Exploring the Effect of Exercise versus Metformin on Insulin Resistance amongst Nigerians with Pre-diabetes: A Randomised Controlled Trial.

BACKGROUND: Pre-diabetes is an important risk factor for the development of type 2 diabetes and is common in Nigeria. Effective intervention can reverse the underlying pathogenesis of insulin resistance in pre-diabetes. This study aimed to determine and compare the impact of moderate exercise and metformin interventions on insulin resistance among participants with pre-diabetes. MATERIALS AND METHODS: Using a randomised placebo-controlled design, 54 Nigerians with pre-diabetes were selected using simple random sampling. They were offered metformin, moderate exercise or placebo treatment and followed up for 12 weeks. Insulin resistance was assessed before and after the interventions and the outcome was compared. RESULTS: Forty-nine participants with pre-diabetes completed the study. Participants in both the exercise and metformin groups had significantly decreased insulin resistance compared to placebo after 12 weeks of intervention. However, there was a decrease in insulin resistance by 77.3% (homeostasis model assessment-insulin resistance [HOMA-IR]) and an increase in insulin sensitivity by 81.2% (quantitative insulin sensitivity check index [QUICKI]) in the exercise group. In comparison, participants in the metformin group had a decrease in insulin resistance by 66.3% (HOMA-IR) and an increase in insulin sensitivity by 76.2% (QUICKI). CONCLUSION: Amongst Nigerians with pre-diabetes, both moderate exercise and metformin have significantly higher efficacy than placebo in improving insulin resistance. However, moderate exercise improved insulin resistance more than the metformin intervention. Participants in this study need to be followed up for a longer period to assess the long-term effects of these interventions.

QSAR, molecular docking, and pharmacokinetic analysis of thiosemicarbazone-indole compounds targeting prostate cancer cells.

Objectives: By 2030, prostate cancer is estimated to account for 1.7 million new cases and 499,000 deaths. The objectives of this research were to create a model revealing the activity of thiosemicarbazone-indole compounds as anticancer agents against the PC3 cell line; perform docking analysis between the compounds and the target enzyme; and predict the pharmacokinetics and drug-likeness of the compounds under investigation. Methods: The quantitative structureactivity relationship (QSAR) method was used to build the model; molecular docking between the compounds and the target enzyme was performed; and the drug-likeness and pharmacokinetics of the inhibiting compounds was examined. Results: The genetic function algorithm-multilinear regression approach was used for building the QSAR model. Build model 1 had the best performance, with R2 (coefficient of determination) = 0.972517, Radj (adjusted R-squared) = 0.964665, (CRp2) = 0.780922, and LOF (leave-one-out cross-validation) = 0.076524, demonstrated strongly indicated by the molecular descriptors. SHBd, SsCH3, JGI2, and RDF60P were highly dependent on proliferative activity. Compounds ID 7 and 22 had the potential to act as androgen receptor inhibitors, as suggested by molecular docking studies between the drugs and their target enzymes. Compounds ID 7 and 22 exhibited binding scores of -8.5 kcal/mol and -8.8 kcal/mol, respectively. The approved maximum medication molecules for oral bioavailability included the molecules with IDs 7 and 22. Conclusion: This research provides valuable insights into the relationships among molecular descriptors, potential inhibitors, and pharmacokinetic properties in the treatment of PC3. These findings may contribute to the understanding and potential development of new therapeutic options for prostate cancer patients.

Exploring the potential of 2-arylbenzimidazole scaffolds as novel α-amylase inhibitors: QSAR, molecular docking, simulation and pharmacokinetic studies.

