Development Of System Research Articles

Development and Implementation of a Safety Incident Report System for Health Care Discipline Students During Clinical Internships: Observational Study.

Patient safety is a fundamental aspect of health care practice across global health systems. Safe practices, which include incident reporting systems, have proven valuable in preventing the recurrence of safety incidents. However, the accessibility of this tool for health care discipline students is not consistent, limiting their acquisition of competencies. In addition, there is no tools to familiarize students with analyzing safety incidents. Gamification has emerged as an effective strategy in health care education. This study aims to develop an incident reporting system tailored to the specific needs of health care discipline students, named Safety Incident Report System for Students. Secondary objectives included studying the performance of different groups of students in the use of the platform and training them on the correct procedures for reporting. This was an observational study carried out in 3 phases. Phase 1 consisted of the development of the web-based platform and the incident registration form. For this purpose, systems already developed and in use in Spain were taken as a basis. During phase 2, a total of 223 students in medicine and nursing with clinical internships from universities in Argentina, Brazil, Colombia, Ecuador, and Spain received an introductory seminar and were given access to the platform. Phase 3 ran in parallel and involved evaluation and feedback of the reports received as well as the opportunity to submit the students' opinion on the process. Descriptive statistics were obtained to gain information about the incidents, and mean comparisons by groups were performed to analyze the scores obtained. The final form was divided into 9 sections and consisted of 48 questions that allowed for introducing data about the incident, its causes, and proposals for an improvement plan. The platform included a personal dashboard displaying submitted reports, average scores, progression, and score rankings. A total of 105 students participated, submitting 147 reports. Incidents were mainly reported in the hospital setting, with complications of care (87/346, 25.1%) and effects of medication or medical products (82/346, 23.7%) being predominant. The most repeated causes were related confusion, oversight, or distractions (49/147, 33.3%) and absence of process verification (44/147, 29.9%). Statistically significant differences were observed between the mean final scores received by country (P<.001) and sex (P=.006) but not by studies (P=.47). Overall, participants rated the experience of using the Safety Incident Report System for Students positively. This study presents an initial adaptation of reporting systems to suit the needs of students, introducing a guided and inspiring framework that has garnered positive acceptance among students. Through this endeavor, a pathway toward a safety culture within the faculty is established. A long-term follow-up would be desirable to check the real benefits of using the tool during education. Trial Registration: ClinicalTrials.gov NCT05350345; https://clinicaltrials.gov/study/NCT05350345.

Has China's hierarchical medical system improved doctor-patient relationships?

Developing harmonious doctor-patient relationships is a powerful way to promote the construction of a new pattern of medical reform in developing countries. We aim to analyze the effects of China's hierarchical medical system on doctor-patient relationships, thus contributing to China's medical and health system reform. With panel data on prefectural-level cities in China from 2012 to 2019, we used a time-varying difference-in-differences model to evaluate the effect of hierarchical medical treatment policy. Hierarchical medical treatment policies can significantly improve doctor-patient relationships, and this conclusion is supported by various robustness tests. And improving doctor-patient relationships can be indirectly realized by the optimization of resource allocation and saving of medical costs. In addition, the marginal effect of the pilot policy on doctor-patient relationships decreased with age within the city population. In focal cities and cities with high levels of fiscal spending on health care, the effect of the pilot policy on doctor-patient relationships was stronger. While reinforcing the literature on the doctor-patient relationship, this study also provides a reference for further exploration of the pilot policy of hierarchical medical treatment and the development of new medical and health system reform in developing countries.

Development of a novel scoring system to predict mortality in canine patients with infection.

To develop a novel illness severity scoring system to identify canine patients with infection that are at higher risk of mortality. Mentation (Modified Glasgow Coma Scale and the Acute Patient Physiologic and Laboratory Evaluation mentation score), heart rate, pH, Pvco2, potassium, and total plasma protein were found to be associated with mortality on univariate analysis. Logistic regression found that mentation, heart rate, and Pvco2 combined to form the following score: [(100×mentation score)+(3×heart rate)+(10×Pvco2], which was predictive of mortality (area under the receiver operating characteristic curve: 0.88). A cutoff of 900 provided a sensitivity of 80% and a specificity of 80%. If the cutoff was changed to 800, the sensitivity was 100% and the specificity was 50%. A novel scoring system was developed to predict mortality in hospitalized dogs with confirmed or suspected infection. Further prospective evaluation in a larger patient cohort is necessary to validate this score.

