Digital resources integration under the knowledge management model: an analysis based on the structural equation model

Purpose

In the age of knowledge explosion, modern technology facilitates the acquisition, organization and effective dissemination of information to support academic research. To achieve long-term educational goals, integrating digital resources into a knowledge management model (KMM) has become a necessary prerequisite for university management. The proposed KMM aims to combine resources and technology to facilitate resource management, navigation and cross-database search for advanced research.

Design/methodology/approach

The published literature on digital resource integration was reviewed, and the status of resource organization was discussed with experts to compile research instruments together with the perspectives of serving professionals in universities. The data obtained was systematically processed to develop an integrated resource KMM. Data volume measurement was done with the SPSS software and AMOS was used for path analysis and modeling. After the conceptual model was developed, many assumptions were associated with it, and the software was run on the data set to validate the proposed theoretical model.

Findings

Library resources with four components (digital resources, information technology, financial planning and service promotion) have been successfully integrated into the knowledge management framework to organize resources and provide academic services for researchers. In addition to the organization of digital resources, the two components of knowledge management, such as the explicit knowledge of its technology-oriented nature and the tacit knowledge of its human-centered positions, remained useful to strengthen the integration process.

Practical implications

With the development of digital technology and the internet, information authentication, access and dissemination have become a complex task for information centers. As an integral part of modern digital libraries, the expansion of digital collections requires proper accessibility organization. Owing to the increasing number of digital resources, organization and management require thorough research and appropriate integration mechanisms. This integrated KMM helps to organize heterogeneous information resources and databases in libraries for long-term academic tasks.

Originality/value

Based on literature studies and discussions with academic experts, integration problems were identified, and raw data were obtained from the library management to find a solution. It is unique research owing to a lack of original work and extensive international literature on resource integration in connection with KMMs. This study has innovative findings that can add value to world literature.

Performance-based evaluation of academic libraries in the big data era

The concept of big data has been extensively considered as a technological modernisation in organisations and educational institutes. Thus, the purpose of this study is to determine whether the modified technology acceptance model (MTAM) is viable for evaluating the performance of librarians in the use of big data analytics in academic libraries. This study used an empirical research method for collecting data from 211 librarians working in Pakistan’s universities. On the basis of the findings of the MTAM analysis by structural equation modelling, the performances of the academic libraries were comprehended through the process of big data. The main influential components of the performance analysis in this study were the big data analytics capabilities, perceived ease of access and the usefulness of big data practices in academic libraries. Subsequently, the utilisation of big data was significantly affected by skills, perceived ease of access and the usefulness of academic libraries. The results also suggested that the various components of the academic libraries lead to effective organisational performance when linked to big data analytics.

Repurposing of respiratory drug theophylline against Candida albicans: mechanistic insights unveil alterations in membrane properties and metabolic fitness

AIMS

Drug repurposing is an attractive chemotherapeutic strategy that serves to make up for the inadequacy of current antifungal drugs. The present study aims to repurpose theophylline (THP) against Candida albicans. THP is a methylxanthine derived from cocoa beans and tea extracts, generally used as the first-line drug for asthma and other respiratory disorders.

METHODS AND RESULTS

We investigated the antifungal activity of THP against C. albicans and non-albicans species. Mechanistic insights revealed that THP induces membrane damage. Enhanced ionic disturbances and depleted ergosterol levels with the concomitant rise in membrane fluidity due to elevated flippase activity confirmed the membrane damaging effect. THP impeded the metabolic adaptability of C. albicans by inhibiting malate synthase and isocitrate lyase enzymes of the glyoxylate cycle. In vivo efficacy of THP was depicted by increased survival of C. albicans infected Caenorhabditis elegans model.

CONCLUSIONS

This study elucidates the antifungal potential of THP with mechanistic insights.

SIGNIFICANCE AND IMPACT OF THE STUDY

This study unveils the antifungal potential of THP, a known respiratory drug that can be further utilized for a wider range of applications such as combating fungal infections. The effect of THP with the known antifungal drugs can be exploited in the combinatorial drug approach for treating candidiasis.

