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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.

The following information was missing in the original manuscript [...]

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]

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.

Rickettsioses, caused by intracellular bacteria of the rickettsia genus, pose a global health threat, particularly affecting underserved communities. Delays in diagnosis and treatment due to limited healthcare access result in severe cases and fatalities. To address this, a multi-epitope vaccine targeting OmpB and GroEL proteins in epidemic and endemic typhus rickettsia was developed using immunoinformatics techniques. T-cell and B-cell epitopes were predicted from OmpB and GroEL proteins, resulting in 5 CTL, 4 HTL, and 4 B-cell epitopes. These epitopes were linked appropriately and combined with suitable adjuvants to construct the vaccine. The vaccine's physicochemical properties and tertiary structure were validated within acceptable ranges. Molecular docking analysis demonstrated favorable binding with TLR4 receptors and MHC molecules, further confirmed by molecular dynamics simulation. Immune simulation analysis predicted T-cell, IFN, and IL-2 responses upon vaccine administration. The vaccine sequence was then optimized and cloned into a plasmid vector pET-23a(+) at the Hind and AlwNI restriction sites. In this in silico experiment, a multi-epitope vaccine derived from OmpB and GroEL proteins is presented, the first validation steps of which have been completed. Subject to successful in vivo studies, this vaccine could prove to be a promising therapeutic strategy against rickettsiosis and address a critical public health challenge.

Background: Surgical approaches used in the treatment of patients with severe lumbar spondylolisthesis( Grade II and Grade III)are usually associated with a great deal of controversies. The objective of the study was to assessthe surgicaloutcomes of severe Lumbar spondylolisthesis treated with either pedicle screw fixation,reduction and fusion or instrumented Fusion in-situ. Methods: We retrospectively studied 32 patients (20 females and 12males),whohadsevere lumbar spondylolisthesis. All patients were divided in two groups (group Areduction and fusionand group B fusion in-situ).The mean follow-up period was 6 months. Radiological and clinical outcomes were measured by slip percentage, slip angle correction rate, Oswestry Disability index(ODI), visual analogue scale (VAS). Data was analyzed by SPSS version 22.0 Results: The analysis of the preoperative visits and final follow-up of all patients indicated that vertebral reduction and fusioncould slightly enhance the surgicaloutcome in comparison to instrumentedfusion in situ. Preoperative and Postoperative data was collected in all patients and found VAS from7.76to 2.08 in group-A and VAS from 8.5 preoperative to 2.4 postoperative in group-B and ODI from69.42% to 20.06 % in group-Aand 70.9% to 22% in group-B and mean slipcorrection rate was59.8 % . There wasno single caseof loss of reduction. Conclusion: The reduction, fusion and spinal decompression enhances surgical outcome and it can be concluded thatsuch procedure is slightly superior over fusionin situ.Excellent and good levels of satisfaction were observed in all group-A patients,although surgical time was slightly more than fusion in-situ group.

Abstract In recent years, the development and research of flexible sensors have gradually deepened, and the performance of wearable, flexible devices for monitoring body temperature has also improved. For the human body, body temperature changes reflect much information about human health, and abnormal body temperature changes usually indicate poor health. Although body temperature is independent of the environment, the body surface temperature is easily affected by the surrounding environment, bringing challenges to body temperature monitoring equipment. To achieve real-time and sensitive detection of various parts temperature of the human body, researchers have developed many different types of high-sensitivity flexible temperature sensors, perfecting the function of electronic skin, and also proposed many practical applications. This article reviews the current research status of highly sensitive patterned flexible temperature sensors used to monitor body temperature changes. First, commonly used substrates and active materials for flexible temperature sensors have been summarized. Second, patterned fabricating methods and processes of flexible temperature sensors are introduced. Then, flexible temperature sensing performance are comprehensively discussed, including temperature measurement range, sensitivity, response time, temperature resolution. Finally, the application of flexible temperature sensors based on highly delicate patterning are demonstrated, and the future challenges of flexible temperature sensors have prospected.

