Information Science Research Articles

Molecular mechanism elucidation of Ocimum basilicum as anticancer using system bioinformatic approach supported by in vitro assay

Breast cancer (BC) is a multifactorial disease involving many pathways and target molecules. Multi-target therapy through multi-compound herbal medicines is an alternative strategy to treat BC. In the present study, we elucidate the molecular mechanism of Ocimum basilicum (OB) as an anticancer agent using system bioinformatic approach and investigate its cytotoxic effect against MCF-7 cells. We performed network pharmacology (NP) and molecular docking studies to provide scientific information regarding the underlying anti-BC mechanism of OB. Based on topology parameters obtained from protein-protein interaction (PPI), we identified six potential targets that play a significant role in the network including SRC, PI3KCA, EGFR, ESR1, AKT1, and MAPK1. Furthermore, consensus docking suggested rutin, quercetin-3-O-diglucoside, and kaempferol-3-O-β-D-rutinoside as the potential compounds of OB. Moreover, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis demonstrated that the cytotoxic effect of OB might be related to the modulation of several pathways such as PI3K-Akt, VEGF, and HIF-1, breast cancer, and estrogen signaling pathways. The in vitro assay revealed that various extracts of OB demonstrated cytotoxic effects against MCF-7 with IC50 = 231 µg/mL (OB ethanolic extract), 408 µg/mL (OB methanolic extract), 479 µg/mL (OB ethyl acetate extract), 1887 µg/mL (OB n-hexanoic extract) and 767 µg/mL (OB butanolic extract) respectively.

OPTIMAL CLIMATE POLICY WITH NEGATIVE EMISSIONS

We can limit the future temperature impact of climate change in two ways: (i) reducing our use of CO2 emitting fuels as an energy source (abatement), and (ii) using negative emission technologies (NETs) to remove existing CO2 from the atmosphere (removal). Using a modification of the DICE model, we analyze the optimal use of these two policy responses to climate change. After calibrating the marginal costs of abatement and CO2 removal to the latest scientific information, we find that carbon removal must play a very large role in an optimal policy. If this policy is followed, we find that the Paris-Agreement 1.5–2[Formula: see text]C warming by 2100 target is not just aspirational, but optimal. When an important role is played by NETs to control global warming, the decrease in carbon emissions can be more gradual, reducing transition risk and social dislocations. We examine the impact on the economy of large-scale carbon removal programs, the potential for moral hazard and the logistical problems associated with the storage of the removed carbon.

Pharmacological interventions for preventing upper gastrointestinal bleeding in people admitted to intensive care units: a network meta-analysis

ObjectivesTo assess the efficacy and safety of pharmacological interventions for preventing upper gastrointestinal (GI) bleeding in people admitted to intensive care units (ICUs).Design and settingSystematic review and frequentist network meta-analysis...

Bismuth as a Z-Type Ligand: an Unsupported Pt-Bi Donor-Acceptor Interaction and its Umpolung by Reaction with H2.

Establishing unprecedented types of bonding interactions is one of the fundamental challenges in synthetic chemistry, paving the way to new (electronic) structures, physicochemical properties, and reactivity. In this context, unsupported element-element interactions are particularly noteworthy since they offer pristine scientific information about the newly identified structural motif. Here we report the synthesis, isolation, and full characterization of the heterobimetallic Bi/Pt compound [Pt(PCy3)2(BiMe2)(SbF6)] (1), bearing the first unsupported transitionmetal→bismuth donor/acceptor interaction as its key structural motif. 1 is surprisingly robust, its electronic spectra are interpreted in a fully relativistic approach, and it reveals an unprecedented reactivity towards H2.

The Impact of Scientific and Technological Information Resource Utilization on Breakthrough Innovation in Enterprises: The Moderating Role of Strategic Aggressiveness

This study aims to explore the relationship between the utilization of scientific and technological information resources and breakthrough innovation in enterprises, examining the moderating role of strategic aggressiveness in this relationship. Based on an investigation of 438,228 patent data from 2616 Chinese enterprises, we construct a theoretical framework of “strategy–capability–performance” and conduct an empirical study using a mixed-effects model. The results indicate that both the intensity and imbalance of scientific and technological information resource utilization have significant positive effects on breakthrough innovation in enterprises. Further analysis reveals that strategic aggressiveness plays a moderating role in the relationship between the utilization of scientific and technological information resources and breakthrough innovation. Additionally, heterogeneity analysis shows differences in the impact of scientific and technological information resource utilization on breakthrough innovation across different regions and ownership types. Specifically, the imbalance of scientific and technological information resource utilization in coastal areas has a greater impact on breakthrough innovation than in non-coastal areas, and the intensity of scientific and technological information resource utilization in state-owned enterprises has a greater impact on breakthrough innovation than in non-state-owned enterprises. The findings of this study provide important insights for enterprise innovation management, helping enterprises to more effectively utilize scientific and technological information resources to drive breakthrough innovation and promote sustainable and healthy development.

