Search

Developing accurate in vitro models that replicate the in vivo tumor environment is essential for advancing cancer research and therapeutic development. Traditional 2D cell cultures often fail to capture the complex structural and functional heterogeneity of tumors, limiting the translational relevance of findings. In contrast, 3D culture systems, such as spheroids, provide a more physiologically relevant context by replicating key aspects of the tumor microenvironment. This study aimed to compare the metabolism of three intrahepatic cholangiocarcinoma cell lines in 2D and 3D cultures to identify metabolic shifts associated with spheroid formation. Cells were cultured in 2D on adhesion plates and in 3D using ultra-low attachment plates. Metabolic exchange rates were measured using NMR, and intracellular metabolites were analyzed using LC-MS. Significant metabolic differences were observed between 2D and 3D cultures, with notable changes in central carbon and glutathione metabolism in 3D spheroids. The results suggest that 3D cultures, which more closely mimic the in vivo environment, may offer a more accurate platform for cancer research and drug testing. [ABSTRACT FROM AUTHOR]

Human error in manufacturing can have substantial consequences, including loss of life, injuries, productivity, and financial losses. Human reliability analysis (HRA) methods can be used to evaluate the likelihood of human error in manufacturing tasks and identify potential sources of error. Performance shaping factors (PSFs) are internal and external factors that influence human performance and can affect the likelihood of human reliability estimates in HRA methods. Understanding the impact of PSFs on human performance in manufacturing is essential for developing effective strategies to minimize the likelihood of human error and improve the safety and efficiency of manufacturing processes. This systematic review scrutinizes the literature on PSFs within manufacturing, highlighting HRA applications. Using the PRISMA protocol, studies from 2000 to 2024 across engineering and psychology were examined, culminating in the analysis of 35 pertinent works. The review identifies and contrasts various PSF taxonomies from established HRA methods like SPAR‐H, HEART, CREAM, and THERP, revealing their diverse applications in different manufacturing settings. The review also uncovers a tendency to devise taxonomies through the lens of experts' domain knowledge, particularly tailored to discrete manufacturing contexts. A critical gap is observed in the lack of a uniform PSF framework, with the current literature reflecting a disparate understanding of PSFs' roles, definitions, and interrelations. This absence is further pronounced by the inadequate integration of human factors in the dialogue surrounding Industry 4.0. The analysis points to the necessity of harmonizing PSFs to better assess human reliability amid technological integration. The findings emphasize the need for an industry‐specific PSF framework that aligns with the intricacies of manufacturing operations, thus enabling more accurate HRA outcomes and informing strategies for error reduction and process optimization. [ABSTRACT FROM AUTHOR]

The evolving landscape of industrial manufacturing is increasingly embracing automation within smart factories. However, the critical role of human operators, particularly in manual assembly and disassembly tasks, remains undiminished. This paper explores the complexities arising from mass customization and remanufacturing, which significantly enhance the intricacy of these manual tasks. Human involvement is essential in these tasks due to their complexity, necessitating a structured learning process to enhance efficiency and mitigate the learning–forgetting cycle. This study focuses on the utilization of virtual reality (VR) as an innovative training tool to address these challenges. By conducting a systematic literature review (SLR) on the impact of VR on training operators for assembly and disassembly tasks, this paper evaluates the current level of VR application, the used technologies, the operator performance, and the VR benefits and limitations. The analysis reveals a limited but promising application of VR in training, highlighting its potential to improve learning outcomes, productivity, and safety while reducing costs. However, the research also identifies gaps in the practical application of VR for training purposes suggesting a future research agenda to explore its full potential. [ABSTRACT FROM AUTHOR]

