Search Results (661)

(1) Background: As society progresses, increasing numbers of individuals are experiencing hair loss, which can be attributed to factors such as unhealthy diets, insufficient sleep, stress, and hormonal imbalances. Currently available pharmacological treatments for hair loss often cause undesirable side effects, highlighting the urgent need to explore safer and more effective agents to promote hair restoration. This study investigated the role of recombinant human type XVII collagen derived from the α1 chain (rhCOL17A1) in facilitating hair growth and restoration. (2) Methods: We analyzed the impact of rhCOL17A1 on the mRNA expression of several growth factors, as well as Bcl-2 and Bax, at the cellular level. Moreover, the effects of rhCOL17A1 on the expression of key proteins in the Wnt/β-catenin and Sonic Hedgehog (SHH)/GLI signaling pathways were examined by Western blotting (WB). At the organismal level, we established a model in C57BL/6 mice through chronic subcutaneous administration of 5% testosterone propionate. We subsequently assessed the effect of rhCOL17A1 on hair regrowth via histological analysis using hematoxylin and eosin (H&E) staining and immunofluorescence staining. (3) Results: rhCOL17A1 contributes to the resistance of hair follicle dermal papilla cells (HFDPCs) to apoptosis. rhCOL17A1 activates the Wnt/β-catenin and SHH/GLI signaling pathways, and increases the expression of type XVII collagen (COLXVII), thereby creating a favorable environment for hair growth. Furthermore, rhCOL17A1 exerts a significant growth-promoting effect at the animal level. (4) Conclusions: rhCOL17 promotes hair growth by activating the Wnt/β-catenin and SHH/GLI signaling pathways and upregulating COLXVII expression. Full article

Background: As intelligent systems increasingly operate in high-risk environments, understanding how they perceive and respond to hazards is critical for ensuring safety. Methods: In this study, we conduct a comparative analysis of 60 real-world accident reports, 30 from process control systems (PCSs) and 30 from autonomous vehicles (AVs), to examine differences in risk triggers, perception paradigms, and interaction failures between humans and artificial intelligence (AI). Results: Our findings reveal that PCS risks are predominantly internal to the system and detectable through deterministic, rule-based mechanisms, whereas AVs’ risks are externally driven and managed via probabilistic, multi-modal sensor fusion. More importantly, despite these architectural differences, both domains exhibit recurring human–AI interaction failures, including over-reliance on automation, mode confusion, and delayed intervention. In the case of PCSs, these failures are historically tied to human–automation interaction; this article extrapolates these patterns to anticipate potential human–AI interaction challenges as AI adaptation increases. Conclusions: This study highlights the need for a hybrid risk perception framework and improved human-centered design to enhance situational awareness and responsiveness. While AI has not yet been implemented in PCS incident studies, this work interprets human–automation failures in these cases as indicative of potential challenges in human–AI interaction that may arise in future AI-integrated process systems. Implications extend to developing safer intelligent systems across industrial and transportation sectors. Full article

Traffic congestion poses a significant challenge to modern urban environments, impacting both driver satisfaction and road safety. This paper investigates the effectiveness of a smart traffic light system (STL), a solution developed under the Intelligent Transportation System (ITS) initiative by the Ministry of Works Malaysia, to address these issues in Malaysia. The system integrates a network of sensors, AI-enabled cameras, and Automatic Number Plate Recognition (ANPR) technology to gather real-time data on traffic volume and vehicle classification at congested intersections. This data is utilized to dynamically adjust traffic light timings, prioritizing traffic flow on heavily congested roads while maintaining safety standards. To evaluate the system’s performance, a comprehensive study was conducted at a selected intersection. Traffic patterns were automatically analyzed using camera systems, and the performance of the STL was compared to that of traditional traffic signal systems. The average travel time from the start to the end intersection was measured and compared. Preliminary findings indicate that the STL significantly reduces travel times and improves overall traffic flow at the intersection, with average travel time reductions ranging from 7.1% to 28.6%, depending on site-specific factors. While further research is necessary to quantify the full extent of the system’s impact, these initial results demonstrate the promising potential of STL technology to enhance urban mobility and more efficient and safer roadways by moving beyond traditional traffic signal functionalities. Full article