Development of a 3D printed perfusable in vitro blood-brain barrier model for use as a scalable screening tool.

Despite recent technological advances in drug discovery, the success rate for neurotherapeutics remains alarmingly low compared to treatments for other areas of the body. One of the biggest challenges for delivering therapeutics to the central nervous system (CNS) is the presence of the blood-brain barrier (BBB). In vitro blood-brain barrier models with high predictability are essential to aid in designing parameters for new therapeutics, assess their ability to cross the BBB, and investigate therapeutic strategies that can be employed to enhance transport. Here, we demonstrate the development of a 3D printable hydrogel blood-brain barrier model that mimics the cellular composition and structure of the blood-brain barrier with human brain endothelial cells lining the surface, pericytes in direct contact with the endothelial cells on the abluminal side of the endothelium, and astrocytes in the surrounding printed bulk matrix. We introduce a simple, static printed hemi-cylinder model to determine design parameters such as media selection, co-culture ratios, and cell incorporation timing in a resource-conservative and high-throughput manner. Presence of cellular adhesion junction, VE-Cadherin, efflux transporters, P-glycoprotein (P-gp) and Breast cancer resistance protein (BCRP), and receptor-mediated transporters, Transferrin receptor (TfR) and low-density lipoprotein receptor-related protein 1 (LRP1) were confirmed via immunostaining demonstrating the ability of this model for screening in therapeutic strategies that rely on these transport systems. Design parameters determined in the hemi-cylinder model were translated to a more complex, perfusable vessel model to demonstrate its utility for determining barrier function and assessing permeability to model therapeutic compounds. This 3D-printed blood-brain barrier model represents one of the first uses of projection stereolithography to fabricate a perfusable blood-brain barrier model, enabling the patterning of complex vessel geometries and precise arrangement of cell populations. This model demonstrates potential as a new platform to investigate the delivery of neurotherapeutic compounds and drug delivery strategies through the blood-brain barrier, providing a useful in vitro screening tool in central nervous system drug discovery and development.

Transformations in postgraduate medical education following the COVID-19 pandemic: lessons learned from advances and challenges.

The COVID-19 pandemic has profoundly reshaped postgraduate medical education, driving immediate and significant adaptations in teaching methodologies and educational frameworks. This review examines the multifaceted transformations within medical education environments, particularly in response to the pandemic. Through a structured narrative review of recent literature, we identify key lessons learned and the subsequent shifts in educational practices. Our analysis underscores the critical importance of flexibility in educational delivery, the integration of technology, and the emphasis on mental health and resilience among medical trainees. We also explore the challenges and successes associated with maintaining equality and diversity in a rapidly evolving educational landscape. The findings highlight the necessity for continuous professional development and robust support systems to navigate future challenges effectively. Recommendations are provided for educational institutions to enhance adaptability, foster inclusive learning environments, and prepare for unforeseen global health emergencies. This study aims to contribute to the ongoing discourse on optimizing postgraduate medical education to better prepare health professionals for a dynamic and uncertain future.

Towards the Development of an In-Process Quality Monitoring System for Polyethylene Recyclates by Pyrolysis Gas Chromatography Ion Mobility Spectrometry

Towards the Development of an In-Process Quality Monitoring System for Polyethylene Recyclates by Pyrolysis Gas Chromatography Ion Mobility Spectrometry

Intelligent process monitoring of smart polymer composites using large area graphene coated fabric sensor.