Unveiling the mechanism of essential oil action against skin pathogens: from ancient wisdom to modern science.

Essential oils are among the most well-known phyto-compounds, and since ancient times, they have been utilized in medicine. Over 100 essential oils have been identified and utilized as therapies for various skin infections and related ailments. While numerous commercial medicines are available in different dosage forms to treat skin diseases, the persisting issues include their side effects, toxicity, and low efficacy. As a result, researchers are seeking novel classes of compounds as substitutes for synthetic drugs, aiming for minimal side effects, no toxicity, and high efficacy. Essential oils have shown promising antimicrobial activity against skin-associated pathogens. This review presents essential knowledge and scientific information regarding essential oil's antimicrobial capabilities against microorganisms that cause skin infections. Essential oils mechanisms against different pathogens have also been explored. Many essential oils exhibit promising activity against various microbes, which has been qualitatively assessed using the agar disc diffusion experiment, followed by determining the minimum inhibitory concentration for quantitative evaluation. It has been observed that Staphylococcus aureus and Candida albicans have been extensively researched in the context of skin-related infections and their antimicrobial activity, including established modes of action. In contrast, other skin pathogens such as Staphylococcus epidermidis, Streptococcus pyogens, Propionibacterium acnes, and Malassezia furfur have received less attention or neglected. This review report provides an updated understanding of the mechanisms of action of various essential oils with antimicrobial properties. This review explores the anti-infectious activity and mode of action of essential against distinct skin pathogens. Such knowledge can be valuable in treating skin infections and related ailments.

Research visualization trends in research data management (RDM): a bibliometric analysis

Purpose This study aims to examine research visualization trends in research data management (RDM), analyzing factors such as contributions, publications, document types, authors and research areas, emphasizing the dynamic nature of RDM research in the scholarly landscape. Design/methodology/approach The study analyzed citation histories for 1,401 publications from 2001 to 2021 in the Web of Science database, extracting no restrictions on document type or language. Literature visualization tools such as Biblioshiny, VOSviewer, ScientoPy and MS Excel were used. The researchers explored institutional collaborations, data-centric trends and RDM frontiers. Findings The majority of RDM research is conducted by librarians and information scientists. Research on RDM has increased over the past 21 years, peaking in 2019. Among universities, Sheffield and Pittsburgh have the most productivity in RDM research, and the USA is the most productive country. Most productive authors are Aleixandre-Benavent-R and Da Silva Jr. RDM; however, improvement is still needed, especially at academic universities. Originality/value This study provides valuable insights into the published literature on RDM and identifies patterns of collaboration among researchers in RDM.

Research visualization trends in research data management (RDM): a bibliometric analysis

Purpose This study aims to examine research visualization trends in research data management (RDM), analyzing factors such as contributions, publications, document types, authors and research areas, emphasizing the dynamic nature of RDM research in the scholarly landscape. Design/methodology/approach The study analyzed citation histories for 1,401 publications from 2001 to 2021 in the Web of Science database, extracting no restrictions on document type or language. Literature visualization tools such as Biblioshiny, VOSviewer, ScientoPy and MS Excel were used. The researchers explored institutional collaborations, data-centric trends and RDM frontiers. Findings The majority of RDM research is conducted by librarians and information scientists. Research on RDM has increased over the past 21 years, peaking in 2019. Among universities, Sheffield and Pittsburgh have the most productivity in RDM research, and the USA is the most productive country. Most productive authors are Aleixandre-Benavent-R and Da Silva Jr. RDM; however, improvement is still needed, especially at academic universities. Originality/value This study provides valuable insights into the published literature on RDM and identifies patterns of collaboration among researchers in RDM.