Despite the great proven advantages of imaging techniques in percutaneous coronary interventions (PCIs), the recent rapid increase in the number of PCI procedures exposes both surgical experts and patients to more radiation and orthopedic hazards in the intervention room. While patients are minimally exposed, many appearance of interventionists subject them to frequent exposure of the operational hazards. Despite promoting the use of robot-assisted intravascular PCI in the Cath-Labs, cognitive and technical skills of interventionists' are yet to be explored towards reducing procedure time and minimal exposure of surgeon to operational hazards. In this study, a random forest classification framework is developed for proper identification of technical manipulation skills of surgeons along with underlying motion patterns of the flexible intravascular tools (viz. guidewire and catheter) during PCI catheterization. For this purpose, analysis of interventionists' muscular activities and related hand motion were decoded from physiological signals recorded with sensors. Surface electromyography, electromagnetic, and tactile force signals were acquired concurrently from seven interventionists during specified guidewire movement viz. pull, push, rotate-pull (clockwise rotation with pull), rotate-push (counterclockwise rotation with push), CR (clockwise rotation), and CCR (counterclockwise rotation). While relations were established between force and muscle activities in the surgeon groups using Spearman's Rank-Order statistical method, Wilcoxon test and Kruskal-Wallis one-way ANOVA test were employed to identify intra-group and inter-group differences. From the experimental results obtained, guidewire delivery patterns exhibit stable characteristics with overall classification accuracies of 94.11% based on nineteen features subset from muscle activities and hand motion, followed by 88.01% based on twelve features subset from muscle activities, 71.97% based on seven features subset from hand motion, 84.56% based on ten features subset from part muscle activities and hand motion. Thus, this study shows existence of significant correlation (p

Neurodegenerative diseases are common progressive nervous system disorders that show intricate clinical patterns. The gait fluctuations reflect the physiology and pathologic alterations in the locomotor control system. Using gait fluctuations for disease state evaluation is an essential way for clinical trials and healthcare monitoring. The classification of gait fluctuations helps improve the life quality and enhance clinical diagnosis ability in neuro-degenerative patients. In this work, we firstly embed the time series of multiple gait fluctuations into the phase space. Then we use persistent homology to extract the topological signatures of barcodes. Together with a random forest classifier, we proposed a topological motion analysis (TMA) framework to analyze the gait fluctuations. Further, we proposed a comprehensive comparison study using the TMA framework in the neuro-degenerative classification tasks for stance-, stride-, and swing-based gait fluctuations. In the tasks of comparing amyotrophic lateral sclerosis (ALS), Huntington's disease (HD), and Parkinson's disease (PD) to the healthy control (HC) group, the best-achieved AUC scores were 0.9135, 0.9906 and 0.9667 respectively, which show the effectiveness of TMA framework. In summary, our study proposed a TMA framework towards gait fluctuations classification in the neuro-degenerative analysis tasks. The proposed method shows promising clinical application value in earlier interventions and state monitoring for neurodegenerative patients.

Interventional therapy is one of the most effective methods for diagnosing and treating vascular-related diseases at present. It relies on achieving precise and safe navigation of intravascular tools within a patient’s vasculature. Vascular Interventional Surgical Robots (VISR) can reduce surgeons’ exposure to operational hazards including radiation. However, the absence of apt position control and force feedback remains a challenge. This study presents an isomorphic master–slave VISR for precise navigation of endovascular tools viz. catheters and guidewires. The master console aids operators in issuing manipulation commands and logs feedback from the force, rotation, and translation data. The slave manipulator uses the commands received from the master platform for actual tool navigation. However, precise master–slave position control and force feedback are precursors for optimal patient outcomes. This study utilized a fuzzy-PID controller for precise tool navigation and a neural network model for resistance force modulation with 50 mN precision. Furthermore, we evaluated the performance of using the learning-based models within our VISR and compared it with the performances from conventional methods. Results show that the models enhanced the proposed robotic system with better navigation precision, faster response speed, and improved force measurement capabilities.