Previous studies have shown that 2-arylbenzimidazole derivatives have a strong anti-diabetic effect. To further explore this potential, we develop new analogues of the compound using ligand-based drug design and tested their inhibitory and binding properties through QSAR analyses, molecular docking, dynamic simulations and pharmacokinetic studies. By using quantitative structure activity relationship and ligand-based modification, a highly precise predictive model and design of potent compounds was developed from the derivatives of 2-arylbenzimidazoles. Molecular docking and simulation studies were then conducted to identify the optimal binding poses and pharmacokinetic profiles of the newly generated therapeutic drugs. DFT was employed to optimize the chemical structures of 2-arylbenzimidazole derivatives using B3LYP/6-31G* as the basis set. The model with the highest R2trng set, R2adj, Q2cv, and R2test sets (0.926, 0.912, 0.903, and 0.709 respectively) was chosen to predict the inhibitory activities of the derivatives. Five analogues designed using ligand-based strategy had higher activity than the hit molecule. Additionally, the designed molecules had more favorable MolDock scores than the hit molecule and acarbose and simulation studies confirm on their stability and binding affinities towards the protein. The ADME and druglikeness properties of the analogues indicated that they are safe to consume orally and have a high potential for total clearance. The results of this study showed that the suggested analogues could act as α-amylase inhibitors, which could be used as a basis for the creation of new drugs to treat type 2 diabetes mellitus.

Identification of estrogen receptor agonists among hydroxylated polychlorinated biphenyls using classification-based quantitative structure-activity relationship models.

Identification of estrogen receptor (ER) agonists among environmental toxicants is essential for assessing the potential impact of toxicants on human health. Using 2D autocorrelation descriptors as predictor variables, two binary logistic regression models were developed to identify active ER agonists among hydroxylated polychlorinated biphenyls (OH-PCBs). The classifications made by the two models on the training set compounds resulted in accuracy, sensitivity and specificity of 95.9 %, 93.9 % and 97.6 % for ERα dataset and 91.9 %, 90.9 % and 92.7 % for ERß dataset. The areas under the ROC curves, constructed with the training set data, were found to be 0.985 and 0.987 for the two models. Predictions made by models I and II correctly classified 84.0 % and 88.0 % of the test set compounds and 89.8 % and 85.8% of the cross-validation set compounds respectively. The two classification-based QSAR models proposed in this paper are considered robust and reliable for rapid identification of ERα and ERß agonists among OH-PCB congeners.

Activity prediction, structure-based drug design, molecular docking, and pharmacokinetic studies of 1,4-dihydropyridines derivatives as α-amylase inhibitors.

Objectives: Diabetes places a substantial economic burden on countries worldwide. The costs associated with diabetes management, including healthcare services, medications, monitoring equipment, and productivity losses, are substantial. The International Diabetes Federation has estimated that global healthcare expenditures associated with diabetes and its complications exceed hundreds of billions of dollars annually. Therefore, a critical need exists to develop drugs that are highly effective, affordable, and easily accessible to society. Methods: This study explored the structural modification of 1,4-DHP derivatives to identify specific α-amylase inhibitors, with the aim of developing more effective and accessible drugs for diabetes. We evaluated the activity and binding ability of the designed compounds. In addition, we performed drug-likeness and pharmacokinetic studies on the modified compounds. Results: Equation (1) had the highest accuracy, on the basis of internal and external assessment parameters, including R2int = 0.852, R2adj = 0.803, Q2cv = 0.731, and R2ext = 0.884. Moreover, the five potent analogs identified through structure-based drug design demonstrated a more favorable interaction than observed for the template or acarbose. Additionally, comprehensive studies on the drug-like properties and pharmacokinetics of the designed compounds supported their oral safety and favorable pharmacokinetic profiles. Conclusions: The designed analogs show promise for developing new hypoglycemic agents. Their positive attributes and performance suggest that they may potentially serve as candidates for further research in improving treatments for high blood sugar-associated conditions.

Ligand-based drug design of quinazolin-4(3H)-ones as breast cancer inhibitors using QSAR modeling, molecular docking, and pharmacological profiling.

