Afe Babalola University

Electricity has become one of the adaptable forms of energy, and the capability to convert solar energy into electricity has facilitated its usefulness. Thus, estimation of the parameters of photovoltaic systems is critical for the design and establishment of an energy system. The objective of the study is to develop an approach that can simultaneously predict large parameters of photovoltaic systems with a high degree of accuracy for energy generation industries. The study introduced radial basis function neural network (RBFN) and feedforward backpropagation artificial neural network (FFBN) algorithms for simultaneous estimation of parameters of photovoltaic systems. In this study, two enhanced artificial neural network approaches are employed to estimate the parameters of photovoltaic systems simultaneously. The two approaches are the enhanced direct artificial neural network (EDANN) and enhanced inverse artificial neural network (EIANN). The results of the enhanced artificial neural network approaches were benchmarked against the findings of the conventional artificial neural network, random forest, and multiple linear regression. The output parameters for both of the enhanced models are radiation insolation (W/m²), generated power output (kWh), total energy (kWh), module temperature (°C), direct current (A), grid current (A), and voltage (V). The input parameters for the enhanced direct artificial neural network are the computed virtual functions from the selected candidate parameters. The input parameters for the enhanced inverse artificial neural network are the computed virtual functions and the predicted output from a single-output model. The accuracy of the EDANN is found to be higher than that of the EIANN for the FFBN and RBFN algorithms. Moreover, the accuracy of the FFBN approaches was found to be higher than that of the RBFN approaches. The accuracy of the FFBN-based enhanced direct artificial neural network is 1.02, 1.07, and 1.05 times that of the enhanced inverse artificial neural network in terms of mean absolute error (MAE), mean square error (MSE), and root mean square error (RMSE), respectively.

The present study aims to evaluate the interaction of gliclazide with proteins related to inflammation-{inhibitor of nuclear factor kappa-B kinase subunit beta (IKK alpha) and NF-kappa-B-inducing kinase (NIK)}; oxidative stress-{kelch domain of Kelch-like ECH-associated protein 1 (KKeap1)} and ER stress-{inositol-requiring enzyme-1alpha (IRE1 alpha)}. X-ray crystal structure of IKK alpha, (PDB ID: 5EBZ), KKeap1 (PDB ID: 4L7B), NIK (PDB ID: 8YHW) and IRE1 alpha (PDB ID: 4YZ9) were obtained from Protein Data Bank and Open Babel 3.1.1 was used to prepare the ligands. Prior to docking, protein structures were prepared by removing water molecules, adding hydrogen atoms, and optimizing side chain conformations using Maestro (Schr & ouml;dinger Suite, version 2024-2) along with the OPLS4 force field. Ligand docking was performed using the Glide application. Molecular dynamics simulation was performed with Desmond (Schr & ouml;dinger Suite) within the Maestro interface for 100 ns for the NPT ensemble at 300 K and 1 atm pressure. Physicochemical and pharmacokinetics properties were analyzed using ADMETlab 3.0 and SwissADME. The binding energies of gliclazide with IKK alpha, NIK, KKeap1 and IRE1 alpha were -8.3, -7.9, -8.4 and -8.8, respectively. Root mean square displacement (RMSD), root mean square fluctuation (RMSF) and radius of gyration analyses predicted relatively strong and stable interactions between gliclazide and the proteins, with favourable pharmacokinetic properties. It was also observed that CYP3A4 metabolizes gliclazide, in addition to CYP2C9 and CYP2C19. The activity of gliclazide against inflammation, oxidative stress and endoplasmic reticulum stress might be via interaction with these proteins.