The use of several solutions as floral preservatives in extending the vase life of cut flowers has been an all-time research objective to meet the demands of florists and buyers. One of the major problems faced with the longevity of cut flowers is the accumulation of microorganism in the vase floral solution. This study was carried out to investigate the influence of Aloe vera gel and Silver thiosulphate solutions used as vase solution on the microbial population of Heliconia cut flowers. The experiment was carried out in the plant physiology laboratory, Floriculture programme, National Horticultural Research Institute, (NIHORT); Ibadan, Nigeria (7O25” N and 3O52” E). Six treatments supplemented with 1% sucrose were used in this experiment, they include; 1%, 2% and 4% Aloe vera gel solutions, 0.5% and 1% Silver thiosulphate solutions and distilled water (which serve as control) labeled AV1, AV2, AV3, STS1, STS2 and CO respectively. All treatments used for the vase life of Heliconia cut flowers were significantly (p ≤ 0.05) different in the parameters analyzed as compared to the control. The vase life, relative fresh weight and relative water content of Heliconia cut flowers were best with Aloe vera gel solutions compared to the control with AV3 recording the longest vase life of 12 days (58.21%). The microbial population in the vases of the cut flowers was greatly reduced with the application of the silver thiosulphate solutions (STS1 and STS2) compared with the control with STS2 recording the lowest microbial colony at 32.67 CFU mL-1. Promoting the use of organic floral preservatives should be encouraged as it is eco-friendly and cost effective. The result of the study reveals that the use of 4% Aloe vera solution has the potential to reduce microbial growth and also enhance the longevity of the cut flowers.

Abstract Background The containment of poliovirus infectious/potentially infectious materials in all biomedical facilities in Nigeria remain crucial to maintaining gains recorded towards polio eradication. Activities involved in the Nigerian Poliovirus type 2-laboratory containment survey in line with the 3rd Global Action Plan III (GAP III) for poliovirus containment are documented in this study. Through these activities, the overall preparedness for poliovirus eradication in Nigeria is assessed. Method A cross-sectional survey was conducted from 19th September-31st October 2016 using structured Laboratory survey and inventory (LSI) questionnaires uploaded onto the SPSS software package in 560 biomedical facilities classified either as high risk or medium risk facilities across the 6 zones in Nigeria. Results In total, 560 biomedical facilities were surveyed in Nigeria in conformity with the GAP III. In total, 86% of the facilities surveyed were with laboratories while 14% were without laboratories. Twelve laboratories with poliovirus potentially infectious materials were identified in this exercise. In total, 50% of the 12 laboratories were under the ministry of education for research purposes. While 33% were among those laboratories surveyed in the phase 1a exercise without any recorded inventory, but have acquired some since the phase 1a survey. A total of 13,484 poliovirus infectious materials were found in the 12 laboratories. Only 8% of the materials were immediately destroyed while the remaining materials (62%) were found in Oyo and Borno states scheduled for destruction within 3–4 months according to WHO protocol for destruction of poliovirus infectious materials. Conclusion This study has revealed the successful containment of all poliovirus infectious materials in the laboratories surveyed. It has also revealed some surveillance gaps. We recommend that the surveillance system be improved to maintain the gains from the containment exercise and avoid reintroduction of infectious materials into biomedical facilities. This reduces the chances of viral reintroduction to the population in general.

