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Abstract Background Messenger RNA (mRNA) vaccines emerged as a powerful tool in the fight against infections. Unlike traditional vaccines, this unique type of vaccine elicits robust and persistent innate and humoral immune response with a unique host cell‐mediated pathogen gene expression and antigen presentation. Methods This offers a novel approach to combat poxviridae infections. From the genome of vaccinia and Mpox viruses, three key genes (E8L, E7R, and H3L) responsible for virus attachment and virulence were selected and employed for designing the candidate mRNA vaccine against vaccinia and Mpox viral infection. Various bioinformatics tools were employed to generate (B cell, CTL, and HTL) epitopes, of which 28 antigenic and immunogenic epitopes were selected and are linked to form the mRNA vaccine construct. Additional components, including a 5′ cap, 5′ UTR, adjuvant, 3′ UTR, and poly(A) tail, were incorporated to enhance stability and effectiveness. Safety measures such as testing for human homology and in silico immune simulations were implemented to avoid autoimmunity and to mimics the immune response of human host to the designed mRNA vaccine, respectively. The mRNA vaccine's binding affinity was evaluated by docking it with TLR‐2, TLR‐3, TLR‐4, and TLR‐9 receptors which are subsequently followed by molecular dynamics simulations for the highest binding one to predict the stability of the binding complex. Results With a 73% population coverage, the mRNA vaccine looks promising, boasting a molecular weight of 198 kDa and a molecular formula of C8901H13609N2431O2611S48 and it is said to be antigenic, nontoxic and nonallergic, making it safe and effective in preventing infections with Mpox and vaccinia viruses, in comparison with other insilico‐designed vaccine for vaccinia and Mpox viruses. Conclusions However, further validation through in vivo and in vitro techniques is underway to fully assess its potential.

Purpose – This study examines the roles of poverty reduction and social inclusion as socioeconomic factors in achieving sustainable development (SD) in Nigeria from 1970 to 2019. Design/methodology/approach – Vector error correction model (VECM) is adopted as the analytical technique. Three groups of factors are employed when determining SD: economic (per capital gross domestic product [GDP] and the inflow of foreign direct investment [FDI]), social (life expectancy, school enrollment, poverty and the proportion of women in parliament) and environmental (CO2 emission and natural resource endowment). Findings – The findings reveal that the economic factors (GDP per capita and the inflow of FDI to the GDP ratio) and two of the social determinants (life expectancy and school enrollment) have a positive effect on SD while the remaining two social determinants (poverty gap and the proportion of women in parliament) and the environmental determinants (CO2 emission and natural resource endowment) have a negative influence on SD in Nigeria during the period under study. Originality/value – First, this study integrates social inclusion into the poverty–SD nexus in the same study framework for a thorough analysis given that social inclusion has been identified as one of the leading variables affecting sustainability. Second, this study fills a gap in the literature by accounting for economic, social and environmental factors that influence SD, as opposed to the majority of existing studies that only employed environmental variables when examining the relationship between poverty and sustainability.

Introduction Estimating COVID-19 cumulative incidence in Africa remains problematic due to challenges in contact tracing, routine surveillance systems and laboratory testing capacities and strategies. We undertook a meta-analysis of population-based seroprevalence studies to estimate SARS-CoV-2 seroprevalence in Africa to inform evidence-based decision making on public health and social measures (PHSM) and vaccine strategy.Methods We searched for seroprevalence studies conducted in Africa published 1 January 2020–30 December 2021 in Medline, Embase, Web of Science and Europe PMC (preprints), grey literature, media releases and early results from WHO Unity studies. All studies were screened, extracted, assessed for risk of bias and evaluated for alignment with the WHO Unity seroprevalence protocol. We conducted descriptive analyses of seroprevalence and meta-analysed seroprevalence differences by demographic groups, place and time. We estimated the extent of undetected infections by comparing seroprevalence and cumulative incidence of confirmed cases reported to WHO.PROSPERO: CRD42020183634.Results We identified 56 full texts or early results, reporting 153 distinct seroprevalence studies in Africa. Of these, 97 (63%) were low/moderate risk of bias studies. SARS-CoV-2 seroprevalence rose from 3.0% (95% CI 1.0% to 9.2%) in April–June 2020 to 65.1% (95% CI 56.3% to 73.0%) in July–September 2021. The ratios of seroprevalence from infection to cumulative incidence of confirmed cases was large (overall: 100:1, ranging from 18:1 to 954:1) and steady over time. Seroprevalence was highly heterogeneous both within countries—urban versus rural (lower seroprevalence for rural geographic areas), children versus adults (children aged 0–9 years had the lowest seroprevalence)—and between countries and African subregions.Conclusion We report high seroprevalence in Africa suggesting greater population exposure to SARS-CoV-2 and potential protection against COVID-19 severe disease than indicated by surveillance data. As seroprevalence was heterogeneous, targeted PHSM and vaccination strategies need to be tailored to local epidemiological situations.