Structuring and Recommendations for Research on the Construction of Intelligent Multi-Industry and Multihazard Emergency Planning Systems

During production and operation, enterprises are faced with occurrences of production accidents. One of the prerequisites for enterprises to achieve sustainable development is building an intelligent emergency command platform. To establish a scientific and advanced emergency management information system and address the challenges related to managing emergency plans to ensure production safety, such as ambiguous roles and responsibilities, inefficient application processes, independent resources, and slow responses by enterprises with multiple types of operations and disasters, an intelligent emergency command platform was built for multiple types of operations and disasters, and this platform was extended to include rescue steps. The structure and digital management of emergency plans under multiple coupled disasters and multipoint cogeneration were determined. Similar emergency plans were automatically recommended by crawler technology and an SVM algorithm based on a public information data lake, and the effectiveness of the plans was evaluated via a fuzzy analytic hierarchy process to promote the preparation of more efficient and scientific emergency plans. Finally, the analysis of pipeline leakage and emergency drill scenarios proved that the system is scientific and reliable. The results are of great significance for improving the deep integration of modern emergency-related information technology and emergency management businesses, promoting institutional and mechanical innovation, to provide a reference for other multibusiness enterprises, wchih can also be integrated into methods for urban safety and rescue.

Emerging technologies and higher education libraries: a bibliometric analysis of the global literature

PurposeThis paper explores emerging technologies in higher education libraries indexed in the Web of Science core collection and Scopus for the periods between 1994 and 2024 (January 18, 2024).Design/methodology/approachData from Web of Science (WoS) and Scopus databases were collected and combined using RStudio software. Once this was completed using RStudio, the combined Scopus and Web of Science Excel file was uploaded into Biblioshiny, an interactive web interface. The data was then categorized to illustrate contributions from authors, journals, countries and academic institutions across the globe.FindingsResults and findings related to publication growth trends, annual growth, core journals, impact and productivity of authors, most cited documents, collaborations, network mapping and country contributions on emerging technologies and higher education libraries are presented.Research limitations/implicationsThis topic requires further exploration as academic librarians are fast becoming integrated into the teaching and learning agenda of institutions globally.Practical implicationsHigher education libraries and library schools to promote the teaching identity of academic librarians by helping them improve their pedagogical and digital skills for online teaching.Social implicationsLibrary and information science schools need to fast track the integration of emerging technologies into the curriculum. Higher education libraries should consider the training of staff in order to keep abreast of emerging technologies. Library management must frame their policies and strategies in order to promote the use of emerging technologies in higher education libraries.Originality/valueThe current study is novel in that it explores emerging technologies and higher education libraries using combined data from Scopus and Web of Science. The topic of emerging technologies and higher education libraries is still developing and therefore is in its infancy. The research is useful for researchers, library management and library schools in the higher education sector globally.

Coupling Hyperbolic GCN with Graph Generation for Spatial Community Detection and Dynamic Evolution Analysis

Spatial community detection is a method that divides geographic spaces into several sub-regions based on spatial interactions, reflecting the regional spatial structure against the background of human mobility. In recent years, spatial community detection has attracted extensive research in the field of geographic information science. However, mining the community structures and their evolutionary patterns from spatial interaction data remains challenging. Most existing methods for spatial community detection rely on representing spatial interaction networks in Euclidean space, which results in significant distortion when modeling spatial interaction networks; since spatial community detection has no ground truth, this results in the detection and evaluation of communities being difficult. Furthermore, most methods usually ignore the dynamics of these spatial interaction networks, resulting in the dynamic evolution of spatial communities not being discussed in depth. Therefore, this study proposes a framework for community detection and evolutionary analysis for spatial interaction networks. Specifically, we construct a spatial interaction network based on network science theory, where geographic units serve as nodes and interaction relationships serve as edges. In order to fully learn the structural features of the spatial interaction network, we introduce a hyperbolic graph convolution module in the community detection phase to learn the spatial and non-spatial attributes of the spatial interaction network, obtain vector representations of the nodes, and optimize them based on a graph generation model to achieve the final community detection results. Considering the dynamics of spatial interactions, we analyze the evolution of the spatial community over time. Finally, using taxi trajectory data as an example, we conduct relevant experiments within the fifth ring road of Beijing. The empirical results validate the community detection capabilities of the proposed method, which can effectively describe the dynamic spatial structure of cities based on human mobility and provide an effective analytical method for urban spatial planning.

Chirality-Induced Magnet-Free Spin Generation in a Semiconductor.

Electrical generation and transduction of polarized electron spins in semiconductors (SCs) are of central interest in spintronics and quantum information science. While spin generation in SCs is frequently realized via electrical injection from a ferromagnet (FM), there are significant advantages in nonmagnetic pathways of creating spin polarization. One such pathway exploits the interplay of electron spin with chirality in electronic structures or real space. Here, utilizing chirality-induced spin selectivity (CISS), the efficient creation of spin accumulation in n-doped GaAs via electric current injection from a normal metal (Au) electrode through a self-assembled monolayer (SAM) of chiral molecules (α-helix l-polyalanine, AHPA-L), is demonstrated. The resulting spin polarization is detected as a Hanle effect in the n-GaAs, which is found to obey a distinct universal scaling with temperature and bias current consistent with chirality-induced spin accumulation. The experiment constitutes a definitive observation of CISS in a fully nonmagnetic device structure and demonstration of its ability to generate spin accumulation in a conventional SC. The results thus place key constraints on the physical mechanism of CISS and present a new scheme for magnet-free SC spintronics.

