Holistic Insights Research Articles

From isolation to linkage: Holistic insights into ecological risk induced by land use change

While landscape ecological risk assessment (LERA) has the potential to positively impact environmental concerns by informing land use policies, a holistic perspective has yet to be adopted in previous investigations of LERA in relation to land use change. To address this gap, our study introduces a novel research framework that applies landscape ecology principles and methodologies, utilizing the concept of ‘landscape’ as a bridge connecting ecological risk and land use change. Building on relevant literature, we propose three hypotheses regarding the systemic nature of ecological risks. We then elucidate the principles, logic, and methods of LERA and employ high-precision land-use data and landscape pattern metrics to evaluate ecological risks resulting from land-use changes in Xiapu County between 2009 and 2013. Our ecological risk and land use overlay analysis validates three assumptions regarding the systematic character of ecological risks: (1) ecological risks in a local area are influenced by more than just land use changes within its spatial boundaries, (2) similar land use shifts can have varying impacts on ecological risk over time, and (3) ecological risk change cannot be solely attributed to the change in land use type. Finally, based on our enhanced understanding of ecological risks, we propose policy recommendations for land use planning and development at both global and local spatial scales. Our study provides a comprehensive understanding of ecological risks and their relationships with land use change, offering valuable insights for policymakers and researchers.

Mechanistic insights into cardiovascular effects of ultrafine particle exposure: A longitudinal panel study

BackgroundUltrafine particle (UFP) has been linked with higher risks of cardiovascular diseases; however, the biological mechanisms remain to be fully elucidated. ObjectivesThis study aims to investigate the cardiovascular responses to short-term UFP exposure and the biological pathways involved. MethodsA longitudinal panel study was conducted among 32 healthy, non-smoking young adults in Shanghai, China, who were engaged in five rounds of follow-ups between December 2020 and November 2021. Individual exposures were calculated based on the indoor and outdoor real-time measurements. Blood pressure, arterial stiffness, targeted biomarkers, and untargeted proteomics and metabolomics were examined during each follow-up. Linear mixed-effect models were applied to analyze the exposure and health data. The differential proteins and metabolites were used for pathway enrichment analyses. ResultsShort-term UFP exposure was associated with significant increases in blood pressure and arterial stiffness. For example, systolic blood pressure increased by 2.10 % (95 % confidence interval: 0.63 %, 3.59 %) corresponding to each interquartile increase in UFP concentrations at lag 0–3 h, while pulse wave velocity increased by 2.26 % (95 % confidence interval: 0.52 %, 4.04 %) at lag 7–12 h. In addition, dozens of molecular biomarkers altered significantly. These effects were generally present within 24 h after UFP exposure, and were robust to the adjustment of co-pollutants. Molecular changes detected in proteomics and metabolomics analyses were mainly involved in systemic inflammation, oxidative stress, endothelial dysfunction, coagulation, and disturbance in lipid transport and metabolism. DiscussionThis study provides novel and compelling evidence on the detrimental subclinical cardiovascular effects in response to short-term UFP exposure. The multi-omics profiling further offers holistic insights into the underlying biological pathways.

Diurnal variation of air pollutants and their relationship with land surface temperature in Bengaluru and Hyderabad cities of India

Air pollution and Land Surface Temperature (LST) are crucial components of urban environments. As urbanization and industrialization increase, the two components affect the natural environment of the urban areas. The present study investigated the daytime and nighttime spatiotemporal distribution of air pollutants and examined their relationship with LST for Bengaluru and Hyderabad cities of India. Daytime/nighttime/seasonal/spatial variations of air pollutants and LST, sensitivity of air pollutant in affecting LST, relationship between air pollutants and LST, and hotspots/coldspots analysis for LST and air pollutants was carried out. The study utilized, air pollutants data of 5-years from air quality monitoring stations and LST data of overlapping period from MODIS satellite. PM2.5 exceeded the national and international air quality standards while all other parameters were within specified limits/guideline values, at both the cities. The study found that LST had maximum sensitivity towards PM2.5 and NO2 for both the cities indicating that both these parameters are more effective in causing changes in the LST values. High Urban Thermal Field Variance Index (UTFVI) values for urban areas demonstrated strong surface urban heat island (SUHI) during nighttime in both the cities. Pearson's correlation analysis showed that LST, at Hyderabad, was positively correlated with PM2.5 (r = 0.714) during daytime. Relationship of LST with all air pollutants and meteorological parameters was investigated simultaneously and very strong relationship of LST with all other parameters was observed for both daytime and nighttime for both the cities. The R2 values at Bengaluru were 0.98 and 0.92 for nighttime and daytime, respectively, while the corresponding values were 0.87 and 0.93, respectively for Hyderabad. Hotspot analysis showed that total area of hotspots/coldspots undergoes temporal variations and the corresponding area during daytime was higher/lower compared to nighttime for different parameters. The trend of increase/decrease of daytime area of hotspots/coldspots, over nighttime area, was also different from different parameters as well as it was observed different for both the cities. Overall, the present study provides holistic insights into the interaction between air pollutants and LST in urban contexts. By understating these interactions and variations it helps urban planning and policymaking mitigate the challenge of the rise in LST and air pollutants.