A retrospective review of pregnancies on biologics for the treatment of dermatological conditions

Psoriasis often first presents in young adulthood, with the average age of diagnosis in women being 28 years, thus in the prime reproductive years. In addition, approximately 50% of pregnancies worldwide are unplanned. Although biologic therapies have revolutionized the treatment of moderate-to-severe psoriasis, there are no controlled studies of biologics in pregnant women. The increasing use of these agents in women of childbearing age highlights the need to further assess their safety during pregnancy. Postmarketing experience regarding the safety of these drugs is accumulating and being published, with largely reassuring results. We present our real-world experience of 17 pregnancies occurring in women on treatment with biologic agents for dermatological conditions to further add to the body of knowledge.

Study of Caspase 8 Inhibition for the Management of Alzheimer's Disease: A Molecular Docking and Dynamics Simulation

Alzheimer’s disease (AD) is the most common type of dementia and usually manifests as diminished episodic memory and cognitive functions. Caspases are crucial mediators of neuronal death in a number of neurodegenerative diseases, and caspase 8 is considered a major therapeutic target in the context of AD. In the present study, we performed a virtual screening of 200 natural compounds by molecular docking with respect to their abilities to bind with caspase 8. Among them, rutaecarpine was found to have the highest (negative) binding energy (−6.5 kcal/mol) and was further subjected to molecular dynamics (MD) simulation analysis. Caspase 8 was determined to interact with rutaecarpine through five amino acid residues, specifically Thr337, Lys353, Val354, Phe355, and Phe356, and two hydrogen bonds (ligand: H35-A: LYS353:O and A:PHE355: N-ligand: N5). Furthermore, a 50 ns MD simulation was conducted to optimize the interaction, to predict complex flexibility, and to investigate the stability of the caspase 8–rutaecarpine complex, which appeared to be quite stable. The obtained results propose that rutaecarpine could be a lead compound that bears remarkable anti-Alzheimer’s potential against caspase 8.

Cross-Talk Between Extracellular Matrix and Skeletal Muscle: Implications for Myopathies

Skeletal muscle (SM) comprises around 40% of total body weight and is among the most important plastic tissues, as it supports skeletal development, controls body temperature, and manages glucose levels. Extracellular matrix (ECM) maintains the integrity of SM, enables biochemical signaling, provides structural support, and plays a vital role during myogenesis. Several human diseases are coupled with dysfunctions of the ECM, and several ECM components are involved in disease pathologies that affect almost all organ systems. Thus, mutations in ECM genes that encode proteins and their transmembrane receptors can result in diverse SM diseases, a large proportion of which are types of fibrosis and muscular dystrophy. In this review, we present major ECM components of SMs related to muscle-associated diseases, and discuss two major ECM myopathies, namely, collagen myopathy and laminin myopathies, and their therapeutic managements. A comprehensive understanding of the mechanisms underlying these ECM-related myopathies would undoubtedly aid the discovery of novel treatments for these devastating diseases.

Lead Optimization Resources in Drug Discovery for Diabetes

BACKGROUND

Diabetes, defined as a chronic metabolic syndrome, exhibits global prevalence and phenomenal rise worldwide. The rising incidence accounts for a global health crisis, demonstrating a profound effect on low and middle-income countries, particularly people with limited healthcare facilities.

METHODS

Highlighting the prevalence of diabetes and its socio-economic implications on the population across the globe, the article aimed to address the emerging significance of computational biology in drug designing and development, pertaining to identification and validation of lead molecules for diabetes treatment.

RESULTS

The drug discovery programs have shifted the focus on in silico prediction strategies minimizing prolonged clinical trials and expenses. Despite technological advances and effective drug therapies, the fight against life-threatening, disabling disease has witnessed multiple challenges. The lead optimization resources in computational biology have transformed the research on the identification and optimization of anti-diabetic lead molecules in drug discovery studies. The QSAR approaches and ADMET/Toxicity parameters provide significant evaluation of prospective "drug-like" molecules from natural sources.

CONCLUSION

The science of computational biology has facilitated the drug discovery and development studies and the available data may be utilized in a rational construction of a drug 'blueprint' for a particular individual based on the genetic organization. The identification of natural products possessing bioactive properties as well as their scientific validation is an emerging prospective approach in antidiabetic drug discovery.