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At this present stage of COVID-19 re-emergence, designing an effective candidate vaccine for different variants of SARS-CoV-2 is a study worthy of consideration. This research used bioinformatics tools to design an mRNA vaccine that captures all the circulating variants and lineages of the virus in its construct. Sequences of these viruses were retrieved across the six continents and analyzed using different tools to screen for the preferable CD8+ T lymphocytes (CTL), CD4+ T lymphocytes (HTL), and B-cell epitopes. These epitopes were used to design the vaccine. In addition, several other co-translational residues were added to the construct of an mRNA vaccine whose molecular weight is 285.29686 kDa with an estimated pI of 9.2 and has no cross affinity with the human genome with an estimated over 68% to cover the world population. It is relatively stable, with minimal deformability in its interaction with the human innate immune receptor, which includes TLR 3 and TLR 9. The overall result has proven that the designed candidate vaccine is capable of modulating cell-mediated immune responses by activating the actions of CD4+ T cells, natural killer cells, and macrophages, and displayed an increased memory T cell and B cell activities, which may further be validated via in vivo and in vitro techniques.

Robotic catheter systems with master–slave designs are employed for teleoperated navigation of flexible endovascular tools for treating calcified lesions. Despite improved tool manipulation techniques, patient safety and lowering operative risks remain top priorities. Therefore, minimizing undesirable drifts and imprecise navigation of flexible tools during intravascular catheterization is essential. In the current master–slave designs, finite displacement lag between position command and actual navigation action at the slave device affects smooth catheterization. In this study, we designed and developed a compact 2-DOF robotic catheter system and characterized the influence of displacement step values, velocity, and motion gap on the position error at the slave device. For uniform and varying motion commands from the master platform, the results indicate that the overall position error increases with the distance traveled and the displacement step values, respectively. Hence, we proposed using recurrent neural networks—long short-term memory and gated recurrent unit controllers to predict the slave robot’s position and appropriate compensation value per translation step. An analysis of in-silico studies with CoppeliaSim showed that the neural-based controllers can ensure uniform motion mapping between the master–slave devices. Furthermore, we implemented the models within the RCS for a catheterization length of 120 mm. The result demonstrates that the controllers suitably aid the slave robot’s stepwise displacement. Thus, the neural-based controllers help match the translational motion and precise tool navigation by the slave robotic device. Therefore, the neural-based controllers could contribute to alleviating patients’ safety concerns during robotic interventions.

