Agricultural chemical use and the rural-urban divide in Canada

Innovation is of fundamental importance for improving food production, as well as sustainability food production. Since 1960, food production has benefited from innovations in plant breeding technologies, fertilizer, chemicals and equipment. These innovations have dramatically increased food production, while the amount of land used has minimally increased. However, future food production increases are jeopardized from widening knowledge gaps between rural food producers and large urban food consuming populations. Over time, that gap has fueled disinformation. The development of disinformation business models contributes to urban consumers receiving inaccurate information about the importance of inputs essential to food production, resulting in political pressures being applied that are targeted at reductions in the use of many food production inputs. The use of chemicals are a frequent target of disinformation campaigns. This article examines how the lack of government clarity about the safe use of chemicals contributes to a lack of public information.

Chimeric antigens displaying GPR65 extracellular loops on a soluble scaffold enabled the discovery of antibodies, which recognized native receptor

GPR65 is a proton-sensing G-protein coupled receptor associated with multiple immune-mediated inflammatory diseases, whose function is relatively poorly understood. With few reagents commercially available to probe the biology of receptor, generation of an anti-GPR65 monoclonal antibody was desired. Using soluble chimeric scaffolds, such as ApoE3, displaying the extracellular loops of GPR65, together with established phage display technology, native GPR65 loop-specific antibodies were identified. Phage-derived loop-binding antibodies recognized the wild-type native receptor to which they had not previously been exposed, generating confidence in the use of chimeric soluble proteins to act as efficient surrogates for membrane protein extracellular loop antigens. This technique provides promise for the rational design of chimeric antigens in facilitating the discovery of specific antibodies to GPCRs.

When enough is enough: Introducing sufficiency corridors to put techno-economism in its place

Today's ecological crises are entwined with inequality dynamics, yet prevailing techno-economic approaches in climate research and policy fall short in addressing the ecological crisis as distributional crisis. Recognising the limitations of techno-economism, focused on markets (price adjustments) and technology (efficiency gains), this contribution introduces sufficiency corridors as a concept, research field, and policy approach. Sufficiency corridors represent the space between a floor of meeting needs and a ceiling of ungeneralisable excess, i.e. within the sufficiency corridor everyone has enough (to satisfy needs) while no one has too much (to endanger planetary boundaries and need satisfaction). Establishing such corridors entails a process over time that continuously narrows the gap between floors and ceilings, lifting the former and pushing down the latter by strengthening forms of consumption and production that contribute to need satisfaction while shrinking those that do not. The article discusses the profound implications of this approach for how societal reality is reproduced and/or changed, highlighting the need for decisions that eliminate options between and within sectors and in the realms of consumption and production. After addressing questions of decision-making and the potential to realise corridors, the contribution concludes that the growing scientific consensus to complement techno-economic approaches with sufficiency measures remains inadequate. Instead, the possibility of a transformation by design hinges on embedding techno-economism within and subordinating it to a sufficiency framework.

Recent advances towards point-of-care devices for fungal detection: Emphasizing the role of plasmonic nanomaterials in current and future technologies

Fungal infections are a significant global health problem, particularly affecting individuals with weakened immune systems. Moreover, as uncontrolled antibiotic and immunosuppressant use increases continuously, fungal infections have seen a dramatic increase, with some strains developing antibiotic resistance. Traditional approaches to identifying fungal strains often rely on morphological characteristics, thus owning limitations, such as struggles in identifying several strains or distinguishing between fungal strains with similar morphologies. This review explores the multifaceted impact of fungi infections on individuals, healthcare providers, and society, highlighting the often-underestimated economic burden and healthcare implications of these infections. In light of the serious constraints of traditional fungal identification methods, this review discusses the potential of plasmonic nanoparticle-based biosensors for fungal infection identification. These biosensors can enable rapid and precise fungal pathogen detection by exploiting several readout approaches, including various spectroscopic techniques, colorimetric and electrochemical assays, as well as lateral-flow immunoassay methods. Moreover, we report the remarkable impact of plasmonic Lab on a Chip technology and microfluidic devices, as they recently emerged as a class of advanced biosensors. Finally, we provide an overview of smartphone-based Point-of-Care devices and the associated technologies developed for detecting and identifying fungal pathogens.

Meta-analysis: eHealth literacy and attitudes towards internet/computer technology

OBJECTIVE

To explore the relationship between eHealth literacy and attitudes towards internet/computer (I/C) technology use in healthcare.

METHODS

Analysis of data from 16 cross-sectional studies, involving literature search from databases like PubMed, EBSCO, JMIR, up to April 2023. Studies were selected based on a quantitative cross-sectional design, with no restrictions on participant characteristics.

RESULTS

A significant positive correlation (0.36; 95% CI 0.37-0.38, p < 0.05) was found between eHealth literacy and positive attitudes towards I/C technology use. Age and regional differences, especially in participants over 50 and from Asian and Middle Eastern countries, were notable.

CONCLUSION

Lower eHealth literacy is associated with more negative attitudes towards I/C technology in healthcare. This trend is consistent across diverse demographics and regions.

Supercritical fluid technology as a sustainable alternative method for textile dyeing: An approach on waste, energy, and CO2 emission reduction

The clothing industry is considered one of the most polluting industries on the planet due to the high consumption of water, energy, chemicals/dyes, and high generation of solid waste and effluents. Faced with environmental concerns, the textile ennoblement sector is the most critical of the textile production chain, especially the traditional dyeing processes. As an alternative to current problems, dyeing with supercritical CO2 (scCO2) has been presented as a clean and efficient process for a sustainable textile future. Supercritical fluid dyeing (SFD) has shown a growing interest due to its significant impact on environmental preservation and social, economic, and financial gains. The main SFD benefits include economy and reuse of non-adsorbed dyes; reduction of process time and energy expenditure; capture of atmospheric CO2 (greenhouse gas); use and recycling of CO2 in SFD; generation of carbon credits; water-free process; effluent-free process; reduction of CO2 emission and auxiliary chemicals. Despite being still a non-scalable and evolving technology, SFD is the future of dyeing. This review presented a comprehensive overview of the environmental impacts caused by traditional processes and confronted the advantages of SFD. The SFD technique was introduced, along with its latest advances and future perspectives. Financial and environmental gains were also discussed.

Biomass gasification, catalytic technologies and energy integration for production of circular methanol: New horizons for industry decarbonisation

The Intergovernmental Panel on Climate Change (IPCC) recognises the pivotal role of renewable energies in the future energy system and the achievement of the zero-emission target. The implementation of renewables should provide major opportunities and enable a more secure and decentralised energy supply system. Renewable fuels provide long-term solutions for the transport sector, particularly for applications where fuels with high energy density are required. In addition, it helps reducing the carbon footprint of these sectors in the long-term. Information on biomass characteristics feedstock is essential for scaling-up gasification from the laboratory to industrial-scale. This review deals with the transformation biogenic residues into a valuable bioenergy carrier like biomethanol as the liquid sunshine based on the combination of modified mature technologies such as gasification with other innovative solutions such as membranes and microchannel reactors. Tar abatement is a critical process in product gas upgrading since tars compromise downstream processes and equipment, for this, membrane technology for upgrading syngas quality is discussed in this paper. Microchannel reactor technology with the design of state-of-the-art multifunctional catalysts provides a path to develop decentralised biomethanol synthesis from biogenic residues. Finally, the development of a process chain for the production of (i) methanol as an intermediate energy carrier, (ii) electricity and (iii) heat for decentralised applications based on biomass feedstock flexible gasification, gas upgrading and methanol synthesis is analysed.

