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Metabolic syndrome (MetS) is a widespread global epidemic that affects individuals across all age groups and presents a significant public health challenge. Comprising various cardio-metabolic risk factors, MetS contributes to morbidity and, when inadequately addressed, can lead to mortality. Current therapeutic approaches involve lifestyle changes and the prolonged use of pharmacological agents targeting the individual components of MetS, posing challenges related to cost, compliance with medications, and cumulative side effects. To overcome the challenges associated with these conventional treatments, herbal medicines and phytochemicals have been explored and proven to be holistic complements/alternatives in the management of MetS. Thymoquinone (TQ), a prominent bicyclic aromatic compound derived from Nigella sativa emerges as a promising candidate that has demonstrated beneficial effects in the treatment of the different components of MetS, with a good safety profile. For methodology, literature searches were conducted using PubMed and Google Scholar for relevant studies until December 2023. Using Boolean Operators, TQ and the individual components of MetS were queried against the databases. The retrieved articles were screened for eligibility. As a result, we provide a comprehensive overview of the anti-obesity, anti-dyslipidaemic, anti-hypertensive, and anti-diabetic effects of TQ including some underlying mechanisms of action such as modulating the expression of several metabolic target genes to promote metabolic health. The review advocates for a paradigm shift in MetS management, it contributes valuable insights into the multifaceted aspects of the application of TQ, fostering an understanding of its role in mitigating the global burden of MetS.

Abstract Dumpsites generate leachates containing bacteria that may carry antibiotic resistance genes, such as extended spectrum β-lactamase (ESBL). However, the contribution of dumpsite leachates in the environmental spread of ESBL genes has not been investigated in greater detail. This study aimed to quantify the impact of Ajakanga dumpsite leachate on the spread of ESBL genes through surface water. The susceptibility of Escherichia coli isolated from dumpsite leachate and the accompanying surface water to selected antibiotics was assessed by the standardized disc diffusion method. The isolates were evaluated for phenotypic ESBL production using the double disc synergy test (DDST). The detection of ESBL genes in the isolates was carried out using a primer-specific polymerase chain reaction (PCR). Escherichia coli isolates from leachate (n = 26/32) and surface water (n = 9/12) expressed ESBL phenotype. The ESBL-producing isolates showed the highest level of resistance to the 3rd generation cephalosporin antibiotics: cefotaxime (100%), cefpodoxime (97%), ceftazidime (97%), with low resistance observed to imipenem (6%) and azithromycin (3%). All the isolates were multidrug-resistant, showing resistance to three or more classes of antibiotics. All the ESBL-producing E. coli obtained carried bla CTX−M, 21/35 (60%) carried bla TEM while none of the isolates bore bla SHV. This study found that ESBL-producing Escherichia coli from dumpsite leachate and nearby surface water had identical resistance signatures indicating the relatedness of the isolates, and that dumpsite leachate could contribute to the transfer of ESBL-producing bacteria and their genes to receiving surface water. This study has necessitated the need for a review of the guidelines and operational procedures of dumpsites to forestall a potential public health challenge.

Abstract Designing a good vehicle for functional ingredients is the major focus of this study. Small molecular weight peptides (

This study evaluates the effects of rabbit compost tea and NPK (15-15-15) fertilizer on the growth parameters of maize (Zea mays L.) at the Teaching and Research Farm of Ekiti State Polytechnic, Isan-Ekiti. The treatments were laid out in a randomized complete block design (RCBD) with three replicates. Each replicate consisted of four (4) treatments. Total land area measured 88 m2 (11 m by 8 m) with 12 plots, and each plot size measured 3 m by 2 m (6 m2) with 1 m alleyways between plots and replicates. The treatments and application rate were the control, rabbit compost tea at 400 l ha-1, a combination of NPK at 100 kg ha-1 and rabbit compost tea at 200 l ha-1, and the application of NPK (15-15-15) fertilizer at the rate of 200 kg ha-1, which was incorporated as the experiment's standard treatment. In the experiment, growth parameters of maize (Zea mays L.) were monitored and evaluated. Findings showed that the application of rabbit compost tea and NPK (15-15-15) fertilizer significantly (p < 0.05) increased the plant height, stem girth, number of leaves, and leaf area when compared with the control, especially when combined. According to this study, rabbit compost tea is an effective and sustainable organic amendment that smallholder maize farmers should consider using to improve growth and output.

The inhuman socioeconomic repercussions of corruption and bad governance inherent in successive male-dominated governments have generated agitation for increased women’s participation in governance. Primarily, this agitation is based on the premise that women are less inclined to corruption, which is a major impediment to good governance. Given the notoriety of these two impediments to development, this study aims to investigate the relationship between women’s participation in governance, corruption, and quality of governance in sub-Saharan Africa from 1996 to 2021. This study analyzed annual panel data of four sub-Saharan African countries using the autoregressive distributed lag model and the Granger causality test. Governance quality was proxied by government effectiveness, while women’s participation in governance and corruption were proxied by the number of women in government positions and control of corruption, respectively. Economic development and institutional quality were used as control variables. The findings revealed negative main and interaction effects of women’s participation in governance and corruption on governance quality, unidirectional causality from corruption to women’s participation in governance and from governance quality to women’s participation in governance, and bidirectional causality between corruption and governance quality. Quantitative increases in women’s participation in governance and corruption exacerbates governance quality. Women’s ability to participate in governance is determined by the prevalence of corruption in previous years. Anticorruption campaigns that focused on women’s participation in governance often result in reductions in corruption insufficient for improvement of governance quality. Corruption and bad governance are mutually reinforcing. Governance quality determines women’s participation in governance. To minimize corruption and bad governance, sub-Saharan African countries should shift their focus away from merely increasing the number of women in government positions to building strong institutions capable of creating a meritocratic political and socioeconomic environment in which selfless women and men have equal chances of being elected or appointed to public offices.

Abstract Neurosurgical management of older patients is very complex and delicate; efforts are being made in identifying groups of older patients at risk of poor surgical outcomes before the surgery, making frailty an important concept in risk Identification and postoperative outcome assessment of older patients in the ever-changing neurosurgical world. It's of great importance for the concept of frailty to be adopted in Africa's neurosurgical practice in other to optimize the outcomes and improve the efficiency of neurosurgery in the older patients whose population is expanding, forming a great quota of people using neurosurgical services in Africa. This article looks into the importance and challenges of frailty studies in African neurosurgical practice which mainly are the longer length of time in carrying out such studies; reduces manpower, lack of availability of specialized equipment in standardizing the assessment, and others; makes recommendations on ways to ease its adoption such as funding frailty research and creation of population-specific frailty assessment tools among others.

Drug discovery and development is a time-consuming process that involves identifying, designing, and testing new drugs to address critical medical needs. In recent years, machine learning (ML) has played a vital role in technological advancements and has shown promising results in various drug discovery and development stages. ML can be categorized into supervised, unsupervised, semi-supervised, and reinforcement learning. Supervised learning is the most used category, helping organizations solve several real-world problems. This study presents a comprehensive survey of supervised learning algorithms in drug design and development, focusing on their learning process and succinct mathematical formulations, which are lacking in the literature. Additionally, the study discusses widely encountered challenges in applying supervised learning for drug discovery and potential solutions. This study will be beneficial to researchers and practitioners in the pharmaceutical industry as it provides a simplified yet comprehensive review of the main concepts, algorithms, challenges, and prospects in supervised learning.