Vegetables and fruits grown in urban areas pose a potential threat to human health due to contamination with heavy metals (HMs). This study aimed to identify and quantify the concentrations of heavy metals (Fe, Mn, Zn, Cu, Pb, Cd) in tomatoes, leafy vegetables, and fruits collected from 16 allotment gardens (AGs) located in Warsaw. A total of 112 samples were analyzed (72 vegetable and 40 fruit samples). Vegetables from AGs accumulated significantly higher levels of HMs than fruits. Leafy vegetables, particularly those cultivated near high-traffic roads, exhibited markedly elevated levels of Pb, Cd, and Zn compared to those grown in peripheral areas. Lead concentrations exceeded permissible limits by six to twelve times, cadmium by one to thirteen times, and zinc by 0.7 to 2.4 times. Due to high levels of Pb and Cd, tomatoes should not be cultivated in urban environments. Regardless of location, only trace amounts of HMs were detected in fruits. The greatest health risk is associated with the consumption of leafy vegetables. Lettuce should be considered an indicator plant for assessing environmental contamination. The obtained Hazard Index (HI) values indicate that only the tested fruits are safe for consumption. Meanwhile, the values of the Hazard Quotient (HQ) indicate no health risk associated with the consumption of lettuce, cherries, and red currants. Among the analyzed elements, Pb showed a higher potential health risk than other metals. This study emphasizes the need for continuous monitoring of HM levels in urban soils and the establishment of baseline values for public health purposes. Remediation of contaminated soils and the implementation of safer agricultural practices are recommended to reduce the exposure of urban populations to the risks associated with the consumption of contaminated produce. In addition, the safety of fruits and vegetables grown in urban areas is influenced by the location of the AGs and the level of industrialization of the agglomeration. Therefore, the safety assessment of plant products derived from AGs should be monitored on a continuous basis, especially in vegetables. Full article

Understanding automated vehicle (AV) behavior in complex road environments and user attitudes in such contexts is critical for their safe and effective integration into smart cities. Despite growing deployment, limited public data exist on AV performance in construction zones; highly dynamic settings marked by irregular lane markings, shifting detours, and unpredictable human presence. This study investigates AV behavior in these conditions through qualitative, video-based analysis of user-documented experiences on YouTube, focusing on Tesla’s supervised Full Self-Driving (FSD) and Waymo systems. Spoken narration, captions, and subtitles were examined to evaluate AV perception, decision-making, control, and interaction with humans. Findings reveal that while AVs excel in structured tasks such as obstacle detection, lane tracking, and cautious speed control, they face challenges in interpreting temporary infrastructure, responding to unpredictable human actions, and navigating low-visibility environments. These limitations not only impact performance but also influence user trust and acceptance. The study underscores the need for continued technological refinement, improved infrastructure design, and user-informed deployment strategies. By addressing current shortcomings, this research offers critical insights into AV readiness for real-world conditions and contributes to safer, more adaptive urban mobility systems. Full article

This paper examines the integration of markerless augmented reality (AR) within the da Vinci Surgical Robot, utilizing artificial intelligence (AI) for improved precision. The main challenge in creating AR for these systems is the small size (5 mm diameter) of the cameras used. Traditional camera-calibration approaches produce significant errors when used for miniature cameras. Further, the use of external markers can be obstructive and inaccurate in dynamic surgical environments. The study focuses on overcoming these limitations of traditional AR methods by employing advanced neural networks for camera calibration and real-time image processing. We demonstrate the use of a dense neural network to reduce the total projection error by directly learning the mapping of a 3D point to a 2D image plane. The results show a median error of 7 pixels (1.4 mm) when using a neural network, as compared to an error of 50 pixels (10 mm) when using a more traditional approach involving camera calibration and robot kinematics. This approach not only enhances the accuracy of AR for surgical procedures but also offers a more seamless integration with existing robotic platforms. These research findings underscore the potential of AI in revolutionizing AR applications in medical robotics and other teleoperated systems, promising efficient and safer interventions. Full article

In high-stakes decision-making environments, predictive models must deliver not only high accuracy but also reliable uncertainty estimations and transparent explanations. This study explores the integration of probability calibration techniques with Conformal Prediction (CP) within a predictive process monitoring (PPM) framework tailored to healthcare analytics. CP is renowned for its distribution-free prediction regions and formal coverage guarantees under minimal assumptions; however, its practical utility critically depends on well-calibrated probability estimates. We compare a range of post-hoc calibration methods—including parametric approaches like Platt scaling and Beta calibration, as well as non-parametric techniques such as Isotonic Regression and Spline calibration—to assess their impact on aligning raw model outputs with observed outcomes. By incorporating these calibrated probabilities into the CP framework, our multilayer analysis evaluates improvements in prediction region validity, including tighter coverage gaps and reduced minority error contributions. Furthermore, we employ SHAP-based explainability to explain how calibration influences feature attribution for both high-confidence and ambiguous predictions. Experimental results on process-driven healthcare data indicate that the integration of calibration with CP not only enhances the statistical robustness of uncertainty estimates but also improves the interpretability of predictions, thereby supporting safer and robust clinical decision-making. Full article