N-Acetylaspartate Is an Important Brain Osmolyte

Most of the human diseases related to various proteopathies are confined to the brain, which leads to the development of various forms of neurological disorders. The human brain consists of several osmolytic compounds, such as N-Acetylaspartate (NAA), myo-inositol (mI), glutamate (Glu), glutamine (Gln), creatine (Cr), and choline-containing compounds (Cho). Among these osmolytes, the level of NAA drastically decreases under neurological conditions, and, hence, NAA is considered to be one of the most widely accepted neuronal biomarkers in several human brain disorders. To date, no data are available regarding the effect of NAA on protein stability, and, therefore, the possible effect of NAA under proteopathic conditions has not been fully uncovered. To gain an insight into the effect of NAA on protein stability, thermal denaturation and structural measurements were carried out using two model proteins at different pH values. The results indicate that NAA increases the protein stability with an enhancement of structure formation. We also observed that the stabilizing ability of NAA decreases in a pH-dependent manner. Our study indicates that NAA is an efficient protein stabilizer at a physiological pH.

An insight into molecular interaction of PGIP with PG for banana cultivar

PolyGalacturonase Inhibiting Proteins (PGIPs) are leucine rich repeat pathogenesis-related (PR) cell wall proteins, which interact and inhibit the PolyGalacturonase (PG), an enzyme secreted by the pathogen to degrade pectin. Interaction of PGIP with PG limits the vulnerability of PG by the activation of host defense response against pathogenic attack. Erwinia is gram-negative soft rot bacteria responsible for rhizome rot disease in banana and many other crop plants. The interaction of PG with PGIP is one of the crucial steps for plant-pathogen interaction. To study the molecular mechanism of PR proteins, we employed molecular modelling, protein-protein docking and molecular dynamics simulations of banana PGIP (bPGIP) with Erwinia carotovora PG (ecPG). Further, insilico site-directed mutagenesis was performed in Phaseolus vulgaris PGIP (pvPGIP2) to elucidate the interaction with ecPG. Docking and simulation studies divulge that binding of bPGIP and PvPGIP2 with active site residues of EcPG induces structural changes and thereby inhibit the enzyme. This study provides a unique insight into PG-PGIP interaction, which may help in the development of bacterial soft-rot resistant banana cultivars.

Pharmacophore-based approaches in the rational repurposing technique for FDA approved drugs targeting SARS-CoV-2 Mpro

Novel coronavirus (CoV) is the primary etiological virus responsible for the pandemic that started in Wuhan in 2019–2020. This viral disease is extremely prevalent and has spread around the world. Preventive steps are restricted social contact and isolation of the sick individual to avoid person-to-person transmission. There is currently no cure available for the disease and the search for novel medications or successful therapeutics is intensive, time-consuming, and laborious. An effective approach in managing this pandemic is to develop therapeutically active drugs by repurposing or repositioning existing drugs or active molecules. In this work, we developed a feature-based pharmacophore model using reported compounds that inhibit SARS-CoV-2. This model was validated and used to screen the library of 565 FDA-approved drugs against the viral main protease (M^pro), resulting in 66 drugs interacting with M^pro with higher binding scores in docking experiments than drugs previously reported for the target diseases. The study identified drugs from many important classes, viz. D₂ receptor antagonist, HMG-CoA inhibitors, HIV reverse transcriptase and protease inhibitors, anticancer agents and folate inhibitors, which can potentially interact with and inhibit the SARS-CoV-2 M^pro. This validated approach may help in finding the urgently needed drugs for the SARS-CoV-2 pandemic with infinitesimal chances of failure.

Novel coronavirus (CoV) is the primary etiological virus responsible for the pandemic that started in Wuhan in 2019–2020.

Correction: Pharmacophore-based approaches in the rational repurposing technique for FDA approved drugs targeting SARS-CoV-2 Mpro

Correction for ‘Pharmacophore-based approaches in the rational repurposing technique for FDA approved drugs targeting SARS-CoV-2 M^pro’ by Vishal M. Balaramnavar et al., RSC Adv., 2020, 10, 40264–40275, DOI: 10.1039/D0RA06038K.