BACKGROUND: Breast cancer is the most common tumor among females globally. Its prevalence is growing around the world, and it is alleged to be the leading cause of cancer death. Approved anti-breast cancer drugs display several side effects and resistance during the early treatment stage. Hence, there is a need for the development of more effective and safer drugs. This research was aimed at designing more potent quinazolin-4(3H)-one molecules as breast cancer inhibitors using a ligand-based design approach, studying their modes of interaction with the target enzyme using molecular docking simulation, and predicting their pharmacological properties. METHODS: The QSAR model was developed using a series of quinazoline-4(3H)-one derivatives by utilizing Material Studio v8.0 software and validated both internally and externally. Applicability domain virtual screening was utilized in selecting the template molecule, which was structurally modified to design more potent molecules. The inhibitive capacities of the design molecules were predicted using the developed model. Furthermore, molecular docking was performed with the EGFR target active site residues, which were obtained from the protein data bank online server (PDB ID: 2ITO) using Molegro Virtual Docker (MVD) software. SwissADME and pkCSM online sites were utilized in predicting the pharmacological properties of the designed molecules. RESULTS: Four QSAR models were generated, and the first model was selected due to its excellent internal and external statistical parameters as follows: R2 = 0.919, R2adj = 0.898, Q2cv = 0.819, and R2pred = 0.7907. The robustness of the model was also confirmed by the result of the Y-scrambling test performed with cR2p = 0.7049. The selected model was employed to design seven molecules, with compound 4 (pIC50 = 5.18) adopted as the template. All the designed compounds exhibit better activities ranging from pIC50 = 5.43 to 5.91 compared to the template and Doruxybucin (pIC50 = 5.35). The results of molecular docking revealed better binding with the EGFR target compared with the template and Doruxybucin. The designed compounds exhibit encouraging therapeutic applicability, as evidenced by the findings of pharmacological property prediction. CONCLUSIONS: The designed derivatives could be utilized as novel anti-breast cancer agents.

Limited emergence of resistance to integrase strand transfer inhibitors (INSTIs) in ART-experienced participants failing dolutegravir-based antiretroviral therapy: a cross-sectional analysis of a Northeast Nigerian cohort.

BACKGROUND: Due to the high prevalence of resistance to NNRTI-based ART since 2018, consolidated recommendations from the WHO have indicated dolutegravir as the preferred drug of choice for HIV treatment globally. There is a paucity of resistance outcome data from HIV-1 non-B subtypes circulating across West Africa. AIMS: We characterized the mutational profiles of persons living with HIV from a cross-sectional cohort in North-East Nigeria failing a dolutegravir-based ART regimen. METHODS: WGS of plasma samples collected from 61 HIV-1-infected participants following virological failure of dolutegravir-based ART were sequenced using the Illumina platform. Sequencing was successfully completed for samples from 55 participants. Following quality control, 33 full genomes were analysed from participants with a median age of 40 years and median time on ART of 9 years. HIV-1 subtyping was performed using SNAPPy. RESULTS: Most participants had mutational profiles reflective of exposure to previous first- and second-line ART regimens comprised NRTIs and NNRTIs. More than half of participants had one or more drug resistance-associated mutations (DRMs) affecting susceptibility to NRTIs (17/33; 52%) and NNRTIs (24/33; 73%). Almost a quarter of participants (8/33; 24.4%) had one or more DRMs affecting tenofovir susceptibility. Only one participant, infected with HIV-1 subtype G, had evidence of DRMs affecting dolutegravir susceptibility-this was characterized by the T66A, G118R, E138K and R263K mutations. CONCLUSIONS: This study found a low prevalence of resistance to dolutegravir; the data are therefore supportive of the continual rollout of dolutegravir as the primary first-line regimen for ART-naive participants and the preferred switch to second-line ART across the region. However, population-level, longer-term data collection on dolutegravir outcomes are required to further guide implementation and policy action across the region.

Virtual screening, pharmacokinetic, and DFT studies of anticancer compounds as potential V600E-BRAF kinase inhibitors.

Objectives: V600E-BRAF kinase is an essential therapeutic target in melanoma and other types of tumors. Because of its resistance to known inhibitors and the adverse effects of some identified inhibitors, investigation of new potent inhibitors is necessary. Methods: In the present work, in silico strategies such as molecular docking simulation, pharmacokinetic evaluation, and density functional theory (DFT) computations were used to identify potential V600E-BRAF inhibitors from a set of 72 anticancer compounds in the PubChem database. Results: Five top-ranked molecules (12, 15, 30, 31, and 35) with excellent docking scores (MolDock score ≥90 kcal mol-1, Rerank score ≥60 kcal mol-1) were selected. Several potential binding interactions were discovered between the molecules and V600E-BRAF. The formation of H-bonds and hydrophobic interactions with essential residues of V600E-BRAF suggested the high stability of these complexes. The selected compounds had excellent pharmacological properties according to the drug likeness rules (bioavailability) and pharmacokinetic properties. Similarly, the energy for the frontier molecular orbitals, such as the HOMO, LUMO, energy gap, and other reactivity parameters, was computed with DFT. The frontier molecular orbital surfaces and electrostatic potentials were investigated to demonstrate the charge-density distributions potentially associated with anticancer activity. Conclusion: The identified compounds were found to be potent hit compounds for V600E-BRAF inhibition with superior pharmacokinetic properties; therefore, they may be promising cancer drug candidates.

