategy for the specific challenge of high-precision spiral trajectory tracking for aquaculture net-cage inspection. At the kinematic level, a serial iterative learning feedforward compensator is combined with a line-of-sight guidance law to form a feedforward-compensated guidance scheme that exploits task repeatability and reduces systematic tracking bias. At the dynamic level, an integrated adaptive robust controller employs projection-based, rate-limited recursive least-squares identification of hydrodynamic parameters, along with a composite feedback law that combines linear error feedback, a nonlinear robust term, and fast dynamic compensation to suppress lumped uncertainties arising from estimation error and external disturbances. A Lyapunov-based analysis establishes uniform ultimate boundedness of all closed-loop error signals. Simulations that emulate net-cage inspection show faster convergence, higher tracking accuracy, and stronger robustness than classical adaptive robust control and other baselines while maintaining bounded control effort. The results indicate a practical and effective route to improving the precision and reliability of autonomous net-cage inspection. Full article

Background: In an increasingly digital marketplace, social media marketing activities (SMMAs) have become vital for building consumer–brand relationships, particularly among Generation Z (Gen Z) consumers. Coffee shops offer a unique context because they are lifestyle-oriented and highly dependent on repeat visits, making them especially responsive to digital engagement. This study examines the impact of SMMAs on brand loyalty in the Saudi Arabian coffee shop sector, with a particular focus on the mediating role of consumer brand preference and the moderating role of brand awareness. Drawing on the Stimulus–Organism–Response (S-O-R) framework and Generational Marketing Theory, the research explores how Gen Z consumers respond to social media efforts that are informative, interactive, trendy, and personalized. Methods: Data were collected using convenience sampling via an online survey of 412 Gen Z consumers in Saudi Arabia who follow at least one local or international coffee shop brand on social media. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to test the hypothesized relationships, mediation, and moderation effects. Results: The findings revealed that SMMAs have a substantial direct effect on both brand loyalty and consumer brand preference. Moreover, consumer brand preference partially mediates the relationship between SMMAs and brand loyalty, underscoring its importance as a psychological mechanism in the formation of loyalty. Additionally, brand awareness was found to significantly moderate the SMMAs–brand loyalty relationship, with more potent effects observed among consumers with higher levels of brand familiarity. Implications: The study contributes theoretically by extending the S-O-R framework with Generational Marketing Theory, demonstrating the partial mediating role of brand preference and the moderating direct effect of brand awareness. Practically, the results suggest that coffee shop marketers should design social media strategies that are informative, interactive, trendy, and personalized while also investing in awareness-building campaigns to amplify loyalty among Gen Z consumers. Full article

This study investigated the influence of aerobic capacity on lactate clearance rate and heart rate recovery during ice hockey matches. Considering the growing intensity and anaerobic demands of modern ice hockey, the ability to recover quickly between high-intensity shifts is essential for optimal performance. Thirty-eight amateur ice hockey players (age: 35 ± 5 years; VO₂max: 48.93 ± 3.88 mL·min⁻¹·kg⁻¹) from the Silesian Amateur Hockey League underwent laboratory ramp tests to determine VO₂max, followed by on-ice repeated sprint tests and heart rate monitoring during matches. The results demonstrated significant positive correlations between VO₂max and lactate clearance (ΔLa4–8min [mmol/L]= 2.55 ± 0.58 mmol·L⁻¹; rho = 0.545; p < 0.001), as well as heart rate recovery (Δ%HRmax = 25.88 ± 2.09%; rho = 0.682; p < 0.001). Players with higher VO₂max exhibited a faster reduction in heart rate during recovery periods between shifts and maintained better sprint performance (rho = –0.877; p < 0.001). These findings confirm that higher aerobic capacity enhances both metabolic and autonomic recovery processes, enabling players to sustain high-intensity efforts more effectively during the game. The study highlights the importance of developing aerobic fitness in hockey training to improve recovery efficiency and match performance. Full article