Herein, we report the development of an online process monitoring system for vacuum-assisted resin transfer molding (VARTM) process using large area graphene coated in-situ fabric sensor. Besides imparting excellent mechanical properties to the final composites, these sensors provide critical information during the composite processing including detecting defects and evaluating processing parameters. The obtained information can be used to create a digital passport of the manufacturing phase to develop a cost-effective production technique and fabricate high-quality composites. The fabric sensor was produced using a scalable dip-coating process by coating 1-, 3- or 5-layers of thermally reduced graphene oxide (rGO) onto glass fabric surface according to the number of dips of the fabrics into GO solution. The electrical resistances from all electrode pairs were simultaneously and continuously recorded during distinct stages of the VARTM process to determine the relative conductance. During the vacuum cycle, the range of relative conductance increased with the number of coated rGO layers, with the 5-layer rGO-coated sensor showing the highest conductance range of 16.9 %. Additionally, it was observed that the 5-layer coated sensor showed a consistent decrease in conductance during the infusion phase due to the fluid flow pressure dominating the resin electrical conductivity.

Efficient Photocatalytic Desulfurization in Air through Improved Photogenerated Carriers Separation in MOF MIL101/Carbon Dots-g-C3N4 Nanocomposites.

The extensive industrial applications of fuel oil, a critical strategic resource, are accompanied by significant environmental and health concerns due to the presence of sulfur-containing compounds in its composition, which result in hazardous combustion waste. Extensive research has been conducted to develop technologies for low-vulcanization fuel production to address this issue. Consequently, the investigation of catalysts for environmentally friendly and safe photocatalytic desulfurization becomes imperative. To that end, we have designed efficient MIL-101(Fe)/CQDs@g-C3N4 (MIL101/CDs-C3N4) Z-scheme heterojunction photocatalysts with high carrier separation and mobility through a thermal polymerization-hydrothermal strategy. The high concentration of photogenerated carriers facilitates the activation of oxygen and H2O2, leading to increased production of ROS (⋅O2 -, ⋅OH, h+), thereby enhancing the photocatalytic desulfurization (PODS). Additionally, DFT (Density functional theory) calculations were utilized to determine the electron migration pathways of the catalysts and adsorption energies of DBT (dibenzothiophene). Moreover, Gibbs free energy calculations indicated that MIL101/CDs-C3N4 exhibited the lowest activation energy for oxygen and H2O2. The mechanism of photocatalytic desulfurization was proposed through a combination of theoretical calculations and experimental studies. This study provides guidance for the development of MOF-based Z-scheme systems and their practical application in desulfurization processes.

Crawling, climbing, perching, and flying by FiBa soft robots.

This paper introduces an approach to fabricating lightweight, untethered soft robots capable of diverse biomimetic locomotion. Untethering soft robotics from electrical or pneumatic power remains one of the prominent challenges within the field. The development of functional untethered soft robotic systems hinges heavily on mitigating their weight; however, the conventional weight of pneumatic network actuators (pneu-nets) in soft robots has hindered untethered operations. To address this challenge, we developed film-balloon (FiBa) modules that drastically reduced the weight of soft actuators. FiBa modules combine transversely curved polymer thin films and three-dimensionally printed pneumatic balloons to achieve varied locomotion modes. These lightweight FiBa modules serve as building blocks to create untethered soft robots mimicking natural movement strategies. These modules substantially reduce overall robot weight, allowing the integration of components such as pumps, valves, batteries, and control boards, thereby enabling untethered operation. FiBa modules integrated with electronic components demonstrated four bioinspired modes of locomotion, including turtle-inspired crawling, inchworm-inspired climbing, bat-inspired perching, and ladybug-inspired flying. Overall, our study offers an alternative tool for designing and customizing lightweight, untethered soft robots with advanced functionalities. The reduction of the weight of soft robots enabled by our approach opens doors to a wide range of applications, including disaster relief, space exploration, remote sensing, and search and rescue operations, where lightweight, untethered soft robotic systems are essential.

Development of a luciferase-based Gram-positive bacterial reporter system for the characterization of antimicrobial agents.