BackgroundIn South Africa, between 1966 and 2014, there were three kidney transplant eras defined by evolving access to certain immunosuppressive therapies defined as Pre-CYA (before availability of cyclosporine), CYA (when cyclosporine became available), and New-Gen (availability of tacrolimus and mycophenolic acid). As such, factors influencing kidney graft failure may vary across these eras. Therefore, evaluating the consistency and reproducibility of models developed to study these variations using machine learning (ML) algorithms could enhance our understanding of post-transplant graft survival dynamics across these three eras.MethodsThis study explored the effectiveness of nine ML algorithms in predicting 10-year graft survival across the three eras. We developed and internally validated these algorithms using data spanning the specified eras. The predictive performance of these algorithms was assessed using the area under the curve (AUC) of the receiver operating characteristics curve (ROC), supported by other evaluation metrics. We employed local interpretable model-agnostic explanations to provide detailed interpretations of individual model predictions and used permutation importance to assess global feature importance across each era.ResultsOverall, the proportion of graft failure decreased from 41.5% in the Pre-CYA era to 15.1% in the New-Gen era. Our best-performing model across the three eras demonstrated high predictive accuracy. Notably, the ensemble models, particularly the Extra Trees model, emerged as standout performers, consistently achieving high AUC scores of 0.95, 0.95, and 0.97 across the eras. This indicates that the models achieved high consistency and reproducibility in predicting graft survival outcomes. Among the features evaluated, recipient age and donor age were the only features consistently influencing graft failure throughout these eras, while features such as glomerular filtration rate and recipient ethnicity showed high importance in specific eras, resulting in relatively poor historical transportability of the best model.ConclusionsOur study emphasises the significance of analysing post-kidney transplant outcomes and identifying era-specific factors mitigating graft failure. The proposed framework can serve as a foundation for future research and assist physicians in identifying patients at risk of graft failure.

Summary: The tumor microenvironment (TME) is characterized by a network of cancer cells, recruited immune cells, and extracellular matrix (ECM). However, the specific role of neutrophils during tumor development, and their interactions with other immune cells is still not well understood. Here, we use both standard well plate culture and an under oil microfluidic (UOM) assay with an integrated ECM bridge to elucidate how naive primary neutrophils respond to tumor cells. Our data demonstrated that tumor cells trigger cluster formation in neutrophils accompanied with the generation of reactive oxygen species (ROS) and neutrophil extracellular trap (NET) release. Using label-free optical metabolic imaging (OMI), we observed changes in the metabolic activities of primary neutrophils during the different clustering phases when challenged with tumor cells. Finally, our data demonstrates that neutrophils in direct contact, or in close proximity, with tumor cells exhibit greater metabolic activities compared to non-contact neutrophils.

Abstract Background Syzygium aromaticum has been used for over a century because it has biological qualities for several health-related problems, and the crude essential oils are known to contain several components that could be responsible for synergistic or antagonistic potentials in relation to their biological uses. The study was designed to compare the biological activities of the crude essential oil from the bud of Syzygium aromaticum and fractions obtained from column chromatography. Materials and methods The essential oil was extracted by hydrodistillation, and two prominent fractions, C1 and C2, were obtained from the column chromatography separation of the crude essential oil. The quantitative phytochemical analysis was done by standard methods, the antioxidant activity was determined by 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid (ABTS) scavenging assays. The antifungal activities were assessed by the agar diffusion method, while the anti-inflammatory activity was done using a lipoxygenase inhibitory assay. The major component observed in the crude and fractions was determined by gas chromatography–mass spectrometry (GC–MS) analysis. Results The phytochemical analysis showed that phenolic acid, tannin, saponin, flavonoids, alkaloids, cardiac glycosides, and terpenoids were present in variable quantities in all of the fractions and crude essential oil. The half-maximal inhibitory concentration (IC50) value for DPPH scavenging activity ranged from 226.1 to 301.2 µg/mL while that of ABTS scavenging activity ranged from 211.0 to 316.0 µg/mL. The lowest value of IC50 for both DPPH and ABTS was observed in fraction C1. The crude essential oil with a minimum inhibitory concentrations (MIC) value of 8.00 mg/mL was the most efficient against Candida albicans, Aspergillus penicillum, and Aspergillus niger. The anti-inflammatory assay showed C1 to have the lowest value of IC50 for the lipoxygenase assay. The major component observed in the crude essential oil as well as fraction C1 was eugenol, while fraction C2 had β-caryophyllene as the major component. Conclusions The result showed that all fractions as well as the crude essential oil exhibited antioxidant, antifungal, and anti-inflammatory activities, and the crude essential oil was synergic only with respect to its antifungal activity, while fraction C1 was more efficient as an anti-inflammatory and antioxidant agent.

Abstract Investigating the mineralogical compositions of soils under different geological formations becomes imperative for maximizing agricultural productivity and ensuring the long-term viability of agricultural practices. Therefore, studies were carried out on mineral compositions and diversities of soils developed over the Basement complex rock, Coastal plain sands and Ewekoro formations in Ogun state Nigeria. A total of nine profile pits (three per location) of 2 m × 1 m × 2 m size were dug in all the three locations. Soil samples were collected from the pedogenic horizons of each profile pits in replicates into a well labeled polyethylene bag. Using X-ray diffractometry (XRD) and scanning electron microscopy (SEM) the mineral contents and their relative abundance, elemental compositions and morphologies of the fine sand, coarse silt and clay fractions of the soils at different topographic positions were identified, described and compared. Results obtained from XRD and SEM analyses exhibited similarities. The most abundant elements in the basement complex and Ewekoro pedon were oxygen, carbon and silicon whereas in the coastal plain sand pedon, oxygen, carbon and aluminum were the most abundant element. The presence of mixed-layer illite, mica, kaolinite, quartz, hematite, anatase, goethite, and chlorite at varying degrees was observed in the pedons developed on these geological formations, although kaolinite and quartz dominated the soil matrix. The mineralogical complexity of the pedons followed the order of basement complex > coastal plain sand > Ewekoro formation. Profiles developed on the Ewekoro formation exhibited the highest degree of weathering, as evidenced by their chemical properties and mineralogical compositions. The petrographic evaluation of the three geological formations revealed that all pedons were rich in quartz and exhibited varying degrees of mineral complexity and maturation. The overlapping and distinct characteristics among the geologies indicated different stages of weathering. By using the mineral maturity index, profiles developed over the basement complex rock and the coastal plain sand could be regarded as sub-matured and this could have contributed significantly to the native fertility of these soils and profiles from the Ewekoro formation were the most weathered. The use of Ewekoro formation for agriculture would necessitate significant investments in agro-inputs and sound principles of soil management through integrated soil fertility management.

In a study of 56 randomly selected Traditional Mud Houses (TMHs) in Nigeria, the radiation health impacts of radon progeny were evaluated using CR-39 radon detectors within a rainy season. The measured radon concentration ranged from 17 to 174 Bq m-3, with an average value of 76 Bq m-3 (SD = 36). This was lower than the WHO’s recommended reference level of 100 Bq m-3. However, 24% of the surveyed houses exceeded this level, indicating potential health risks. The estimated Potential Alpha Energy Concentration (PAEC) due to its progeny ranged from 1.84 to 18.81 mWL with an average value of 8.24 mWL (SD=3.91). The computed annual effective doses yielded an average value of 3.06 ± 1.44 mSv y1, which is far less than the recommended reference level of 10 mSv y1 by the International Commission on Radiological Protection. The lifetime excess absolute risks varied from 0.4 × 104 to 3.9 × 104, with an average of 1.7 ± 0.8 × 104. Improved the ventilation systems, the application of cements plaster and distempers to the building walls and floor were recommended for older TMHs with ages greater than 50 y to mitigate radon exposure. This data can inform potential policy measures for indoor radon progeny control in Nigeria.