Librarian’s perspective for the implementation of big data analytics in libraries on the bases of lean-startup model

Purpose

This study aims to propose a model based on philosophical thoughts of Dr S.R Ranganathan and the lean-startup method for the execution of big data analytics (BDA) in libraries. The research paves a way to understand the role and required competencies of Library and Information Science (LIS) professionals for the implementation of BDA in libraries.

Design/methodology/approach

In the BDA analytics context, a session with a proposed model was presented to the audience to get the response of librarians about the required competencies and skills. The research tool was developed based on the literature review to know the role of LIS professionals and their required competencies/skills for BDA. The questionnaire was distributed in the BDA session to collect the responses of the participating audience on the variables that focused on the role and core competencies of LIS professionals in BDA. In the analysis of results, the independent t-test was applied to know the mean value of the overall response rate.

Findings

The findings show that perceptions of LIS professionals in the understanding of BDA ranked high in data privacy, data availability, data organization and data literacy. Digital data curation, policies supervision and providing the data consultancy also showed a significant relationship among these variables. Besides, the correlation between the required skills for BDA, metadata skills, data ethics, data acquisition, data cleaning, data organization, data analysis, digital curation, data clustering, data protection rules and digital visualization also showed a beneficial relationship.

Originality/value

This study also helps to understand the perspective of LIS professionals for the implementation of BDA in libraries and to fill the literature gap in the respective.

Technology integration for students’ information and digital literacy education in academic libraries

Purpose

Digital literacy has become a widely studied topic for connecting people, participation in government and public affairs. It encourages library professionals to train students and effectively acquire, preserve and disseminate knowledge. Academic libraries involve using digital technology improved the students’ level of digital literacy and technological skills. This paper aims to understand the students’ technological competence in using database resources and searching for online information. In addition, to evaluate the training contents and designated instructors on digital literacy education, the study also focuses on digitally exposed students’ learning behavior, the library management and students’ academic interaction on new technological trends.

Design/methodology/approach

This study uses a quantitative method for which primary data were collected from university students using a structured research questionnaire. Through targeted random sampling techniques, 1,500 printed questionnaires were distributed among students, and 1,266 (84.4%) responses were received. The authors applied descriptive statistics to analyze the demographic information of male and female students. The statistical technique Chi-square test (χ2) was applied using SPSS to determine the association between variables. Moreover, Bonferroni correction for the new a value [modified = 0.05/number of possible comparisons/analysis for each question shown in Tables (II-IX)] was also used to avoid a family-wise error.

Findings

The results inferred a strong association between students’ technological skill with using digital tools, utilization of database resources and browsing networked information on the Web. The association between universities in terms of recruiting designated instructors on digital literacy education, introducing ICT based curriculum and the association between library management in maintaining a regular training program on digital literacy demonstrated a negative association. Besides, the findings disclosed that student’s digital exposure is not the forcing factor in developing technological competence, but found to be a more encouraging factor. It was also concluded that library technological involvement significantly improves student technology-based learning skills.

Practical implications

The results obtained after the analyzed data may help library management in providing long-term strategy for improving digital literacy education and training for students in the effective utilization of technology for better academic performance and social integration.

Originality/value

The study was based on quantitative methods using a questionnaire. Extensive database coverage and digital literacy skills based on coach input can improve student performance and academic quality.

Role of Azoles in Cancer Prevention and Treatment: Present and Future Perspectives

BACKGROUND

Cancer has gradually become one of the leading causes of death worldwide. The incidence of cancer among the population has increased alarmingly over the last two decades, primarily due to an increasing population of immune-compromised patients and the continuing rise in anti-cancer drug resistance. Azole found privileged structure in medicinal chemistry and pharmaceutical industry and also found to be showing antioxidant; antimicrobial, anthelmintic, anticancer, antiviral, anti-parasitic, anti-inflammatory, anti-HIV, and antihypertensive activities.

OBJECTIVE

In this review, we highlight some areas of current interest in context to azoles and their derivatives as potential chemotherapeutic agents and inhibitors.

METHOD

A comprehensive literature search was performed for writing this review. An updated view on different derivatives of azoles and use in cancer management has been discussed.