Green manufacturing for achieving carbon neutrality goal requires innovative technologies: A bibliometric analysis from 1991 to 2022

Recent years have seen a significant increase in interest in green manufacturing as a key driver of global carbon-neutral efforts and sustainable development. To find the research hotspots of green manufacturing and reveal future research trends, this study reviewed and analyzed research articles from the Web of Science database on green manufacturing from 1991 to 2022 using a bibliometric method. The findings indicate a significant rise in the number of articles related to green manufacturing since the 2010s. Moreover, there has been an increase in the involvement of scholars from developing countries such as China and India in this field. Based on the literature review and bibliometric cluster analysis on green manufacturing, we believed that future research may continue following the lines of intelligent technology integration, adoption of frontier engineering techniques, and industry development in line with carbon reduction targets. A framework for future green manufacturing development is proposed, with a focus on Chinese policies. The framework could provide policy implications for developing countries looking to pursue opportunities for development in green manufacturing.

Deep mining of antibody phage-display selections using Oxford Nanopore Technologies and Dual Unique Molecular Identifiers

Antibody phage-display technology identifies antibody-antigen interactions through multiple panning rounds, but traditional screening gives no information on enrichment or diversity throughout the process. This results in the loss of valuable binders. Next Generation Sequencing can overcome this problem. We introduce a high accuracy long-read sequencing method based on the recent Oxford Nanopore Technologies (ONT) Q20 + chemistry in combination with dual unique molecular identifiers (UMIs) and an optimized bioinformatic analysis pipeline to monitor the selections. We identified binders from two single-domain antibody libraries selected against a model protein. Traditional colony-picking was compared with our ONT-UMI method. ONT-UMI enabled monitoring of diversity and enrichment before and after each selection round. By combining phage antibody selections with ONT-UMIs, deep mining of output selections is possible. The approach provides an alternative to traditional screening, enabling diversity quantification after each selection round and rare binder recovery, even when the dominating binder was > 99% abundant. Moreover, it can give insights on binding motifs for further affinity maturation and specificity optimizations. Our results demonstrate a platform for future data guided selection strategies.

Retrospective analysis of the main feedstocks for animal feed in the world: How the green revolution has affected their environmental performance over the last 60 years, from 1961 to 2021

At the end of the 1950s, studies began to create high-yield cultivars with the aim of increasing the supply of basic foods in the world, this action was called "green evolution". It was associated with the increase in the use of inputs to increase production levels, leading agriculture to a possible increase in environmental impacts and "harmful habits" of management. To characterize the historical damage of this action, it is necessary to use methods that generate universal results, capable of representing the world. Then, we use Life cycle assessment (LCA) to estimate the historical evolution of the environmental impacts of the two main feedstock for feed in the world, soybeans, and corn, from 1961 to 2021. To better understand the variation in their impacts, we consider the change in agricultural management when we use as a functional unit the amount of area needed to produce 1 kg of grain. Although emissions and impacts from agriculture, by area, have increased each decade, when considering productivity through the area/production ratio, we note that a number of emissions were avoided, along with impacts in all categories evaluated. Therefore, the development and use of technologies that modify the area/production ratio can contribute to avoiding environmental impacts.

Electronic knowledge books (eK-Books) as a medium to capitalise on and transfer scientific, engineering, operational, technological and craft knowledge

The capitalisation on and transfer of technological, engineering and scientific knowledge associated with empirical know-how is an important issue for the sustainability and development of manufacturing. Indeed, certain sectors of industry are facing the increasing ageing of the labour force, recruitment difficulties and high staff turnover, leading to a loss of knowledge and know-how. In a context of numerical and digital transition and the migration of processes to industry 4.0, one of major challenges manufacturers face today is their capacity to build intelligent platforms for acquiring, storing and transferring their know-how and knowledge. It is crucial to create new media and tools for staff training and development capable of capturing knowledge and reusing it to create a project history through expertise and data collection. This paper presents the methodology and guidelines for implementing electronic knowledge books (eK-Books), along with their uses. The eK-Book is a semantic web-based hypertext medium (channel) allowing stakeholders to capitalise on, structure and transfer knowledge by using concept maps, process maps, influence graphs, downloadable documents, web pages and hypermedia knowledge sheets. They are intended for engineers, expert or novice technicians, manufacturers, sector coordinators and plant managers, as well as trainers and learners. They are usable and manageable in all types of environments and with different levels of accessibility. This paper highlights (1) the transfer knowledge capacity of eK-Books and (2) their usability in two agri-food sectors namely (1) the cheese sector with protected designation of origin (PDO) and protected geographical indication (PGI), and (2) the butchery and cold meat sectors.

Recent advances in smart wearable sensors for continuous human health monitoring

In recent years, the biochemical and biological research areas have shown great interest in a smart wearable sensor because of its increasing prevalence and high potential to monitor human health in a non-invasive manner by continuous screening of biomarkers dispersed throughout the biological analytes, as well as real-time diagnostic tools and time-sensitive information compared to conventional hospital-centered system. These smart wearable sensors offer an innovative option for evaluating and investigating human health by incorporating a portion of recent advances in technology and engineering that can enhance real-time point-of-care-testing capabilities. Smart wearable sensors have emerged progressively with a mixture of multiplexed biosensing, microfluidic sampling, and data acquisition systems incorporated with flexible substrate and bodily attachments for enhanced wearability, portability, and reliability. There is a good chance that smart wearable sensors will be relevant to the early detection and diagnosis of disease management and control. Therefore, pioneering smart wearable sensors into reality seems extremely promising despite possible challenges in this cutting-edge technology for a better future in the healthcare domain. This review presents critical viewpoints on recent developments in wearable sensors in the upcoming smart digital health monitoring in real-time scenarios. In addition, there have been proactive discussions in recent years on materials selection, design optimization, efficient fabrication tools, and data processing units, as well as their continuous monitoring and tracking strategy with system-level integration such as internet-of-things, cyber-physical systems, and machine learning algorithms.

Review on ultrasonic technology enhanced biological treatment of wastewater

As a clean, sustainable and efficient technology of wastewater treatment, ultrasonic irradiation has gained special attention in wastewater treatment. It has been widely studied for degrading pollutants and enhancing biological treatment processes for wastewater treatment. This review focuses on the mechanism and updated information of ultrasonic technology to enhance biological treatment of wastewater. The mechanism involved in improving biological treatment by ultrasonic includes: 1) degradation of refractory substances and release carbon from sludges, 2) promotion of mass transfer and change of cell permeability, 3) facilitation of enzyme-catalyzed reactions and 4) influence of cell growth. Based on the above discussion, the effects of ultrasound on the enhancement of wastewater biological treatment processes can be categorized into indirect and direct ways. The indirect effect of ultrasonic waves in enhancing biological treatment is mainly achieved through the use of high-intensity ultrasonic waves. These waves can be used as a pretreatment to improve biodegradability of the wastewater. Moreover, the ultrasonic-treated sludge or its supernatant can serve as a carbon source for the treatment system. Low-intensity ultrasound is often employed to directly enhance the biological treatment of wastewater. The propose of this process is to improve activated sludge, domesticate polyphosphate-accumulating organisms, ammonia-oxidizing bacteria, and anammox bacteria, and achieve speedy start-up of partial nitrification and anammox. It has shown remarkable effects on maintaining stable operation, tolerating adverse conditions (i.e., low temperature, low C/N, etc.), resisting shock load (i.e., organic load, toxic load, etc.), and collapse recovery. These results indicate a promising future for biological wastewater treatment. Furthermore, virous ultrasonic reactor designs were presented, and their potential for engineering application was discussed.

