Adekunle Ajasin University
Recent publications
This study evaluated aqueous Vernonia amygdalina leaf extract in drinking water as a mitigation strategy against Aflatoxin B1-induced toxicity in broilers, focusing on performance, haematology, serum biochemistry, pro-inflammatory cytokines, cellular stress markers, and liver histology. Two hundred and forty (240) day-old chicks (mixed sex), of the Cobb 500 breed were divided into four groups: control (CONT), AFB1-exposed (AFLB1), and two treatment groups (VE1AF and VE2AF) receiving 0.5 mg/kg AFB1 and Vernonia amygdalina aqueous extract at 1 g/L and 2 g/L, respectively. At 42 days, VE1AF and VE2AF chickens showed higher (P < 0.05) final weights and weight gains than CONT and AFLB1 groups. The red blood cells, packed cell volume, haemoglobin, and white blood cell counts were higher (P < 0.05) in CONT, VE1AF, and VE2AF groups compared to AFLB1. Mean cell volume, and mean cell haemaoglobin were higher (P < 0.05) in AFLB1 and VE2AF. Serum analysis revealed lower (P < 0.05) total protein, globulin, and albumin in AFLB1, which were restored by the extract. The tumor necrosis factor-α, interleukin-6, interleukin-1β, and interferon-γ, were elevated (P < 0.05) in AFLB1 but reduced in VE1AF and VE2AF. The heat shock protein 70, 8-hydroxy-2'-deoxyguanosine and adiponectin levels were higher (P < 0.05) in AFLB1, but were normalized by the extract in VE1AF and VE2AF. Leptin and triiodothyronine levels were significantly (P < 0.05) better in VE1AF and VE2AF, compared to AFLB1. Liver histology showed reduced inflammation in VE1AF and VE2AF, with near-normal hepatic architecture. In conclusion, Vernonia amygdalina leaf extract effectively counteracts AFB1 toxicity, enhancing overall health and performance in broiler chickens.
Diabetes mellitus is a chronic condition characterized by elevated blood glucose levels, which can lead to severe health complications if not properly managed. The increasing prevalence of diabetes worldwide has made it a major public health concern. This study formulates and analyzes an optimal control model for diabetes management, focusing on minimizing complications and treatment costs. The model is structured around a population of diabetic patients, incorporating dynamic interactions between healthy, susceptible, diabetic, complication, and treatment populations. An objective functional is defined, integrating costs associated with complications and treatment efforts, and is subjected to optimization through control strategies aimed at enhancing patient education, regular monitoring, and comprehensive care. The application of the Pontryagin Maximum Principle provides a solid theoretical foundation for identifying optimal control strategies. Utilizing a fourth-order Runge-Kutta method, the model is simulated under varying control conditions to assess the impact of interventions. The results demonstrate that increasing control measures significantly reduces the incidence of complications while improving treatment rates. The findings highlight the importance of strategic health management interventions in mitigating the burden of diabetes-related complications and emphasize the model's applicability in real-world healthcare settings. This research provides a robust framework for policymakers and healthcare providers to devise effective strategies that enhance the quality of care for diabetic patients.
Despite efforts to improve quality human capital, Nigeria consistently scores poorly in the human development index (HDI). The significance of institutions in human development has been emphasized in recent times as countries grapple with achieving sustainable development goals. Studies show that quality institutions provide equitable and fair development opportunities and capabilities to enhance human development. This study, therefore, examined the effect of institutions—corruption, democratic accountability, and government stability on Nigeria’s human capital development index. The ARDL model is employed to analyze data from 1990 to 2022. The outcomes show that a stable political system, high levels of democratic accountability, improved per capita GDP, employment generation, and consistent government spending on essential sectors are all critical for human capital development. Conversely, high rates of poverty and corruption have negative impacts on human capital. The findings lend credence to the intuition that strong institutions have a significant impact on enhancing quality human capital through improved healthcare, education, human capabilities, poverty reduction, employment opportunities, and security. It is therefore recommended that institutional reform that guarantees human development be pursued.