Background: Older adults have a high prevalence of chronic conditions like arthritis with morbidities, especially depression ranging up to 40% – 70%. Therefore, it is important to explore depression in older adults with arthritis. Aim: This study aimed to determine if any demographic and clinical factors are associated with depression in older adults aged ≥ 60 years with arthritis attending a rheumatology clinic. Setting: This is a cross-sectional study conducted over 6 months among 127 older adults on follow-up care in a university teaching hospital in the North-Eastern region of Nigeria. Methods: A clinical proforma with information about the type of arthritis, duration of illness, hospitalisation, use of medications, co-morbidity was utilised for the data collection. The Geriatric Depression Scale (GDS-30), sociodemographic questionnaire and clinical proforma were administered. Data were analysed using Statistical Product and Service Solutions (SPSS) version 26.0 with the level of significance set as 0.05. Results: The mean age (± standard deviation [s.d.]) was 66.6 (± 5.5) years, with males constituting 57.5%. The prevalence of depression was 57.8%. Osteoarthritis 30.2%, while 69.8% had rheumatoid arthritis. Sociodemographic factors associated with depression include age (p = 0.049), marital status (p = 0.001), and level of education (p = 0.001). Duration of illness (p = 0.02), hospitalisation (p = 0.03), and number of medications (p = 0.01) were clinical factors associated with depression score. Conclusion: The prevalence of depression in older people with arthritis is high and was associated with females, the widowed, no formal education; and those with long duration of illness, those using multiple medications, and those with repeated hospitalisation. Contribution: This finding can enhance the suspicion index for depression to establish standard operating procedures, which will help to improve therapeutic practice for caring for the older adult age group.

Diabetes mellitus is a global pandemic that is also fast rising in Africa, including Nigeria. Chronic consumption of white rice (WR) increases the risk of developing insulin resistance (IR) and type 2 diabetes (T2D). Similarly, Drosophila melanogaster is a suitable model organism for studying metabolic disorders. We hypothesized that maternal WR consumption could alter offspring's metabolic health and predispose to IR. Drosophila melanogaster (fruit fly) eggs were laid and developed on either Control, 50 % WR and 50 % brown rice (BR); and female adults maintained on these dietary regimens for 7 days. F1 and F2 offspring of these flies were fed either a normal diet or high sugar diet (HSD). The effects of maternal WR consumption on indices related to IR and T2D such as weight, locomotor activity, glucose, trehalose, glycogen and triglyceride (TG) were assessed in the parent and offspring generations. Similarly, the mRNA expression levels of ILP2, IRS, PEPCK and ACC were investigated. We found that WR consumption induced IR in the parent as evidenced by weight gain, significant increases in glucose, trehalose and TG levels, and reduced glycogen levels. Similarly, maternal WR consumption appeared to program for elevated glucose, trehalose and TG levels in F1 offspring with significant increases in trehalose and TG levels in the F2 offspring. These metabolic perturbations were accompanied by overexpression of ILP2, IRS, PEPCK and ACC. Offspring reared on HSD exhibited worsened conditions. In contrast, the levels of these metabolic signatures in the BR groups were comparable with the control. Taken together, our study demonstrates the potential of WR but not BR to program for transgenerational inheritance of IR-T2D-like phenotypes. This suggests that offspring of chronic WR consumers may be at risk of developing IR, affecting the development and health of future generations.

Neglected Tropical Diseases (NTDs) are debilitating, chronic illnesses that have the power to prolong poverty due to their negative effects on productivity, child development, social embarrassment, and maternal problems. Insufficient resources are available to raise awareness of these illnesses or locate previously unknown cases. More than one billion people worldwide are still affected by NTDs, which have significant social and financial repercussions for developing nations. Global targets have been set by the World Health Organization to prevent, control, eliminate, or eradicate NTDs, as well as broad and interdisciplinary aims linked to the Sustainable Development Goals targets. The Kigali Declaration, in which leading organizations and countries declared fresh commitments to step up efforts to eradicate NTDs, and the London Declaration aimed to control and eradicate ten NTDs by 2020. We reviewed the epidemiology and burden of NTDs, the success and challenges of eliminating NTDs, as well as therapeutic interventions for the management of NTDs. We also opined on future directions necessary for effective and holistic eradication of NTDs in affected regions. The successful eradication of NTD will significantly increase the socioeconomic and educational levels of the affected countries, thereby increasing the productive workforce and assisting in the accomplishment of some sustainable development goals. As a result, there is a need for global commitment to funding drug research and development.

Though insects have been part of African diets since ancient times due to their nutritional benefits, consumption of insects remains unpopular among some literate Nigerians. This study examined the knowledge and determinants of the use of insects as food among undergraduates in three south-western Nigerian universities, using 600 structured questionnaires. About 53% of the respondents have never eaten insects, while most respondents identified grasshopper (82.3%) and cockroaches (88.7%) as animal feed but not human diet. About 70% and 67% associated eating of cricket and termites, respectively to both human and animals. Factors that encouraged entomophagy include the awareness of insects as good sources of protein, the influence of family members who eat insects and the awareness of the medicinal values of insects. The major constraints to entomophagy were ignorance of the nutritive values of insects which accounted for 34.0% of the respondents and personal hatred for insect species (28.7%), stigmatization against those who eat insects (27.0%) and poor hygiene of those who process insects into food (23.0%). Age and value addition processing methods positively influenced insect consumption. Lack of money to buy other animal protein and meat type will cause the respondents to embrace entomophagy. Creating awareness on the benefits of edible insects will increase the practice of entomophagy and encourage more people to engage in insect farming.

This study was conducted to determine if it is Malthusian theory that viewed population growth as depressing employment opportunity, or Keynesian theory that supports the view of population growth enhancing employment opportunities that holds in the population and unemployment relationship in Nigeria within the period of 1981 to 2019. Data on age dependency and working–age population ratio were used to measure population growth, with unemployment rate as the explained variable. The datasets were sourced from the World Development Indicator database. The study employed the ARDL approach to cointegration to determine the long-run relationship of the variables. The results of the analysis show a long-run relationship between population and unemployment growth rate in Nigeria. Population growth was shown to be capable of significantly reducing unemployment in the long run thereby upholding the proposition of Keynesian theory of unemployment. However, the effect was shown to be the other way in the short run, thereby supporting the proposition of the Malthusian theory of population. The study therefore posits that the effect of population on unemployment is time variant. It is therefore recommended that the government of Nigeria should improve the quality of her population through education and health in order to be able to reap the gain in the future as population grows. Also, the potentialities in the growing population could be harnessed through increased aggregate demand when the government of Nigeria uses his fiscal stance to enhance the people’s income.

Since the Finance Act 2020 became effective, there have been scholarly debates regarding the impact of the hike in the value-added tax (VAT) rate from 5% to 7.5% on the general economy of Nigeria. One of the macroeconomic variables that often features in academic discussions is unemployment. Therefore, this study was aimed at examining the impact of the new VAT regime on the situation of unemployment in Nigeria. Autoregressive distributed lag (ARDL) framework was employed in the analysis. Thus, unemployment rate is the dynamic dependent variable while VAT revenue is the dynamic regressor. For robustness purposes, inflation rate and manufacturing output, which are commonly-discussed drivers of unemployment, are included as the control variables. Data on the macro variables were sourced from the World Bank’s World Development Indicators, Central Bank of Nigeria’s Statistical Bulletins and the Federal Inland Revenue Service’s Financial Reports. The data covered the period 1994−2021. Empirical findings revealed that the VAT revenues have a positive relationship with the unemployment rate, suggesting that the hike in VAT rate might have a contractionary impact on employment. Furthermore, the unemployment and inflation appear to have positive relationship over the long run. The proposition of Phillips curve is therefore rejected using data sourced from the Nigerian economy

The performance measurement of decision-making units (DMUs) can be optimised by strategically choosing the optimal input and output weights. This approach circumvents the potential complexities associated with establishing a common basis for ranking homogeneous units and managing the results from multiple efficient frontiers. Efficient frontier ranking is simplified by limiting the weights based on the intrinsic or technical connections between relevant inputs and outputs. It also creates a coherent framework that coordinates various considerations across all under-evaluated DMUs and variables. This method effectively examines the complexities related to the inputs and outputs of homogeneous units using conventional data envelopment analysis (DEA) models to evaluate the efficiency of these units.In the banking sector, the relationship between inputs and outputs is complex. This complexity requires careful attention, particularly in cases where the existence of one input or output is conditional on the existence of another. This dynamic is accentuated by the integration of advanced fintech solutions, which inherently provide significant benefits to banking operations. The use of appropriate analytical models for banking data is important. The synergy between advanced financial technologies and analytical methods has reached its peak in reducing losses and strengthening profits. This, in turn, facilitates the optimal allocation of financial resources to growth-oriented projects.The empirical application of weight-restricted DEA models to Turkey's mobile-internet-banking sector underscores their efficacy. These modified models contrast with the standard DEA versions, which often encounter challenges stemming from the allocation of weights to pivotal variables. This study demonstrates the tangible benefits of our approach and its potential to revolutionise the efficiency assessment landscape in the banking sector.The proposed unconventional model which is applied to Turkish Internet banking for the period extending from 2006 to 2018 and which takes a comprehensive weight restriction approach to DEA and encompasses all relevant input and output variables, resulted in strictly positive weights and a reduced count of inflated efficient units along with their scores. This is practically beneficent to banking sector in so far as it facilitates decision-making and related economic and financial planning, and as it proves to be a reliable benchmark by local or international banks intending to provide or develop Internet banking services.