Adapting to Demographic Shifts: China's Policy Approaches in Mitigating Healthcare and Retirement Challenges Posed by Aging Populations

China is witnessing a profound demographic transformation marked by a swift rise in its elderly population, posing significant challenges to healthcare and retirement systems. This study investigates the multifaceted impact of this demographic shift, evaluating the effectiveness of government policies in mitigating these challenges. Driven by increased life expectancy and declining fertility rates, this demographic transition necessitates strategic policy responses. The central argument revolves around scrutinizing the efficacy of China's policies in addressing healthcare and retirement hurdles arising from this demographic change. The hypothesis posits that governmental initiatives, such as healthcare infrastructure investments, pension system reforms, and expanded healthcare coverage, will partially alleviate existing challenges. Moreover, the paper hypothesizes on the societal impact of these policies, aiming to enhance elderly individuals' quality of life, alleviate healthcare-related financial burdens, and stimulate economic growth while relieving social welfare pressures. Employing a literature analysis methodology, this study critically evaluates existing scholarly works, policy documents, and empirical studies. While acknowledging the present challenges, it anticipates potential disparities in medical resources, sustainability concerns in pension systems, and issues surrounding the social integration of the elderly as the aging population expands. Recommendations underscore the necessity for adaptive policies to sustainably address these challenges. Through a comprehensive approach, this paper analyzes current policies, forecasts their impact, and conjectures future challenges, aiming to provide holistic insights into the effectiveness of policies aimed at managing the intricacies of an aging population in China.

Therapeutic progress in relapsed/refractory multiple myeloma.

Improvement in the therapeutics for multiple myeloma (MM) has been continuously developed owing to the application of novel drugs and technologies in the last 20 years. The standard first-line therapy for MM consists of a three-drug induction regimen based on immunomodulatory drugs and proteasome inhibitors combined with autologous stem cell transplantation. However, MM remains incurable; therefore, therapies for relapsed/refractory MM (RRMM) are emerging and evolving rapidly. This study aimed to summarize and review the results of RRMM trials over the past 5 years to provide a holistic overview and insights for practitioners in related fields and to provide additional ideas for clinical trialists. This study shows that daratumumab and isatuximab continue to significantly advance as treatment options. Additionally, novel antibody drugs, such as elotuzumab and selinexor, as well as bispecific antibodies, teclistamab and talquetamab, are currently undergoing clinical research with promising outcomes. However, chimeric antigen receptor-T cell therapy targeting B-cell maturation antigen remains the optimal approach for MM treatment.

Macroeconomic impacts and co-benefits of deep-decarbonization in Thailand

The updated Nationally Determined Contributions (NDC) in 2022 of Thailand includes an aggressive GHG emission reduction target of 40% in 2030 from its baseline emissions. However, the macroeconomic impacts and co-benefits associated with reducing GHG emissions are not addressed. This study analyzes the macroeconomic implications and co-benefits of GHG emission reduction in Thailand to achieve the NDC and net zero emission (NZE) targets by 2050 using the AIM/Hub-Thailand model. This paper provides co-benefits for Thailand on ambitious long-term GHG emission reduction targets. Considering the co-benefit analysis in the policy documents will provide holistic insights on the positive impacts of GHG mitigation. Results show that Thailand would have to bear a GDP loss of 7.7% in 2050 compared to the BAU level if the net zero emissions need to be achieved. Fuel switching from fossil fuel to electricity in the demand side and improvement of technologies in the power sector also reduces air pollutant emissions. The increasing dependence on domestic energy supply in the NZE scenario will make the country less vulnerable to the fluctuating prices in the international energy market. In terms of trade-offs, the land use for sustainable biomass in both the NDC and NZE scenarios will be larger than in the BAU scenario. Results show better land use for biomass production and higher yields in agricultural production. Moreover, the achievement of NZE pathway will require effective usage of land area and better use of energy resources, thereby making the country more energy secure.