Discovering new classes of antibiotics is desperately needed to combat the emergence of multidrug-resistant pathogens. To facilitate the drug discovery process, a simple cell-based assay for mechanistic studies is essential to characterize antimicrobial candidates. In this work, we developed a luciferase-based reporter system to quantify the transcriptional and translational effects of potential compounds and validated our system using two currently marketed drugs. Reporter strains generated in this study provide readily available means for identifying bacterial transcription inhibitors as prospective novel antibacterials. We also provided a series of plasmids for characterizing promoters under various conditions such as stress.

Enzyme-Responsive Supramolecular Self-Assembly in Small Amphiphiles.

Enzyme-responsive molecular assemblies have recently made remarkable progress, owing to their widespread applications. As a class of catalysts with high specificity and efficiency, enzymes play a critical role in producing new molecules and maintaining metabolic stability in living organisms. Therefore, the study of enzyme-responsive assembly aids in understanding the origin of life and the physiological processes occurring within living bodies, contributing to further advancements across various disciplines. In this Review, we summarize three kinds of enzyme-responsive assembly systems in amphiphiles: enzyme-triggered assembly, disassembly, and structural transformation. Furthermore, motivated by the fact that biological macromolecules and complex structures all originated with small molecules, our focus lies on the small amphiphiles (e.g., peptides, surfactants, fluorescent molecules, and drug molecules). We also provide an outlook on the potential of enzyme-responsive assembly systems for biomimetic development and hope this Review will attract more attention to this emerging research branch at the intersection of assembly chemistry and biological science.

The hard life of an octopus embryo is seen through gene expression, energy metabolism, and its ability to neutralize radical oxygen species

The reproductive process in Octopus maya was analyzed to establish the amount of reactive oxygen species that the embryos inherit from females, during yolk synthesis. At the same time, respiratory metabolism, ROS production, and the expression of some genes of the antioxidant system were monitored to understand the ability of embryos to neutralize maternal ROS and those produced during development. The results indicate that carbonylated proteins and peroxidized lipids (LPO) were transferred from females to the embryos, presumably derived from the metabolic processes carried out during yolk synthesis in the ovary. Along with ROS, females also transferred to embryos glutathione (GSH), a key element of the antioxidant defense system, thus facilitating the neutralization of inherited ROS and those produced during development. Embryos are capable of neutralizing ROS thanks to the early expression of genes such as catalase (CAT) and superoxide dismutase (SOD), which give rise to the synthesis of enzymes when the circulatory system is activated. Also, it was observed that the levels of the routine metabolic rate of embryos are almost as high as those of the maximum activity metabolism, which leads, on the one hand, to the elevated production of ROS and suggests that, at this stage of the life cycle in octopuses, energy production is maximum and is physically limited by the biological properties inherent to the structure of embryonic life (oxygen transfer through the chorion, gill surface, pumping capacity, etc.). Due to its role in regulating vascularization, a high expression of HIf-1A during organogenesis suggests that circulatory system development has begun in this phase of embryo development. The results indicate that the routine metabolic rate and the ability of O. maya embryos to neutralize the ROS are probably the maximum possible. Under such circumstances, embryos cannot generate more energy to combat the free radicals produced by their metabolism, even when environmental factors such as high temperatures or contaminants could demand excess energy.

Stable and Tunable Quantum Conductance in Spider-Silk-like Synaptic Device for Neurocomputing.

The quantum conductance (QC) behaviors in synaptic devices with stable and tunable conductance states are essential for high-density storage and brain-like neurocomputing (NC). In this work, inspired by the discontinuous transport of fluid in spider silk, a synaptic device composed of a silicon oxide nanowire network embedded with silicon quantum dots (Si-QDs@SiOx) is designed. The tunable QC behaviors are achieved in both the SET and RESET processes, and the QC states exhibit stable retention time exceeding 104 s in the synaptic device and show stable reproducibility after an interval of two months. The synaptic plasticity, including long-term potentiation/depression and Pavlovian conditioning function, is simulated based on the tunable conductance. The mechanism of stable and tunable QC behaviors is analyzed and clarified by beading effect of spider silk in Si-QDs@SiOx nanowires structure. The digit recognition capability of the device is evaluated by simulation using an artificial neural network consisting of the Si-QDs@SiOx-based synaptic device. These results provide insights into the development of neurocomputing systems with high classification accuracy.