Recent advances in swine wastewater treatment technologies for resource recovery: A comprehensive review

Swine wastewater (SW), characterized by highly complex organic and nutrient substances, poses serious impacts on aquatic environment and public health. Furthermore, SW harbors valuable resources that possess substantial economic potential. As such, SW treatment technologies place increased emphasis on resource recycling, while progressively advancing towards energy saving, sustainability, and circular economy principles. This review comprehensively encapsulates the state-of-the-art knowledge for treating SW, including conventional (i.e., constructed wetlands, air stripping and aerobic system) and resource-utilization-based (i.e., anaerobic digestion, membrane separation, anaerobic ammonium oxidation, microbial fuel cells, and microalgal-based system) technologies. Furthermore, this research also elaborates the key factors influencing the SW treatment performance, such as pH, temperature, dissolved oxygen, hydraulic retention time and organic loading rate. The potentials for reutilizing energy, biomass and digestate produced during the SW treatment processes are also summarized. Moreover, the obstacles associated with full-scale implementation, long-term treatment, energy-efficient design, and nutrient recovery of various resource-utilization-based SW treatment technologies are emphasized. In addition, future research prospective, such as prioritization of process optimization, in-depth exploration of microbial mechanisms, enhancement of energy conversion efficiency, and integration of diverse technologies, are highlighted to expand engineering applications and establish a sustainable SW treatment system.

Can new urbanization pilot policies promote green technology innovation in cities: Empirical evidence from China

The development of urbanization has brought new challenges to the ecological environment, and the promotion of green technology innovation and development is widely recognized as an essential method to achieve cities' economic benefits and environmental protection. This paper examines whether the new urbanization pilot policies (NUP) increase green technology innovation (GTI) from both theoretical and empirical perspectives. This paper examines the impact of new urbanization on GTI by analyzing data from 285 cities in China between 2010 and 2021, using the multi-period DID model with the implementation of NUP as an exogenous policy shock. The study results indicate that NUP significantly affects GTI, and the conclusion still holds after the parallel trend test, placebo test, and other robustness tests. Heterogeneity analysis shows that the NUP significantly enhances GTI in low environmental pollution, non-resource-based, Medium-sized, and Central Region cities. The test of moderating effect shows that NUP has a "linkage effect" with the government's environmental attention, financial investment in innovation, and regional talent pooling. The findings of this paper provide empirical evidence and decision-making reference for promoting NUP and sustainable development of cities.

Macro-micro exploration on dynamic interaction between aflatoxigenic Aspergillus flavus and maize kernels using Vis/NIR hyperspectral imaging and SEM technology

Aspergillus flavus and its toxic metabolites-aflatoxins infect and contaminate maize kernels, posing a threat to grain safety and human health. Due to the complexity of microbial growth and metabolic processes, dynamic mechanisms among fungal growth, nutrient depletion of maize kernels and aflatoxin production is still unclear. In this study, visible/near infrared (Vis/NIR) hyperspectral imaging (HSI) combined with the scanning electron microscope (SEM) was used to elucidate the critical organismal interaction at kernel (macro-) and microscopic levels. As kernel damage is the main entrance for fungal invasion, maize kernels with gradually aggravated damages from intact to pierced to halved kernels with A. flavus were cultured for 0-120 h. The spectral fingerprints of the A. flavus-maize kernel complex over time were analyzed with principal components analysis (PCA) of hyperspectral images, where the pseudo-color score maps and the loading plots of the first three PCs were used to investigate the dynamic process of fungal infection and to capture the subtle changes in the complex with different hardness of the maize matrix. The dynamic growth process of A. flavus and the interactions of fungus-maize complexes were explained on a microscopic level using SEM. Specifically, fungus morphology, e.g., hyphae, conidia, and conidiophore (stipe) was accurately captured on the microscopic level, and the interaction process between A. flavus and nutrient loss from the maize kernel tissues (i.e., embryo, and endosperm) was described. Furthermore, the growth stage discrimination models based on PLSDA with the results of CCRC = 100 %, CCRV = 97 %, CCRIV = 93 %, and the prediction models of AFB1 based on PLSR with satisfactory performance (R2C = 0.96, R2V = 0.95, R2IV = 0.93 and RPD = 3.58) were both achieved. In conclusion, the results from both macro-level (Vis/NIR-HSI) and micro-level (SEM) assessments revealed the dynamic organismal interactions in A. flavus-maize kernel complex, and the detailed data could be used for modeling, and quantitative prediction of aflatoxin, which would establish a theoretical foundation for the early detection of fungal or toxin contaminated grains to ensure food security.

Researching big IT in the UK National Health Service: A systematic review of theory-based studies

OBJECTIVE

To identify and discuss theory-based studies of large-scale health information technology programs in the UK National Health Service.

MATERIALS AND METHODS

Using the PRISMA systematic review framework, we searched Scopus, PubMed and CINAHL databases from inception to March 2022 for theory-based studies of large-scale health IT implementations. We undertook detailed full-text analyses of papers meeting our inclusion criteria.

RESULTS

Forty-six studies were included after assessment for eligibility, of which twenty-five applied theories from the information systems arena (socio-technical approaches, normalization process theory, user acceptance theories, diffusion of innovation), twelve from sociology (structuration theory, actor-network theory, institutional theory), while nine adopted other theories. Most investigated England's National Program for IT (2002-2011), exploring various technologies among which electronic records predominated. Research themes were categorized into user factors, program factors, process outcomes, clinical impact, technology, and organizational factors. Most research was qualitative, often using a case study strategy with a longitudinal or cross-sectional approach. Data were typically collected through interviews, observation, and document analysis; sampling was generally purposive; and most studies used thematic or related analyses. Theories were generally applied in a superficial or fragmentary manner; and articles frequently lacked detail on how theoretical constructs and relationships aided organization, analysis, and interpretation of data.

CONCLUSION

Theory-based studies of large NHS IT programs are relatively uncommon. As large healthcare programs evolve over a long timeframe in complex and dynamic environments, wider adoption of theory-based methods could strengthen the explanatory and predictive utility of research findings across multiple evaluation studies. Our review has confirmed earlier suggestions for theory selection, and we suggest there is scope for more explicit use of such theoretical constructs to strengthen the conceptual foundations of health informatics research. Additionally, the challenges of large national health informatics programs afford wide-ranging opportunities to test, refine, and adapt sociological and information systems theories.