All for One and One for All: Dissecting PREMIERE’s Inclusive AKIS Stakeholder Engagement Strategy

Innovation is increasingly being considered a social process, more bottom-up and interactive, than top-down science to implementation. Projects funded at a European level under Cluster 6 of the Horizon Europe Work Programme, and EIP-AGRI Operational Groups at a national and regional level in each of the 27 EU Member States, reflect this by placing a greater focus on making the best use of different types of knowledge and complimentary expertise (practical, scientific, technical, organisational, etc.) through the Multi-actor Approach (MAA). A wealth of strategic management literature exists on good practice stakeholder engagement strategies which mobilise the necessary bidirectional and cross-sectoral knowledge exchange and idea generation required for successful co-innovation ecosystems. Its counterpart however, from an Agricultural Knowledge and Innovation Systems (AKIS) perspective, is largely absent. This method article addresses this disparity and gap in literature by describing a 5-step AKIS Stakeholder Engagement Strategy developed by the PREMIERE Horizon Europe Project to help co-create an ‘enabling environment’ to foster and ‘speed up’ innovation, knowledge sharing and digitisation in agriculture, forestry and related sectors through mutually beneficial interactions between an extensive and diverse network of AKIS actors (e.g. researchers, advisors, agri-businesses, farmers) at EU, National and regional level. The inclusive nature of the multi-staged stakeholder engagement strategy outlined in this paper, inspired by strategic management literature, helps close the innovation gap between policy, research and practice through genuine multi-actor dialogue, holistic insights and feedback from project inception to completion, thereby helping to build trusting, meaningful and lasting relationships of mutual respect amongst relevant AKIS stakeholders, ranging from policy makers to harder to reach groups ‘on-the ground’, in place of mere, one-off consultations. The resultant knowledge exchange will significantly contribute to meeting objectives and targets set out in the European Green Deal, EU Climate Policy, Common Agricultural Policy and Farm to Fork Strategy.

Advancing Intelligent Organ-on-a-Chip Systems with Comprehensive In Situ Bioanalysis.

In vitro models are essential to a broad range of biomedical research, such as pathological studies,drug development, and personalized medicine. As a potentially transformative paradigm for 3D in vitro models, organ-on-a-chip (OOC) technology has been extensively developed to recapitulate sophisticated architectures and dynamic microenvironments of human organs by applying the principles of life sciences and leveraging micro- and nanoscale engineering capabilities. A pivotal function of OOC devices is to support multifaceted and timely characterizationof cultured cellsand their microenvironments. However, in-depth analysis of OOC modelstypically requires biomedical assay procedures that are labor-intensive and interruptive. Herein,the latest advances toward intelligent OOC (iOOC) systems, where sensors integrated with OOC devices continuously report cellular and microenvironmental information for comprehensive in situ bioanalysis, are examined. It is proposed that the multimodal data in iOOC systems can support closed-loop control of the in vitromodels and offer holistic biomedical insights for diverse applications. Essential techniques for establishing iOOC systems are surveyed, encompassing in situ sensing, data processing, and dynamic modulation. Eventually, the future development of iOOC systems featuring cross-disciplinary strategies is discussed.

Processing Speed and Attentional Shift/Mental Flexibility in Patients with Stroke: A Comprehensive Review on the Trail Making Test in Stroke Studies.