Camphora officinarum Nees constitutes a pivotal tree species within the evergreen broad-leaved forests of East Asia, endowed with significant economic, ornamental, and ecological importance. Nevertheless, previous research has markedly underestimated the genetic diversity of this species, thereby hindering our efforts in conserving resources and enhancing genetic breeding. The current study generated 155 chloroplast genomes from specimens of C. officinarum obtained from six provinces/regions in China. The results reveal the identification of seven distinct clades (I–VII), with Clades II, III, V, and VII exhibiting genome expansions, primarily influenced by lineage-specific elongation of inverted repeats (IRs), whereas Clades I, IV, and VI maintained conserved IR lengths. Despite the structural plasticity, the GC content remained highly conserved. Geographic patterns indicated gene flow between adjacent regions (e.g., Hunan and Hubei with identical IR lengths), but genetic isolation in Fujian. High-polymorphism regions (psba-matK, ycf1, ycf2, and ndhF) were identified as superior phylogenetic markers, enhancing intraspecies-level resolution. Simple sequence repeats (SSRs) varied significantly among clades, dominated by A/T-rich mononucleotide repeats. These repeats, along with divergent repeat types (e.g., absence of reverse repeats in Clades V/VI), serve as robust tools for resource identification and evolutionary trajectory inference. Phylogenetically, samples from Fujian formed a distinct lineage, while samples from other regions, especially Guangdong, were mixed, with this finding probably being a reflection of historical cultivation and anthropogenic translocation. This study offers a framework for the genetic breeding and investigation of the evolutionary history of C. officinarum. Full article

Tryptophan (Trp) and tryptamine (Tryp), critical biomarkers in mood regulation, immune function, and metabolic homeostasis, are increasingly recognized for their roles in both oral and systemic pathologies, including neurodegenerative disorders, cancers, and inflammatory conditions. Their rapid, sensitive detection in biofluids such as saliva—a non-invasive, real-time diagnostic medium—offers transformative potential for early disease identification and personalized health monitoring. This review synthesizes advancements in electrochemical sensor technologies tailored for Trp and Tryp quantification, emphasizing their clinical relevance in diagnosing conditions like oral squamous cell carcinoma (OSCC), Alzheimer’s disease (AD), and breast cancer, where dysregulated Trp metabolism reflects immune dysfunction or tumor progression. Electrochemical platforms have overcome the limitations of conventional techniques (e.g., enzyme-linked immunosorbent assays (ELISA) and mass spectrometry) by integrating innovative nanomaterials and smart engineering strategies. Carbon-based architectures, such as graphene (Gr) and carbon nanotubes (CNTs) functionalized with metal nanoparticles (Ni and Co) or nitrogen dopants, amplify electron transfer kinetics and catalytic activity, achieving sub-nanomolar detection limits. Synergies between doping and advanced functionalization—via aptamers (Apt), molecularly imprinted polymers (MIPs), or metal-oxide hybrids—impart exceptional selectivity, enabling the precise discrimination of Trp and Tryp in complex matrices like saliva. Mechanistically, redox reactions at the indole ring are optimized through tailored electrode interfaces, which enhance reaction kinetics and stability over repeated cycles. Translational strides include 3D-printed microfluidics and wearable sensors for continuous intraoral health surveillance, demonstrating clinical utility in detecting elevated Trp levels in OSCC and breast cancer. These platforms align with point-of-care (POC) needs through rapid response times, minimal fouling, and compatibility with scalable fabrication. However, challenges persist in standardizing saliva collection, mitigating matrix interference, and validating biomarkers across diverse populations. Emerging solutions, such as AI-driven analytics and antifouling coatings, coupled with interdisciplinary efforts to refine device integration and manufacturing, are critical to bridging these gaps. By harmonizing material innovation with clinical insights, electrochemical sensors promise to revolutionize precision medicine, offering cost-effective, real-time diagnostics for both localized oral pathologies and systemic diseases. As the field advances, addressing stability and scalability barriers will unlock the full potential of these technologies, transforming them into indispensable tools for early intervention and tailored therapeutic monitoring in global healthcare. Full article

Background: Mixed martial arts (MMA) requires athletes to generate repeated bursts of high-intensity effort with minimal recovery time. Despite the sport’s reliance on anaerobic power, there are minimal data assessing pre-competition physiological capacity in MMA fighters. This study aimed to evaluate anaerobic performance using the Wingate Anaerobic Test (WAnT) and Countermovement Jump (CMJ) in professional MMA athletes, and to examine relationships between performance metrics across weight classes. Methods: Twelve professional male MMA fighters (age 29.00 ± 4.80 years, weight 85.60 ± 13.90 kg) completed both CMJ and WAnT assessments using sensor-integrated devices (Just Jump mat and Wattbike Pro). CMJ height and WAnT variables (peak power, average power, and fatigue index) were measured. Pearson correlations were used to examine the relationships between CMJ and Wingate outputs. Independent t-tests compared performance between lighter (<83.9 kg) and heavier (≥83.9 kg) weight groups. Results: CMJ performance showed significant positive correlations with both average power (r = 0.71, p < 0.001) and peak power (r = 0.61, p = 0.004). Peak power was also positively correlated with fatigue index (r = 0.84, p < 0.001), suggesting greater fatigue in higher power-producing athletes. Finally, the heavier weight group of fighters produced significantly (p = 0.03) more peak power when compared to the lighter weight group. Conclusions: The findings support the use of CMJ and WAnT testing as practical tools for evaluating anaerobic performance in MMA athletes. These assessments can help guide individualized training strategies, particularly when accounting for weight group specific differences in power and fatigue dynamics. Full article