Modeling the influence of connected vehicles on driving behaviors and safety outcomes in highway crash scenarios across varied weather conditions: A multigroup structural equation modeling analysis using a driving simulator experiment

Equipped with advanced sensors and capable of relaying safety messages to drivers, connected vehicles (CVs) hold the potential to reduce crashes. The goal of this study is to assess the impacts of CV technologies on driving behaviors and safety outcomes in highway crash scenarios under diverse weather conditions, including clear and foggy weather. A driving simulator experiment was conducted and the multigroup structural equation modeling (SEM) was employed to explore the complex interrelationships between the propensity of traffic conflicts, utilization of CV alerts, weather, psychological factors, driving behaviors, and other relevant variables for two different crash locations, namely a straight section and a horizontal curve. Two latent psychological factors including aggressiveness and unawareness were constructed from driving behavior as vehicles passed by crash scenes such as brake, throttle, steering angle, lane offset, and yaw. The SEM can measure latent psychological factors and model interrelationships concurrently through a single statistical estimation procedure. Results of the multigroup SEM showed that CV alerts could significantly reduce the unawareness on a horizontal curve and thus lower the propensity of traffic conflicts. Additionally, the overall effect of foggy weather on conflicts was found to be positive on a horizontal curve, despite the potential benefit of improving situational awareness. In contrast, the single group SEM failed to reveal any significant interrelationships in its structural model by pooling data from both crash locations. The obtained insights can guide the development of driving assistance systems, highlighting the necessity of customization considering weather conditions and location-specific factors.

The effect of virtual simulation technology applied to undergraduate teaching of periodontal probing

INTRODUCTION

The rise of virtual simulation technology and dental simulators has created a new pedagogical approach for undergraduate medical education. The purpose of this study is to evaluate the effect of virtual simulation (VS) technology on improving the students' comprehensive abilities in periodontal probing teaching in pre-practicum periodontology, such as increasing the accuracy of probing, tactile perception and performance on force control.

MATERIALS AND METHODS

Twenty students were randomly selected among the fourth-year students and equally divided into VS technology teaching group (VS group) and traditional teaching group (TT group) by drawing half lots. One day later, students were required to probe the periodontal pathology model. The consistency rate between PD measurements and PD reference values, time consumption and final exam scores were recorded and statistically analysed using an unpaired Student's t test and p < .05 was considered statistical significance. Finally, questionnaires relating to teaching methods evaluation and the fidelity of the digital VS training system were distributed to students and teachers.

RESULTS

VS group had a significantly higher consistency rate (72.976 ± 6.811%) than TT group (64.107 ± 4.988%, p = .004). To specify, the difference of consistency rates between the two groups in posterior teeth was larger than anterior teeth. Similarly, a larger difference was also found in proximal surfaces compared with buccal-lingual surfaces. As the pocket depth increased, the difference between the two groups increased too. These results indicated that VS is more efficient in complicated parts of periodontal probing teaching. In addition, students in VS group spent less time and gained a higher score than TT group (p < .05). The overall satisfaction rating in VS group was significantly higher than TT group. Lastly, teachers gave significant lower scores than students concerning the fidelity of VS system.

CONCLUSION

Although there are much to improve, VS technology has obvious advantages in periodontal probing teaching in pre-practicum periodontology.

Technology Use Among Older Adults and Their Caregivers: Cross-Sectional Survey Study

Background

Informal caregivers are called upon to provide substantial care, but more needs to be known about technology use among older adult and caregiver dyads.

Objective

This study described technology use among older adults and their caregivers, explored potential correlates of technology use, and highlighted implications for practice.

Methods

A cross-sectional survey was conducted among unpaid caregivers of older adults (n=486). Primary outcomes were self-reported technology (devices and functions) use among caregivers and their oldest care recipient. The concordance of technology use among caregivers and care recipients was also examined. Multivariable regression models were conducted separately for caregivers and care recipients.

Results

Greater proportions of caregivers used all examined technologies, except for the medication alerts or tracking function, than care recipients. Caregivers used an average of 3.4 devices and 4.2 functions, compared to 1.8 devices and 1.6 functions used by their care recipients. Among caregivers, younger age, higher income, and higher education were associated with more technology use (P<.05). Among care recipients, younger age, not having cognitive dysfunction, and caregiver's technology use were associated with more technology use (P<.05).

Conclusions

Understanding technology use patterns and device adoption across diverse caregiver and care recipient populations is increasingly important for enhancing geriatric care. Findings can guide recommendations about appropriate technology interventions and help providers communicate and share information more effectively with patients and their caregivers.

Planned behavior, social networks, and perceived risks: Understanding farmers' behavior toward precision dairy technologies

Precision dairy tools (PDT) can provide timely information on individual cow's physiological and behavioral parameters, which can lead to more efficient management of the dairy farm. Although the economic rationale behind the adoption of PDT has been extensively discussed in the literature, the socio-psychological aspects related to the adoption of these technologies have received far less attention. Therefore, this paper proposes a socio-psychological model that builds upon the theory of planned behavior and develops hypotheses regarding cognitive constructs, their interaction with the farmers' perceived risks and social networks, and their overall influence on adoption. These hypotheses are tested using a generalized structural equation model for (a) the adoption of automatic milking systems (AMS) on the farms and (b) the PDT that are usually adopted with the AMS. Results show that adoption of these technologies is affected directly by intention, and the effects of subjective norms, perceived control, and attitudes on adoption are mediated through intention. A unit increase in perceived control score is associated with an increase in marginal probability of adoption of AMS and PDT by 0.05 and 0.19, respectively. Subjective norms are associated with an increase in marginal probability of adoption of AMS and PDT by 0.009 and 0.05, respectively. These results suggest that perceived control exerts a stronger influence on adoption of AMS and PDT, particularly compared with their subjective norms. Technology-related social networks are associated with an increase in marginal probability of adoption of AMS and PDT by 0.026 and 0.10, respectively. Perceived risks related to AMS and PDT negatively affect probability of adoption by 0.042 and 0.16, respectively, by having negative effects on attitudes, perceived self-confidence, and intentions. These results imply that integrating farmers within knowledge-sharing networks, minimizing perceived risks associated with these technologies, and enhancing farmers' confidence in their ability to use these technologies can significantly enhance uptake.

Revolutionizing Personalized Protein Energy Malnutrition Treatment: Harnessing the Power of Chat GPT

Protein energy malnutrition (PEM) is a global public health concern, and personalized treatment approaches are crucial for improved outcomes. This study explores the transformative potential of Chat GPT, an AI language model, in revolutionizing personalized treatment for PEM. By providing accurate information, personalized dietary recommendations, food choices, psychological counseling of the patient and real-time monitoring and support, Chat GPT can enhance the effectiveness of PEM interventions. Along with the benefits it is also important to acknowledge its potential flaws and limitations. The study emphasizes the importance of collaboration between AI technology and healthcare professionals to leverage Chat GPT's capabilities effectively. By combining human expertise with AI capabilities, personalized PEM treatment can be revolutionized, leading to improved patient outcomes and a comprehensive approach to addressing this global public health concern. The study highlights the significant impact of Chat GPT in providing tailored guidance and continuous support throughout the treatment process, empowering individuals and improving their overall well-being.