Aims: The heterozygous phospholamban (PLN) mutation R14del (PLN R14del+/−) is associated with a severe arrhythmogenic cardiomyopathy (ACM) developing in the adult. "Superinhibition" of SERCA2a by PLN R14del is widely assumed to underlie the pathogenesis, but alternative mechanisms such abnormal energy metabolism have also been reported. This work aims to (1) to evaluate Ca2+ dynamics and energy metabolism in a transgenic (TG) mouse model of the mutation prior to cardiomyopathy development; (2) to test whether they are causally connected. Methods: Ca2+ dynamics, energy metabolism parameters, reporters of mitochondrial integrity, energy, and redox homeostasis were measured in ventricular myocytes of 8–12 weeks‐old, phenotypically silent, TG mice. Mutation effects were compared to pharmacological PLN antagonism and analyzed during modulation of sarcoplasmic reticulum (SR) and cytosolic Ca2+ compartments. Transcripts and proteins of relevant signaling pathways were evaluated. Results: The mutation was characterized by hyperdynamic Ca2+ handling, compatible with a loss of SERCA2a inhibition by PLN. All components of energy metabolism were depressed; myocyte energy charge was preserved under quiescence but reduced during stimulation. Cytosolic Ca2+ buffering or SERCA2a blockade reduced O2 consumption with larger effect in the mutant. Signaling changes suggest cellular adaptation to perturbed Ca2+ dynamics and response to stress. Conclusions: (1) PLN R14del+/− loses its ability to inhibit SERCA2a, which argues against SERCA2a superinhibition as a pathogenetic mechanism; (2) depressed energy metabolism, its enhanced dependency on Ca2+ and activation of signaling responses point to an early involvement of metabolic stress in the pathogenesis of this ACM model. [ABSTRACT FROM AUTHOR]

This study explores the impact of augmented reality (AR) on worker performance in manufacturing contexts through an analysis of case studies extant in the literature. Two specific analyses were conducted to assess the impacts of AR technologies on worker performance in terms of objective and subjective metrics, and in terms of their age, experience with the task and experience with the AR device. Regarding objective metrics, the results showed that the task completion time was reduced for some AR devices (projectors, monitors, tablets, smartphones), whereas the use of the head-mounted display (HMD) increased task-completion time; moreover, the error rate was reduced with any AR device compared with traditional methods. Regarding subjective metrics, the analysis underlined that operator perceived a lower workload with the HMD or the monitor compared with traditional methods. The age of operators did not influence performance, while the operators' experience allowed for the improvement of human performance. [ABSTRACT FROM AUTHOR]

Background: Remote monitoring is recommended for patients with implantable cardiac monitors (ICMs), but compared to other cardiac implantable devices, ICMs are less accurate and transmit a higher number of alerts. Objective: The aim of this study was to investigate the predictors of false‐positive (FP) arrhythmic alerts in patients with unexplained syncope who were implanted with ICM and followed by an automatic remote monitoring system. Methods: We retrospectively evaluated all consecutive patients who received a long‐sensing vector ICM for unexplained syncope between January 2019 to September 2021 at our Syncope Unit. The primary endpoint was the incidence of the first FP episode. The secondary endpoints included assessing the incidence of FP episodes for all types of algorhythms and indentifying the reasons for the misdetection of these episodes. Results: Among 105 patients (44.8% males, median age 51 years), 51 (48.6%) transmitted at least one FP alert during a median follow‐up of 301 days. The presence of pre‐ventricular complexes (PVCs) on the resting electrocardiogram was the only clinical characteristic associated with an increased risk of FP alerts (adjusted Hazard ratio [HR] 5.76 [2.66–12.4], p = 0.010). The other significant device‐related variables were a low‐frequency filter at 0.05 Hz versus the default 0.5 Hz (adjusted HR 3.82 [1.38–10.5], p = 0.010) and the R‐wave amplitude (adjusted HR 0.35 [0.13–0.99], p = 0.049). Conclusion: Patients who have PVCs are at higher risk of inappropriate ICM activations. To reduce the occurrence of FP alerts, it may be beneficial to target a large R‐wave amplitude during device insertion and avoid programming a low‐frequency filter at 0.05 Hz. [ABSTRACT FROM AUTHOR]

Population ageing is acknowledged as a global trend affecting the manufacturing workforce. The progressive age-related decline of human capabilities may lead to an increase in human-system errors (HSEs) in production environments; hence, the study conducted a scoping literature review to determine the relationship between ageing and HSEs in manufacturing contexts. The review identified only 26 relevant studies, which showed that age is associated with HSEs in complex ways. With increasing age, the number, frequency, and probability of HSEs tend to increase, but this trend may be countered by experience effects. The review results suggested that it is necessary to consider the impact of ageing on operators' performance. A theoretical framework for addressing the relationship between ageing and HSEs in manufacturing contexts was proposed. The framework highlighted the absence of studies reporting on perceptual, cognitive, and/or physical task demands, and the limited application of existing error typologies in the current literature. The results highlighted that important safety, productivity, and quality benefits accrue from paying attention to HSEs in system design and management, which should motivate further research in this area of growing importance. [ABSTRACT FROM AUTHOR]