New flavone-based arylamides as potential V600E-BRAF inhibitors: Molecular docking, DFT, and pharmacokinetic properties.

Objectives: The V600E-BRAF protein kinase is an attractive and essential therapeutic target in melanoma and other tumors. However, because of its resistance to the known inhibitors and side effects of some identified inhibitors, new potent inhibitors need to be identified. Methods: In the present work, in silico strategies such as the molecular docking simulation, DFT (Density-Functional-Theory) computations, and pharmacokinetic evaluation were used to determine potential V600E-BRAF inhibitors from a set of 31 synthesized novel flavone-based arylamides. Results: The docking result demonstrated that four compounds (10, 11, 28, and 31) had acceptable docking scores (MolDock score of -167.523 kcal mol-1, -158.168 kcal mol-1, -160.581 kcal mol-1,-162.302 kcal mol-1, and a Rerank score of -124.365, -129.365, -135.878 and -117.081, respectively) appeared as most active and potent V600E-BRAF inhibitors that topped vemurafenib (-158.139 and -118.607 kcal mol-1). The appearance of H-bonds and hydrophobic interactions with essential residues for V600E-BRAF proved the high stability of these complexes. The energy for the frontier molecular orbitals such as HOMO, LUMO, energy gap, and other reactivity parameters was computed using DFT. The frontier molecular-orbital surfaces and electrostatic potentials (EPs) were investigated to demonstrate the charge-density distributions that might be linked to anticancer activity. Similarly, the chosen compounds revealed superior pharmacological properties according to the drug-likeness rules (bioavailability) and pharmacokinetic properties. Conclusion: The chosen compounds were recognized as potent V600E-BRAF inhibitors with superior pharmacokinetic properties and could be promising cancer drug candidates.

Pharmacokinetic profiling of quinazoline-4(3H)-one analogs as EGFR inhibitors: 3D-QSAR modeling, molecular docking studies and the design of therapeutic agents.

Objectives: Breast tumor is ranked as the most common tumor type identified among women globally with over 1.7 million cases annually, representing 11.9% of the total number of cancer cases. Approved anti-breast tumor drugs exhibit several side effects and some patients develop resistance during the early treatment stage. This study aimed to use an in-silico approach to identify and design potential therapeutic agents. Methods: Robust 3D-QSAR models were developed using quinazoline-4(3H)-one analogs as EGFR inhibitors. The best model was then selected based on statistical parameters and was subsequently used to design more potent therapeutic agents. Molecular docking simulation was executed using the data set and the designed compounds to identify lead compounds which were further screened by pharmacokinetic profiling by applying SwissADME and pkCSM software. Results: Internal validations of the best CoMFA and CoMSIA models (R2 = 0.855 and 0.895; Q2 = 0.570 and 0.599) passed the threshold values for the establishment of a consistent QSAR model. The constructed models were further validated externally using six compounds as a test set, thus revealing a satisfactory predicted correlation coefficient (R2 pred = 0.657 and 0.681). The CoMSIA_SHE models with the best statistical parameters were further subjected to applicability domain checks and only three influentials were detected. These were then utilized to design five novel compounds with activities ranging from 5.62 to 6.03. Molecular docking studies confirmed that compounds 20 to 26, with docking scores ranging from -163.729 to -169.796, represented lead compounds with higher docking scores compared to Gefitinib (-127.495). Furthermore, the designed compounds exhibited better docking scores ranging from -171.379 to -179.138. Conclusions: Pharmacological studies identified compounds 20, 24 26 and the designed compounds 2, 3, 5 as feasible drug candidates. However, these theoretical findings should now be validated experimentally.

Modelling PIP4K2A inhibitory activity of 1,7-naphthyridine analogues using machine learning and molecular docking studies.