This article is devoted to applying bioinformatics and immunoinformatics approaches for the development of a multi-epitope mRNA vaccine against the spike glycoproteins of circulating SARS-CoV-2 variants in selected African countries. The study’s relevance is dictated by the fact that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) began its global threat at the end of 2019 and since then has had a devastating impact on the whole world. Measures to reduce threats from the pandemic include social restrictions, restrictions on international travel, and vaccine development. In most cases, vaccine development depends on the spike glycoprotein, which serves as a medium for its entry into host cells. Although several variants of SARS-CoV-2 have emerged from mutations crossing continental boundaries, about 6000 delta variants have been reported along the coast of more than 20 countries in Africa, with South Africa accounting for the highest percentage. This also applies to the omicron variant of the SARS-CoV-2 virus in South Africa. The authors suggest that bioinformatics and immunoinformatics approaches be used to develop a multi-epitope mRNA vaccine against the spike glycoproteins of circulating SARS-CoV-2 variants in selected African countries. Various immunoinformatics tools have been used to predict T- and B-lymphocyte epitopes. The epitopes were further subjected to multiple evaluations to select epitopes that could elicit a sustained immunological response. The candidate vaccine consisted of seven epitopes, a highly immunogenic adjuvant, an MHC I-targeting domain (MITD), a signal peptide, and linkers. The molecular weight (MW) was predicted to be 223.1 kDa, well above the acceptable threshold of 110 kDa on an excellent vaccine candidate. In addition, the results showed that the candidate vaccine was antigenic, non-allergenic, non-toxic, thermostable, and hydrophilic. The vaccine candidate has good population coverage, with the highest range in East Africa (80.44%) followed by South Africa (77.23%). West Africa and North Africa have 76.65% and 76.13%, respectively, while Central Africa (75.64%) has minimal coverage. Among seven epitopes, no mutations were observed in 100 randomly selected SARS-CoV-2 spike glycoproteins in the study area. Evaluation of the secondary structure of the vaccine constructs revealed a stabilized structure showing 36.44% alpha-helices, 20.45% drawn filaments, and 33.38% random helices. Molecular docking of the TLR4 vaccine showed that the simulated vaccine has a high binding affinity for TLR-4, reflecting its ability to stimulate the innate and adaptive immune response.

Big data technologies, Analytics and Artificial Intelligence are great tools with capabilities to accomplish complex tasks at levels beyond human skills. The trio are becoming more and more prominent these days as they can be utilized to collect, organize, and analyze large varied data sets in order to reveal hidden patterns and trends that can help address several problems peculiar to sustainable development. Nevertheless, a number of challenges arise in the process of exploring these technologies for proffering solutions. This special issue presents novel research approaches adopted in Africa in relation to Big Data, Analytics and Artificial Intelligence in different domains. It also presents the challenges and issues that can be explored in the future.

Arboviruses are distributed worldwide and constitute significant health burden globally. Outbreaks of arboviruses have been reported in Africa and beyond. In Nigeria, like in many other countries, arbovirus infections are more often than not neglected. As the early clinical features of arbovirus infections are generally nonspecific, most healthcare providers mistake them for other diseases. Outbreaks have been reported in Africa and beyond. The consequence of missed diagnosis of diseases cannot be overstated. In this review, some epidemiological data, classical syndromes, and risk factors for five human arboviruses (yellow fever YF, dengue DENV, chikungunya CHIKV, Rift Valley fever RVF, and West Nile virus WNV) found in Nigeria are presented. Health practitioners should ensure in-depth analysis rather than a superficial diagnosis of diseases before declaring a course of treatment.

This paper explores the roots of critical thinking and its importance. It also attempts a clarification of critical thinking as a concept. Using the method of philosophical analysis, the paper proceeds to investigate the place of critical thinking in teacher education in Nigeria. Among other things, it is suggested that the acquisition of critical thinking skills be included among the stated goals of Teacher Education and that necessary measures be taken by the relevant authorities to ensure that critical thinking is actually taught and practiced by pre-service teachers in Nigeria.