Design and Application of Intelligent Subject System Based on TPACK Framework

With the continuous advancement of educational informatization deepening of teachers' professional development, educational technology ability has become a necessary quality and skill for college teachers. This article introduces the basic concept of the TPACK framework and the design concept of intelligent disciplinary systems and elaborates in detail on how to apply the TPACK framework to the design and development of intelligent disciplinary systems. Through case analysis, this article demonstrates the advantages of intelligent subject systems in improving teaching quality and promoting active learning among students. Finally, this article discusses the future development direction and application prospects of intelligent disciplinary systems. The intelligent subject system based on the TPACK framework provides a new teaching solution for the education field, which helps to promote the process of educational informatization and personalized teaching. Cultivate students' rigorous scientific literacy and good practice habits, and master standardized experimental analysis methods.

Measuring system resilience through a comparison of information- and flow-based network analyses

Quantifying the properties of complex, self-organizing systems is increasingly important for understanding the development and state of modern systems. Case studies have recommended sustainability frameworks predominately in literature, but little emphasis has been placed on methodological evaluation. Data availability is often an obstacle that constrains conventional flow-based network analysis, but a novel information-based technique (QtAC) developed by zu Castell and Schrenk overcomes these constraints by modelling interactions between agents as information transfers. This study compares the QtAC method to conventional flow analysis by applying both to the same 90-year dataset containing socio-economic data from the island of Samothraki, Greece. Resilience indicators, based on Ulanowicz’s ascendency analysis, are derived on both the information- and flow-based networks. We observe that the resulting dynamics of the information-based networks align closer with complex system dynamics as theorized by the adaptive cycle model. Additionally, we discuss how QtAC offers different interpretations of network indicators when compared to usual interpretations of flow analysis. Ultimately, QtAC is shown to provide an alternative for complex systems analysis if the data situation does not allow for conventional flow-analysis. Furthermore, we show that the combination of both approaches can yield valuable new insights.

A facile and scalable fabrication method of scrolled graphene/boron nitride-based van der Waals superlattice heterostructure materials for highly stable supercapacitor electrode application.

Due to the increasing demand for the development of efficient renewable energy supply systems to reduce the mismatch between energy demand and utilization, supercapacitors have attracted increasing attention in the energy industry. However, the development of energy storage electrode materials to be applied at the industrial level is still challenging due to the unsatisfactory durability and scalable production issues. This study suggested a facile and scalable one-pot fabrication method of using graphene/hexagonal boron nitride (G/BN)-based one-dimensional (1D) van der Waals superlattice heterostructures (vdWSLs) as highly stable electrode materials to enhance the energy storage performance by improving the mesopore volume content, specific surface area, electrical properties, and interfacial interaction between the stacked G/BN layers. The G/BN-based vdWSLs were fabricated by a simple scrolling process through the electromagnetic interaction between the attached magnetic iron oxide nanoparticles (Fe3O4 NPs) on the surface of a G/BN vdW heterostructure (vdWH) and the applied magnetic field. The investigation results demonstrate that the changed morphology of the fabricated G/Fe/BN(NS) strongly affects the fine pore distribution, electrochemical performance, and electrical properties. Consequently, as a synergistic effect of an increased mesopore volume content, specific surface area, and C-B-N heterojunction interfacial area, the fabricated G/Fe/BN(NS) electrode showed a 100% enhancement of specific capacitance (207 F g-1 at 0.5 A g-1) and almost 7 times enhancement of electrical conductivity (800 S cm-1) with a nearly 2.3 times increase of carrier mobility (716 cm2 V-1 s-1) compared to that of the G/Fe/BN electrode. Furthermore, it exhibited outstanding long-term cycling stability with almost 119% capacitance retention even after 100 000 charge-discharge cycles. These results suggest that G/Fe/BN(NS) has tremendous potential as an electrode to fabricate high-performance supercapacitors with excellent cycling stability.