Pulsed electric field technology in vegetable and fruit juice processing: A review

The worldwide market for vegetable and fruit juices stands as a thriving sector with projected revenues reaching to $81.4 billion by 2024 and an anticipated annual growth rate of 5.27% until 2028. Juices offer a convenient means of consuming bioactive compounds and essential nutrients crucial for human health. However, conventional thermal treatments employed in the juice and beverage industry to inactivate spoilage and pathogenic microorganisms, as well as endogenous enzymes, can lead to the degradation of bioactive compounds and vitamins. In response, non-thermal technologies have emerged as promising alternatives to traditional heat processing, with pulsed electric field (PEF) technology standing out as an innovative and sustainable choice. In this context, this comprehensive review investigated the impact of PEF on the microbiological, physicochemical, functional, nutritional, and sensory qualities of vegetable and fruit juices. PEF induces electroporation phenomena in cell membranes, resulting in reversible or irreversible changes. Consequently, a detailed examination of the effects of PEF process variables on juice properties is essential. Monitoring factors such as electric field strength, frequency, pulse width, total treatment time, and specific energy is important to ensure the production of a safe and chemically/kinetically stable product. PEF technology proves effective in microbial and enzymatic inactivation within vegetable and fruit juices, mitigating factors contributing to deterioration while maintaining the physicochemical characteristics of these products. Furthermore, PEF treatment does not compromise the content of substances with functional, nutritional, and sensory properties, such as phenolic compounds and vitamins. When compared to alternative processing methods, such as mild thermal treatments and other non-thermal technologies, PEF treatment consistently demonstrates comparable outcomes in terms of physicochemical attributes, functional properties, nutritional quality, and overall safety.

A systematic review of the use of in-vehicle telematics in monitoring driving behaviours

BACKGROUND

Road traffic deaths are increasing globally, and preventable driving behaviours are a significant cause of these deaths. In-vehicle telematics has been seen as technology that can improve driving behaviour. The technology has been adopted by many insurance companies to track the behaviours of their consumers. This systematic review presents a summary of the ways that in-vehicle telematics has been modelled and analysed.

METHODOLOGY

Electronic searches were conducted on Scopus and Web of Science. Studies were only included if they had a sample size of 10 or more participants, collected their data over at least multiple days, and were published during or after 2010. 45 relevant papers were included in the review. 27 of these articles received a rating of "good" in the quality assessment.

RESULTS

We found a divide in the literature regarding the use of in-vehicle telematics. Some articles were interested in the utility of in-vehicle telematics for insurance purposes, while others were interested in determining the influence that in-vehicle telematics has on driving behaviour. Machine learning analyses were the most common forms of analysis seen throughout the review, being especially common in articles with insurance-based outcomes. Acceleration, braking, and speed were the most common variables identified in the review.

CONCLUSION

We recommend that future studies provide the demographical information of their sample so that the influence of in-vehicle telematics on the driving behaviours of different groups can be understood. It is also recommended that future studies use multi-level models to account for the hierarchical structure of the telematics data. This hierarchical structure refers to the individual trips for each driver.

A study on the impact of ESG rating on green technology innovation in enterprises: An empirical study based on informal environmental governance

Improving corporate green technology innovation is a key link in achieving green transformation and development. Compared with formal environmental regulations that force companies to carry out green innovation passively, ESG ratings under soft environmental regulations can better stimulate the internal motivation of companies. This study uses the ESG ratings of listed companies published for the first time by SynTao Green Finance as an exogenous impact. Taking China's A-share listed companies from 2011 to 2022 as a research sample, the multi-period differences-in-differences model was used to empirically test the impact of ESG rating soft supervision on corporate green technology innovation. The results show that the impact of ESG rating events as a soft market regulation has a significant positive impact on the improvement of corporate green technology innovation. This conclusion still holds after a series of robustness tests. Meanwhile, enterprise digital transformation plays a positive regulatory role. The heterogeneity test shows that the green technology innovation of state-owned enterprises is more affected by ESG ratings. Mechanism research has found that ESG rating events promote corporate green technology innovation by easing corporate financing constraints and reducing managerial myopia. Further research found that under the influence of the external environment, intensified market competition and increased attention from the capital market are also conducive to the improvement of corporate green technology innovation. This study strengthens the corporate ESG concept under the guidance of green development and provides empirical evidence for promoting corporate green transformation.

The Promise of Artificial Intelligence-Assisted Point-of-Care Ultrasonography in Perioperative Care

The role of point-of-care ultrasonography in the perioperative setting has expanded rapidly over recent years. Revolutionizing this technology further is integrating artificial intelligence to assist clinicians in optimizing images, identifying anomalies, performing automated measurements and calculations, and facilitating diagnoses. Artificial intelligence can increase point-of-care ultrasonography efficiency and accuracy, making it an even more valuable point-of-care tool. Given this topic's importance and ever-changing landscape, this review discusses the latest trends to serve as an introduction and update in this area.

Expanding the horizon of transient CAR T therapeutics using virus-free technology

The extraordinary success that chimeric antigen receptor (CAR) T cell therapies have shown over the years on fighting hematological malignancies is evidenced by the six FDA-approved products present on the market. CAR T treatments have forever changed the way we understand cellular immunotherapies, as current research in the topic is expanding even outside the field of cancer with very promising results. Until now, virus-based strategies have been used for CAR T cell manufacturing. However, this methodology presents relevant limitations that need to be addressed prior to wide spreading this technology to other pathologies and in order to optimize current cancer treatments. Several approaches are being explored to overcome these challenges such as virus-free alternatives that additionally offer the possibility of developing transient CAR expression or in vivo T cell modification. In this review, we aim to spotlight a pivotal juncture in the history of medicine where a significant change in perspective is occurring. We review the current progress made on viral-based CAR T therapies as well as their limitations and we discuss the future outlook of virus-free CAR T strategies to overcome current challenges and achieve affordable immunotherapies for a wide variety of pathologies, including cancer.

Review of osmotic dehydration: Promising technologies for enhancing products' attributes, opportunities, and challenges for the food industries

Osmotic dehydration (OD) is an efficient preservation technology in that water is removed by immersing the food in a solution with a higher concentration of solutes. The application of OD in food processing offers more benefits than conventional drying technologies. Notably, OD can effectively remove a significant amount of water without a phase change, which reduces the energy demand associated with latent heat and high temperatures. A specific feature of OD is its ability to introduce solutes from the hypertonic solution into the food matrix, thereby influencing the attributes of the final product. This review comprehensively discusses the fundamental principles governing OD, emphasizing the role of chemical potential differences as the driving force behind the molecular diffusion occurring between the food and the osmotic solution. The kinetics of OD are described using mathematical models and the Biot number. The critical factors essential for optimizing OD efficiency are discussed, including product characteristics, osmotic solution properties, and process conditions. In addition, several promising technologies are introduced to enhance OD performance, such as coating, skin treatments, freeze-thawing, ultrasound, high hydrostatic pressure, centrifugation, and pulsed electric field. Reusing osmotic solutions to produce innovative products offers an opportunity to reduce food wastes. This review explores the prospects of valorizing food wastes from various food industries when formulating osmotic solutions for enhancing the quality and nutritional value of osmotically dehydrated foods while mitigating environmental impacts.