Background: Messenger RNA (mRNA) vaccines emerged as a powerful tool in the fight against infections. Unlike traditional vaccines, this unique type of vaccine elicits robust and persistent innate and humoral immune response with a unique host cell‐mediated pathogen gene expression and antigen presentation. Methods: This offers a novel approach to combat poxviridae infections. From the genome of vaccinia and Mpox viruses, three key genes (E8L, E7R, and H3L) responsible for virus attachment and virulence were selected and employed for designing the candidate mRNA vaccine against vaccinia and Mpox viral infection. Various bioinformatics tools were employed to generate (B cell, CTL, and HTL) epitopes, of which 28 antigenic and immunogenic epitopes were selected and are linked to form the mRNA vaccine construct. Additional components, including a 5′ cap, 5′ UTR, adjuvant, 3′ UTR, and poly(A) tail, were incorporated to enhance stability and effectiveness. Safety measures such as testing for human homology and in silico immune simulations were implemented to avoid autoimmunity and to mimics the immune response of human host to the designed mRNA vaccine, respectively. The mRNA vaccine's binding affinity was evaluated by docking it with TLR‐2, TLR‐3, TLR‐4, and TLR‐9 receptors which are subsequently followed by molecular dynamics simulations for the highest binding one to predict the stability of the binding complex. Results: With a 73% population coverage, the mRNA vaccine looks promising, boasting a molecular weight of 198 kDa and a molecular formula of C8901H13609N2431O2611S48 and it is said to be antigenic, nontoxic and nonallergic, making it safe and effective in preventing infections with Mpox and vaccinia viruses, in comparison with other insilico‐designed vaccine for vaccinia and Mpox viruses. Conclusions: However, further validation through in vivo and in vitro techniques is underway to fully assess its potential. [ABSTRACT FROM AUTHOR]

BackgroundMental health disorders are the leading cause of health-related problems worldwide. It is projected that mental health disorders will be the leading cause of morbidity among adults as the incidence rates of anxiety and depression grow worldwide. Recently, “extended reality” (XR), a general term covering virtual reality (VR), augmented reality (AR), and mixed reality (MR), is paving the way for the delivery of mental health care. ObjectiveWe aimed to investigate the adoption and implementation of XR technology used in interventions for mental disorders and to provide statistical analyses of the design, usage, and effectiveness of XR technology for mental health interventions with a worldwide demographic focus. MethodsIn this paper, we conducted a scoping review of the development and application of XR in the area of mental disorders. We performed a database search to identify relevant studies indexed in Google Scholar, PubMed, and the ACM Digital Library. A search period between August 2016 and December 2023 was defined to select papers related to the usage of VR, AR, and MR in a mental health context. The database search was performed with predefined queries, and a total of 831 papers were identified. Ten papers were identified through professional recommendation. Inclusion and exclusion criteria were designed and applied to ensure that only relevant studies were included in the literature review. ResultsWe identified a total of 85 studies from 27 countries worldwide that used different types of VR, AR, and MR techniques for managing 14 types of mental disorders. By performing data analysis, we found that most of the studies focused on high-income countries, such as the United States (n=14, 16.47%) and Germany (n=12, 14.12%). None of the studies were for African countries. The majority of papers reported that XR techniques lead to a significant reduction in symptoms of anxiety or depression. The majority of studies were published in 2021 (n=26, 30.59%). This could indicate that mental disorder intervention received higher attention when COVID-19 emerged. Most studies (n=65, 76.47%) focused on a population in the age range of 18-65 years, while few studies (n=2, 3.35%) focused on teenagers (ie, subjects in the age range of 10-19 years). In addition, more studies were conducted experimentally (n=67, 78.82%) rather than by using analytical and modeling approaches (n=8, 9.41%). This shows that there is a rapid development of XR technology for mental health care. Furthermore, these studies showed that XR technology can effectively be used for evaluating mental disorders in a similar or better way that conventional approaches. ConclusionsIn this scoping review, we studied the adoption and implementation of XR technology for mental disorder care. Our review shows that XR treatment yields high patient satisfaction, and follow-up assessments show significant improvement with large effect sizes. Moreover, the studies adopted unique designs that were set up to record and analyze the symptoms reported by their participants. This review may aid future research and development of various XR mechanisms for differentiated mental disorder procedures.