The Trail Making Test (TMT) is one of the most commonly administered tests in clinical and research neuropsychological settings. The two parts of the test (part A (TMT-A) and part B (TMT-B)) enable the evaluation of visuoperceptual tracking and processing speed (TMT-A), as well as divided attention, set-shifting and cognitive flexibility (TMT-B). The main cognitive processes that are assessed using TMT, i.e., processing speed, divided attention, and cognitive flexibility, are often affected in patients with stroke. Considering the wide use of TMT in research and clinical settings since its introduction in neuropsychological practice, the purpose of our review was to provide a comprehensive overview of the use of TMT in stroke patients. We present the most representative studies assessing processing speed and attentional shift/mental flexibility in stroke settings using TMT and applying scoring methods relying on conventional TMT scores (e.g., time-to-complete part A and part B), as well as derived measures (e.g., TMT-(B-A) difference score, TMT-(B/A) ratio score, errors in part A and part B). We summarize the cognitive processes commonly associated with TMT performance in stroke patients (e.g., executive functions), lesion characteristics and neuroanatomical underpinning of TMT performance post-stroke, the association between TMT performance and patients' instrumental activities of daily living, motor difficulties, speech difficulties, and mood statue, as well as their driving ability. We also highlight how TMT can serve as an objective marker of post-stroke cognitive recovery following the implementation of interventions. Our comprehensive review underscores that the TMT stands as an invaluable asset in the stroke assessment toolkit, contributing nuanced insights into diverse cognitive, functional, and emotional dimensions. As research progresses, continued exploration of the TMT potential across these domains is encouraged, fostering a deeper comprehension of post-stroke dynamics and enhancing patient-centered care across hospitals, rehabilitation centers, research institutions, and community health settings. Its integration into both research and clinical practice reaffirms TMT status as an indispensable instrument in stroke-related evaluations, enabling holistic insights that extend beyond traditional neurological assessments.

Outlier item detection in bundle recommendation via the attention mechanism

Bundle recommendation offers users more holistic insights by recommending multiple compatible items at once. However, the intricate correlations between items, varied user preferences, and the pronounced data sparsity in combinations present significant challenges for bundle recommendation algorithms. Furthermore, current bundle recommendation methods fail to identify mismatched items within a given set, a process termed as “outlier item detection”. These outlier items are those with the weakest correlations within a bundle. Identifying them can aid users in refining their item combinations. While the correlation among items can predict the detection of such outliers, the adaptability of combinations might not be adequately responsive to shifts in individual items during the learning phase. This limitation can hinder the algorithm’s performance. To tackle these challenges, we introduce an encoder–decoder architecture tailored for outlier item detection. The encoder learns potential item correlations through a self-attention mechanism. Concurrently, the decoder garners efficient inference frameworks by directly assessing item anomalies. We have validated the efficacy and efficiency of our proposed algorithm using real-world datasets.

Holistic insights into carbon nanotubes and MXenes as a promising route to bio-sensing applications.

Essential biosensor use has become increasingly important in drug discovery and recognition, biomedicine, food safety, security, and environmental research. It directly contributed to the development of specialized, reliable diagnostic instruments known as biosensors, which use biological sensing components. Traditional biosensors have poor performance, so scientists need to develop advanced biosensors with promising selectivity, sensitivity, stability, and reusability. These are all parameter modifications associated with the characteristics of the sensing material. Carbon nanotubes (CNTs) and MXenes are promising as targeted sensing agents in advanced functional materials because of their promising chemical and physical properties and limited toxic effects. Based on available data and sensing performance, MXene is better for biosensing applications than CNTs. Because of their large specific surface area (SSA), superior electrical conductivity, and adaptable surface chemistry that facilitates simple functionalization and robust interactions with biomolecules, MXenes are typically regarded as the superior option for biosensors. Additionally, because of their hydrophilic nature, they are more suited to biological settings, which increases their sensitivity and efficacy in identifying biological targets. MXenes are more suitable for biosensing applications due to their versatility and compatibility with aquatic environments, even if CNTs have demonstrated stability and muscular mechanical strength. However, MXenes offer better thermal stability, which is crucial for applications in diverse temperature environments. This study reviews and compares the biosensing capabilities, synthesis methods, unique properties, and toxicity of CNTs and MXenes. Both nanomaterials effectively detect various pollutants in food, biological substances, and human bodies, making them invaluable in environmental monitoring and medical diagnostics. In conclusion, CNTs work better for biosensors that must be strong, flexible, and long-lasting under different conditions. MXenes, on the other hand, work better when chemical flexibility and compatibility with wet environments are essential.