Potential for GPT Technology to Optimize Future Clinical Decision-Making Using Retrieval-Augmented Generation

Advancements in artificial intelligence (AI) provide many helpful tools for healthcare, one of which includes AI chatbots that use natural language processing to create humanlike, conversational dialog. These chatbots have general cognitive skills and are able to engage with clinicians and patients to discuss patients' health conditions and what they may be at risk for. While chatbot engines have access to a wide range of medical texts and research papers, they currently provide high-level, generic responses and are limited in their ability to provide diagnostic guidance and clinical advice to patients on an individual level. The essay discusses the use of retrieval-augmented generation (RAG), which can be used to improve the specificity of user-entered prompts and thereby enhance the detail in AI chatbot responses. By embedding more recent clinical data and trusted medical sources, such as clinical guidelines, into the chatbot models, AI chatbots can provide more patient-specific guidance, faster diagnoses and treatment recommendations, and greater improvement of patient outcomes.

Efficacy of information and communication technology interventions for the management of diabetes mellitus: An umbrella review and evidence map

INTRODUCTION

We validated the quality of evidence and potential benefits of information and communication technology interventions on diabetes-related health outcomes.

METHODS

We systematically searched PubMed/MEDLINE, Embase, Google Scholar, and CINAHL and manually searched the reference lists of the retrieved review articles from each database's inception to October 2022. Randomized controlled trials were included to determine the benefits of information and communication technology interventions on diabetes outcomes.

RESULTS

Ten meta-analyses of randomized controlled trials were included, with 37 unique outcomes encompassing 379 studies and >70,000 participants across 47 countries and six continents. Information and communication technology intervention was associated with reduced HbA1c levels in patients with type 1 (moderate certainty), type 2 (moderate certainty), and gestational diabetes (low certainty) and showed potential benefits for type 2 diabetes, demonstrating a reduction in systolic blood pressure (high certainty), low-density lipoprotein cholesterol (low certainty), and body weight (low certainty), whereas those for gestational diabetes demonstrated a reduction in fasting (low certainty) and 2-h postprandial blood glucose levels (low certainty).

CONCLUSION

This umbrella review and evidence map revealed varying evidence on the potential benefits of information and communication technology interventions for diabetes-related outcomes. Our results demonstrate these interventions to be novel treatment options for policymakers and physicians to establish personalized health strategies.

Will advancement in technologies bring fear and damage human employment? Evidence from China's manufacturing industry

Advancement in technologies such as robotic industries and artificial intelligence bring fear among human being that jobs will be substituted by robots. Base on the panel data of 28 China's manufacturing industries, this research analyzed the impact of technical progress bias on employment. First, we calculate the technical progress bias index of 28 industries base on the stochastic frontier model with transcendental logarithm function found 16 industries were toward the skilled labor while the remaining 12 industries were toward the unskilled labor. Second, the empirical results show that technical progress bias has a positive impact on the total manufacturing employment and significant positive effect on the unskilled labor, while no significant impact on skilled labor employment. Third, the threshold effect test proves that if taking industry value-added per capita or R&D capital stock as threshold variable, the threshold about the impact exist, making the impact on skilled labor was insignificant.

Technological innovation for workload allocation in nursing care management: an integrative review

Background

Technology reduces the nursing workload, improve the quality care processes, patient's safety, and avoid staff burnout. Innovative technologies are disrupting healthcare systems by improving the efficiency of processes and management. There is a discussion on the benefits, challenges, and barriers of these technologies and considering human factors of nursing management. The aim was to analyze the influence of technologies on the distribution of workload for nursing care management.

Methods

An integrative literature review was performed. Four databases were searched: Scopus, Scielo, PUBMED, and CINALH following PRISMA guidelines. Articles published from January 2016 to December 2020, published in English, Spanish and Portuguese were included. Studies were excluded when they were not original research, did not met the quality criteria or they did not answer the research questions. Quality appraisal was performed using the Crowe Critical Appraisal Tool version 1.4 (CCAT). Two reviewers independently examined the title and abstract for eligibility according to the inclusion and exclusion criteria.

Results

2818 potentially relevant articles were found, but once the inclusion and exclusion criteria in the abstracts were analyzed, 177 remained for evaluation. After following the PRISMA Guidelines, 35 studies were included in the review. Three categories were identified: Nursing workload; Information technologies and technological means for management; Technology acceptance.

Conclusions

Technology has the potential to improve care management by estimating nurse workload in ICUs and non-critical units, but scientific evidence is more detailed in the former type of services. The literature provides insights about the factors that factors and the barriers that promote the technology acceptance and usability. We did not find studies comparing technologies and no scientific evidence proving improvements in care.

Medicine-Both a Science (Care) and an Art (CARE)

This Viewpoint discusses the concept of CARE (compassion, assistance, respect, and empathy) as a way physicians can practice the art of medicine in the current era of care that increasingly incorporates predictive analytics and artificial intelligence.

A dynamical perspective: moving towards mechanism in single-cell transcriptomics

As the field of single-cell transcriptomics matures, research is shifting focus from phenomenological descriptions of cellular phenotypes to a mechanistic understanding of the gene regulation underneath. This perspective considers the value of capturing dynamical information at single-cell resolution for gaining mechanistic insight; reviews the available technologies for recording and inferring temporal information in single cells; and explores whether better dynamical resolution is sufficient to adequately capture the causal relationships driving complex biological systems. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.

Optimizing Nucleic Acid Delivery Systems through Barcode Technology

Conventional biological experiments often focus on in vitro assays because of the inherent limitations when handling multiple variables in vivo, including labor-intensive and time-consuming procedures. Often only a subset of samples demonstrating significant efficacy in the in vitro assays can be evaluated in vivo. Nonetheless, because of the low correlation between the in vitro and in vivo tests, evaluation of the variables under examination in vivo and not solely in vitro is critical. An emerging approach to achieve high-throughput in vivo tests involves using a barcode system consisting of various nucleotide combinations. Unique barcodes for each variant enable the simultaneous testing of multiple entities, eliminating the need for separate individual tests. Subsequently, to identify crucial parameters, samples were collected and analyzed using barcode sequencing. This review explores the development of barcode design and its applications, including the evaluation of nucleic acid delivery systems and the optimization of gene expression in vivo.

Does the opening of producer services promote the wage growth of the downstream manufacturing industry?-Empirical evidence from Chinese manufacturing listed companies

Based on the vertical connection between upstream and downstream industries, a unique theoretical model is constructed to analyse the impact mechanism of the opening of producer services on downstream manufacturing wage growth. The empirical tests are carried out using the data of China's manufacturing listed companies from 1999 to 2020. Our findings indicate that the opening of producer services has an inverted-U-shaped impact on downstream manufacturing wage growth, and the average level of the opening of producer services in the sample period is lower than the corresponding threshold. Overall, it is in the stage of promoting the wage growth of the downstream manufacturing industry. The opening of producer services mainly affects the wage growth of the downstream manufacturing industry through two channels: labour productivity and labour income share. The results of heterogeneity analysis show that the wages of capital and technology-intensive and low-competitive manufacturing industries are relatively strongly promoted by the opening of producer services. Therefore, promoting the orderly opening of producer services and strengthening the technological links between industries will help promote the wage growth of downstream manufacturing industries.