RESULTS

Here we have discussed the present scenario of azoles and their derivatives as potential chemotherapeutic agents and inhibitors. Along with, the future perspectives of azoles in cancer prevention and treatment are also discussed.

CONCLUSION

The information provided in this review might be useful to researchers in designing of novel and potent multifunctional azole analogues for the treatment of cancer and other multifactorial diseases.

Dengue protease inhibition activity of selected Malaysian medicinal herbs

Dengue fever is one of major health problem around the world including Malaysia. It is caused by the arthropode-borne flavivirus and transmitted by the bite of the Aedes aegypti or Aedes albopictus mosquito infected with one of the four dengue virus serotypes (DENV-1, DENV-2, DENV-3, or DENV-4). In this study, a screening exercise of various Malaysian medicinal plants showed that the extracts of Lawsonia inermis, Dryobalanops aromatica, Punica granatum, Zizyphus jujuba Lam. and Zingiber zerumbet exhibited potent inhibitory activity against NS2B-NS3 serine protease. The methanol extracts of Dryobalanops aromatica showed inhibition of 99.70 % at concentration of 200 µg/mL with IC₅₀ value of 0.30 ± 0.16 µg/mL.

Protein-protein Interactions and their Role in Various Diseases and their Prediction Techniques

Protein-protein interaction (PPI) is necessary for most of the biological processes and requisite for host-pathogen communication. Most of the threatening human diseases are caused by different types of interactions of proteins with their prior infected proteins or with pathogen's proteins. Understanding of involved mechanisms of interacting pairs, functional domains and characterizing specific molecular interaction of host and pathogen is critical. In this era of advanced research in medical and pharmaceutical sciences, the treatment of severe diseases is being tackled at genetic and PPI level. In this review, a brief introduction and application of PPI is described. Moreover, the classifications of PPI and their application in diseases are highlighted. Furthermore, methods for prediction of PPI are also discussed including brief introduction and update on detection techniques. We hope this review will prove to be very helpful for researchers to get better understanding and update on PPI.

Mechanistic Insights into the Antimicrobial Actions of Metallic Nanoparticles and Their Implications for Multidrug Resistance

Multiple drug-resistant bacteria are a severe and growing public health concern. Because relatively few antibiotics have been approved over recent years and because of the inability of existing antibiotics to combat bacterial infections fully, demand for unconventional biocides is intense. Metallic nanoparticles (NPs) offer a novel potential means of fighting bacteria. Although metallic NPs exert their effects through membrane protein damage, superoxide radicals and the generation of ions that interfere with the cell granules leading to the formation of condensed particles, their antimicrobial potential, and mechanisms of action are still debated. This article discusses the action of metallic NPs as antibacterial agents, their mechanism of action, and their effect on bacterial drug resistance. Based on encouraging data about the antibacterial effects of NP/antibiotic combinations, we propose that this concept be thoroughly researched to identify means of combating drug-resistant bacteria.

Targeting Caspase 8: Using Structural and Ligand-Based Approaches to Identify Potential Leads for the Treatment of Multi-Neurodegenerative Diseases

Caspase 8 is a central player in the apoptotic cell death pathway and is also essential for cytokine processing. The critical role of this protease in cell death pathways has generated research interest because its activation has also been linked with neural cell death. Thus, blocking the activity of caspase 8 is considered a potential therapy for neurodegenerative diseases. To extend the repertoire of caspase 8 inhibitors, we employed several computational approaches to identify potential caspase 8 inhibitors. Based on the structural information of reported inhibitors, we designed several individual and consensus pharmacophore models and then screened the ZINC database, which contains 105,480 compounds. Screening generated 5332 candidates, but after applying stringent criteria only two candidate compounds, ZINC19370490 and ZINC04534268, were evaluated by molecular dynamics simulations and subjected to Molecular Mechanics/Poisson Boltzmann Surface Area (MM-PBSA) analysis. These compounds were stable throughout simulations and interacted with targeted protein by forming hydrogen and van der Waal bonds. MM-PBSA analysis showed that these compounds were comparable or better than reported caspase 8 inhibitors. Furthermore, their physical properties were found to be acceptable, and they are non-toxic according to the ADMET online server. We suggest that the inhibitory efficacies of ZINC19370490 and ZINC04534268 be subjected to experimental validation.