Tunable quantum emitters on large-scale foundry silicon photonics

Controlling large-scale many-body quantum systems at the level of single photons and single atomic systems is a central goal in quantum information science and technology. Intensive research and development has propelled foundry-based silicon-on-insulator photonic integrated circuits to a leading platform for large-scale optical control with individual mode programmability. However, integrating atomic quantum systems with single-emitter tunability remains an open challenge. Here, we overcome this barrier through the hybrid integration of multiple InAs/InP microchiplets containing high-brightness infrared semiconductor quantum dot single photon emitters into advanced silicon-on-insulator photonic integrated circuits fabricated in a 300 mm foundry process. With this platform, we achieve single-photon emission via resonance fluorescence and scalable emission wavelength tunability. The combined control of photonic and quantum systems opens the door to programmable quantum information processors manufactured in leading semiconductor foundries.

Structural violence, social suffering, and the COVID-19 syndemic: discourses and narratives on the margins of the state in Texas

While the repercussions of the novel Coronavirus or COVID-19 have been felt across the world over the past few years, the impact has not been consistent. Instead, it has been mediated by the systemic ways in which existing social and structural disparities have failed vulnerable populations globally. Drawing on document analysis and fifteen in-depth interviews (n=15) conducted among the key stakeholders in the city of San Antonio, South Central Texas, this paper reveals how structural violence worsened during the COVID-19 pandemic resulting in making it a syndemic pandemic of high rates of deaths and illnesses among the most vulnerable and disadvantaged groups. A grounded theory approach particularly revealed themes of social suffering such as low income and pre-existing medical conditions that contributed to higher mortality rates, the presence of racism and misinformation, the importance of trustworthy communication channels, and streamlined collaborative partnerships with clear and effective communication through all levels of the government, especially when communicating scientific information.

Artificial intelligence literacy: a proposed faceted taxonomy

Purpose The purpose of this paper is to propose a taxonomy of artificial intelligence (AI) literacy to support AI literacy education and research. Design/methodology/approach This study makes use of the facet analysis technique and draws upon various sources of data and information to develop a taxonomy of AI literacy. The research consists of the following key steps: a comprehensive review of the literature published on AI literacy research, an examination of well-known AI classification schemes and taxonomies, a review of prior research on data/information/digital literacy research and a qualitative and quantitative analysis of 1,031 metadata records on AI literacy publications. The KH Coder 3 software application was used to analyse metadata records from the Scopus multidisciplinary database. Findings A new taxonomy of AI literacy is proposed with 13 high-level facets and a list of specific subjects for each facet. Research limitations/implications The proposed taxonomy may serve as a conceptual AI literacy framework to support the critical understanding, use, application and examination of AI-enhanced tools and technologies in various educational and organizational contexts. Practical implications The proposed taxonomy provides a knowledge organization and knowledge mapping structure to support curriculum development and the organization of digital information. Social implications The proposed taxonomy provides a cross-disciplinary perspective of AI literacy. It can be used, adapted, modified or enhanced to accommodate education and learning opportunities and curricula in different domains, disciplines and subject areas. Originality/value The proposed AI literacy taxonomy offers a new and original conceptual framework that builds on a variety of different sources of data and integrates literature from various disciplines, including computing, information science, education and literacy research.

Artificial intelligence for library and information science education: using mnemonics to improve learning and retention

Purpose This paper aims to familiarize students and instructors in the field of library and information science (LIS) with some features and benefits of mnemonics in the context of learning artificial intelligence (AI). Design/methodology/approach A narrative review among literature exists on mnemonics, AI and library services. Findings In the field of LIS, the use of mnemonics can be highly beneficial for both students and instructors. Mnemonics can aid in the retention and recall of complex concepts, classification systems, information retrieval strategies, jargon learning and library memory that are fundamental to the field. In the field of AI, mnemonics can be a valuable tool for students learning complex algorithms, concepts and techniques. Mnemonics can help students remember key components of AI models, understand the underlying principles and apply them effectively in problem-solving. Originality/value To the best of the authors’ knowledge, this paper is among the first ones exploring the use of mnemonics for learning subject areas related to artificial intelligence in LIS.