Cola nitida, also known as Kola nut, is a tropical plant native to West Africa and has a rich history of traditional medicinal use. In this narrative review, we aim to provide an overview of the protective effects of Cola nitida in various health and disease states. Cola nitida has been traditionally used for its medicinal properties, and its bioactive compounds include caffeine, alkaloids, tannins, flavonoids, and phenolics. These compounds contribute to its potential therapeutic effects. Here, we examine the potential benefits of Cola nitida in several areas of health, discussing its role in cognitive function, cardiovascular health, immune system function, gastrointestinal health, and metabolic and endocrine health. Relevant original articles available from PubMed, African Journals Online (AJOL), SCOPUS, and Google Scholar were retrieved using the keywords “cola” AND “nitida” without date restriction until July 17, 2023. Evidence suggests that Cola nitida may have positive effects on health, with indications of adverse effects only from its chronic usage. However, more research is needed to establish its efficacy and safety. Cola nitida holds promise as a natural remedy for various health conditions. Understanding the benefits and limitations of Cola nitida will contribute to its effective utilization in health and disease management.

In recent years, machine learning (ML) has become a pivotal tool for predicting and diagnosing thyroid disease. While many studies have explored the use of individual ML models for thyroid disease detection, the accuracy and robustness of these single-model approaches are often constrained by data imbalance and inherent model biases. This study introduces a filter-based feature selection and stacking-based ensemble ML framework, tailored specifically for thyroid disease detection. This framework capitalizes on the collective strengths of multiple base models by aggregating their predictions, aiming to surpass the predictive performance of individual models. Such an approach can also reduce screening time and costs considering few clinical attributes are used for diagnosis. Through extensive experiments conducted on a clinical thyroid disease dataset, the filter-based feature selection approach and the ensemble learning method demonstrated superior discriminative ability, reflected by improved receiver operating characteristic-area under the curve (ROC-AUC) scores of 99.9%. The proposed framework sheds light on the complementary strengths of different base models, fostering a deeper understanding of their joint predictive performance. Our findings underscore the potential of ensemble strategies to significantly improve the efficacy of ML-based detection of thyroid diseases, marking a shift from reliance on single models to more robust, collective approaches.

Diabetic ketoacidosis (DKA) is a serious complication that affects millions of individuals globally and presents significant health complications. Hyperchloremia, an electrolyte imbalance characterized by high levels of chloride in the blood, may result in gastrointestinal problems, kidney damage, and even death, especially in DKA patients. Early detection and treatment of hyperchloremia are of utmost importance in the management of DKA. This study explores the potential of the bootstrap aggregating ensemble with random subspaces machine learning approach to predict the occurrence of hyperchloremia, providing a basis for early intervention and improved patient outcomes. We tested our approach with the retrospective MIMIC-III database containing 1177 DKA patients and compared it with previous studies with an area under the curve (AUC) of 100%. Our approach showed significant performance outperforming other methods. The combination of this approach may enhance the early detection and timely intervention of hyperchloremia cases, ultimately leading to improved patient outcomes and a more effective management of DKA-associated complications. Our work aims to contribute to the development of decision support tools for healthcare professionals, assisting them in making informed decisions for DKA patients, with a focus on preventing and managing hyperchloremia.

Abstract Background Drug resistance has been a global burden in the management of epilepsy. It is desirable if this could be predicted earlier in the course of management to give time for alternative and a more definitive mode of management, such as epilepsy surgeries. Methods We conducted a systematic review and meta-analysis to investigate the relationship between elevated age at the onset of the first seizure or cortical imaging abnormalities and the development of drug resistance in epilepsy. We performed a systematic search in PubMed, EMBASE, and SCOPUS databases for studies investigating the predictive utility of age of onset or cortical imaging abnormalities on drug resistance. Results Odds ratios (ORs) and hazard ratios (HRs) with 95% confidence intervals (CIs) were extracted and analyzed by the RevMan 5.4 software. Meta-analysis was done across 12 studies involving 5315 patients. Age of onset of seizures younger than 5 years was found to be associated with the development of drug resistance (OR: 0.685, 95% CI 0.410–0.960), also cortical imaging abnormalities were found to be associated with the development of drug resistance. Conclusion Children with early onset seizures could better from neurosurgical management than pharmacological management as the early age of onset was associated with drug resistance and cortical abnormalities on neuroimaging could be an indication for neurosurgical management of epilepsies.

Abstract This study modeled geophysical derived parameters and multi-critically synthesized their themes based on geospatial and analytical hierarchy processes (AHP) approaches for groundwater potentiality prediction mapping. These methodologies were investigated in a typical hard rock geologic terrain, southwestern, Nigeria. Considering the spatially acquired 96 vertical electrical sounding (VES) data in the area, geoelectric sections revealing five subsurface layers including the topsoil, laterite, weathered layer, fractured basement and fresh basement rock were produced mindful of the 2-D resistivity structure subsurface imaging data interpreted results. The correlative results of the 2-D resistivity structure images and VES data interpretation results delineated major low resistivity vertical discontinuity typical of fractured zones characterized with width range of 25–40 m, while the depth vary from about 40 to > 60 m. Themes of groundwater potential conditioning factors (GPCFs), namely: regolith, bedrock relief, hydraulic head, coefficient of anisotropy, aquifer resistivity and aquifer thickness were prepared from the re-analyzed hydrogeological and geophysical data. The produced themes were appropriately weighted in the context of AHP data mining technique. The groundwater potential prediction index (GPPI) mathematical modeling equation for the area was established via applying the weight linear average algorithm involving the AHP weightage results. The synthesized results of the applied GPPI model equation on the GPCFs’ hydrogeologic themes give GPPI values in the range 1.59–3.65 for the study area. The geospatial modeling of the GPPI estimated values result produced groundwater potential prediction index map for the area. The produced GPPI model map zoned the area into low (1.59–2.30), medium (2.30–2.61), medium–high (2.61–3.02) and high (3.02–3.65) groundwater potential classes. The area analysis of the GPPI map indicates that more than 70% of the study area has ‘low to medium groundwater potential. The GPPI map result verification using reacting operating characteristics technique results gave 86% and 81% success and prediction rates, respectively. The findings of this study are useful to water managers and decision-makers for locating appropriate positions of new productive wells in the study area and other areas with similar geologic settings.

