Search Results (5,952)

The CRISPR-Cas9 system has transformed biomedical research by enabling precise genetic modifications. However, efficient delivery of CRISPR components remains a major hurdle for therapeutic applications. To address this, we employed a new modified cationic hyper-branched cyclodextrin-based polymer (Ppoly) system to deliver an integrating GFP gene using the TILD-CRISPR method, which couples donor DNA linearization with RNP complexes. The physicochemical properties, loading efficiency, and cellular uptake of RNP with Ppoly were studied. After transfection, antibiotic selection and single-cell cloning were performed. Junction PCR was then performed on the isolated clones, and we compared the knock-in efficiency of Ppoly with that of the commercial CRISPRMAX™ reagent (Thermo Fisher, Invitrogen™, Waltham, MA, USA). The results demonstrate the encapsulation efficiency of over 90% for RNP and Ppoly, and cell viability remaining above 80%, reflecting the minimal toxicity of this approach. These attributes facilitated successful GFP gene integration using the TILD-CRISPR with RNP delivered via cyclodextrin-based nanosponges. The present method achieved a remarkable 50% integration efficiency in CHO-K1 cells, significantly outperforming the 14% observed with CRISPRMAX™ while maintaining lower cytotoxicity. This study highlights a promising platform for precise and efficient genome editing, with strong potential for therapeutic and regenerative medicine applications. Full article

Background and Objectives: Therapeutic goals for ulcerative colitis (UC) have expanded beyond symptom control to include mucosal and histological healing. However, the long-term prognostic value of achieving both targets remains uncertain, particularly in Asian populations. This study aimed to evaluate long-term outcomes and relapse predictors in patients with UC who achieved both endoscopic and histologic remission. Materials and Methods: This prospective observational study consecutively enrolled adults with clinically inactive UC who attained endoscopic remission (Mayo endoscopic subscore = 0) and histologic remission (Nancy index ≤1) between June 2014 and May 2018. Demographic, clinical, and laboratory data—including fecal calprotectin—were collected. Clinical relapse was defined as a Mayo score increase >3 or initiation of systemic corticosteroids or biologics. Patients were followed longitudinally for a median of 55 months (minimum 12 months), and relapse risk was evaluated using Kaplan–Meier and univariate Cox regression analyses. Results: A total of 41 patients were included (mean age 54 ± 14 years; 56% male). The median follow-up was 54 months (range 17–78). Ten patients (24.4%) relapsed during follow-up, with cumulative relapse rates of 9.8%, 10.3%, 15.8%, and 24.1% at 12, 24, 36, and 48 months, respectively. Kaplan–Meier analyses demonstrated significantly higher relapse in patients with non-E1 disease (E2 + E3, p = 0.021), immunomodulator use (p = 0.008), and biologics use (p = 0.007). In univariate Cox regression, immunomodulator (HR 4.7, 95% CI 1.3–16.4, p = 0.02) and biologics use (HR 4.9, 95% CI 1.4–17.5, p = 0.01) were significant predictors of relapse, whereas disease extent showed only a non-significant trend with wide CIs. Baseline fecal calprotectin was higher in the relapse group (182 ± 370 μg/g vs. 108 ± 164 μg/g) but was not statistically significant. Conclusions: Approximately one-quarter of UC patients who achieved dual remission relapsed within 4 years. These findings highlight the limitations of using dual remission as the sole therapeutic endpoint and underscore the need for additional prognostic factors. High-risk subgroups—such as those with extensive disease or prior exposure to advanced therapies—may require closer monitoring and individualized strategies. Future multicenter studies integrating clinical, endoscopic, histologic, and biomarker data are needed to refine relapse prediction. Full article