Breast cancer, the most commonly diagnosed disease worldwide, has been linked to the overexpression of the kinesin Eg5 protein, a spindle motor protein crucial for the assembly and maintenance of the bipolar spindle during mitosis. This makes Eg5 an attractive therapeutic target for tumor treatment. To address the urgent need for effective treatments for this lifethreatening illness, we utilized generative AI to design novel and potential inhibitors of this protein. In this study, a generative LSTM model was pretrained on SMILES data from ChEMBL and subsequently fine-tuned using SMILES of compounds with reported activity against the Eg5 protein. The fine-tuned model generated valid compounds, which were screened using a machine learning model, drug-likeness filters, molecular docking, and molecular dynamics (MD) simulations conducted over 200 ns. Five novel compounds with better binding affinities to Eg5 compared to the co-crystallized ligand were identified. The top compound, Compound 103 (a bioisostere of the co-crystallized ligand), demonstrated a significantly improved binding free energy (-82.68 kcal/mol) compared to the co-crystallized ligand (-76.98 kcal/mol), as determined by MM-GBSA calculations. ADMET predictions and MD simulations further confirmed that the top compounds interacted effectively with the target protein and exhibited drug-like properties. This study shows the potential of generative AI to explore our vast chemical space and find promising drug candidates. However, further in vitro and in vivo studies are needed to confirm the predicted biological effects of the top compounds.
Unlabelled: Lead optimization is vital for turning hit compounds into therapeutic drugs. This study builds upon a prior in silico research, where the hit compounds had better binding affinity and stability compared to a reference drug. Using a genetic algorithm, 12,500 analogs of the top compounds from the prior study were generated. Virtual screening was done using a quantitative structure-activity relationship (QSAR) model. Top analogs, selected based on pChembL values below 6.000nM, underwent molecular docking targeting Human Eg5. The top five analogs from this study (Compound 9794, Compound 8592, Compound 9786, Compound 2744, and Compound 3246) demonstrated strong binding energies and interactions with key amino acids (GLU 116, GLU 117, and ARG 119). MMGBSA analysis revealed comparable affinities to the co-crystallized ligand, suggesting the top analogs' potential as Human Eg5 inhibitors. Induced fit docking highlighted Compound 9786's superior efficacy. Quantum Polarized Ligand Docking indicated promising scores for Compounds 8592 and 9786. ADMET predictions offered insights into pharmacological properties, with all compounds predicted to be HIA-positive and non-carcinogenic. Further MD simulation study confirms the stability of the top compounds in the active site of Eg5. This study shows the significance of integrated strategies in drug design. However, in vitro and in vivo studies should be conducted for these promising candidates to confirm their efficacy as Eg5 inhibitors. Supplementary information: The online version contains supplementary material available at 10.1007/s40203-024-00300-6.
The thermally induced, solvent-based synthesis of [Cu(Ina)2·(H2O)]ISB (CuMOF) and [Ba(Ina)2·(H2O)]ISB (BaMOF) was achieved by refluxing at 200 °C for 30 min while stirring at 1000 revolutions per minute. The resulting complexes were characterized using elemental analysis, melting point determination, IR spectroscopy, UV–Visible spectroscopy, and mass spectroscopy. Yields of 79% and 96% were obtained for BaMOF and CuMOF, respectively. The IR spectra of the MOFs showed distinct differences from those of the ligand, indicating successful coordination between the ligand and the metal ion. Elemental analyses for C, H, and N were consistent with the proposed product formula units, demonstrating a strong correlation between the theoretically calculated values and the experimentally determined results. Characterization results revealed that copper and barium ions coordinate with isonicotinic acid through the carbonyl oxygen and the nitrogen of the pyridine ring. Additionally, a water molecule coordinates with the metal ions, contributing to an octahedral geometry with the ligand. Furthermore, isobutanol (C4H7O) is likely to act as a guest molecule within the complex's pore, forming an intermolecular hydrogen bond with the metal-isonicotinate. Quantum chemical calculations were performed on the molecular geometry, electronic, and optical properties of CuMOF and BaMOF using the DFT/B3LYP/LANL2DZ/6-311++G(d,p) level of theory. The reactivity parameters (such as energy gap) computed using hybrid B3LYP were standardized against highly parameterized M06-2x/LANL2DZ/6-311++G(d,p) method. The static (ħω = 0) and dynamic (ħω = 0.042823 au) optical properties of these materials were compared to those of potassium dihydrogen phosphate as a standard. The analysis of kinetic stability and selectivity indices including energy gap, electronegativity, global softness, electrophilicity, and electroaccepting power indicated that CuMOF is more chemically reactive, polarizable, and strongly electrophilic than BaMOF, while exhibiting lower electron-donating power. The molecular electrostatic potential analysis revealed that the nitrogen atom of isonicotinic acid and the oxygen atom of the carboxyl group serve as strong local nucleophilic sites. The nonlinear optical (NLO) response of the materials was significantly enhanced, showing an increase of 2 to 16 times compared to the standard. Additionally, CuMOF exhibited superior NLO properties compared to BaMOF. Notably, both materials demonstrated laser-enhanced NLO properties, as their dynamic optical characteristics exceeded those of their static counterparts suggesting their potentials in optical communication, optical data storage, optical limiters and optical switches.