Abstract Background Current malaria diagnosis methods that rely on microscopy and Histidine Rich Protein-2 (HRP2)-based rapid diagnostic tests (RDT) have drawbacks that necessitate the development of improved and complementary malaria diagnostic methods to overcome some or all these limitations. Consequently, the addition of automated detection and classification of malaria using laboratory methods can provide patients with more accurate and faster diagnosis. Therefore, this study used a machine-learning model to predict Plasmodium falciparum (Pf) antigen positivity (presence of malaria) based on sociodemographic behaviour, environment, and clinical features. Method Data from 200 Nigerian patients were used to develop predictive models using nested cross-validation and sequential backward feature selection (SBFS), with 80% of the dataset randomly selected for training and optimisation and the remaining 20% for testing the models. Outcomes were classified as Pf-positive or Pf-negative, corresponding to the presence or absence of malaria, respectively. Results Among the three machine learning models examined, the penalised logistic regression model had the best area under the receiver operating characteristic curve for the training set (AUC = 84%; 95% confidence interval [CI]: 75–93%) and test set (AUC = 83%; 95% CI: 63–100%). Increased odds of malaria were associated with higher body weight (adjusted odds ratio (AOR) = 4.50, 95% CI: 2.27 to 8.01, p

Abstract Recent advances in computer vision (CV) and natural language processing have been driven by exploiting big data on practical applications. However, these research fields are still limited by the sheer volume, versatility, and diversity of the available datasets. CV tasks, such as image captioning, which has primarily been carried out on natural images, still struggle to produce accurate and meaningful captions on sketched images often included in scientific and technical documents. The advancement of other tasks such as 3D reconstruction from 2D images requires larger datasets with multiple viewpoints. We introduce DeepPatent2, a large-scale dataset, providing more than 2.7 million technical drawings with 132,890 object names and 22,394 viewpoints extracted from 14 years of US design patent documents. We demonstrate the usefulness of DeepPatent2 with conceptual captioning. We further provide the potential usefulness of our dataset to facilitate other research areas such as 3D image reconstruction and image retrieval.

Production of zeolite-Y catalyst from natural substrate has been a research trend in the scientific community. Published articles revealed that zeolite-Y recovery from locally sourced metakaolin is confined to laboratory practice. Scale-up process design and its economic feasibility for zeolite-Y catalyst recovery are rarely found in the scientific bibliography. Therefore, this study presented conceptual scale-up process design, base-case techno-economics and Monte-Carlo simulation of zeolite Y recovery from Nigerian metakaoline. ASPEN Base Case Simulation (ABCS), scale-up design and economics were accomplished using inherent design and costing algorithms in ASPEN Batch Process Developer (ABPD) V10. Process economic parameters: Net Present Value (NPV), Internal Rate of Return (IRR), Return on Investment (ROI) and Payback Time (PBT), were modelled and optimized using Design Expert V13 software; while zeolite Unit Production Cost (UPC), Annual Production Cost (APC), Total Capital Investment (TCI) and interest/discount rate were considered as model inputs. Monte-Carlo Simulation (MCS) in Crystal Ball Oracle software was used to perform the sensitivity and uncertainty analyses. The base-case techno-economic results of process design of 600,000 kg/year zeolite production gave batch size 5000 kg/batch with 104 batches/year, batch time (4149 min), TCI ($15,930,306), APC ($147,145), NPV ($41,983,375), ROI (38.13 %) and PBT (2.14 years). The coefficient of determination (R2) of the economic models were 0.9978, 0.9989 and 0.9986 for NPV, ROI and IRR respectively. The optimum economic variables that maximized synthesis of 5000 kg/batch zeolite Y are UPC ($11.68), APC ($100,033) and TPC ($15,930,200). MCS uncertainty for NPV, IRR and ROI are negligible. Therefore, this study demonstrated that scale-up zeolite-Y production from the local substrate is economically feasible.

This study aims to assess the effectiveness of recent advancements in COVID-19 treatment, specifically antiviral medicines and monoclonal antibodies, in curbing the virus’s spread. We present a mathematical model incorporating these factors and qualitatively demonstrate its efficiency via positivity, existence and uniqueness of solution. Analyzing the basic reproductive threshold and sensitivity, we find that these therapeutic measures, coupled with heightened human awareness, effectively mitigate disease transmission. Employing the Laplace-Adomian decomposition method, we derive the model’s solution, confirming its accuracy via the ratio test. Numerical experiments using real-world COVID-19 data in Maple 18 software practically implies that while antiviral medications or monoclonal antibodies alone can lead to eradication, their combined implementation with increased human awareness results in rapid elimination.

We investigated the effect of both electron donating group and e//lectron withdrawing group on biological activity of pyrimidine-based compounds as metalloproteinase-7 inhibitors and predicting a library of drug-like compounds with potent cytotoxicity using in silico approach. The selected compounds were optimized and subjected to both docking as well as absorption, distribution, metabolism, excretion and toxicity (ADMET) analyzes. We observed that the addition of electron withdrawing group (–CF3) to the predicted pyrimidine-based compound induced a radical improvement in the hydrogen bond strength with Leu181 and Ala182 in matrix metalloproteinase-7. Also, communal orientation of 2-mercapto-4-(3-(trifluoromethyl)phenyl)-6-((4-(trifluoromethyl)phenyl)amino) pyrimidine-5-carbonitrile (PC10) and matrix metalloproteinase-7 showed improved binding tendency with calculated binding affinity value of -10.2 kcal mol−1 than other studied compounds. Our findings may open door for the design and development of library of efficient pyrimidine-based drug-like compounds as potential anti-cancer agents.

Untreated banana peels biomass of 15 x 10, 30 x 20 and 60 x 40 mm sizes were dried at 60 oC while untreated and pretreated (hot water and sulphite treated) biomass of 10 x 10 mm size were dried at 80 – 140 oC, to find out the influence of surface area, pretreatment and temperature on convective hot air oven drying of the biomass. The rate of drying of banana peels increased with increasing surface area and temperature while hot water and sulphite pretreatments reduced the time needed for drying. The drying operation occurred primarily in the falling-rate phase. Effective moisture diffusivities for the drying operations were in the range 5.19 x 10-10 – 1.55 x 10-8 m2 s-1. The activation energies for drying untreated, sulphite treated and hot water treated peels were 24.7, 21.4 and 21.3 kJ mol-1, respectively. The biomass drying kinetics was well described by the Weibull model. Specific energies needed for drying the 15 x 10, 30 x 20 and 60 x 40 mm banana peels biomass at 60 oC were 157.9 – 335.6 kWh/kg while those required for drying both untreated and pretreated 10 x 10 mm sized banana peels biomass at 80 – 140 oC were 33.5 – 93.9 kWh/kg. The rate of drying banana peels in hot air oven can be considerably improved and the energy needed for drying appreciably reduced by increasing the peel surface area, drying at higher temperatures and pretreating the biomass with hot water or sulphite solution.

Abstract Background Surgical management is one of the mainstay management options for cerebrovascular diseases, which is not only curative but also preventive. However, there's a gap between the surgical management of cerebrovascular disease in Africa when compared to the developed parts of the world. Methods A literature search was done on the state of Cerebrovascular surgery in Africa from databases such as Pubmed, Embase, and Google Scholar, articles we fetched and meticulously reviewed. Results We found gaps in the surgical management of cerebrovascular diseases such as stroke in African countries when compared to developed countries. The challenges facing the surgical management of cerebrovascular disease in Africa include a low number of neurosurgeons and vascular surgeons trained in the surgical management of these diseases, a lack of adequate facilities for surgical management, and others. The burden of cerebrovascular diseases in Africa is great, and this warrants an improvement in the surgical management of the conditions, which includes primary prevention of such diseases through public health education on risk factors, improvement of health facilities to accommodate recent advances in the cerebrovascular surgeries, establishments of several neurosurgery training centers. Conclusion The practice of surgical management of cerebrovascular disease in Africa needs to be optimized for it to be at the global standard and for better outcomes and management of patients.