Sanskrit Scriptures (Ancient Indian History) and Their Scientific Relevance in Modern Science

Abstract: Ancient Indian Science has a plethora of knowledge which include Vedas, Upanishads, Bhagavad Gita, and Puranas but limited online resources available to everyone. to Indian Ancient History preserves the truths of modern science and many justifications of present questions raised in the field of sciences. Most of these scriptures were written in 500-1500 BCE, an era which is believed to have lacked scientific knowledge and reasonings. Many of the Indian transcripts testify data and proofs evident in the Ancient Indian Literature. The Vedas contain intricate details about celestial bodies, their movements, and the concept of time, reflecting an advanced understanding of astronomy. Mathematical concepts, including geometry and algebraic principles, are discernible in texts like the Shulba Sutras. Moreover, Ayurveda, an ancient Indian medical system documented in Sanskrit, provides holistic insights into healthcare, emphasizing a balance of physical, mental, and spiritual well-being. The scriptures also exhibit ecological awareness, prescribing sustainable practices for harmonious coexistence with nature. Sushruta Samhita and other scriptures provide in depth details of utilization of every plant part for cure of diseases. This study encompasses reasonings and specific citing of exact verses of scientific findings found years before modern scientists. Further research will contribute in expansion of knowledge and help delve deeper into Ancient Indian Text.

Learner-Centered Analysis in Educational Metaverse Environments: Exploring Value Exchange Systems through Natural Interaction and Text Mining

Amid Education 4.0 and the Fourth Industrial Revolution, we explore the integration of self-directed learning within the metaverse. This study envisions empowered learners, merging the metaverse’s immersive potential with self-directed learning. Using text mining and co-occurrence analysis for student responses prompts questions about their preference over traditional methods. Text mining extracts nuanced insights from open-ended responses, surpassing structured data. Co-occurrence analysis reveals hidden concept relationships, enhancing student engagement and understanding. Beyond XR, the metaverse encompasses avatars, virtual experiences, and value systems. Educators navigate this landscape with text mining, shaping value exchange through engaging content. Integrating real-world experiences in the metaverse merges immersion and personalized learning. Challenges include data precision and semantic intricacies in co-occurrence graphs. Future solutions involve real- time adaptability and sentiment analysis for holistic insights into learner emotions. This study envisions a synergy of self- directed learning and the metaverse, bridging digital and physical realms. Learners navigate interconnected experiences, fostering autonomy. Uncovering the metaverse’s potential contributes to education for digitally adept learners.

Research Trends in Motivation and Weight Loss: A Bibliometric-Based Review

Obesity is a complex disease that, like COVID-19, has reached pandemic proportions. Consequently, it has become a rapidly growing scientific field, represented by an extensive body of research publications. Therefore, the aim of this study was to present the research trends in the scientific literature on motivation and weight loss. Because traditional knowledge synthesis approaches are not appropriate for analyzing large corpora of research evidence, we utilized a novel knowledge synthesis approach called synthetic knowledge synthesis (SKS) to generate new holistic insights into obesity research focusing on motivation. SKS is a triangulation of bibliometric analysis, bibliometric mapping, and content analysis. Using it, we analyzed the corpus of publications retrieved from the Scopus database, using the search string TITLE-ABS-KEY((obesity or overweight) and “weight loss” and motiv*) in titles, keywords, and abstracts, without any additional inclusion or exclusion criteria. The search resulted in a corpus of 2301 publications. The United States of America, the United Kingdom, and Australia were the most productive countries. Four themes emerged, namely, weight loss and weight-loss maintenance through motivational interventions, lifestyle changes supported by smart ICT, maintaining sustainable weight with a healthier lifestyle, and weight management on the level of primary healthcare and bariatric surgery. Further, we established that the volume of research literature is growing, as is the scope of the research. However, we observed a regional concentration of research and its funding in developed countries and almost nonexistent research cooperation between developed and less-developed countries.