To assess the ameliorative effects of wireweed leaf supplement (WLS) and ascorbate on reproductive potentials and gonadal oxidative status of cocks fed aflatoxin B1 (AFB1) contaminated diets, a total of 250 sexually mature cocks were distributed into five treatment groups: 1 (Control/Basal diet), 2 (Basal + 1 mg/kg AFB1), 3 (Basal + 1 mg/kg AFB1 + 200 mg/kg Ascorbate), 4 (Basal + 1 mg/kg AFB1 + 2.50 g/kg WLS) and 5 (Basal + 1 mg/kg AFB1 + 5.00 g/kg WLS). Each group was replicated 5 times with 10 cocks per replicate. The cocks in group 2 recorded significantly (P < 0.05) reduced daily sperm production and efficiency; gonadal antioxidative enzymes: superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GPx), total proteins, luteinising hormone and testosterone concentrations while there were significant (P < 0.05) elevations in the gonadal malondialdehyde (MDA), myeloperoxidase (MPO) peroxidation activity, 8-hydroxy-2′-deoxyguanosine (8-OHdG) and nitric oxide (NO) levels when compared with cocks in the control group. However, cocks in groups 3, 4 and 5 recorded improvements in all the parameters studied when compared with group 2 cocks. Therefore, inclusions of WLS and ascorbate were beneficial to the reproductive potentials of cocks fed AFB1 contaminated diets.
This article considers criminal law protection of property in Nigeria with particular focus on the offences of stealing and theft under the Criminal Code and Penal Code applicable in Southern and Northern Nigeria respectively. A comparative analysis and critique of the features of the offences under the two Codes are clearly spelt out. The English Theft Act, 1968 as amended by the Criminal Justice Act, 1991 and Penal Legislation of other jurisdictions are utilized for comparative analysis with a view to pointing out some loopholes and lacunas in the Criminal Code and the Penal Code with particular regard to the two offences. At the tail of the article, the writers proffered suggestions for the way forward and the need for legislative intervention to redraft some of the provisions of the two Codes dealing with stealing and theft.
A geoelectrical survey was carried out in parts of the Chad Basin Fadama Floodplain as a means of evaluating both the soil corrosivity and protective capacity. One hundred and six Schlumberger Vertical Electrical Sounding data were collected at the corners of a 225 x 225 m square grid network. Topsoil resistivity and topsoil longitudinal unit conductance maps were generated from the first and second order geoelectric parameters respectively. Areas considered as high corrosivity are the north central, southwestern, southern and northern parts with (r<180w-m). Part of the study area characterized by materials of poor to weak protective capacity has longitudinal conductance values of less than 0.1 and (0.1 - 0.19) mhos respectively. Values between (0.2 - 0.79 mhos - sandy clay cover) and (0.8 - 4.9 mhos - clay cover) correspond to moderate and good protective capacity respectively. It can thus be concluded that the flanks of the floodplain underlain by appreciable clayey topsoil thickness columns are susceptible to corrosion tendency. These same flanks are characterized by materials of moderate to good protective capacity and serve as sealing potential for the underlying hydrogeological system in the area.
The effect of Space weather is usually linked to disturbances in the ionosphere (gradients in the Total electron content (TEC)). This has signi?cant effect especially for GPS users causing degradation in range measurements, loss of lock by the receiver of the GPS signal. Knowledge of these TEC gradients is important to various GPS users. When a GPS signal encounters large gradients in TEC, the ionospheric error in the range measurement is difficult to model and therefore eliminated (for single frequency GPS users) or, in the case of differential GPS, cannot be canceled out. For differential GPS (DGPS) or real time kinematic (RTK) users, differences over the baseline as small as 2 TEC units, where one TEC unit is 10¹6 electrons/m2, can be problematic in resolving ambiguities. Though quite a lot has been done in the developed nations in this respect, there is a dearth of such information for the developing region. This paper therefore presents the variation of total electron content (TEC) over a tropical in at Akure, Nigeria (7.15ºN, 5.12ºE) using GPS data collected over a period of one year. The data was analyzed using the GPS-TEC analysis application software provided by Institute of scienti?c research, Boston College, USA. Result obtained shows signi?cant daily and seasonal variation TEC gradients in the region.