Abstract Background Globally, child mortality and morbidity remain a serious health challenge and infectious diseases are the leading causes. The use of count models together with spatial analysis of the number of doses of childhood vaccines taken is limited in the literature. We used a Bayesian zero-inflated Poisson regression model with spatio-temporal components to assess the number of doses of childhood vaccines taken among children aged 12–23 months and their associated factors. Methods Data of 19,564 children from 2003, 2008, 2013 and 2018 population-based cross-sectional Nigeria Demographic and Health Survey were used. The childhood vaccines include one dose of Bacillus-Calmette-Guérin; three doses of Diphtheria-Pertussis-Tetanus; three doses of Polio and one dose of Measles. Uptake of all nine vaccines was regarded as full vaccination. We examined the multilevel factors associated with the number of doses of childhood vaccines taken using descriptive, bivariable and multivariable Bayesian models. Analysis was conducted in Stata version 16 and R statistical packages, and visualization in ArcGIS. Results The prevalence of full vaccination was 6.5% in 2003, 14.8% in 2008, 21.8% in 2013 and 23.3% in 2018. Full vaccination coverage ranged from 1.7% in Sokoto to 51.9% in Anambra. Factors associated with the number of doses of childhood vaccines taken include maternal age (adjusted Incidence “risk” Ratio (aIRR) = 1.05; 95% Credible Interval (CrI) = 1.03–1.07) for 25–34 years and (aIRR = 1.07; 95% CrI = 1.05–1.10) for 35–49 years and education: (aIRR = 1.11, 95% CrI = 1.09–1.14) for primary and (aIRR = 1.16; 95% CrI = 1.13–1.19) for secondary/tertiary education. Other significant factors are wealth status, antenatal care attendance, working status, use of skilled birth attendants, religion, mother’s desire for the child, community poverty rate, community illiteracy, and community unemployment. Conclusion Although full vaccination has remained low, there have been improvements over the years with wide disparities across the states. Improving the uptake of vaccines by educating women on the benefits of hospital delivery and vaccines through radio jingles and posters should be embraced, and state-specific efforts should be made to address inequality in access to routine vaccination in Nigeria.

Waste from low-density polyethylene products after lifespan accounts for 70% of solid waste in most dumpsites, contributing to environmental impacts. Eggshell foul smells are a threat to human and animal health. Before this study, there was no research documentation on transforming both wastes into green composites for engineering applications. This work developed composites using recycled low-density polyethylene (RLDPE) and eggshell Nanoparticles. They were evaluated structurally and mechanically. Straining, which affirms an improvement in the load-bearing capacity of the RLDPE due to the incorporation of eggshell Nanoparticles, was established by the composite XRD peak broadness. Structural integrities of the composites were confirmed with SEM. Maximum tensile strength was noted at 10% eggshell Nanoparticle additions to the RLDPE, equal to a 68% increase. About 52 and 19% enhancements in respective flexural strength and hardness value with a 0.85% reduction in impact energy were noted at 12% eggshell Nanoparticle additions. The probability value, 0.0481

Schistosomiasis remains one of the severe ailments that affect both man and woman in South Africa. It is caused by blood fluke, and the rate at which it causes death is alarming in some areas of America, Asia as well as in African countries. It is a neglected tropical disease (NTD) with grave impact on social and economic situation of countries with low sanitation awareness. Thus, the search for lasting solution to this menace, has drawn the attention of many global researchers using phytochemicals from Scilla natalensis via in silico approach. The studied compounds were optimized using Spartan 14. Docking study was executed via Pymol, Autodock tool, Auto dock vina and discovery studio. Compound 9 with –8.2 kcal mol–1 and –9.4 kcal mol–1 as binding affinity proved to possess highest ability to inhibit glutathione S-transferase and thioredoxin-glutathione reductase than other compounds. Also, ADMET properties for compound 9 and praziquantel were explored and reported. Our findings may open the door for the design of novel drug-like molecules with better efficiency.

Purpose Rice is a staple food in Nigeria, but its cultivation faces constraints of soil acidity, low soil fertility and rainfall variability. Research has shown that biochar has the potential to alleviate the effects of these conditions, but responses vary depending on soil and climate factors. Therefore, this study was conducted to evaluate the effects of different application rates of rice husk biochar on upland rice growth and yield.Method Two field experiments were conducted within two years in Kwara State located in the southern Guinea savanna agroecological zone of Nigeria. Four biochar rates (0, 5, 15 and 25 t/ha) were used and replicated thrice in a randomised complete block design set up on three soils in three locations. Agronomic data were subjected to analysis of variance (ANOVA) to quantify variations in treatment responses, followed by a separation of significantly different means using the least significant difference (LSD) at p≤ 0.05.Results Better growth was recorded in the first year compared to the second year. Percentage decreases of 9.4 and 11.4% were recorded in plant height (12 weeks after planting), and tiller productivity from the first to the second year, respectively. Biochar amendment significantly (p≤0.01) improved rice seedling emergence (34.6%) and seed weight (5.8%) relative to control. The highest grain yield of 5.24 t/ha was recorded under 15 t/ha biochar application rate compared to 2.37 t/ha under control.Conclusion The application rate of 15 t/ha increased rice yield by 55.0% relative to the control, whereas at 25 t/ha the growth and yield were reduced.

Abstract Background Hunteria umbellatta (HU) is a predominant plant with a share of therapeutic properties against various human diseases with no scientific report of its in vitro ethno-toxicology coupled with molecular implication in the literature. This study, therefore, evaluated in vitro toxicological activity and quantification of expression of specific swarming gene, lateral flagellar (Laf A) and adhesion gene (ExsE) of Vibrio parahaemolyticus (VP) treated with methanol seed and stem extracts of HU at 500, 250, 125, 62.5, 31.25, 15.625, 7.8125, 3.90625 µg/µL concentrations. Results The toxicological results of all the eight tested concentrations from as low as 3.90625 µg/µL to as high as 500 µg/µL of HU seed and stem extracts revealed significantly (p ˂ 0.05) uninhibited bacterial growth in a dose-dependent manner compared to controls (positive and negative). The quantity of Laf A and ExsE genes’ expressions in VP was significantly higher (p ˂ 0.05) at 500 µg/µL of HU seed and stem compared to control while at 125 µg/µL of the same extract (seed and stem) showed significantly lowered (p ˂ 0.05) expression of swarming and adhesion genes in VP relative to control. Comparative to control, adhesion gene (ExsE) expression in VP significantly increased (p ˂ 0.05) at 250 µg/µL of HU seed and stem extracts. Conclusions The results obtained suggest toxicity at varying concentrations and higher concentration dosing of HU seed and stem is harmful as it could lead to increased expression of the gene colonization factor of VP as a major contributory agent of gastroenteritis.

Abstract This study compared some quality properties of yellow-fleshed sweet potato flour samples as affected by pretreatments (0.02% sulfite; blanching 85 °C for 3 min 30 s and steam blanching 100 °C for 2 min) and drying methods (oven, sun, and drum drying). The physicochemical composition, functional properties, pasting profile, and least gelation concentration of the flours were determined. Before pretreatment, the sweet potato tubers were sorted, weighed, rinsed, peeled, and diced. The smallest particle size (58 μm) was recorded for samples blanched at 85 °C followed by oven drying while drum-dried samples had the largest particle size (119.5 μm). The pH values (5.58 - 5.90) of the pretreated sun- and oven-dried samples were significantly (p

Abstract Background and Aims With the global rise in type 2 diabetes, predictive modeling has become crucial for early detection, particularly in populations with low routine medical checkup profiles. This study aimed to develop a predictive model for type 2 diabetes using health check‐up data focusing on clinical details, demographic features, biochemical markers, and diabetes knowledge. Methods Data from 444 Nigerian patients were collected and analysed. We used 80% of this data set for training, and the remaining 20% for testing. Multivariable penalized logistic regression was employed to predict the disease onset, incorporating waist‐hip ratio (WHR), triglycerides (TG), catalase, and atherogenic indices of plasma (AIP). Results The predictive model demonstrated high accuracy, with an area under the curve of 99% (95% CI = 97%–100%) for the training set and 94% (95% CI = 89%–99%) for the test set. Notably, an increase in WHR (adjusted odds ratio [AOR] = 70.35; 95% CI = 10.04–493.1, p‐value

Objective To develop an international consensus statement to advise on designing, delivering and evaluating sport-based interventions (SBIs) aimed at promoting social, psychological and physical well-being in prison.Design Modified Delphi using two rounds of survey questionnaires and two consensus workshops.Participants A multidisciplinary panel of more than 40 experts from 15 international jurisdictions was formed, including representation from the following groups and stakeholders: professionals working in the justice system; officials from sport federations and organisations; academics with research experience of prisons, secure forensic mental health settings and SBIs; and policy-makers in criminal justice and sport.Results A core research team and advisory board developed the initial rationale, statement and survey. This survey produced qualitative data which was analysed thematically. The findings were presented at an in-person workshop. Panellists discussed the findings, and, using a modified nominal group technique, reached a consensus on objectives to be included in a revised statement. The core research team and advisory board revised the statement and recirculated it with a second survey. Findings from the second survey were discussed at a second, virtual, workshop. The core research team and advisory board further revised the consensus statement and recirculated it asking panellists for further comments. This iterative process resulted in seven final statement items; all participants have confirmed that they agreed with the content, objectives and recommendations of the final statement.Conclusions The statement can be used to assist those that design, deliver and evaluate SBIs by providing guidance on: (1) minimum levels of competence for those designing and delivering SBIs; (2) the design and delivery of inclusive programmes prioritising disadvantaged groups; and (3) evaluation measures which are carefully calibrated both to capture proposed programme outcomes and to advance an understanding of the systems, processes and experiences of sport engagement in prison.