Supplier selection (SS) and order allocation (OA) are strategic decisions that have a substantial effect on a company's performance. However, order allocation is often neglected, since it results from supplier selection and is considered supplementary: little attention has been paid to its specific nature and complexity. Consequently, the authors conducted a systematic literature review specifically regarding order allocation methods. The research aimed to evaluate how often and when the issue has been dignified with an individual focus, independently of the supplier selection problem. This study conducted a comprehensive examination of the order allocation models and solutions, criteria for order quantity allocation, features of suppliers, items, planning periods, and demand most commonly considered in the literature. Finally, it aimed to discover whether supply chain configurations and trends have been considered in efforts to find a solution to the problem. The scientific contribution of this study is threefold: (i) to expand the review of scientific literature regarding order allocation models, (ii) to identify research gaps and highlight research opportunities, and (iii) to suggest a research agenda for the development of order allocation models according to the requirements of current trends in supply chain management. [ABSTRACT FROM AUTHOR]

This document explores the complex relationship between innovation and sustainability. While innovation has the potential to drive progress towards sustainability, there is ongoing debate about its impact. The prevailing techno-economic paradigm, focused on competition and short-term strategies, can have adverse effects on ecological regulations and social dynamics. However, new paradigms based on sustainability, such as the circular economy and the Quintuple Helix innovation model, offer more positive connections between innovation and sustainability. Many companies are embracing sustainability-driven innovation, integrating sustainability criteria into their products and processes. The document also includes contributions that examine the relationship between innovation and sustainability in various industrial sectors, including logistics, quality management, green productivity, blockchain for sustainable communication, and energy efficiency. These contributions offer valuable insights and methodologies for navigating the complex landscape of modern industrial operations and highlight the need for further research in areas such as sustainability communication and decision-making frameworks. Overall, the document emphasizes the importance of leveraging technology to drive sustainable development and achieve long-term success while preserving the planet's future. [Extracted from the article]

Monitoring production systems is a key element for identifying waste and production efficiency, and for this purpose, the calculation of the Key Performance Indicator (KPI) Overall Equipment Effectiveness (OEE) is validly recognized in the scientific literature. The collection and analysis of the cause of the interruption of the plants is particularly useful in this sense. The use of Internet of Things (IoT) technology in order to automate data collection for the purpose of calculating the OEE and the causes of interruption is effective. Furthermore, the existing literature lacks research studies that aim to improve the data quality of important process data that cannot be collected automatically. This study proposes the use of IoT technologies to request targeted and intelligent information inputs from the operators directly involved in the process, improving the completeness and accuracy of the information through the real-time and smart combination of manual and automated data. The Business Process Model and Notation (BPMN) methodology was used to analyze and redesign the collection data process and define the architectural model with a deep knowledge of the specific process. The proposed architecture, designed for application to a plastic injection molding production line, comprises several elements: the telemetry of the injection molding machine, an intervention request system, an intervention tracking system, and a human–system interface. Furthermore, a dashboard was developed using the Power BI software, 2.122.746.0 version, to analyze the information collected. Reducing the randomness of manual data makes it possible to direct production efficiency efforts more effectively, helping to reduce waste and production costs. Reducing production costs appears to be strongly linked to reducing environmental impacts, and future studies will be able to quantify the benefits obtained from the solution in terms of environmental impact. [ABSTRACT FROM AUTHOR]