This study evaluated the inclusion of increasing levels of xylanase in reduced-energy diets for commercial laying hens. A total of 280 Lohmann LSL white laying hens were equally allocated one of five dietary treatments, with seven replicates of eight hens each being a positive control: a wheat and soybean meal-based diet (PC, ME 2725 kcal/kg), a negative control diet (NC, PC minus 100 kcal) and three diets with increasing xylanase levels of 50, 100 and 150 g/MT (NC + XM50, NC + XM100 and NC + XM150, respectively). The hens were monitored from 20 to 40 weeks of age to assess productive performance, egg quality and intestinal health, including histomorphometry, permeability and microbiota composition. Xylanase inclusion at 50 and 100 g/MT significantly improved egg production and egg mass, as well as shell strength and thickness, while maintaining feed intake and feed conversion efficiency, while xylanase inclusion at 150 g/MT decreased egg production and egg mass. Additionally, intestinal permeability was significantly reduced, and positive changes were observed in the gut microbiota. Higher doses of xylanase (100 and 150 g/MT) increased bacterial abundance and diversity, with a greater presence of beneficial phyla such as Bacteroidota, which play an important role in gut health. There was also a reduction in Actinobacteriota, indicating a lower presence of potential pathogens. Changes in Campylobacterota, Cyanobacteria and Proteobacteria were observed, especially with the highest xylanase dose. These findings suggest that xylanase can improve laying hen performance and promote intestinal integrity and microbial balance when included in energy-reduced diets, offering a promising strategy to enhance health and productivity in commercial egg production systems. Full article

In precast concrete shear wall structures, the joints formed during the vertical connection of precast units are referred to as the “horizontal joint”. Serving as vertical connection nodes in this structure system, the construction quality of theses horizontal joints significantly influences the structural integrity. To investigate the influence of horizontal joint quality defects on the mechanical behaviour of precast concrete shear walls, three precast concrete shear wall specimens with quality defects in different regions and three control specimens were designed. Quasi-static tests under a constant axial load were conducted to investigate the effects of defect area, location and other factors on the mechanical behaviour of the walls. Results demonstrate that the quality defects in horizontal joints significantly affect the mechanical behaviour of precast concrete shear walls. When the ratio of the quality defect area to the cross-sectional area of the boundary member reaches 100%, the yield load and peak load of the precast concrete shear wall decrease by 13% and 20%, respectively. Additionally, the structural stiffness exhibited a 13% degradation at a drift angle of 1/1000. Although the failure mode remains largely unchanged, yielding of longitudinal reinforcement in the boundary members is observed. Moreover, as the proportion of the quality defect area to the cross-sectional area decreases, its adverse effects on the mechanical behaviour of the precast concrete shear wall gradually diminish. The established numerical analysis model is shown to be reasonable and reliable. When the defective area of the horizontal joints is less than 25% of the total cross-sectional area, the quality defects essentially have no influence on the mechanical behaviour of the precast concrete shear walls. Full article

Base excision repair (BER) is an important mechanism for maintaining genomic integrity and preventing DNA damage and mutations induced by oxidative stress. This study aimed to examine the relationship between oxidative stress and BER activity in newborn piglets by supplementing their mothers’ diets during pregnancy with long-chain n-3 polyunsaturated fatty acids (PUFAs) from algal and fish oils, provided either in natural form or as nanoparticles. BER enzyme activity was assessed using a nicking assay, and their gene expression levels by RT-qPCR in the livers of pregnant gilts and their offspring. Preliminary results indicated that maternal supplementation with oils rich in long-chain n-3 PUFAs significantly reduced (by 32%) BER capacity in the livers of their offspring. A corresponding decrease in mRNA expression of BER genes (TDG, MPG, OGG1) was observed in piglets from gilts receiving fish and algal oil supplements. Maternal supplementation with long-chain n-3 PUFAs may protect foetuses and neonates against oxidative stress, reducing DNA damage and enhancing genomic stability, which could positively influence early postnatal growth. The observed reduction in BER enzyme activity in newborn piglets likely reflected improved DNA integrity, and natural oil forms appeared more effective than their nanoparticle formulations. Disparities in socioeconomic areas related to access to functional foods with health-promoting properties highlight the importance of targeted strategies that integrate local systems and promote nutritional equity. Full article

In situ process monitoring systems (IPMSs) are rapidly gaining importance in quality assurance of laser powder bed fusion (L-PBF) parts, yet standardized methods for their objective evaluation are lacking. This study introduces a novel, system-independent assessment method for IPMSs based on a specially designed Energy Step Cube (ESC) test specimen. The ESC enables systematic variation in volumetric energy density (VED) by adjusting laser scan speed, without disclosing complete process parameters. Two industrially relevant IPMSs—PrintRite3D by Divergent and Trumpf’s integrated system—were evaluated using the ESC approach with AlSi10Mg as the test material. System performance was assessed based on sensitivity to VED changes and correlation with actual porosity, determined by metallographic analysis. Results revealed significant differences in sensitivity and effective observation windows between the systems. PrintRite3D demonstrated higher sensitivity to small VED changes, while the Trumpf system showed a broader stable observation range. The study highlights the challenges in establishing relationships between IPMS signals and resulting part properties, currently restricting their standalone use for quality assurance. This work establishes a foundation for standardized IPMS evaluation in additive manufacturing, offering valuable insights for technology advancement and enabling objective comparisons between various IPMSs, thereby promoting innovation in this field. Full article