The need for making human asset of an economy, public and private, relevant and adequately responsive to thegrowth and development of the nation is stressed in this paper. Public sector is owned and controlled by thegovernment. This makes government to be the largest employer of labour. The onus of developing humanresources largely devolves on employers of labour. Human resources are relevant in organization for they makethings happen. The paper critically examined the concept of human resource, human resource management andworkers development and training as well as the relevance of human resource and the need for employeedevelopment in an organization. This paper submits that training and re-training of workers is needed, especiallyfor low-skilled workers for any organization to survive and realize its goals in this era of globalization andcompetitive economy.
The study empirically investigates the relationship between all public expenditures and industrial growth in Nigeria between the periods of 1970–2012. The dependent variables used is index of industrial productivity which serves as a proxy for industrial growth while the explanatory variables are government expenditure on Administration, economic services, social and community services, and transfers. The findings of the co-integration result reveal a long run relationship between industrial growth and government expenditure components. However, the estimated results reveal that government expenditure on administration, economic services, and transfers maintain a negative long run relationship with industrial growth in Nigeria while government expenditure on social and community services maintain a positive long run relationship. The Granger causality test shows that there exist no directional causality between government expenditure components and industrial growth in Nigeria in two lag periods. The study therefore serves as a pointer to the policy makers that there is need to accelerate industrial growth by changing the productive content of public expenditure in Nigeria.
Increasing attention has been drawn to the concentrations of particulate matter in cities because of the consequent health burden and environmental impacts. Due to its importance, particulate matter has been integrated into the UN SDG 11 as a target for monitoring and fostering sustainable communities. However, the paucity and irregularity of data pose a challenge to achieving the SDGs. This study aims to investigate the concentrations of particulate matter (PM2.5) in Nigerian cities and compare the predictions using machine learning models and open-source data, including satellite-derived data. The influence of meteorological factors, population growth, and human activities on PM2.5 emissions in eleven locations in Nigeria was investigated. The algorithms are linear regression (LR), K nearest neighbor (KNN), decision tree regression (DTR), support vector regression (SVR), artificial neural networks (ANN) and CatBoost (CBT). Hyperparameter optimization of the models was carried out by an exhaustive search of possible values and fivefold cross-validation. The results showed that the SVR, CBT, and ANN mostly predict PM2.5 to be more correlated to the actual targets than the KNN, DTR and LR during the training and test phases. The CatBoost is the best predictor with a root mean square error (RMSE) of 9.88 whereas decision tree regression had the highest error with an RMSE of 15.75. Precipitation made the highest contribution to the CatBoost prediction model, followed by temperature and nighttime light. The findings can be used in the management of particulate matter concentrations in the context of ground data paucity.
The Externalists and Internalists interrogated the crisis of development in Africa and have suggested solutions. In response to the challenge, successive governments have adopted theories, initiated policies and strategies to remedy the situation. In spite of these efforts, the attainment of a commendable stage of development has eluded majority of African nations, this is largely because the conception of development is erroneously predicated on the monistic neglecting the dualistic aspects of development. This paper, does not only correct this misconception it also philosophically explore how Africa can overcome contemporary and future sustainable development challenges, by articulating sustainable development paradigm appropriate for the continent. The paper argued for the necessity of a complement involving the quantitative and qualitative aspects of the dualistic conception rather than a straight jacketed approach that focuses more on the quantitative aspect in the quest for development. The paper employs the analytic and prescriptive approaches of philosophical inquiry.
This research delved into the intricate physiological responses of African land snails exposed to leachates from metal scrap dumpsites in Ado Ekiti metropolis. Raw leachates were collected from different leachate wells at the two dumpsites, these were used to form concentrations (v/v; leachate: dechlorinated tap water) and offered as drinking water throughout the study. A total of 80 points of lay snails ( Archachatina marginata ) 160.25 ± 5.84g and 7–8 months were used as test organism to assess the effect of the leachate. The snails were randomly allotted into four treatments, with four replicates and five snails per replicate representing the different leachate sample concentrations i.e T1-0%, T2-33.3%, T3- 66.67% and T4-100%. Results obtained indicated that the sodium, calcium, potassium, chromium, manganese and magnesium values of the leachates were higher than safety limits. The final weight of snails in T3 was significantly (P<0.05) higher than other treatment. The gonadosomatic index of snails in T1 was similar to T3 and T4 but significantly (p<0.05) higher than those on T2. Snails exposed to metal leachates have lower antioxidant activities compared with those on T1. In conclusion, the exposure of snails to higher concentrations of the leachates indicates potential toxicity and a tendency for impairment in reproductive capacity.