3,4-Methylenedioxymethamphetamine (MDMA), widely misused for its euphoric and stimulant properties, induces overt neurotoxicity in rodents and non-human primates and is associated with profound neurochemical and structural brain alterations. Its deleterious effects are primarily mediated through oxidative stress, neuroinflammatory responses, and apoptotic pathways. Glutathione, a crucial endogenous antioxidant, has been proposed as a potential neuroprotective agent capable of mitigating MDMA-induced cerebral damage.Sixty adult male Wistar rats were randomly assigned to six experimental groups and administered oral treatments for 56 days: MDMA (5 mg/kg or 15 mg/kg), glutathione (15 mg/kg), or their combinations. After treatment, brain tissues were harvested and evaluated for oxidative stress biomarkers (8-OHdG, MDA, GPx, GSH, GST, SOD), pro-inflammatory cytokines (MPO, NF-κB, TNF-α), ion transport enzymes (Na⁺/K⁺ ATPase, Ca²⁺ ATPase), neurotransmitter levels (dopamine, serotonin, AChE), and the apoptotic marker caspase-3. Histological analysis of the hippocampus was conducted to assess structural integrity. MDMA administration led to significant elevations in MDA and 8-OHdG, reductions in antioxidant enzymes (GPx, GST, GSH, SOD), upregulation of inflammatory mediators (MPO, NF-κB, TNF-α), and disruption of ion homeostasis via altered Na⁺/K⁺ ATPase and Ca²⁺ ATPase activities. Neurotransmitter imbalances were observed, characterized by increased AChE and serotonin levels and decreased dopamine. Caspase-3 activity was markedly elevated, indicating enhanced apoptosis. Co-administration of glutathione at low MDMA doses ameliorated these effects, restoring antioxidant defenses, suppressing inflammation, and preserving hippocampal architecture. However, its protective efficacy was notably diminished at higher MDMA concentrations. Glutathione confers partial neuroprotection against MDMA-induced neurotoxicity, particularly under moderate exposure conditions. Its antioxidative capacity contributes to the restoration of redox equilibrium and cellular integrity. Nonetheless, under high-dose MDMA exposure, the therapeutic potential of glutathione is limited, suggesting the necessity for complementary interventions targeting excitotoxicity and mitochondrial dysfunction.

Repair complications following surgical repair, such as leakage, are associated with high mortality, highlighting the importance of determining the best method for closing perforated peptic ulcers. Accordingly, we compared methods of primary closure for perforated peptic ulcers. We conducted a literature search of PubMed, EBSCOhost, and the Cochrane Library for randomized trials that compared different techniques for open repair of giant and normal-sized perforated peptic ulcers (Graham’s patch, modified Graham’s patch, omental plugging, figure-of-eight repair, duodenal exclusion, jejunal serosa patch, and simple repair without an omental patch). The primary outcome was leakage of the repair. In total, 20 randomized controlled studies, mainly conducted in Asia and Africa, with six interventions and 1323 patients, were used for this network meta-analysis. Omental plugging was associated with the lowest postoperative leak rate for treating normal-sized perforated peptic ulcers (odds ratio [OR]: 0.0727; credible interval [CrI]: 0.00397, 0.608; P score=77.57

Heavy metal contamination of fruits is a growing public health concern globally, precisely in developing urbanizing regions where environmental surveillance is poor. The study investigated the concentration levels of seven heavy metals: As, Cd, Cr, Co, Mn, Ni and Pb in two commonly consumed fruits (watermelon and orange), purchased from four selected urban markets in Ado Ekiti, southwest, Nigeria. These fruits samples were purchase monthly for a period of 12 months. The samples were homogenized, digested and analyzed using atomic absorption spectrophotometry (AAS). Overall, majority of the heavy metal concentration levels was within WHO threshold. Although, isolated exceedances were observed, precisely for arsenic, which was well above the 0.10 mg/kg limit in both fruit types from Market 4 during the month of August. Concentration of Cr and Cd showed obvious monthly variations, although their concentration levels remained within WHO threshold in all markets used for sampling. Levels of Mn were the highest during the months of August to October, precisely in orange, while Pb levels were consistently low. Nickel concentrations revealed moderate temporal variations and high peaks were observed during the dry months without exceeding the WHO threshold. As regards spatial analysis, Market 4 constantly revealed elevated levels across months and metals. Seasonal variations was observed as higher metal variability was recorded during the late rainy season and early dry season. This study provides an uncommon multi-market 1 year-long assessment of heavy metals in fruits in southwest Nigeria, which could serve as a base line data for food safety monitoring.