Long-term effects on cardiorespiratory and behavioral responses in male and female rats prenatally exposed to cannabinoid.

Development of the respiratory system can be affected by the use of drugs during pregnancy, as the prenatal phase is highly sensitive to pharmacological interventions, resulting in long-term consequences. The deleterious effects of external cannabinoids during gestation may be related to negative interference in central nervous system formation, cardiorespiratory system function, and behavioral disorders. Nevertheless, the impact of external cannabinoids on cardiorespiratory network development, chemosensitivity, and its future consequences in adulthood is still unclear. We evaluated the effects of prenatal exposure to a synthetic cannabinoid (WIN 55,212-2, 0.5 mg.kg-1.day-1) on the cardiorespiratory control and panic-like behavior of male and female rats in adulthood. Exogenous cannabinoid exposure during pregnancy resulted in a sex-dependent difference in breathing control. Specifically, males showed increased chemosensitivity to CO2 and O2, while females exhibited decreased sensitivity. Altered cardiovascular control was evident, with prenatally treated males and females being more susceptible to hypertension and tachycardia under adverse environmental conditions. Moreover, WIN-treated males exhibited higher fragmentation of sleep episodes, while females displayed anxiolytic and panicolytic behavioral responses to CO2. However, no changes were observed in the mechanical component of the respiratory system, and there were no neuroanatomical alterations, such as changes in the expression of CB1 receptors in the brainstem or in the quantification of catecholaminergic and serotonergic neurons. These findings highlight that external interference in cannabinoid signaling during fetal development causes sex-specific long-lasting effects for the cardiorespiratory system and behavioral responses in adulthood.

Priority areas for the development of the health technology assessment system in Ukraine: survey results

Priority areas for the development of the health technology assessment system in Ukraine: survey results

Computer Vision―The Frontier of Modern Environmental Diagnostics: A Review

Computer vision (CV), in combination with various sensors and image analysis algorithms, is a frontier direction in diagnosing the state of the environment and its biogenic and abiogenic objects. The work generalizes scientific achievements and identifies scientific and technical problems in this area of research based on the conceptual system of analysis on the time axis: from implemented achievements as part of the past and present to original new solutions—the future. Our work gives an idea of three areas of application of CV in diagnosing the state of the environment: phenotype recognition in digital images, monitoring of living and abiogenic objects, and development of new methods for identifying pollution and its consequences. The advantages of CV, which can be attributed to scientific achievements in this field of research, are shown: an increase in the volume of analyzed samples, simultaneous analysis of several parameters of the object of observation, and leveling of subjective evaluation factors. The main CV problems currently solved are the accuracy of diagnostics and changing quality of the survey, identification of the object of analysis with minimal operator participation, simultaneous monitoring of objects of different quality, and development of software and hardware systems with CV. A promising direction for the future is to combine the capabilities of CV and artificial intelligence. Thus, the review can be useful for specialists in environmental sciences and scientists working in interdisciplinary fields.

Recommending Career Transitions to Job Seekers Using Earnings Estimates, Skills Similarity, and Occupational Demand

This paper describes a career recommendation algorithm that uses government administrative data to help job seekers discover new careers that similar job seekers have successfully switched to in the past. Algorithm development was motivated by workers and contractors who were displaced by the COVID-19 economic crisis and by workers in declining industries seeking new careers in growing ones. Traditional job boards available through state government websites list all available jobs but do little to remove uncertainty associated with moving to a new industry or occupation. Our recommendation algorithm can lower this uncertainty. It uses causal machine learning techniques and administrative data on the universe of individual-level employment histories and earnings to identify career transitions that have resulted in increased earnings and employment for previous job seekers. We combine these estimates with measures of skill similarity across occupations, derived from natural-language processing of millions of full-text job descriptions, and with occupational demand, as measured by nightly job posting volume. The algorithm parses applicant resumes and returns recommended careers that use similar skills, have available jobs, and are estimated to lead to higher earnings and employment. We have implemented our algorithm in production workforce development systems in five U.S. states.