This paper presents a novel methodology for planning and operating biogas energy systems based on the transactive energy concept to determine multilevel operating regimes for distributed generation. The developed model is used to manage the production, storage, and dispatch of biogas energy systems to meet the load demands of the biogas producer and support the operation of the distribution network operator. An Integer Linear Programming (ILP) is fitted to optimize the biogas production of the biogas producer, including the operation of the biogas storage systems and their interaction with the network operator. The model’s objective is to maximize benefits for the participating agents in a transactive energy context. The model’s effectiveness is validated using seven case studies involving biogas systems having different operating ranges and modes to achieve enhanced flexibility and reliability for the system operation with a large proportion of intermittent energy resources. The simulation results showed that the approach could effectively manage the operation of biogas systems and their interaction with the network operator. The developed model is suitable for systems fostering net metering charging and real-time pricing.

Plummeting the burden that is increasingly posed by water related diseases is amongst the major public health goals for a developing country. The required growth and development experienced in developing countries will always weigh on this important component of earth from either industrial waste, sewage or domestic waste. A general estimate from WHO global evidence synthesis on water related complications and diseases posits that about 94% could be preventable through environmental modification and applica-tion of simple techniques to treat water1,2. Amongst other explored purification protocols, flocculation and chlorination as a chemical process has been linked to few health conditions after long time of exposure3. This has been largely adduced to the synthetic source and thus the need to explore flocculants of biological origin that can effectively purify water and presents little or no health risk. Surface water, which is often cate-gorized as harbor of large numbers of microorganisms amongst other characteristics was, explored for the presence of bacteria flocculants producers from three surface water in Ilorin, Kwara State in Nigeria.

Over the past few decades, tactile sensors have become an emerging field of research in both academia and industry. Recent advances have demonstrated application of tactile sensors in the area of biomedical engineering and opened up new opportunities for building multifunctional electronic skin (e-skin) which is capable of imitating the human sense-of-touch for medical purposes. Analyses have shown that current smart tactile sensing technology has the advantages of high performance, low-cost, time efficiency, and ease-of-fabrication. Tactile sensing systems have thus sufficiently matured for integration into several fields related to biomedical engineering. Furthermore, artificial intelligence has the potential for being applied in human-machine interfacing, for instance, in medical robotic manipulation, especially during minimally invasive robotic surgery, where tactile sensing is usually a problem. In this survey, we present a comprehensive review of the state of the art of tactile sensors. We focus on the technical details of transduction mechanisms such as piezoresistivity, capacitance, piezoelectricity, and triboelectric and highlight the role of novel and commonly used materials in tactile sensing. In addition, we discuss contributions that have been reported in the field of biomedical engineering, which includes its present and future applications in building multifunctional e-skins, human-machine interfaces, and minimally invasive surgical robots. Finally, some challenges and notable improvements that have been made in the technical aspects of tactile sensing systems are reported.

Chronic low back pain (CLBP) is a common musculoskeletal disorder and a major source of disability in adults. The assessment of lumbar muscle functioning has proven as an appropriate approach for early identification of CLBP when significant pathological signs and symptoms are absent. Thus, earlier therapy or rehabilitation can be administered to prevent further deterioration, such as spinal stenosis or disk herniation. In this paper, surface electromyography (sEMG) signal analysis was explored for the recognition of low back pain in subjects with non-specific symptoms; 88 CLBP subjects and a control group of 83 subjects were recruited for sEMG data acquisition. Subjects were asked to perform four specific movements, namely forward bending, backward bending, right lateral flexion, and left lateral flexion. While performing each movement, sEMG signals from three pairs of lumbar muscles were captured, and 31 features from both the time and frequency domains were extracted from the signal. Finally, the main feature group and four subsets, derived from it, were explored. The suggested method allowed to achieve CLBP recognition accuracy of 98.04% based on subset C for forward bending, followed by 96.15% based on subset E for right lateral flexion, 93.33% based on subset E for left lateral flexion, and 91.30% based on subset B for backward bending. A combination of support vector machine classifiers and optimal feature selection allowed for improved classification performance. The main aim of this paper is to recognize CLBP in subjects with non-specific pathology during the four types of movement. The major steps carried out to achieve this are pre-processing, feature selection, and classification of the sEMG signals acquired from 171 subjects. Results suggest CLBP recognition based on sEMG as a promising alternative to the conventional methods. Therefore, this paper could inspire the design of appropriate programs that can ensure effective rehabilitation of CLBP patients.