Objective: Tramadol and 3,4-methylenedioxy-methamphetamine (MDMA) use over an extended period is linked to deficits in memory encoding and retrieval. We aimed to determine the neurotoxic effects of co-administration of MDMA and tramadol (TRAM) on hippocampal function and investigate the potential of FMRFamide in attenuating resulting alterations in the Wistar rat model. Methods: Thirty adult male Wistar rats were grouped into six (n=5): Control, FMRFamide, TRAM, MDMA, TRAM+MDMA, and TRAM + MDMA + FMRFamide groups. The opiates were administered orally at 20mg/kg each, while 2mg/kg of FMRFamide was administered intraperitoneally for 12 days using normal saline as a vehicle. The Barnes and Morris water mazes were used to evaluate spatial learning and memory functions, followed by H&E staining, and immunohistochemical staining for glial fibrillary acid protein (GFAP). Results: The opiates significantly increased total latencies in the Barnes Maze test, indicating that short- and long-term memory functions were impaired. Also, high levels of escape latency were observed following MDMA administration, suggesting that MDMA reduced the spatial navigation ability of the animals. These discrepancies were noticeably extreme in animals that received co-administration of opiates. However, FMRFamide showed significant potential in attenuating the damage induced by opiates, thus repairing and restoring memory formation and retention functions. Conclusion: FMRFamide may attenuate the Tramadol- and MDMA-mediated memory dysfunction by enhancing cholinergic and glutaminergic synthesis and transporting and restoring exploratory and navigational abilities in the hippocampus of male Wistar rats.

AbstractThe need to ensure availability of locust beans when off-season forms the basis of this study. The study investigated the drying characteristics, nutritional composition and some anti-nutritional contents of dried locust beans. Fermented locust beans were dried at 50°C, 60°C, 70°C and 90°C. The moisture contents of the fermented locust seeds were determined at different time intervals between 0 and 480 min. Lower moisture content was achieved in a shorter drying time at higher temperature. The dried locust bean samples had lower moisture contents (12.36–12.76%) compared to control sample (38.76%). Higher drying temperature resulted in low ash content of the samples but increased the fibre, fat and protein content of the samples. The dried samples had low mineral contents compared to the fresh sample, which was used as control. The most abundant mineral in the samples were found to be calcium and zinc. No significant difference was observed in the titratable acidity and the pH of the locust bean samples at varying drying temperature. Increase in temperature resulted to a reduction in the antioxidant, phenolic composition and the anti-nutritional properties of the dried locust bean samples. Panelists preferred samples dried at lower temperature (50°C and 60°C compared with the samples dried at high temperature. The study concluded that locust bean should be dried using a carefully selected temperature to avoid negative impacts on the nutrients of the beans.

A field experiment was conducted to evaluate the response of soil microorganisms (bacteria and fungi), to some soil amendments (organic and inorganic) at site A and site B. The experiments were laid out in a randomized complete block design (RCBD). The treatments applied were compost (3.4 t/ha), poultry manure (4.2 t/ha), Tithonia diversifolia (4.8 t/ha), NPK (15:15:15) (0.8 t/ha) at 120 kg N/ha, and the control. Treatments were replicated three times. Tomato seedlings were raised in the nursery and transplanted to the field after 3 weeks with a spacing of 50 × 50 cm. Soil microbiomes (Fungi and Bacteria) were isolated using the serial dilution technique. Compost improved both the total number of fungi by 12%–178% and diversity by 1.09%–85% compared to the other amendments at both sites, while the diversity of bacteria was increased more by Tithonia diversifolia (11%–75%). The total number of bacteria was highest in plots amended with compost at site A. Compost had the highest percentage of bacteria suppressed compared to other amendments studied at both sites (27.3% and 28.5%, respectively). NPK had the highest bacteria suppression at site A. The plot amended with NPK had the highest percentage of bacteria enhanced at site A. NPK had the highest at site B. Poultry had the highest reduction in bacteria at site A. Tithonia diversifolia had the highest percentage proliferation of allochthonous bacteria at both sites with 23.7% and 27.7%, respectively, while compost plots had the least allochthonous bacteria at both sites. At both sites, the percentage of suppressed fungi was highest in plots amended with poultry manure and control. Compost and T. diversifolia had the highest percentage of fungus growth reduction in site A (26.3%). At site A, compost had the highest percentage of allochthonous fungi (29%). Application of compost, poultry manure, and Tithonia diversifolia is recommended for the improvement of soil microbial properties.

Conventional drug delivery systems have several limitations, including poor bioavailability and an inability to effectively transport antibiotics to the needed site of infection in the bone. A formulation of ciprofloxacin-loaded microparticles derived from coconut oil and shea butter was developed to enable a selective and targeted distribution of the broad-spectrum antibiotic. Solid microparticles (SM), a mixture of solid and liquid lipid (coconut oil), solid-liquid microparticles (SLM), or coconut oil alone; liquid microparticles (LM), loaded with ciprofloxacin using the hot homogenization technique, were formulated. Evaluation of the microparticulate formulations included testing for particle size, the efficacy of entrapment, antibacterial activity, and in vitro drug release. The size of the microparticles that were loaded with ciprofloxacin ranked SM (5.25 ± 2.50 - 5.56 ± 2.01 μm) < SLM (7.94 ± 3.89 - 7.98 ± 2.00 μm) < LM (15.5 ± 1.50 - 20.29 ± 10.75 μm). The microparticulate formulations had an entrapment efficiency of 43.26% and 63.34% for the antibiotic ciprofloxacin. When tested against Staphylococcus aureus, all formulations exhibited good antibacterial activity; however, the microparticles generated from coconut oil and shea butter exhibited more significant antibacterial activity (zone of inhibition 24.0 ± 0.8 - 39.5 ± 9.2 mm), in comparison to the other formulations. LM had the fastest ciprofloxacin release (t50 = 5.5 min), but the microparticles formed from shea butter had a higher cumulative release (t50 = 12.7 min) compared to that from the mixture (p>0.05). These findings were obtained from in vitro drug release studies. The Korsmeyer-Peppas model could account for every formulation using the Fickian Case I transport mechanism. Because of their increased antibacterial activity, size, ability to entrap drugs, and in vitro drug release, the ciprofloxacin-loaded microparticles made from cold-pressed coconut oil combined with shea butter have the potential to provide a more effective treatment for bone diseases.