Can digital economy compensate the effect of aging on total factor productivity?

In China, the number of senior citizens has grown, along with the burden of old age, and aging has hampered economic growth. The advent of the digital age has led to the emergence of the digital economy as a new engine for economic growth. This paper uses DEA-Malmquist index model to measure the total factor productivity growth rate of 31 provinces in China from 2011 to 2021, and uses the moderating effects model to empirically investigate the relationship between the digital economy, aging and total factor productivity, and to verify whether the development of the digital economy can mitigate the negative impact of aging on total factor productivity. The results show that aging inhibits total factor productivity growth, and the digital economy can promote total factor productivity growth. Digital economy can alleviate the negative impact of aging on total factor productivity growth, and has a moderating effect. Digital economy plays a moderating role by improving the level of human capital and facilitating technological progress. The regional heterogeneity analysis shows that the moderating effect of the digital economy exists in the eastern and western regions and the southern region, but not in the central region and the northern region. Furthermore, the digital economy has a moderating effect on both the high and low aging groups. The research in this paper not only helps to evaluate the productivity effects of the digital economy, but also has important implications for finding ways to mitigate the negative effects of aging.

A model study of teaching method reform of computer laboratory course integrating internet of things technology

The Internet of Things (IoT) is gradually changing the way teaching and learning take place in on-campus programs. In particular, face capture services improve student concentration to create an efficient classroom atmosphere by using face recognition algorithms that support end devices. However, reducing response latency and executing face analysis services effectively in real-time is still challenging. For this reason, this paper proposed a pedagogical model of face recognition for IoT devices based on edge computing (TFREC). Specifically, this research first proposed an IoT service-based face capture algorithm to optimize the accuracy of face recognition. In addition, the service deployment method based on edge computing is proposed in this paper to obtain the best deployment strategy and reduce the latency of the algorithm. Finally, the comparative experimental results demonstrate that TFREC has 98.3% accuracy in face recognition and 72 milliseconds in terms of service response time. This research is significant for advancing the optimization of teaching methods in school-based courses, meanwhile, providing beneficial insights for the application of face recognition and edge computing in the field of education.

Exploring the impact of climate technology, financial inclusion and renewable energy on ecological footprint: Evidence from top polluted economies

Most South Asian countries' economies have grown dramatically during the past few decades. However, in light of their environmental sustainability goals, the quality of such growth performances by South Asian nations is called into doubt by the concurrent degradation in environmental quality. Consequently, reducing the environmental challenges these nations encounter is prioritized on the agendas of the relevant authorities. This study aimed to analyze the effect of the top 11 most polluted countries' levels of financial inclusion, technological innovation, consumption of renewable energy, and adoption of climate technology on environmental deterioration from 2000 to 2022. Therefore, this research aims to use cutting-edge panel data econometric techniques to investigate the factors contributing to high carbon footprints in the world's most polluted nations. The results support an inverted U-shaped relationship between economic growth and carbon footprints, crediting the environmental Kuznets curve concept. In addition, it has been shown that TECH, REC, and CT can reduce carbon footprints in both the short and long term, while GDP and financial inclusion only affect carbon footprints in the long term. The results further endorsed the pollution haven hypothesis by showing that GDP positively affects carbon footprint. As a result, leading polluting economies need to strengthen their financial sectors, create green technology, migrate to renewable energy, and limit financial inclusion to improve environmental quality.

Technology empowerment: Digital transformation and enterprise ESG performance-Evidence from China's manufacturing sector

In light of the long-term constraints posed by the "dual carbon" objective, can digital technology emerge as a transformative solution for enterprises to embark on a sustainable development trajectory? The existing body of research has yet to reach a consensus. In order to shed further light on the intricate relationship between digital transformation and ESG performance of enterprises, this study empirically examines the mechanisms and boundaries through which digital transformation influences ESG performance, based on observational data from A-share manufacturing listed companies in Shanghai Stock Exchange and Shenzhen Stock Exchange spanning from 2011 to 2021. The findings demonstrate that digital transformation exerts a significant positive impact on the ESG performance of manufacturing enterprises. Mechanism analysis reveals that the enabling effect of digital transformation primarily enhances company transparency, thereby fostering continuous improvements in ESG performance among manufacturing enterprises. The performance expectation gap will give rise to the phenomenon of "stop-loss in time" and impede the promotional impact of digital transformation. Further investigation into industrial characteristics and industry competition intensity indicates that state-owned enterprises and those operating within highly competitive environments experience more pronounced effects of digital transformation on their ESG performance. This study expands the mechanism and boundary of digital transformation on ESG performance of manufacturing enterprises, and provides a new perspective for manufacturing enterprises to realize the collaborative transformation of digital and green.

How does the external context affect an implementation processes? A qualitative study investigating the impact of macro-level variables on the implementation of goal-oriented primary care

BACKGROUND

Although the importance of context in implementation science is not disputed, knowledge about the actual impact of external context variables on implementation processes remains rather fragmented. Current frameworks, models, and studies merely describe macro-level barriers and facilitators, without acknowledging their dynamic character and how they impact and steer implementation. Including organizational theories in implementation frameworks could be a way of tackling this problem. In this study, we therefore investigate how organizational theories can contribute to our understanding of the ways in which external context variables shape implementation processes. We use the implementation process of goal-oriented primary care in Belgium as a case.

METHODS

A qualitative study using in-depth semi-structured interviews was conducted with actors from a variety of primary care organizations. Data was collected and analyzed with an iterative approach. We assessed the potential of four organizational theories to enrich our understanding of the impact of external context variables on implementation processes. The organizational theories assessed are as follows: institutional theory, resource dependency theory, network theory, and contingency theory. Data analysis was based on a combination of inductive and deductive thematic analysis techniques using NVivo 12.

RESULTS

Institutional theory helps to understand mechanisms that steer and facilitate the implementation of goal-oriented care through regulatory and policy measures. For example, the Flemish government issued policy for facilitating more integrated, person-centered care by means of newly created institutions, incentives, expectations, and other regulatory factors. The three other organizational theories describe both counteracting or reinforcing mechanisms. The financial system hampers interprofessional collaboration, which is key for GOC. Networks between primary care providers and health and/or social care organizations on the one hand facilitate GOC, while on the other hand, technology to support interprofessional collaboration is lacking. Contingent variables such as the aging population and increasing workload and complexity within primary care create circumstances in which GOC is presented as a possible answer.

CONCLUSIONS

Insights and propositions that derive from organizational theories can be utilized to expand our knowledge on how external context variables affect implementation processes. These insights can be combined with or integrated into existing implementation frameworks and models to increase their explanatory power.