The article is devoted to the study of human behavior during the COVID-19 pandemic in two African countries – Tanzania and Nigeria. Using our own field data, the authors analyzed the dynamics of the level of anxiety on the background of stress from the spread of COVID-19 during two large waves of the pandemic: 1) from May to August 2020 with an average peak on May 11; 2) from June to September 2021. The total sample was 1034 people. One of the authors’ hypotheses was that different control strategies in these countries led to different levels of stress in the population. The most important factor was not only the level of morbidity and mortality in the country, but also the lack of information and misinformation. Using the example of the two African countries, it is shown that misinformation, concealment of official statistics and fear of uncertainty led to an increase in anxiety among the population of Tanzania and slowed down the psychological adaptation of people in the context of a global crisis, observed in many countries around the world a year after the spread of coronavirus infections.
Recently, significant progress has been made in establishing relationships between geophysical and geotechnical datasets to evaluate subsurface geological characteristics, especially to address engineering infrastructure failures. This research, therefore, explores the efficiency of machine learning (ML) combined with descriptive statistics in optimizing geophysical and geotechnical datasets from electrical resistivity tomography (ERT) and standard penetration tests (SPT-N) for subsurface lithological characterization of the Kabota-Tawau area in Sabah, Malaysia. As the first report of such analysis in this area, the study aims to address infrastructure design challenges posed by the increasing needs of the growing population. The derived ERT models, coupled with k-means clustering and regression results for modeled resistivity–SPT-N data at varying depths, clearly depict the main lithologies of the study area. The lithological units include the topsoil, weathered soil units, highly weathered/fractured units, and relatively weathered/fractured units. The use of regression analysis enabled the identification of new statistical correlations between resistivity and SPT-N in the area. These correlations accurately predicted outcomes with a 77% accuracy rate, supported by highly efficient performance values from the descriptive statistics. The predictions were based on resistivity values specific to different lithologies, which were determined to be < 150 Ωm. This progress is useful for forecasting SPT-N and reducing survey expenses, especially in extensive regions earmarked for infrastructure projects. Despite the study area’s generally low resistivities, associated with low load-bearing capacity, the study suggests modifications for the placement of medium to heavy infrastructure weights in highly to relatively weathered units. However, piling to the fresh bedrock is advised for high-rise buildings of super weights. Based on the research findings, the established ML-assisted methodological approach can be applied to other terrains with similar geology, particularly for early-stage subsurface characterization.
Despite the age-long ban on the production of polychlorinated biphenyls (PCBs), exposure to humans continues because of the persistent nature of the chemical. This study is a baseline assessment of the exposure level of the blood and urine of auto-mechanics to PCB congeners in Akure metropolis, Nigeria. Exposure assessment was based on total PCBs in blood and urine of smoking and non-smoking auto-mechanics. PCB congeners were analyzed by high-resolution gas chromatography coupled with an electron capture detector (GC-ECD). Total PCB concentrations in blood and urine, computed as the sum of the 19 congeners ranged from 0.365 to 7.534 µg/L and 0.069 to 1.099 µg/L, respectively. The study showed no correlation between PCB concentrations in blood and urine. The study observed a significantly lower sum of non-dioxin-like PCBs (PCB-28, 52, 101, 118, 138, 153, and 180) in urine (0.021–0.267 µg/L) than those in blood (0.056–3.001 µg/L). On average, the dioxin-like PCBs constituted over 20% and 25% of the total PCBs in blood and urine, respectively. Six low-chlorinated PCB congeners (1, 31, 52, 66, 77, and 118) constituted on average 81% and 41% of the total average PCBs in blood and urine samples, respectively. Thus, they could serve as indicator PCBs in the blood and urine samples of artisans. Comparatively, the study recorded greater contributions of different dioxin-like PCBs to the total toxic equivalent quantity (TEQ) in smoking than in non-smoking auto-mechanics. Our findings showed PCBs and dioxin-like activity as potential biomarkers in the blood and urine samples of artisans. The study also suggests potential exposure to PCBs via occupational and domestic engagements.
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714 members
Isaac Ayodele Ololade
  • Chemical Sciences
Ebenezer Oniya
  • Department of Physics and Electronics
Oludare Temitope Osuntokun
  • Department of Microbiology
Oluyinka Akanmu Ojedokun
  • Pure & Applied Psychology
Andrew B Falowo
  • Department of Animal Science
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Address
Ondo, Nigeria
Head of institution
Prof. Olugbenga Ige