Optimal sensing devices exhibit a combination of key performance attributes, including an extensive detection limit, exceptional selectivity, high sensitivity, consistent repeatability, precise measurement, and rapid response times with efficient analyte flow. In recent years, biosensing platforms incorporating nanoscale materials have garnered considerable attention due to their diverse applications across various scientific and technological domains. The integration of nanoparticles (NPs) in biosensor design primarily bridges the dimensional gap between the signal transduction element and the biological recognition component, both of which operate at nanometer scales. The synergistic combination of NPs with electrochemical techniques has facilitated the development of biosensors characterized by enhanced sensitivity and superior analyte discrimination capabilities. This comprehensive analysis examines the evolution and recent advancements in nanomaterial (NM)-based biosensors, encompassing an extensive array of nanostructures. These consists of one-dimensional nanostructures including carbon nanotubes (CNTs), nanowires (NWs), nanorods (NRs), and quantum dots (QDs), as well as noble metal and metal and metal oxide nanoparticles (NPs). The article examines how advancements in biosensing techniques across a range of applications have been fueled by the growth of nanotechnology. Researchers have significantly improved biosensor performance parameters by utilizing the distinct physiochemical properties of these NMs. The developments have increased the potential uses of nanobiosensors in a wide range of fields, from food safety and biodefense to medical diagnostics and environmental monitoring. The continuous developments in NM-based biosensors are the result of the integration of several scientific areas, such as analytical chemistry, materials science, and biotechnology. This interdisciplinary approach continues to drive innovations in sensor design, signal amplification strategies, and data analysis techniques, ultimately leading to more sophisticated and capable biosensing platforms. As the field progresses, challenges related to the scalability, reproducibility, and long-term stability of nanobiosensors are being addressed through innovative fabrication methods and surface modification techniques. These efforts aim to translate the promising results observed in laboratory settings into practical, commercially viable biosensing devices that can address real-world analytical challenges across various sectors. Full article

Laser Powder Bed Fusion (LPBF) has emerged as a leading additive manufacturing (AM) process for producing complex metal components. Despite its advantages, the inherent LPBF process complexity leads to challenges in achieving consistent quality and repeatability. To address these concerns, recent research efforts have focused on sensor fusion techniques for process monitoring, and on developing more elaborate control strategies. Sensor fusion combines information from multiple in situ sensors to provide more comprehensive insights into process characteristics such as melt pool behavior, spatter formation, and layer integrity. By leveraging multimodal data sources, sensor fusion enhances the detection and diagnosis of process anomalies in real-time. Closed-loop control systems may utilize this fused information to adjust key process parameters–such as laser power, focal depth, and scanning speed–to mitigate defect formation during the build process. This review focuses on the current state-of-the-art in sensor fusion monitoring and control strategies for LPBF. In terms of sensor fusion, recent advances extend beyond CNN-based approaches to include graph-based, attention, and transformer architectures. Among these, feature-level integration has shown the best balance between accuracy and computational cost. However, the limited volume of available experimental data, class-imbalance issues and lack of standardization still hinder further progress. In terms of control, a trend away from purely physics-based towards Machine Learning (ML)-assisted and hybrid strategies can be observed. These strategies show promise for more adaptive and effective quality enhancement. The biggest challenge is the broader validation on more complex part geometries and under realistic conditions using commercial LPBF systems. Full article