Observing and measuring public life is essential for designing inclusive, vibrant, and climate-resilient public spaces. While urban planners have traditionally relied on manual observation, recent advances in open-source Computer Vision (CV) now enable automated analysis. However, most CV sensors in urban studies focus on transportation analysis, offering limited insight into nuanced human behaviors such as sitting or socializing. This limitation stems in part from the challenges CV algorithms face in detecting subtle activities within public spaces. This study introduces the Public Life Sensor Kit (PLSK), an open-source, do-it-yourself system that integrates a GoPro camera with an NVIDIA Jetson edge device, and evaluates whether pose estimation-enhanced CV models can improve the detection of fine-grained public life behaviors, such as sitting and social interaction. The PLSK was deployed during a public space intervention project in Sydney, Australia. The resulting data were measured against data collected from the Vivacity sensor, a commercial transportation-focused CV system, and traditional human observation. The results show that the PLSK outperforms the commercial sensor in detecting and classifying key public life activities, including pedestrian traffic, sitting, and socializing. These findings highlight the potential of the PLSK to support ethically collected and behavior-rich public space analysis and advocate for its adoption in next-generation urban sensing technologies. Full article

Rising atmospheric CO₂ is expected to fertilize forest photosynthesis; yet, ecosystem-scale observations often reveal muted responses, creating a critical knowledge gap in global climate projections. In this review, we explore this paradox by moving beyond the traditional ‘CO₂ fertilization’ paradigm. We propose an integrated framework that positions elevated CO₂ as a complex modulator whose net effect is determined by a hierarchy of cross-scale constraints. At the plant level, photosynthetic acclimation acts as a universal first brake on the initial biochemical potential. At the ecosystem level, nutrient availability—primarily nitrogen in temperate/boreal systems and phosphorus in the tropics—emerges as the dominant bottleneck limiting long-term productivity gains. Furthermore, interactions with the water cycle, such as increased water-use efficiency, create state-dependent dynamic responses. By synthesizing evidence from pivotal Free-Air CO₂ Enrichment (FACE) experiments, we systematically evaluate these constraining factors. We conclude that accurately predicting the future of the forest carbon sink necessitates a paradigm shift: from single-factor analysis to multi-stressor approaches, and from ecosystem-scale observations to an integrated understanding that links these phenomena to their underlying molecular and genetic mechanisms. This review provides a roadmap for future research and informs more realistic strategies for forest management and climate mitigation in a high-CO₂ world. Full article

Background: The recently proposed Staging of Airflow Obstruction by Ratio (STAR) system classifies severity based on the FEV₁/FVC ratio, potentially offering improved prognostic performance. This study aimed to evaluate the prognostic performance of STAR in patients hospitalized for COPD exacerbation. Methods: A retrospective observational single-center study was conducted including COPD patients who were discharged after hospitalization for a severe exacerbation at a university hospital. The clinical and spirometric data in a stable condition, GOLD classification, STAR system, and mortality outcomes were recorded. Results: A total of 197 patients (23% female) were included. The follow-up was performed for a minimum of 38 months or until death if it occurred earlier. During the study period, 91 patients died (46%). Patients were distributed according to the STAR classification as follows: 21% in STAR 1, 32% in STAR 2, 28% in STAR 3, and 19% in STAR 4. The agreement between STAR and GOLD was fair (Cohen’s kappa = 0.28), with a moderate correlation (Tau-b = 0.49, p < 0.001). STAR grades 2 to 4 demonstrated progressively increasing mortality, while STAR grade 1 showed a mortality similar to grade 2. STAR showed a trend toward a superior discrimination for mortality than GOLD (AUC 0.63 [95%CI 0.55–0.71] vs. 0.55 [0.47–0.63]; p = 0.055), although BODEx remained the most accurate predictor (AUC = 0.70 [0.63–0.77]). Conclusions: The STAR system effectively stratified the mortality risk among hospitalized COPD patients across grades 2 to 4. However, STAR grade 1 failed to differentiate patients with a lower risk. Although STAR may underestimate severity in individual patients with relatively preserved ratios, its integration into clinical evaluation could enhance prognostic assessments. Full article