PIP4K2A is a type II lipid kinase that catalyzed the rate-limiting step of the conversion of phosphatidylinositol-5-phosphate (PI5P) into phosphatidylinositol 4,5-bisphosphate (PI4,5P2). PIP4K2A has been intricately linked to the inhibition of various types of tumors via reactive oxygen species-mediated apoptosis, making it an important therapeutic target. In the quest of finding biologically active substances with efficient PIP4K2A inhibitory activity, machine learning algorithms were used to investigate the quantitative relationship between structures and inhibitory activities of 1,7-naphthyridine analogues. Three machine learning algorithms (MLR, ANN, and SVM) were used to develop QSAR models that can effectively predict the PIP4K2A inhibitory activity of a library of 1,7-naphthyridine analogues. The cascaded feature selection method was performed by sequential application of GFA and MP5 algorithms to identify a molecular descriptor subset that can best describe the PIP4K2A inhibitory activity of 1,7-naphthyridine analogues. PIP4K2A inhibitory activities predicted by the ML models were strongly correlated with the experimental values. The QSAR Modelling indicates that the best-performing ML model was SVM with the RBF kernel function. The SVM model performed very well in predicting PIP4K2A inhibitory activity of the 1,7-naphthyridine analogues with RTR and QEX values of 0.9845 and 0.8793 respectively. To further gain more structural insight into the origin of PIP4K2A inhibitory activity of 1,7-naphthyridine analogues, molecular docking studies were performed. The results indicate that five compounds; 15, 25, 13, 09, and 28 were found to have a high binding affinity with the receptor molecules. Hydrogen bonding, pi-pi interaction, and pi-cation interactions were found to modulate the binding interaction of the inhibitors. Although the SVM gives essentially a black-box model which cannot be readily interpreted, using SVM in tandem with MLR and ANN provides a unique perspective in building robust QSAR predictive models. The superior predictive performance of the ML models and the explanatory power of MLR models were combined to provide a unique insight into the structure-activity relationship of 1,7-naphthyridine inhibitors. This is relevant in that it provides information that can be invaluable as guidelines for the design of novel PIP4K2A inhibitors.

L-Arginine Grafted Chitosan as Corrosion Inhibitor for Mild Steel Protection.

Corrosion prevention has been a global phenomenon, particularly in metallic and construction engineering. Most inhibitors are expensive and toxic. Therefore, developing nontoxic and cheap corrosion inhibitors has been a way forward. In this work, L-arginine was successfully grafted on chitosan by the thermal technique using a reflux condenser. This copolymer was characterized by Fourier-transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), and X-ray diffraction (XRD). The corrosion inhibition performance of the composite polymer was tested on mild steel in 0.5M HCl by electrochemical methods. The potentiodynamic polarization (PDP) and electrochemical impedance spectroscopy (EIS) results were consistent. The inhibition efficiency at optimum concentration rose to 91.4%. The quantum chemical calculation parameters show good properties of the material as a corrosion inhibitor. The molecular structure of the inhibitor was subjected to density functional theory (DFT) to understand its theoretical properties, and the results confirmed the inhibition efficiency of the grafted polymer for corrosion prevention.

In silico analysis of noscapine compounds as anti-tumor agents targeting the tubulin receptor.

Objective: This research aims to develop a mathematical model that relates the structural features of noscapine with anti-tumor activity, to explains the mode of binding between noscapine compounds and the target receptor tubulin by docking analysis. By considering the results of docking analysis and predictions of pharmacokinetic properties/drug likeness, we designed novel noscapine compounds as anti-tumor agents against pancreatic cancer. Methods: We used an in silico quantitative structure-activity relationship (QSAR) approach, molecular docking analysis and online tools for pharmacokinetics and drug likeness prediction to develop novel compounds. Results: A QSAR model with good validations parameters and quality of fit (R2 = 0.9731, Q2 CV = 0.9434, R2 adj = 0.9647 and R2 test set = 0.8343) was built utilizing 70% of the dataset as a training set and the remaining 30% as an external validation to ascertain its predictive capability. Three novel compounds were designed: D3, D4 and D6 with binding scores of -11.2, -10.2 and 10.6 kcal/mol, respectively, exhibiting high affinity towards the tubulin receptor than the template (parent compound) and the co-crystallized ligand (E∗) with a binding score of 9.2 kcal/mol. Conclusion: The QSAR approach and molecular docking analysis is an important approach for modern drug discovery. Pharmacokinetics studies of the selected novel compounds revealed good drug properties and can be used as candidate compounds for the development of anti-tumor agents for pancreatic cancer.