We propose a flexible, dry, and antibacterial electrode with a low and stable skin electrode contact impedance for bio-potential signal monitoring. We fabricated a bacterial cellulose/polyaniline/AgNO3 nanocomposite membrane (BC/PANI/AgNO3) and used it for bio-potential signal monitoring. The bacterial cellulose (BC) provides a 3-D nanoporous network structure, and it was used as a substrate material in the BC/PANI/AgNO3 nanocomposite membrane. Polyaniline (PANI) and AgNO3, acting as conductive and antibacterial components, respectively, were polymerized and deposited on the surfaces of BC nanofibers to produce uniform thin film membrane with flexible, antibacterial, and conductive properties. Various measurements were conducted, in terms of antibacterial activity, skin electrode contact impedance, and qualitative analysis of ECG signal recordings. The BC/PANI/AgNO3 membrane revealed 100% antibacterial activities against both the Staphylococcus aureus and Escherichia coli bacteria. The skin electrode contact impedance of the proposed BC/PANI/AgNO3 electrode is lower than that of the Ag/AgCl gel electrode, with the same active area. In addition, the electrocardiogram (ECG) signals acquired with the proposed electrodes have stable characteristic waveforms, and they are not contaminated by noise. The waveform fidelity of the BC/PANI/AgNO3 membrane electrodes over 800 ECG cardiac cycles is 99.49%, and after the electrodes were worn for 24 hours, a fidelity of 98.40% was recorded over the same number of cardiac cycles. With the low and stable skin electrode contact impedance, the proposed dry BC/PANI/AgNO3 membrane electrode provided high fidelity for ECG signal recordings, thus offering a potential approach for bio-potential signal monitoring. With the above benefits, the novel flexible and dry BC/PANI/AgNO3 electrode has a significant antibacterial. Most of all, it is the first research to develop antibacterial in the electrode design.

Abstract Background Muscular performance is an important factor for the mechanical stability of lumbar spine in humans, in which, the co-contraction of lumbar muscles plays a key role. We hypothesized that when executing different daily living motions, the performance of the lumbar muscle co-contraction stabilization mechanism varies between patients with lumbar disc herniation (LDH) and healthy controls. Hence, in this study, co-contraction performance of lumbar muscles between patients with LDH and healthy subjects was explored to check if there are significant differences between the two groups when performing four representative movements. Methods Twenty-six LDH patients (15 females, 11 males) and a control group of twenty-eight subjects (16 females, 12 males) were recruited. Surface electromyography (EMG) signals were recorded from the external oblique, lumbar multifidus, and internal oblique/transversus abdominis muscles during the execution of four types of movement, namely: forward bending, backward bending, left lateral flexion and right lateral flexion. The acquired EMG signals were segmented, and wavelet decomposition was performed followed by reconstruction of the low-frequency components of the signal. Then, the reconstructed signals were used for further analysis. Co-contraction ratio was employed to assess muscle coordination and compare it between the LDH patients and healthy controls. The corresponding signals of the subjects in the two groups were compared to evaluate the differences in agonistic and antagonistic muscle performance during the different motions. Also, sample entropy was applied to evaluate complexity changes in lumbar muscle recruitment during the movements. Results Significant differences between the LDH and control groups were found in the studied situations (p