Revolutionizing Application Monitoring : A Review of DizBoard's Unified Dashboard Approach

In today's software landscape, the continuous and flawless operation of applications stands as a pivotal requirement. The genesis of the "DizBoard: Server and Database Manager" project stemmed from a pressing necessity to guarantee the seamless functionality and resilience of client-server applications. This imperative emerged from firsthand encounters with the escalating intricacies inherent in modern application ecosystems. An exploration of the existing technological milieu unveiled a diverse array of tools and solutions dedicated to application monitoring. However, the discerned need for a unified dashboard catering to databases, web services, and application servers became increasingly apparent. Current fragmented solutions often resulted in monitoring gaps and an absence of holistic insights into overall application health. The implementation of the "DizBoard: Server and Database Manager" project is geared towards bridging these gaps, addressing limitations highlighted in the literature review. Through a fusion of frontend technologies, Python-backed backend logic, and the automation prowess of shell scripting, this endeavor endeavors to craft a unified dashboard offering real-time visibility into critical components' statuses. This review paper embarks on a journey to expound upon the aspirations and methodologies driving the "DizBoard" project. It aims not only to present a comprehensive view of application health but also to delineate the voids that prevailing technologies leave. Envisioned as a user-friendly and automated monitoring dashboard, "DizBoard: Server and Database Manager" aspires to redefine the paradigm of application health management. Its ultimate goal is to elevate reliability, proactively address issues, and ultimately augment user satisfaction in the realm of application management.

Rapid and highly efficient adsorption of dye and heavy metal on low-cost adsorbent derived from human feces and Chlorella vulgaris

Wastewater management is a pressing global concern, demanding effective, efficient, cost-friendly, and user-friendly solutions. Among the various methods available, adsorption has emerged as a practical choice. The primary culprits responsible for many human diseases in wastewater are heavy metals and dyes. In this study, we successfully harnessed low-cost biochar derived from human feces and Chlorella vulgaris to significantly accelerate and enhance the removal of heavy metals and dyes. Human feces and Chlorella vulgaris were transformed into biochar under three distinct conditions: biochar, Chlorella vulgaris, and a combination of both. Notably, these materials exhibited exceptional capabilities, removing heavy metals and dyes by as much as 98 % within a mere 10-minute timeframe. This material have adsorption capacity up to 56.8 mg/g for Mn and 20 mg/g for Methylene Blue. To comprehensively evaluate the performance of the optimal samples, we conducted a battery of tests, including performance assessments, sorption capacity measurements, exploration of five isotherm models, and kinetic analyses. Furthermore, we elucidated the sorption mechanisms through thorough characterizations of the materials using SEM, XRD, FTIR, and XRF, providing holistic insights into their properties. This study extends its relevance beyond the laboratory, offering valuable insights into future prospects and policy recommendations. In doing so, it serves as a pivotal resource for researchers and governmental bodies alike, facilitating progress in wastewater treatment and environmental policy development.

Predictors of preschoolers’ classroom engagement: teacher–child interactions, teacher–child relationships, and child’s self-control

ABSTRACT The study examined predictors (teacher–child interactions, teacher–child relationships, child’s self-control) of preschoolers’ classroom engagement (135 preschoolers, 15 East Tennessee classrooms). Hierarchical linear regression revealed child’s self-control significantly contributed to engagement. Teacher–child closeness enhanced engagement, but reverse-coded teacher–child conflict negatively impacted it after controlling teacher-child individualized interaction. Control variables included child gender, age, mother and father education. These findings offer holistic insights into preschoolers’ engagement mechanisms, aiding intervention program design. Discussions and practical applications of results are provided.

Unravelling barriers in high-tech technology start-ups: practical insights and solutions for healthcare enterprises