Nigerian Muslim's Perceptions of Changes in Diet, Weight, and Health Status during Ramadan: A Nationwide Cross-Sectional Study.

The Islamic month of Ramadan is marked by fasting, when Muslims refrain from eating and drinking from dawn to sunset, which has an impact on their dietary habits. The study aimed to assess Nigerian Muslims' dietary modifications during Ramadan and their related changes in body weight and health status. A web-based cross-sectional study was conducted among Nigerian adult Muslims. The survey assessed sociodemographic, dietary habits, eating behaviors, food choices, perceived weight changes, and health status. The logistic regression model was used to assess the predictors of weight change and perceived health status. There were 770 participants, 62.9% of whom were women, ranging in age from 18 to 60 years with a mean age of 27.7 ± 6.4 years. Fruits, palm dates, homemade foods, milk products, and vegetables were more frequently consumed. There were fewer energy drinks, pastries, salty snacks, and carbonated or sugared drinks consumed during Ramadan than before. Over half (54.6%, 95% CI: 51.0-58.9%) of the respondents lost weight during Ramadan, 37.0% (95% CI: 17.4-38.6%) maintained their weight and 8.4% (95% CI: 6.6-10.6%) gained weight during the month. Nearly all (97.3%, 95% CI: 95.8-98.3%) reported having good health during Ramadan, and 2.7% (95% CI: 1.7-4.1%) reported having a poorer health state during Ramadan. There was a significant weight loss and healthy dietary change associated with Ramadan fasting in Nigeria. Public health measures must be in place to impart such positive health behaviors so that such healthy habits continue throughout the year.

Kinetics and computational study of butyrylcholinesterase inhibition by methylrosmarinate: relevance to Alzheimer's disease treatment.

Butyrylcholinesterase (BChE) performs a significant function in Alzheimer's disease progression. Experimental studies have shown that the function of BChE in the attenuation of cholinergic neurotransmission is essentially altered in brains of advanced AD patients. Here, using the complimentary methods of enzyme kinetic studies, molecular modeling and protein-ligand interaction profiling, we sought to reveal the mechanistic and structural features of BChE-methyrosmarinate interactions. Molecular docking simulations revealed that methylrosmarinate dwelled well in the active centre of BChE, where it got involved in stabilizing non-covalent associations with myriad subsites. Enzyme kinetic experiments showed that the V m and K s values were 156.20 ± 3.11 U mg-1 protein and 0.13 ± 0.01 µM, respectively. The inhibition studies showed that methylrosmarinate apparently inhibited BChE in a linear mixed manner, with an IC 50 value of 10.31 µM and a K i value of 3.73 ± 1.52 µM. Taken together, the extremely reduced K i value and the increased number of BChE-methylrosmarinate interactions presuppose that methylrosmarinate is a good inhibitor of BChE, despite the fact that the mechanism for the effect of BChE inhibition on several pathological conditions in vivo remains unexplored.

Assessment of family needs of children with cerebral palsy in Northern-Nigeria: A cross-sectional study.

PURPOSE: This study aimed to identify the needs and priorities of parents of children with cerebral palsy (CP) in order to improve care by increasing family participation in rehabilitation programmes. METHODS: This cross-sectional questionnaire-based study was conducted between January to March 2019. Convenience sampling was used to recruit 43 family members (18 years and above) of children with CP who came to the physiotherapy departments for rehabilitation services for their children. Fisher's exact test was used to analyse the association between socio-demographic characteristics and each of the need items. RESULTS: Five different items were identified to be the family needs that were most frequently met: a) 'need for active involvement in the child's treatment and therapies' (n= 40; 93.0%), b) 'need for the provision of standard medical care (n= 39; 90.7%), c) 'need for questions to be answered honestly' (n= 38; 88.4%), d) 'need for healthcare professionals to respect the child's wishes' (n= 36; 83.7%), e) 'need for mothers to discuss their feelings (depression, stress etc.) with someone who has similar experience' (n= 36; 83.7%). Conversely, three items were the most unmet family needs: a) 'need to have professionals to consult whenever the child needs help' (n= 39; 90.7%), b) 'need to be informed about the child's prognosis' (n= 41; 95.3%), and c) 'need to have financial support to provide the child with adequate care' (n= 43; 100%). CONCLUSION: All participants overwhelmingly reported that their financial needs were their highest priority. The multiple needs of families of children with disabilities must be assessed and considered in rehabilitation services when treating children with CP.