In the present era, achieving sustainability requires the development of planning strategies to develop a safer urban infrastructure. This study examines the realistic aspects of cyclist safety by analysing cyclists’ fields of view, using Geographic Information Systems (GIS) and spatial data analysis. The research introduces novel geoprocessing tools-based GIS techniques that mathematically simulate cyclists’ angles of view and the distances to nearby environmental features. It provides precise insights into some potential hazards and infrastructure challenges encountered while cycling. This research focuses on managing and analysing the data collected, utilising OpenStreetMap (OSM) as vector-based supporting data. It integrates cyclists’ behavioural data with the urban environmental features encountered, such as intersections, road design, and traffic controls. The analysis is categorised into specific classes to evaluate the impacts of these aspects of the environment on cyclists’ behaviours. The current investigation highlights the importance of integrating the objective environmental elements surrounding the route with subjective perceptions and then determining the influence of these environmental elements on cyclists’ behaviours. Unlike previous studies that ignore cyclists’ visual perspectives in the context of real-world data, this work integrates objective GIS data with cyclists’ field of view-based modelling to identify high-risk areas and highlight the need for enhanced safety measures. The proposed approach equips urban planners and designers with data-informed strategies for creating safer cycling infrastructure, fostering sustainable mobility, and mitigating urban congestion. Full article

Neonicotinoids are extensively used in agricultural production, yet increasing evidence highlights their cytotoxic effects on various cell types. Research has demonstrated that these pesticides can significantly impair the viability and function of reproductive, adipose, neural, immune, and epithelial cells. The underlying mechanisms involve metabolic disturbances, mitochondrial dysfunction, and oxidative stress. These cellular effects raise serious concerns about the potential risks neonicotinoids pose to both human health and the environment. Further investigation is essential to fully understand their toxicological impact and to inform safer pesticide regulation and use. Full article

Green starches, sourced from sustainable and unconventional plant and protist sources, are gaining prominence in functional ingredient research due to their combined technological and bioactive properties. Within the context of circular economy and green chemistry, this review addresses the extraction processes of native, modified, and phytochemically enriched starches. It highlights diverse applications, focusing on the advantages of phytochemical enrichment over other modification methods, given the acquired properties from bioactive compound incorporation. Initially, the review approaches the circular economy and green chemistry’s contributions. Various starch modification processes are presented, emphasizing chemical alterations and their impacts on food safety and the environment. Recent studies employing this principle are detailed, focusing on food applications, extending to pharmaceuticals, cosmetics, and culminating in bioelectronics. Finally, new research ideas are proposed, aiming to inspire further studies in the field. This review underscores a significant and growing interest in sustainable starch applications, particularly biocompound-enriched starches, across diverse sectors like pharmaceuticals, agriculture, textiles, and packaging. This trend is driven by the need for safer, eco-friendlier alternatives, with emerging fields such as bioelectronics and 3D/4D printing also recognizing starch’s versatile potential. Full article

Per- and polyfluoroalkyl substances (PFASs) are synthetic chemicals extensively used in various industries due to their unique physicochemical properties. Their persistence in the environment and potential for bioaccumulation have raised significant health concerns. This review aims to elucidate the sources, exposure pathways, toxicological effects, and regulatory measures related to PFASs, with a particular focus on pediatric populations and medical applications. A comprehensive narrative review was conducted using PubMed, Scopus, and Web of Science to identify peer-reviewed literature published between 2000 and 2025. The search focused on PFAS use in healthcare, environmental contamination, exposure pathways, health effects, and regulatory actions. Relevant studies, reports, and policy documents were screened and thematically synthesized by the authors to evaluate clinical and environmental risks, particularly in pediatric populations. PFAS exposure is linked to various adverse health effects, including immunotoxicity, endocrine disruption, metabolic disorders, and carcinogenicity. Children are particularly vulnerable due to developmental susceptibilities and exposure through medical devices and environmental sources. Regulatory measures are evolving, but gaps remain, especially concerning medical device applications. There is an urgent need for comprehensive strategies to monitor and mitigate PFAS exposure, particularly in vulnerable populations. Enhanced regulatory frameworks, safer alternatives in medical devices, and public health interventions are essential to address the challenges posed by PFASs. Full article