Real influence: A novel approach to characterize the visibility of journals and publications

Abstract For the last fifty years, the journal impact factor (IF) has been the most prominent of all bibliometric indicators. Since the first Journal Citation Report was launched, the IF has been used, often improperly, to evaluate institutions, publications, and individuals. Its well-known significant technical limitations have not detracted from its popularity, and they contrast with the lack of consensus over the numerous alternatives suggested as complements or replacements. This paper presents a percentile distribution-based proposal for assessing the influence of scientific journals and publications that corrects several of the IF’s main technical limitations using the same set of documents as is used to calculate the IF. Nearly 400 journals of Library Science and Information Science and Biochemistry and Molecular Biology categories were analyzed for this purpose. The results show that the new indicator retains many of its predecessor’s advantages and adds benefits of its own: It is more accurate, more gaming-resistant, more complete, and less influenced by the citation window or extreme observations.

OSTEOARTHRITIS AND CARDIOVASCULAR DISEASES: ETIOLOGICAL AND CLINICAL-PATHOGENETIC RELATIONSHIPS, TREATMENT AND PREVENTION

In recent years, numerous studies have shown a link between osteoarthritis (OA) and cardiovascular disease (CVD). Comorbidity of one of these diseases is directly and significantly associated with an increased risk of developing another. Objective. Carrying out a critical analysis of the results ofstudies related to the relationship between CVD and OA, as well as an assessment of the possibilities of their joint prevention and treatment. Methods. Publications from the Google search system, electronic databases PubMed, Scopus, Web of Science and other relevant sources of scientific and medical information were analyzed. The results. The main pathogenetic explanation of the relationship between CVD and OA is the presence of systemic,slowly progressing inflammation, which becomes especially important in patients of older age groups. The similarity of the composition of pro-inflammatory cytokines in the development of both CVD and OA enhances pathological changes in the structure of comorbidity. CVD and OA share common pathological mechanisms, such as oxidative and metabolic stress, molecular factors of endothelial dysfunction, hyperlipidemia, and systemic and local vascular remodeling. At the same time, it was established that OA develops against the backgroundof CVD risk factors and progresses along with their accumulation. Special care should be taken when prescribing non-steroidal anti-inflammatory drugs (NSAIDs). The appointment of systemic forms of NSAIDs is not recommended for patientswith high and very high cardiovascular risk. Conclusions. In patients with both conditions, the risk of one is directly related to an increased risk of the other. Further study of the role of comorbiditiesin the pathogenesis of OA will expand the understanding of the integration of cardiovascular risk factors. These facts provide prospects for further studying the role of comorbidities in the pathogenesis of OA, expanding the understandingof the integration of cardiovascular risk factors and successful cardiovascular prevention and treatment of OA.

Prior Attitude, Individualism and Perceived Scientists’ Expertise

Abstract: On Chinese social media, the stigmatization of homosexuals is tightly connected to the belief that they have a higher risk of contraction than others. However, scientists’ estimation of such risks is selectively framed on media outlets, and could cause confusion about and even polarization around the topic. In the theoretical framework of motivated reasoning, the current study showcases a cognition-intention link in the processing of scientific information regarding homosexuals’ high HIV/AIDS prevalence in China. An online survey experiment ( N = 695) using different emphasis frames of the findings from a scientific report shows that ad hoc identification with homosexuals’ rights, and individualism, strongly moderates the direct effect of exposure to different messages on intention of message forwarding, and also the indirect effect mediated by the perception of scientists’ expertise.

Susceptibility to scientific misinformation and perception of news source reliability in secondary school students

In the current post-truth era, the ability to assess the reliability of information is an essential citizenship attribute. With nearly half of the present internet traffic estimated to be generated by bots, and misinformation being regularly weaponised by numerous parties for economic or political gain, it is imperative that citizens are equipped with the tools to discriminate facts from fiction, particularly for health- and science-related matters. The present study reports the results of a survey (n = 776) carried out to evaluate susceptibility to scientific misinformation and perception of news source reliability amongst students in an English secondary school. Two distinct scores were developed in order to differentially measure susceptibility to disinformation (i.e. deliberately false information) and unintentional misinformation (i.e. getting the facts wrong). Non-parametric analysis indicated that students’ misinformation (as measured by both scores) decreased significantly over the course of the 5 years of secondary education. Interestingly, the adolescents who took part in the survey exhibited considerably lower belief in common science-based conspiracy theories than the levels previously reported among British adults. Students indicated teachers as their most frequent choice of scientific news. While social media were also indicated as common news sources, students expressed awareness of the unreliability of the content available on social media. Analysis of the open answers indicated that students considered BBC as the most trustworthy source of scientific information, and TikTok as the least trustworthy.