QSAR modelling and molecular docking studies for anti-cancer compounds against melanoma cell line SK-MEL-2.

A dataset of seventy-two (72) cytotoxic compounds of the National Cancer Institute (NCI) was studied by QSAR and docking approaches to gain deeper insights into ligands selectivity on SK-MEL-2 cell line. The QSAR model was built using fifty (50) molecules and the best-generated model based on multiple linear regression showed, respectively good quality of fits ( R 2 (0.864), R a d j u s t e d 2 (0.845), Q2 cv (0.799) and R p r e d 2 (0.706)). The model's predictive ability was determined by a test set of twenty-two (22) compounds. Compounds 30 and 41 were selected as templates for in silico design because they had high pGI50 activity and are in the model's applicability domain. The obtained information from the model was explored to design novel molecules by introducing various modifications. Moreover, the designed compounds with better-predicted activity (pGI50) values were selected and docked on the active site of the protein (PDB-CODE: 3OG7) which is responsible for melanoma cancer to elucidate their binding mode. AN2 (-12.1kcalmol-1) and AC4 (-12.4kcalmol-1) showed a better binding score for the target when compared with (vemurafenib, -11.3kcalmol-1) the known inhibitor of the target (V600E-BRAF). These findings may be very helpful in early anti-cancer drug development.

Removing the mask on hypertension (REMAH) study: Design; quality of blood pressure phenotypes and characteristics of the first 490 participants.

Purpose: Previous studies that evaluated the prevalence of hypertension in Nigeria were either clinic based, non-standardized or did not include out-of-clinic blood pressure (BP) measurement. Materials and Methods: We selected a rural and an urban community in one state in each of the 6 geopolitical zones of Nigeria. Five consecutive BP of adults older than 18 years were measured in the clinic following which, each participant was provided with a home BP device to obtain duplicate morning and evening BP for 3 days. Result: Out of 556 invited from Anambra State, South-East Nigeria, 490 (88%) consented. Overall, more women participated in both rural (115 vs 61, p < .0001) and urban (213 vs 101; p < .0001) sites. About 35.9% of participants had their home BP monitored. Of the 4890 clinic BP readings, 29.8%, 16.3%, 16.6%, 16.4% and 20.8% ended in 0,2,4,6 and 8 digits respectively. Only 0.8% ended in odd numbers. Of the identical BP readings,5 (0.20%), 6 (0.25%), 56 (2.30%) and 316 (12.9%) SBP and 8 (0.33%), 17 (0.70%), 93 (3.80%), 319 (13.1%) DBP had no difference in five, four, three and two values of the five consecutive readings. Conclusion: REMAH is feasible and the quality of BP will ensure that the final results are robust.

Meningococcus serogroup C clonal complex ST-10217 outbreak in Zamfara State, Northern Nigeria.

After the successful roll out of MenAfriVac, Nigeria has experienced sequential meningitis outbreaks attributed to meningococcus serogroup C (NmC). Zamfara State in North-western Nigeria recently was at the epicentre of the largest NmC outbreak in the 21st Century with 7,140 suspected meningitis cases and 553 deaths reported between December 2016 and May 2017. The overall attack rate was 155 per 100,000 population and children 5-14 years accounted for 47% (3,369/7,140) of suspected cases. The case fatality rate (CFR) among children 5-9 years was 10%, double that reported among adults ≥ 30 years (5%). NmC and pneumococcus accounted for 94% (172/184) and 5% (9/184) of the laboratory-confirmed cases, respectively. The sequenced NmC belonged to the ST-10217 clonal complex (CC). All serotyped pneumococci were PCV10 serotypes. The emergence of NmC ST-10217 CC outbreaks threatens the public health gains made by MenAfriVac, which calls for an urgent strategic action against meningitis outbreaks.