This study investigated the application of Finite Element Analysis (FEA) to optimize the design and material selection for the construction of the telescopic arm of an elevating work platform (EWP) used in agricultural environments. By comparing the structural performance of four materials—Aluminum Alloy (EN-AW 1200), Aluminum Alloy (EN-AW 2014), High-Strength Low-Alloy (HSLA) Steel Fe275JR, and HSLA Steel S700—under simulated operational conditions, this research identified the most suitable material for robust yet lightweight platforms. The results revealed that HSLA Steel S700 provides superior performance in terms of strength, low deformation, and high safety factors, making it ideal for scenarios requiring maximum durability and load-bearing capacity. Conversely, Aluminum Alloy (EN-AW 2014), while exhibiting lower strength compared with HSLA Steel S700, significantly reduces platform weight by approximately 60% and lowers the center of gravity, enhancing maneuverability and compatibility with smaller, less powerful tractors. These findings highlight the potential of FEA in optimizing EWP design by enabling precise adjustments to material selection and structural geometry. The outcomes of this research contribute to the development of safer, more efficient, and cost-effective EWPs, with a specific focus on improving productivity and safety in agricultural operations such as pruning and harvesting. Future work will explore advanced geometries and hybrid materials to further enhance the performance and versatility of these platforms. Full article

Pedestrian behaviour and safety are essential components of urban sustainability. They are influenced by a complex interplay between various factors from different perspectives, particularly in culturally and linguistically diverse (CALD) communities. This study presents a comprehensive overview of the factors influencing pedestrian behaviour and safety with a focus on CALD communities. By synthesizing the existing literature, the study identifies six key groups of influencing factors: social–psychological, cultural, risk perceptions, environmental, technological distractions, and demographic differences. It discovers that well-designed interventions, such as tailored education campaigns and programs, may effectively influence pedestrian behaviour. These interventions emphasize the importance of targeted messaging to address specific risks (e.g., using mobile phones while crossing the road) and engage vulnerable groups, including children, seniors, and CALD communities. The study reveals that CALD communities face higher risks of pedestrian injuries and fatalities due to language barriers, unfamiliarity with local road rules, and different practices and approaches to road safety due to cultural differences. This study underlines the importance of developing and promoting tailored road safety education programs to address the unique challenges faced by CALD communities to help promote safer pedestrian environments for all. Full article

Adeno-associated virus (AAV) vectors have emerged as the leading platform for retinal gene therapy due to their favorable safety profile, low immunogenicity, and ability to mediate long-term transgene expression within the immune-privileged ocular environment. By integrating diverse strategies such as gene augmentation and gene editing, AAV-based therapies have demonstrated considerable promise in treating both inherited and acquired retinal disorders. However, their clinical translation remains limited by several key challenges, including restricted packaging capacity, suboptimal transduction efficiency, the risk of gene therapy-associated uveitis, and broader societal concerns such as disease burden and ethical oversight. This review summarizes recent advances aimed at overcoming these barriers, with a particular focus on delivery route-specific disease applicability, multi-vector systems, and capsid engineering approaches to enhance payload capacity, targeting specificity, and biosafety. By synthesizing these developments, we propose a conceptual and technical framework for a more efficient, safer, and broadly applicable AAV platform to accelerate clinical adoption in retinal gene therapy. Full article

Postharvest losses of Solanaceae crops, which include potatoes (Solanum tuberosum), tomatoes (Solanum lycopersicum), bell peppers (Capsicum annuum), and others, are one of the major challenges in agriculture throughout the world, impacting food security and economic viability. Agrochemicals have been successfully employed to prevent postharvest losses in agriculture. However, the excessive use of agrochemicals may cause detrimental effects on consumer health, the emergence of pesticide-resistant pathogens, increased restrictions on existing pesticides, environmental harm, and the decline of beneficial microorganisms, such as natural antagonists to pests and pathogens. Hence, there is a need to search for a safer and more environmentally friendly alternative. Microbial antagonists have gained more attention in recent years as substitutes for the management of pests and pathogens because they minimize the excessive applications of toxic substances while providing a sustainable approach to plant health management. However, more research is required to make microbial agents more stable and effective and less toxic before they can be used in commercial settings. Therefore, research is being conducted to develop new biological control agents and obtain knowledge of the mechanisms of action that underlie biological disease control. To accomplish this objective, the review aims to investigate microbial antagonists’ modes of action, potential future applications for biological control agents, and difficulties encountered during the commercialization process. We also highlight earlier publications on the function of microbial biological control agents against postharvest crop diseases. Therefore, we can emphasize that the prospects for biological control are promising and that the use of biological control agents to control crop diseases can benefit the environment. Full article