Post-exertional malaise (PEM) is a defining symptom of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS), yet its molecular underpinnings remain elusive. This study investigated the temporal–longitudinal DNA methylation changes associated with PEM using a structured two-day maximum repeated effort cardiopulmonary exercise testing (CPET) protocol involving pre- and two post-exercise blood samplings from five ME/CFS patients. Cardiopulmonary measurements revealed complex heterogeneous profiles among the patients compared to typical healthy controls, and VO₂ peak indicated all patients had poor normative fitness. The switch to anaerobic metabolism occurred at a lower workload in some patients on Day Two of the test. Reduced Representation Bisulphite Sequencing followed by analysis with Differential Methylation Analysis Package-version 2 (DMAP2) identified differentially methylated fragments (DMFs) present in the DNA genomes of all five ME/CFS patients through the exercise test compared with ‘before exercise’. With further filtering for >10% methylation differences, there were early DMFs (0–24 h after first exercise test) and late DMFs between (24–48 h after the second exercise test), as well as DMFs that changed gradually (between 0 and 48 h). Of these, 98% were ME/CFS-specific, compared with the two healthy controls accompanying the longitudinal study. Principal component analysis illustrated the three distinct clusters at the 0 h, 24 h, and 48 h timepoints, but with heterogeneity among the patients within the clusters, highlighting dynamic methylation responses to exertion in individual patients. There were 24 ME/CFS-specific DMFs at gene promoter fragments that revealed distinct patterns of temporal methylation across the timepoints. Functional enrichment of ME-specific DMFs revealed pathways involved in endothelial function, morphogenesis, inflammation, and immune regulation. These findings uncovered temporally dynamic epigenetic changes in stress/immune functions in ME/CFS during PEM and suggest molecular signatures with potential for diagnosis and of mechanistic significance. Full article

Accurate and reliable characterization of current transformer (CT) performance is essential for maintaining grid stability and power quality in modern electrical networks. CT measurements are key to effective monitoring of harmonic distortions, supporting regulatory compliance and ensuring the safe operation of the grid. This paper addresses a method for the characterization of CTs across an extended frequency range from 50 Hz up to 150 kHz, driven by increasing power quality issues introduced by renewable energy installations and non-linear loads. Traditional CT calibration approaches involve measurement setups that offer ppm-level uncertainty but are complex to operate and limited in practical frequency range. To simplify and expand calibration capabilities, a calibration system employing a sampling ammeter (power analyzer) was developed, enabling the direct measurement of CT secondary currents of an unknown CT and a reference CT without any further auxiliary equipment. The resulting expanded magnitude ratio uncertainties for the wideband CT calibration system are 10 ppm ($k=2$) up to 10 kHz and less than 120 ppm from 10 kHz to 150 kHz; these uncertainties do not include the uncertainty of the reference CT. Additionally, the operational conditions and setup design choices, such as instrument warm-up duration, grounding methods, measurement shunt selection, and cable type, were evaluated for their impact on measurement uncertainty and repeatability. The results highlight the significance of minimizing parasitic impedances at higher frequencies and maintaining consistent testing conditions. The developed calibration setup provides a robust foundation for future standardization efforts and practical guidance to characterize CT performance in the increasingly important supraharmonic frequency range. Full article

Background: Major depression is a significant source of suffering and economic loss. Despite efforts to understand this condition and find better treatments, the burden imposed by this disease continues to rise. Most approved pharmacological treatments for depression focus on controlling the availability of monoamines in synapses. However, accumulating evidence suggests that neuroinflammation, oxidative stress, and reduced hippocampal neurogenesis play key roles as causal factors in the development of major depression symptoms. Therefore, preclinical testing of pharmacological approaches targeting these factors is essential. Mesenchymal stem cells (MSCs) are known for their potential as powerful antioxidants and anti-inflammatory agents, exerting neuroprotective actions in the brain. They produce various therapeutic molecules in a paracrine manner, collectively known as secretome. Methods: In this work, we evaluated the antidepressant potential of repeated intranasal administration of MSC-derived secretome in an animal model of major depressive disorder induced by chronic mild unpredictable stress. Results: We observed that intranasal administration of MSC-derived secretome reduced the appearance of some of the behavioral parameters commonly associated with major depression, including anhedonic, apathetic, and anxious behaviors, inducing a strong reduction in the overall depression score compared to vehicle-treated animals. At the structural level, secretome administration prevented increased astrocyte density and the atrophy of astrocyte processes observed in vehicle-treated stressed animals. Additionally, secretome administration induced an increase in myelin levels and oligodendroglia in the cortex. Conclusions: Our data suggests that intranasal administration of MSC-derived secretome may represent a potential therapeutic alternative to current treatments for this devastating pathology. Full article