Dermatopontin in Skeletal Muscle Extracellular Matrix Regulates Myogenesis

Dermatopontin (DPT) is an extensively distributed non-collagenous component of the extracellular matrix predominantly found in the dermis of the skin, and consequently expressed in several tissues. In this study, we explored the role of DPT in myogenesis and perceived that it enhances the cell adhesion, reduces the cell proliferation and promotes the myoblast differentiation in C2C12 cells. Our results reveal an inhibitory effect with fibronectin (FN) in myoblast differentiation. We also observed that DPT and fibromodulin (FMOD) regulate positively to each other and promote myogenic differentiation. We further predicted the 3D structure of DPT, which is as yet unknown, and validated it using state-of-the-art in silico tools. Furthermore, we explored the in-silico protein-protein interaction between DPT-FMOD, DPT-FN, and FMOD-FN, and perceived that the interaction between FMOD-FN is more robust than DPT-FMOD and DPT-FN. Taken together, our findings have determined the role of DPT at different stages of the myogenic process.

Evaluating the impact of digital library database resources on the productivity of academic research

Purpose

Digital library database resources have a significant impact on stimulating the research culture in higher education. The use of digital databases makes it possible to understand intellectual growth, research productivity, planning and identification of user information needs. Evaluating the effectiveness of user database resource utilization and research, the purpose of this study is to assist management in developing an excellent academic policy.

Design/methodology/approach

This study establishes a quantitative method to analyze the productivity of academic research using digital databases. The secondary data extracted from the databases of 52 universities provided by Higher Education Commission (HEC) and the literature published on the Institute of Scientific Information (ISI) Web of Science. The statistical technique simple linear regression was used to analyze the data for understanding the impact of independent variables the “digital databases” on the dependent variable “research productivity”.

Findings

The result of the coefficient of multiple determination,R-squared,R20.679, indicated 67 per cent impact of the predictor on the outcome variable. However, the standardized coefficient Beta 0.824 revealed 82 per cent impact of the individual predictor on the outcome variable. Overall, the result of linear regression showed a significant effect of independent variables on the dependent variable. Besides, the result of correlation and the strength of association between the database resources and the academic publication was significant (p< 0.005).

Practical implications

This research work is a supportive tool for managing gaps and promoting the development of necessary measures to develop strategies and solutions to create a better academic environment. The ultimate use of standard database resources can foster higher academic research to develop innovative ideas and improve researchers’ cognitive abilities.

Originality/value

From Pakistan’s point of view, this study is the first one that gives insight into the intellectual growth of young researchers in higher education. The study provides first-hand information on the use of database resources and their significant impact on the productivity of academic research.

NeuroMuscleDB: a Database of Genes Associated with Muscle Development, Neuromuscular Diseases, Ageing, and Neurodegeneration

Skeletal muscle is a highly complex, heterogeneous tissue that serves a multitude of biological functions in living organisms. With the advent of methods, such as microarrays, transcriptome analysis, and proteomics, studies have been performed at the genome level to gain insight of changes in the expression profiles of genes during different stages of muscle development and of associated diseases. In the present study, a database was conceived for the straightforward retrieval of information on genes involved in skeletal muscle formation, neuromuscular diseases (NMDs), ageing, and neurodegenerative disorders (NDs). The resulting database named NeuroMuscleDB ( http://yu-mbl-muscledb.com/NeuroMuscleDB ) is the result of a wide literature survey, database searches, and data curation. NeuroMuscleDB contains information of genes in Homo sapiens, Mus musculus, and Bos Taurus, and their promoter sequences and specified roles at different stages of muscle development and in associated myopathies. The database contains information on ~ 1102 genes, 6030 mRNAs, and 5687 proteins, and embedded analytical tools that can be used to perform tasks related to gene sequence usage. The authors believe NeuroMuscleDB provides a platform for obtaining desired information on genes related to myogenesis and their associations with various diseases (NMDs, ageing, and NDs). NeuroMuscleDB is freely available on the web at http://yu-mbl-muscledb.com/NeuroMuscleDB and supports all major browsers.