Measles is a highly contagious, dangerous virus-borne disease. Prior to the advent of the measles vaccine and widespread immunization in 1963, severe outbreaks occurred every 2-3 years. Mathematical model of measles with logistic growth and enlightenment to go for vaccination was proposed and presented, the disease-free and endemic equilibria were obtained and their stabilities were investigated, basic reproduction number was generated using next generation matrix. Laplace-Adomian decomposition was utilized to carry out the numerical simulation in order to investigate the impact of the parameters of the model. The results were presented graphically and it was established that both enlightenments to go for vaccination and vaccination itself are effective methods are the measure to eradicate transmission of the disease measles in the population

Abstract Previous studies on wind turbine and wind farm optimization for Levellized cost of energy (LCOE) and annual energy production (AEP) have focused on horizontal axis wind turbines (HAWT) and vertical axis wind turbines (VAWT). Regions with lower wind speed resources tend to have a higher levellized cost of energy and lower annual energy production. In this paper, the authors investigate the optimization of a novel, Ferris wheel wind turbine (FWT) for low wind speed regions of Africa. The research used an Excel‐based Multi‐Objective Optimization (EMOO) model. The EMOO program has both binary‐coded and real‐coded Elitist Non‐Dominated Sorting Genetic Algorithm (NSGA‐II). The optimization is conducted by studying the effect of varying the rim diameter, number of blades, and the rated wind speeds for an 800‐kW generator on the performance and economics in 21 African cities. The results show that, on average, the return‐on‐investment increases over the base design by up to 182%, and both the simple payback period (SPP) and the levellized cost of electricity decreased by 39% as the rim diameter increases combined with a 50% reduction in blade numbers. In addition, a 75% reduction in blade numbers caused a further 32% decrease on average for both the simple payback period and the levellized cost of electricity.

Abstract Healthcare tends to be one of the most complicated sectors, and hospitals exist at the core of healthcare activities. One of the most significant elements in hospitals is service quality level. Moreover, the dependency between factors, dynamic features, as well as objective and subjective uncertainties involved endure challenges to modern decision-making problems. Thus, in this paper, a decision-making approach is developed for hospital service quality assessment, using a Bayesian copula network based on a fuzzy rough set within neighborhood operators as a basis of that to deal with dynamic features as well as objective uncertainties. In the copula Bayesian network model, the Bayesian Network is utilized to illustrate the interrelationships between different factors graphically, while Copula is engaged in obtaining the joint probability distribution. Fuzzy rough set theory within neighborhood operators is employed for the subjective treatment of evidence from decision makers. The efficiency and practicality of the designed method are validated by an analysis of real hospital service quality in Iran. A novel framework for ranking a group of alternatives with consideration of different criteria is proposed by the combination of the Copula Bayesian Network and the extended fuzzy rough set technique. The subjective uncertainty of decision makers’ opinions is dealt with in a novel extension of fuzzy Rough set theory. The results highlighted that the proposed method has merits in reducing uncertainty and assessing the dependency between factors of complicated decision-making problems.

Introduction: The probability of contamination is frequently elevated in scenarios where a well and pit latrine coexist, or in situations where heavy rain causes the overflow of open excreta dumps, which in turn flush into wells and surface water. Many possible negative health effects might arise from exposure to various ecological and biological agents in the environment. Therefore, there is a need to examine the risk of disease transmission in Ife North Local Government Area (LGA) of Osun state, using epidemiological, environmental, and ecological factors. Materials and Methods: Geostatistical analysis was used to examine the epidemiological risk, based on various environmental, biological, and ecological variables. The technique employed demonstrated the complexity and multiple parameters that raise the probability of an epidemic. The Shapiro-Wilk test was used to determine whether or not the data were normally distributed. Fuzzy logic, correlation, and spline surface interpolation analysis were conducted using ArcGIS 10.3 and ENVI 5.0 software. Three levels of epidemic risk were used to construct the disease surveillance and projection maps. Results: According to the final susceptibility map, 8.08 km2 of 460.12 km2 of the research area were considered to be at very low risk for an epidemic, followed by 364.98km2 of low risk and 87.06km2 of moderate risk areas, with percentages of 1.75%, 79.32%, and 18.92%, respectively. Conclusion: A very substantial correlation was observed between biological and ecological components and water-borne diseases. It is, therefore, advised that all water sources be treated before consumption, and community involvement be encouraged in environmental sanitation programs.

Prostate cancer (PCa) symptoms are commonly confused with benign prostate hyperplasia (BPH), particularly in the early stages due to similarities between symptoms, and in some instances, underdiagnoses. Clinical methods have been utilized to diagnose PCa; however, at the full-blown stage, clinical methods usually present high risks of complicated side effects. Therefore, we proposed the use of support vector machine for early differential diagnosis of PCa (SVM-PCa-EDD). SVM was used to classify persons with and without PCa. We used the PCa dataset from the Kaggle Healthcare repository to develop and validate SVM model for classification. The PCa dataset consisted of 250 features and one class of features. Attributes considered in this study were age, body mass index (BMI), race, family history, obesity, trouble urinating, urine stream force, blood in semen, bone pain, and erectile dysfunction. The SVM-PCa-EDD was used for preprocessing the PCa dataset, specifically dealing with class imbalance, and for dimensionality reduction. After eliminating class imbalance, the area under the receiver operating characteristic (ROC) curve (AUC) of the logistic regression (LR) model trained with the downsampled dataset was 58.4%, whereas that of the AUC-ROC of LR trained with the class imbalance dataset was 54.3%. The SVM-PCa-EDD achieved 90% accuracy, 80% sensitivity, and 80% specificity. The validation of SVM-PCa-EDD using random forest and LR showed that SVM-PCa-EDD performed better in early differential diagnosis of PCa. The proposed model can assist medical experts in early diagnosis of PCa, particularly in resource-constrained healthcare settings and making further recommendations for PCa testing and treatment.

Public health education is pivotal in the management and control of infectious and non-infectious diseases. This manuscript presents and analyses a nonlinear fractional model of tungiasis dynamics with the impact of public health education for the first time. The human population is split into five classes depending on their disease status. The infected population is split into two subgroups; infected but unaware and infected but aware. The model focuses on the impacts of public health education, contact and treatment contact on tungiasis transmission dynamics. Notably, public health education is important for containing as well as reducing disease outbreaks in communities. The Caputo fractional derivative is utilised in defining the model governing equations. Model equilibrium points existence and stability are investigated using simple matrix algebra. Model analysis shows that tungiasis is contained when the reproduction number is less than unity. Otherwise, if it is greater than unity, the disease persists and spread in the population. The generalised Adams-Bashforth-Moulton approach is utilised in solving the derived tungiasis model numerically. The impacts of public health education, treatment and contact rate on overall disease dynamics are discussed through numerical simulations. From the simulations, we see that for given fractional order, public health education and treatment increase the quality of life plus reduce equilibrium numbers of tungiasis-infected individuals. We observe that population classes converge quicker to their steady states when α is increased. Thus, we can conclude that the derivative order α captures the role of experience or knowledge that individuals have on the disease's history.

Abstract Induction motors (IMs) are the most widely employed electrical motors due to their robust construction and adaptability. Due to their versatility and wide range of applications, it is crucial to examine the performance of these motors using a simple but thorough simulation model. In this study, we present the simulation models to conduct the DC test, the no-load test, and the locked rotor test on a three-phase induction motor using MATLAB/Simulink. These three tests are fundamental to determining the characteristics of a three-phase induction motor equivalent circuit. Furthermore, the authors extend the model to determine the starting current, starting torque, and breakdown torque of the motors under inquiry. The research further employs the right code in the MATLAB environment to ascertain the motors' torque-speed and current-speed properties. The results of the simulations are found to closely match the values achieved in real trials. Hence, this model can be employed to enhance teaching and research in the field of electrical machinery. Article Highlights This paper explains a computerized procedure employing MATLAB software to carry out vital tests on induction motors. The research shows that using the methods described in this paper, induction motors can be safely tested for their operating characteristics. The benefit of the computerized methodology described in this paper is that it provides a modelling tool and methodology to expand research on induction motors with high accuracy and reliability. The numerical method developed in this article is a suitable tool in teaching and education. Beyond the three common tests (dc test, no-load test and locked rotor test) to determine the equivalent circuit of induction motors, this paper further extends the research to use the simulation models to determine the starting current, starting torque and the breakdown torque of an induction motor as well as its torque-speed and current-speed characteristics.