PurposeAlong with technology-based ecosystems, healthcare start-ups are expanding multi-fold. On the other hand, underlying uncertainties pose several challenges for these health-tech enterprises at macro-meso-micro level, influencing their business circumstances and profitability. The current study aims to comprehend the macro-, meso- and micro-level barriers that make it difficult for enterprises to set up healthcare technology start-ups. The study also observed the perceived effect of these challenges on firms' performance and cost structure over time. Using the theory of behaviour under uncertainty, the study revealed multiple systemic, sector-related, human and implementation barriers that hinder business growth and lead to uncertainties for health-tech start-ups.Design/methodology/approachUsing a grounded theory approach, the study collected the views of 51 health tech start-ups in the UK using an online participants pool. The data was collected using qualitative data techniques in the form of open-ended essays, and a content analysis using thematic coding process was conducted. The questions centered around the different institutional uncertainties or barriers while setting up or running a healthcare start-up.FindingsThe study revealed several macro-, meso- and micro-level barriers these technology-based enterprises perceive in the healthcare industry. These are recognised as systemic barriers, such as lack of funding and procedural issues; sector-related barriers, such as market-related impediments; human barriers, including psychological barriers and resistance to new technology; and implementation barriers, such as operational and personnel issues.Research limitations/implicationsThe study used qualitative, open-ended essay techniques to collect the data. Future studies may use a mixed-methods approach to provide holistic insights. The study is conducted in a single developed country, the UK. Future work may expand these findings by comparing developed market challenges with those of emerging markets and by assessing the viewpoints of healthcare start-ups.Practical implicationsThis research will assist the healthcare sector and government understand health tech start-up hurdles and uncertainty. Policymakers must assist start-ups and encourage entrepreneurial innovation. Regulating and enabling policies will help. The paper examines start-ups' macro, meso and micro uncertainties. Policymakers promoting sector entrepreneurship must consider these barriers while designing policy guidelines.Originality/valueThe study contributes to the existing literature on technology start-ups, particularly in the healthcare industry, and identifies significant barriers these start-ups face. The study synthesizes research on health-tech start-up uncertainty and bridges the gap between theory and practice by applying empirical findings.

Profiling of conserved orthologs and miRNAs for understanding their role in salt tolerance mechanism of Sesuvium portulacastrum L.

Sesuvium portulacastrum is a facultative halophyte capable of thriving in a saline environment. Despite molecular studies conducted to unravel its salt adaptation mechanism, there is a paucity of information on the role of salt-responsive orthologs and microRNAs (miRNAs) in this halophyte. Here, we searched the orthology to identify salt-responsive orthologs and miRNA targets of Sesuvium using the Arabidopsis genome. The relative fold change of orthologs, conserved miRNAs, and miRNA targets of Sesuvium was analyzed under 100mM (LS) and 250mM NaCl (HS) treatment at 24h using qRT-PCR. The comparison between the expression of Sesuvium orthologs and Arabidopsis orthologs (Arabidopsis eFP browser database) was used to identify differentially expressed genes. Upon salt treatment, we found that SpCIPK3 (1.95-fold in LS and 2.90-fold in HS) in Sesuvium roots, and SpNHX7 (1.61-fold in LS and 6.39-fold in HS) and, SpSTPK2 (2.54-fold in LS and 7.65-fold in HS) in Sesuvium leaves were upregulated in a salt concentration-specific manner. In Arabidopsis, these genes were either downregulated or did not show significant variation, implicating its significance in the halophytic nature of Sesuvium. Furthermore, miRNAs like miR394a, miR396a, and miR397a exhibited a negative correlation with their targets-Frigida interacting protein 1, Cysteine proteinases superfamily protein, and Putative laccase, respectively under different salt treatments. The study revealed that the high salt tolerance in Sesuvium is associated with distinct transcriptional reprogramming, hence, to gain holistic mechanistic insights, global-scale profiling is required.

Quantifying the Impact of Renewable Energy Research on Environmental Sustainability

The imperative of addressing environmental sustainability and energy security has propelled extensive research into renewable energy technologies. This study employs bibliometric analysis to explore the impact of renewable energy research on environmental sustainability. Utilizing data from Web of Science and Scopus, a comprehensive dataset of scholarly articles and patents was compiled. The methodology involves keyword formulation, citation analysis, and collaboration network evaluation, supplemented by VOSviewer analysis for network visualization. The analysis unveils thematic clusters, influential citations, and keyword occurrences, unravelling the multifaceted nature of renewable energy research. Six thematic clusters emerge, encompassing biomass utilization, climate change, economic growth, efficiency optimization, energy systems, and energy consumption. Key citations provide insights into modeling techniques, sustainability indicators, and environmental assessment methodologies. Frequent keywords, such as life cycle assessment and technology, underscore the core pillars of the field, while less frequent terms like climate change and electricity highlight vital concepts. The findings provide holistic insights into the growth, impact, and interconnections within renewable energy research, offering valuable guidance for policymakers, researchers, and stakeholders committed to advancing environmental sustainability through renewable energy solutions.