Background: There has been an increase in the occurrence of infections due to Extended Spectrum Beta lactamases (ESBL) producing bacteria. ESBLs exhibit an enhanced capacity to hydrolyze the extended spectrum Beta-lactams, which has led to an increase in the antibiotic resistance capability of uropathogenic microorganisms. This study was aimed at determining the production of beta lactamase and extraction of beta lactamase genes from urinary tract infection due to Escherichia coli. Methods: Plasmid curing was carried out using sub inhibitory concentration of 0.10 mg/ml of acridine orange to determine the location (plasmid-borne or chromosomal) of the drug resistance marker(s). Beta-lactamase test was performed using the Starch Paper Method, while DNA extraction, genomic gene analysis and polymerase chain reaction were done to determine the presence and analysis of beta lactamase genes. Results: Ninety-eight (98) Escherichia coli isolates analyzed, thirty-one (31) were plasmid mediated and of this, Sixteen (16) was resistant to amoxillin, six (6) to augmentin, three (3) to nitrofurantoin and six (6) to tetracycline. Results further revealed that out of the E. coli isolates that were plasmid mediated only nine (9) were beta lactamase producers. None of the ESBL producing E. coli contained SHV beta-lactamase genes. However, three (3) and five (5) strains of ESBL producing E. coli contained TEM and CTX-M beta-lactamase genes respectively. Conclusion: This study shows that the resistant of urinary tract infection (UTI) isolates to beta-lactams were due to production of TEM and CTX-M beta-lactamases. Identification of these genes provides for accurate treatment and further understanding of the mechanism of resistance. Key Words: Extended Spectrum Beta-lactamase, Escherichia coli, Antibiotics, Plasmid mediated.

This article is devoted to applying bioinformatics and immunoinformatics approaches for the development of a multi-epitope mRNA vaccine against the spike glycoproteins of circulating SARS-CoV-2 variants in selected African countries. The study's relevance is dictated by the fact that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) began its global threat at the end of 2019 and since then has had a devastating impact on the whole world. Measures to reduce threats from the pandemic include social restrictions, restrictions on international travel, and vaccine development. In most cases, vaccine development depends on the spike glycoprotein, which serves as a medium for its entry into host cells. Although several variants of SARS-CoV-2 have emerged from mutations crossing continental boundaries, about 6000 delta variants have been reported along the coast of more than 20 countries in Africa, with South Africa accounting for the highest percentage. This also applies to the omicron variant of the SARS-CoV-2 virus in South Africa. The authors suggest that bioinformatics and immunoinformatics approaches be used to develop a multi-epitope mRNA vaccine against the spike glycoproteins of circulating SARS-CoV-2 variants in selected African countries. Various immunoinformatics tools have been used to predict T- and B-lymphocyte epitopes. The epitopes were further subjected to multiple evaluations to select epitopes that could elicit a sustained immunological response. The candidate vaccine consisted of seven epitopes, a highly immunogenic adjuvant, an MHC I-targeting domain (MITD), a signal peptide, and linkers. The molecular weight (MW) was predicted to be 223.1 kDa, well above the acceptable threshold of 110 kDa on an excellent vaccine candidate. In addition, the results showed that the candidate vaccine was antigenic, non-allergenic, non-toxic, thermostable, and hydrophilic. The vaccine candidate has good population coverage, with the highest range in East Africa (80.44%) followed by South Africa (77.23%). West Africa and North Africa have 76.65% and 76.13%, respectively, while Central Africa (75.64%) has minimal coverage. Among seven epitopes, no mutations were observed in 100 randomly selected SARS-CoV-2 spike glycoproteins in the study area. Evaluation of the secondary structure of the vaccine constructs revealed a stabilized structure showing 36.44% alpha-helices, 20.45% drawn filaments, and 33.38% random helices. Molecular docking of the TLR4 vaccine showed that the simulated vaccine has a high binding affinity for TLR-4, reflecting its ability to stimulate the innate and adaptive immune response. [ABSTRACT FROM AUTHOR]