Background/Objectives: Artificial Intelligence (AI) is rapidly advancing in medicine, facilitating personalized care by leveraging complex clinical data, imaging, and patient monitoring. This study characterizes current practices in AI use within oncology clinical trials by analyzing completed U.S. trials within the Cancer Control Continuum (CCC), a framework that spans the stages of cancer etiology, prevention, detection, diagnosis, treatment, and survivorship. Methods: This cross-sectional study analyzed U.S.-based oncology trials registered on ClinicalTrials.gov between January 2015 and April 2025. Using AI-related MeSH terms, we identified trials addressing stages of the CCC. Results: Fifty completed oncology trials involving AI were identified; 66% were interventional and 34% observational. Machine Learning was the most common AI application, though specific algorithm details were often lacking. Other AI domains included Natural Language Processing, Computer Vision, and Integrated Systems. Most trials were single-center with limited participant enrollment. Few published results or reported outcomes, indicating notable reporting gaps. Conclusions: This analysis of ClinicalTrials.gov reveals a dynamic and innovative landscape of AI applications transforming oncology care, from cutting-edge Machine Learning models enhancing early cancer detection to intelligent chatbots supporting treatment adherence and personalized survivorship interventions. These trials highlight AI’s growing role in improving outcomes across the CCC in advancing personalized cancer care. Standardized reporting and enhanced data sharing will be important for facilitating the broader application of trial findings, accelerating the development and clinical integration of reliable AI tools to advance cancer care. Full article

The application of orchard inspection robots has become increasingly widespread. How-ever, achieving autonomous navigation in unstructured environments continues to pre-sent significant challenges. This study investigates the Simultaneous Localization and Mapping (SLAM) navigation system of an orchard inspection robot and evaluates its performance using Light Detection and Ranging (LiDAR) technology. A mobile robot that integrates tightly coupled multi-sensors is developed and implemented. The integration of LiDAR and Inertial Measurement Units (IMUs) enables the perception of environmental information. Moreover, the robot’s kinematic model is established, and coordinate transformations are performed based on the Unified Robotics Description Format (URDF). The URDF facilitates the visualization of robot features within the Robot Operating System (ROS). ROS navigation nodes are configured for path planning, where an improved A* algorithm, combined with the Dynamic Window Approach (DWA), is introduced to achieve efficient global and local path planning. The comparison of the simulation results with classical algorithms demonstrated the implemented algorithm exhibits superior search efficiency and smoothness. The robot’s navigation performance is rigorously tested, focusing on navigation accuracy and obstacle avoidance capability. Results demonstrated that, during temporary stops at waypoints, the robot exhibits an average lateral deviation of 0.163 m and a longitudinal deviation of 0.282 m from the target point. The average braking time and startup time of the robot at the four waypoints are 0.46 s and 0.64 s, respectively. In obstacle avoidance tests, optimal performance is observed with an expansion radius of 0.4 m across various obstacle sizes. The proposed combined method achieves efficient and stable global and local path planning, serving as a reference for future applications of mobile inspection robots in autonomous navigation. Full article

Background: Oral health plays a critical role in systemic wellbeing, with growing evidence supporting strong associations between oral conditions and cardiovascular disease (CVD). These connections extend beyond periodontal disease and involve oral microbiota imbalance, systemic inflammation, and oral side effects of cardiovascular pharmacotherapy. Objective: To explore these links, a narrative literature review was performed using PubMed, Scopus, and ScienceDirect, covering studies published between 2000 and 2025. Methods: A comprehensive literature search was conducted in PubMed, Scopus, and ScienceDirect for studies published between January 2000 and May 2025. Both MeSH and free-text terms related to oral health, periodontal disease, systemic inflammation, endothelial dysfunction, and atherosclerosis were used. Eligible studies included observational and interventional research, systematic reviews, and meta-analyses. Key findings: The evidence consistently supports an association between chronic periodontal inflammation and cardiovascular risk, mediated by systemic dissemination of proinflammatory cytokines (IL-6, TNF-α, CRP) and microbial products that promote endothelial activation and atherogenesis. Interventional data indicate that periodontal therapy may reduce systemic inflammatory burden and improve vascular parameters, though heterogeneity across studies limits causal inference. Conclusions: Current findings highlight a significant oral–systemic connection through inflammatory and endothelial mechanisms. Strengthening interdisciplinary collaboration between dental and cardiovascular care providers is essential to translate this evidence into preventive and therapeutic practice. Further longitudinal and mechanistic studies are required to confirm causality and guide clinical integration. Full article