Beyond the promise: Exploring the complex interactions of nanoparticles within biological systems

The exploration of nanoparticle applications is filled with promise, but their impact on the environment and human health raises growing concerns. These tiny environmental particles can enter the human body through various routes, such as the respiratory system, digestive tract, skin absorption, intravenous injection, and implantation. Once inside, they can travel to distant organs via the bloodstream and lymphatic system. This journey often results in nanoparticles adhering to cell surfaces and being internalized. Upon entering cells, nanoparticles can provoke significant structural and functional changes. They can potentially disrupt critical cellular processes, including damaging cell membranes and cytoskeletons, impairing mitochondrial function, altering nuclear structures, and inhibiting ion channels. These disruptions can lead to widespread alterations by interfering with complex cellular signaling pathways, potentially causing cellular, organ, and systemic impairments. This article delves into the factors influencing how nanoparticles behave in biological systems. These factors include the nanoparticles' size, shape, charge, and chemical composition, as well as the characteristics of the cells and their surrounding environment. It also provides an overview of the impact of nanoparticles on cells, organs, and physiological systems and discusses possible mechanisms behind these adverse effects. Understanding the toxic effects of nanoparticles on physiological systems is crucial for developing safer, more effective nanoparticle-based technologies.

Protein click chemistry and its potential for medical applications

A revolution in chemical biology occurred with the introduction of click chemistry. Click chemistry plays an important role in protein chemistry modifications, providing specific, sensitive, rapid, and easy-to-handle methods. Under physiological conditions, click chemistry often overlaps with bioorthogonal chemistry, defined as reactions that occur rapidly and selectively without interfering with biological processes. Click chemistry is used for the posttranslational modification of proteins based on covalent bond formations. With the contribution of click reactions, selective modification of proteins would be developed, representing an alternative to other technologies in preparing new proteins or enzymes for studying specific protein functions in different biological processes. Click-modified proteins have potential in diverse applications such as imaging, labeling, sensing, drug design, and enzyme technology. Due to the promising role of proteins in disease diagnosis and therapy, this review aims to highlight the growing applications of click strategies in protein chemistry over the last two decades, with a special emphasis on medicinal applications.

Trends in low temperature and non-thermal technologies for the degradation of persistent organic pollutants

The daunting effects of persistent organic pollutants on humans, animals, and the environment cannot be overemphasized. Their fate, persistence, long-range transport, and bioavailability have made them an environmental stressor of concern which has attracted the interest of the research community. Concerted efforts have been made by relevant organizations utilizing legislative laws to ban their production and get rid of them completely for the sake of public health. However, they have remained refractive in different compartments of the environment. Their bioavailability is majorly a function of different anthropogenic activities. Landfilling and incineration are among the earliest classical means of environmental remediation of waste; however, they are not sustainable due to the seepage of contaminants in landfills, the release of toxic gases into the atmosphere and energy requirements during incineration. Other advanced waste destruction technologies have been explored for the degradation of these recalcitrant pollutants; although, some are efficient, but are limited by high amounts of energy consumption, the use of organic solvents and hazardous chemicals, high capital and operational cost, and lack of public trust. Thus, this study has systematically reviewed different contaminant degradation technologies, their efficiency, and feasibility. Finally, based on techno-economic feasibility, non-invasiveness, efficiency, and environmental friendliness; radiation technology can be considered a viable alternative for the environmental remediation of contaminants in all environmental matrices at bench-, pilot-, and industrial-scale.

The first interactive science museum in Peru: the origin and creation of TECNO-ITINTEC, 1975-1979

This paper examines the development of the TECNO-ITINTEC museum, the first interactive science museum in Peru, which opened in 1979. The museum functioned under the Institute of Industrial Technology Research and Technical Standards (ITINTEC), a public institution established during the government of Velazco Alvarado. In 1975, Jorge Heraud became the president of ITINTEC's Board of Directors and proposed a science museum to inspire future generations of scientists. José Castro Mendívil joined as the exhibition's director and designer. Their motivation to open a museum coincided with the government's ideals for modernization and nationalization. This article analyzes various sources including newspapers, laws that regulated the institute, reports, and interviews with people involved in the museum to understand how science and politics intersected in TECNO-ITINTEC.

Metal oxide nanomaterials based electrochemical and optical biosensors for biomedical applications: Recent advances and future prospectives

The amalgamation of nanostructures with modern electrochemical and optical techniques gave rise to interesting devices, so-called biosensors. A biosensor is an analytical tool that incorporates various biomolecules with an appropriate physicochemical transducer. Over the past few years, metal oxide nanomaterials (MONMs) have significantly stimulated biosensing research due to their desired functionalities, versatile chemical stability, and low cost along with their unique optical, catalytic, electrical, and adsorption properties that provide an attractive platform for linking the biomolecules, for example, antibodies, nucleic acids, enzymes, and receptor proteins as sensing elements with the transducer for the detection of signals or signal amplifications. The signals to be measured are in direct proportionate to the concentration of the bioanalyte. Because of their simplicity, cost-effectiveness, portability, quick analysis, higher sensitivity, and selectivity against a broad range of biosamples, MONMs-based electrochemical and optical biosensing platforms are exhaustively explored as powerful early-diagnosis tools for point of care applications. Herein, we made a bibliometric analysis of past twenty years (2004-2023) on the application of MONMs as electrochemical and optical biosensing units using Web of Science database and the results of which clearly reveal the increasing number of publications since 2004. Geographical area distribution analysis of these publications shows that China tops the list followed by the United States of America and India. In this review, we first describe the electrochemical and optical properties of MONMs that are crucial for the creation of extremely stable, specific, and sensitive sensors with desirable characteristics. Then, the biomedical applications of MONMs-based bare and hybrid electrochemical and optical biosensing frameworks are highlighted in the light of recent literature. Finally, current limitations and future challenges in the field of biosensing technology are addressed.

Mesoporous Silica Nanoparticles-Enhanced Microarray Technology for Highly Sensitive Simultaneous Detection of Multiplex Foodborne Pathogens

Ensuring food safety is paramount for the food industry and global health concerns. In this study, we have developed a method for the detection of prevalent foodborne pathogenic bacteria, including Escherichia coli, Salmonella spp., Listeria spp., Shigella spp., Campylobacter spp., Clostridium spp., and Vibrio spp., utilizing antibody-aptamer arrays. To enhance the fluorescence signals on the microarray, the mesoporous silica nanoparticles (MSNs) conjugated with fluorescein, streptavidin, and seven detection antibodies-biotin were employed, forming fluorescein doped mesoporous silica nanoparticles conjugated with detection antibodies (MSNs-Flu-SA-Abs) complexes. The array pattern was designed for easy readability and enabled the simultaneous detection of all seven foodborne pathogens, referred to as the 7FP-biochip. Following the optimization of MSNs-Flu-SA-Abs complexes attachment and enhancement of the detection signal in fluorescent immunoassays, a high level of sensitivity was achieved. The detection limits for the seven pathogens in both buffer and food samples were 102 CFU/mL through visual screening, with fluorescent intensity quantification achieving levels as low as 20-34 CFU/g were achieved on the antibody-aptamer arrays. Our antibody-aptamer array offers several advantages, including significantly reduced nonspecific binding with no cross-reaction between bacteria. Importantly, our platform detection exhibited no cross-reactivity among the tested bacteria in this study. The multiplex detection of foodborne pathogens in canned tuna samples with spiked bacteria was successfully demonstrated in real food measurements. In conclusion, our study presents a promising method for detecting multiple foodborne pathogens simultaneously. With its high sensitivity and specificity, the developed antibody-aptamer array holds great potential for enhancing food safety and public health.