Developments in flexible electronics have adopted various approaches which have enhanced the applicability of human–machine interface fields. Recently, microstructural integration and hybrid functional materials were designed for realizing human somatosensory. Nonetheless, designing tactile sensors with smart structures using facile and low-cost fabrication processes remains challenging. Furthermore, using the sensors for recognizing stimuli and feedback applications remains poorly validated. In this study, a highly flexible piezoresistive tactile sensor was developed by homogeneously dispersing carbon black (CB) in a microstructure porous sugar/PDMS-based sponge. Owning to its high flexibility and softness, the sensor can be mounted on human or robotic systems for different clinical applications. We validated the applicability of the proposed sensor by applying it to recognizing grasp and release forces in an open setting and to classifying hand motions that surgeons apply on the master interface of a robotic system during intravascular catheterization. For this purpose, we implemented the long short-term memory (LSTM)-dense classification model and five traditional machine learning methods, namely, support vector machine, multilayer perceptron, decision tree, and k-nearest neighbor. The models were used to classify the different hand gestures obtained in an open-setting experiment. Amongst all, the LSTM-dense method yielded the highest overall recognition accuracy (87.38%). Nevertheless, the performance of the other models was in a similar range, showing that our sensor structure can be applied in intelligence sensing or tactile feedback systems. Secondly, the sensor prototype was applied to analyze the motions made while manipulating an interventional robot. We analyzed the displacement and velocity of the master interface during typical axial (push/pull) and radial operations with the robot. The results obtained show that the sensor is capable of recording unique patterns during different operations. Thus, a combination of the flexible wearable sensors and machine learning could yield a future generation of flexible materials and artificial intelligence of things (AIoT) devices.

Abstract Background Snake-like robot is an emerging form of serial-link manipulator with the morphologic design of biological snakes. The redundant robot can be used to assist medical experts in accessing internal organs with minimal or no invasion. Several snake-like robotic designs have been proposed for minimal invasive surgery, however, the few that were developed are yet to be fully explored for clinical procedures. This is due to lack of capability for full-fledged spatial navigation. In rare cases where such snake-like designs are spatially flexible, there exists no inverse kinematics (IK) solution with both precise control and fast response. Methods In this study, we proposed a non-iterative geometric method for solving IK of lead-module of a snake-like robot designed for therapy or ablation of abdominal tumors. The proposed method is aimed at providing accurate and fast IK solution for given target points in the robot’s workspace. n-1 virtual points (VPs) were geometrically computed and set as coordinates of intermediary joints in an n-link module. Suitable joint angles that can place the end-effector at given target points were then computed by vectorizing coordinates of the VPs, in addition to coordinates of the base point, target point, and tip of the first link in its default pose. The proposed method is applied to solve IK of two-link and redundant four-link modules. Results Both two-link and four-link modules were simulated with Robotics Toolbox in Matlab 8.3 (R2014a). Implementation result shows that the proposed method can solve IK of the spatially flexible robot with minimal error values. Furthermore, analyses of results from both modules show that the geometric method can reach 99.21 and 88.61% of points in their workspaces, respectively, with an error threshold of 1 mm. The proposed method is non-iterative and has a maximum execution time of 0.009 s. Conclusions This paper focuses on solving IK problem of a spatially flexible robot which is part of a developmental project for abdominal surgery through minimal invasion or natural orifices. The study showed that the proposed geometric method can resolve IK of the snake-like robot with negligible error offset. Evaluation against well-known methods shows that the proposed method can reach several points in the robot’s workspace with high accuracy and shorter computational time, simultaneously.

Background: In Okelele, Ilorin, Kwara State, Nigeria, malaria remains an important public health concern with a little information about its prevalence. Objective: To determine the prevalence of malaria infection at Okelele Health Centre, Okelele, Ilorin. Methodology: A cross-sectional descriptive study in which patients were diagnosed clinically with severe or uncomplicated malaria at the study site was conducted. Rapid diagnostic testing (RDT) for malaria and microscopy using Giemsa staining by thick and thin blood smears were done for study patients. Results: In this study, 200 malaria patients attending Okelele Health Centre, Okelele, Ilorin, were tested for malaria infection, with females having the highest prevalence rates and parasitemia density. The highest positivity rates were found in children