In children, the respiratory syncytial virus and adenovirus majorly cause acute respiratory infections. The study evaluated the seroprevalence and conducted the molecular characterization of human respiratory syncytial virus (HRSV) and human adenovirus (HAdV) among children. Venous blood, nasopharyngeal, and oropharyngeal swabs were collected from children presenting with acute respiratory infections in a tertiary health facility in Ado‐Ekiti, Nigeria. A serological investigation was carried out on the sera samples for the detection of anti‐HRSV immunoglobulin M (IgM), anti‐HRSV IgG, anti‐HAdV IgM, and anti‐HAdV IgG using ELISA (enzyme‐linked immunosorbent assay) kits. The amplification and sequencing of HRSV and HAdV were carried out using specific primer pairs that targeted the glycoprotein (G) gene of HRSV and the hexon gene of HAdV, respectively. The seroprevalence of HRSV IgG and IgM was 73% and 7.5%, respectively, while the seroprevalence of HAdV IgG and IgM was 98.5% and 8.5%, respectively. The age of enrolled children, presence of fever, and cough were associated (p < 0.05) with the infection. HRSV subtype B (HRSV‐B) (13.3%), and species of HAdV (Mastadenovirus B and C) (11.7%) were detected among the studied population. There was no viral coinfection with both HRSV and HAdV. In infancy and early childhood, HRSV‐B, HAdV species B and C are common etiologic agents of respiratory infections as reported in this study. Further studies on molecular characterization of respiratory tract viruses including circulating respiratory syncytial virus and adenovirus are hereby advocated. Keypoints: Respiratory syncytial virus (RSV) and adenovirus (AdV) are detected among children with respiratory tract infections.HRSV subtype B genotype BA9 and Human adenovirus (B and C species) circulates among children in Ado‐Ekiti, Nigeria.Anti‐HRSV IgM, anti‐HRSV IgG, anti‐HAdV IgM and anti‐HAdV IgG are detected in sera samples using ELISA (enzyme‐linked immunosorbent assay) kits. [ABSTRACT FROM AUTHOR]

Existing surgical guidewire endpoint localization methods in X‐ray images face challenges owing to their small size, simple appearance, nonrigid nature of objects, low signal‐to‐noise ratio of X‐ray images, and imbalance between the number of guidewire and background pixels, which lead to errors in surgical navigation. An eight‐neighborhood‐based method for increasing the localization accuracy of guidewire endpoint to improve the safety of interventional procedures is proposed herein. The proposed method includes two stages: 1) An improved U‐Net network is employed for segmenting the data of the guidewire to extract regions of interest containing guidewire endpoints with higher precision and to reduce interference from other anatomical structures and imaging artifacts. 2) The proposed method detects guidewire endpoints using the adjacent relationship between pixels in the eight‐neighborhood regions. This stage covers skeletonization extraction, removal of bifurcation points, and repair of fracture points. This study achieves mean pixel errors of 2.02 and 2.13 pixels in an in vivo rabbit and porcine X‐ray fluoroscopy images, outperforming ten classic heatmap and regression methods, achieving state‐of‐the‐art detection results. The proposed method can also be applied to detect other tiny surgical instruments such as stents and balloons, while preserving the flexibility of the guidewire bending angle.

The adoption of non-surgical procedures for the treatment of cardiovascular diseases has yielded several benefits such as lesser perioperative pain, shorter hospital stay, and faster recovery time while introducing radiation-specific, orthopedic, force-related health risks etc. during manual procedures. To address these challenges, robotic catheter systems were unveiled for better procedural outcomes while also offering a vast decline in orthopedic and radiation risks witnessed aforetime. However, distal force sensing and feedback acquisition were lacking in most of these systems. Currently, miniaturized force-sensing catheters for smart catheterization and acquisition of tool-tissue or tool-vessel contact force rely mostly on electrical or optical-based approaches with fiber Bragg grating (FBG) sensing technique receiving an increased attention lately. Hence, this paper presents an extensive overview of FBG-based distal force sensors for both conventional and robot-assisted cardiac interventions with emphasis on its fundamental principles, progressive development, design methodology, significance, as well as current challenges. In addition, the safety and feasibility of existing robotic catheter systems was analyzed based on existing studies. An outlook on future improvement of robotic catheter systems and adoption of FBG-based distal force sensors for wider minimally invasive applications were presented. [ABSTRACT FROM AUTHOR]