Production planning and control (PPC), responsible for all the activities that keep production running regularly, plays an essential role in the transition to more sustainable manufacturing systems. PPC decision-making processes need to be driven by sustainable principles even if this makes them more effortful and complex from the strategic to operative level. This study aims to review the scientific literature relating to sustainable PPC. A bibliometric analysis of 437 papers published on the Scopus database was performed to identify the most relevant articles, authors, and journals and to provide the current topic trends and future research themes and gaps. The findings revealed the increasing interest in this topic mainly since 2018. China and the USA are the most productive countries, whereas the Journal of Cleaner Production and Sustainability are the most productive journals. The analysis has also highlighted the ways to address sustainability issues in PPC, e.g., by integrating in scheduling models objectives related to sustainability or by removing barriers to reverse logistics and circular economy at the PPC level. The following topics, instead, deserve further research: attention to the social issues in PPC and the development of decision support systems that will improve companies' PPC decision-making capabilities in sustainable optics. [ABSTRACT FROM AUTHOR]

Maintenance involves a large amount of data management. Although many tools, strategies, and systems, have been developed to organize the maintenance information resources, SMEs have not found the same benefits as large companies due to their inherent characteristics and, above all, the maturity level of the maintenance department. Maturity models are useful tools for assessing the maturity of maintenance information practices; however, existing models are not suitable for any type of business context, as they required companies to have a clear organizational structure and definite informative infrastructure. Moreover, they do not assist in identifying and defining actions to reach the highest level. This paper proposes a model for assessing and improving maintenance management information practices. It allows a clear measure of the maturity of the maintenance information management practices in industrial contexts and provides improvement actions identifying the information and data needed to enhance maintenance management information practices. [ABSTRACT FROM AUTHOR]

More than 60 years has passed since the installation of the first robot in an industrial context. Since then, industrial robotics has seen great advancements and, today, robots can collaborate with humans in executing a wide range of working activities. Nevertheless, the impact of robots on human operators has not been deeply investigated. To address this problem, we conducted an empirical study to measure the errors performed by two groups of people performing a working task through a virtual reality (VR) device. A sample of 78 engineering students participated in the experiments. The first group worked with a robot, sharing the same workplace, while the second group worked without the presence of a robot. The number of errors made by the participants was collected and analyzed. Although statistical results show that there are no significant differences between the two groups, qualitative analysis proves that the presence of the robot led to people paying more attention during the execution of the task, but to have a worse learning experience. [ABSTRACT FROM AUTHOR]

Background: Digital twins have the potential to significantly improve the efficiency and sustainability of the agri-food supply chain by providing visibility, reducing bottlenecks, planning for contingencies, and improving existing processes and resources. Additionally, they can add value to businesses by lowering costs and boosting customer satisfaction. This study is aimed at responding to common scientific questions on the application of digital twins in the agri-food supply chain, focusing on the benefits, types, integration levels, key elements, implementation steps, and challenges. Methods: This article conducts a systematic literature review of recent works on agri-food supply chain digital twins, using a list of peer-reviewed studies to analyze concepts using precise and well-defined criteria. Thus, 50 papers were selected based on inclusion and exclusion criteria, and descriptive and content-wise analysis was conducted to answer the research questions. Conclusions: The implementation of digital twins has shown promising advancements in addressing global challenges in the agri-food supply chain. Despite encouraging signs of progress in the sector, the real-world application of this solution is still in its early stages. This article intends to provide firms, experts, and researchers with insights into future research directions, implications, and challenges on the topic. [ABSTRACT FROM AUTHOR]

Heterogeneity describes the differences among cancer cells within and between tumors. It refers to cancer cells describing variations in morphology, transcriptional profiles, metabolism, and metastatic potential. More recently, the field has included the characterization of the tumor immune microenvironment and the depiction of the dynamics underlying the cellular interactions promoting the tumor ecosystem evolution. Heterogeneity has been found in most tumors representing one of the most challenging behaviors in cancer ecosystems. As one of the critical factors impairing the long-term efficacy of solid tumor therapy, heterogeneity leads to tumor resistance, more aggressive metastasizing, and recurrence. We review the role of the main models and the emerging single-cell and spatial genomic technologies in our understanding of tumor heterogeneity, its contribution to lethal cancer outcomes, and the physiological challenges to consider in designing cancer therapies. We highlight how tumor cells dynamically evolve because of the interactions within the tumor immune microenvironment and how to leverage this to unleash immune recognition through immunotherapy. A multidisciplinary approach grounded in novel bioinformatic and computational tools will allow reaching the integrated, multilayered knowledge of tumor heterogeneity required to implement personalized, more efficient therapies urgently required for cancer patients. [ABSTRACT FROM AUTHOR]