A sliding mode predictive control (SMPC) scheme integrated with an extreme learning machine (ELM) disturbance observer is proposed for the trajectory tracking of a flexible air-breathing hypersonic vehicle (FAHV). To streamline the controller design, the longitudinal model is decoupled into a velocity subsystem and an altitude subsystem. For the velocity subsystem, a proportional-integral sliding mode surface is designed, and the control law is derived by minimizing a cost function that weights the predicted sliding mode surface and the control input. For the altitude subsystem, a backstepping control framework is adopted, with the SMPC strategy embedded in each step. Multi-source disturbances are modeled as composite additive disturbances, and an ELM-based neural network observer is constructed for their real-time estimation and compensation, thereby enhancing system robustness. The semi-globally uniformly ultimately bounded (SGUUB) stability of the closed-loop system is rigorously proven using Lyapunov stability theory. Simulation results demonstrate the comprehensive superiority of the proposed method: it achieves reductions in Root Mean Square Error (RMSE) of 99.60% and 99.22% for velocity and altitude tracking, respectively, compared to Prescribed Performance Control with Backstepping Control (PPCBSC), and reductions of 98.48% and 97.12% relative to Terminal Sliding Mode Control (TSMC). Under parameter uncertainties, the developed ELM observer outperforms RBF-based observer and Extended State Observer (ESO) by significantly reducing tracking errors. These findings validate the high precision and strong robustness of the proposed approach. Full article

Background: Integrating deep regional hyperthermia (HT) with neoadjuvant chemoradiotherapy (CRT) may enhance treatment efficacy in locally advanced rectal cancer (LARC), yet feasibility and tolerance data remain scarce for both short-course (SCRT) and long-course (LCRT) radiotherapy (RT) regimens. Methods: In this single-center prospective observational study, 67 LARC patients received neoadjuvant RT and chemotherapy (CT) combined with deep radiative HT using a phased-array system (ALBA 4D). Patients treated with SCRT (5 × 5 Gy) were prescribed two HT sessions; those treated with LCRT (25 × 2 Gy) were prescribed ten. HT planning was guided by dedicated software, and real-time thermometry ensured precise thermal delivery. Feasibility was defined as completion of ≥50% of prescribed sessions. Tolerance and toxicity were assessed with standardized clinical scales (QMHT, UMC, CTCAE v4.03). Results: HT was feasible in both groups: 100% of SCRT and 63.6% of LCRT patients completed ≥50% of prescribed sessions. In total, 243 sessions were delivered. Most symptoms were mild and transient, predominantly localized pain. No grade ≥3 HT-related toxicities occurred. All scheduled RT and surgery proceeded without delay. Median T50 was 40.3 °C (SCRT) and 40.4 °C (LCRT); the median RT-to-HT interval was 42 min in both groups. Conclusion: This first Spanish experience shows that deep radiative HT can be seamlessly integrated into both SCRT and LCRT neoadjuvant protocols for rectal cancer. High adherence, favorable tolerance, and reliable thermal control support clinical implementation. Any between-schedule observations are descriptive only; no formal comparative testing was performed. The study was not designed or powered to establish comparative effectiveness between SCRT and LCRT, and the sample size was insufficient to detect rare HT-specific adverse events. Full article

Modal analysis is essential for evaluating the small-signal stability of power systems by identifying poorly damped oscillatory modes. This paper introduces an automated framework for residue computation directly within DIgSILENT PowerFactory, exploiting its internal state-space matrices and scripting environment. Unlike traditional approaches that rely on external data processing, the proposed method enables a fully integrated, repeatable, and scalable workflow for residue-guided control design. The framework automatically extracts and computes modal residues, quantifying both controllability and observability to identify the most effective control locations. Its application to benchmark systems demonstrates accurate detection of critical modes and effective damping enhancement through residue-based tuning. This integration of automated residue analysis into PowerFactory bridges theoretical modal analysis with practical implementation, offering a novel and efficient tool for oscillatory stability assessment in modern power grids. Full article