African neuroscience on the global stage: Nigeria as a model

Of the 572 neuroscience-related studies published in Nigerian from 1996 to 2017, <5% used state-of-the-art techniques, none used transgenic models, and only one study was published in a top-tier journal

CHRONIC KIDNEY DISEASE AMONGST SICKLE CELL ANAEMIA PATIENT AT THE UNIVERSITY OF MAIDUGURI TEACHING HOSPITAL, NORTH EASTERN NIGERIA: A STUDY OF PREVALENCE AND RISK FACTORS

ABSTRACT Introduction: Involvement of the kidneys in patient with sickle cell anaemia is a well recognized chronic complication of this disorder. The index study seeks to determine the prevalence of chronic kidney disease in patients with homozygous sickle cell disease (HbSS) and to identify risk factors associated with its development. Methodology: The subjects consisted of adolescents and adults with HbSS recruited sequentially from the adult haematology outpatient clinic and Day care ward of the unit. Clinical variables including age of diagnosis of SCA, frequency of vaso-occlusive crisis and transfusion therapy, as well as laboratory data including haematological profile, renal function test were obtained from routine blood result. The glomerular filtration rate was estimated (eGFR) using the ‘modification of diet in renal disease’ (MDRD) formula.. Results: Two hundred and eighty-four HbSS patients were recruited. The prevalence of CKD amongst them was 38.9%.  Further stratification of the patients based on eGFR showed that sixty-nine (26.8%) had hyperfiltration; 35 (13.6%) stage 1 CKD; 53 (20.6%) stage 2 CKD; 61 (23.7%) stage 3 CKD; 30 (11.7%) stage 4 CKD and 9 (3.5%) had end stage renal disease. There was significant association between eGFR and clinical parameters such as age (r -0.353, p=0.000), SBP (r -0.148, p= 0.021), DBP (r -0.213, p=0.001) and total number of blood received (r -0.276, p=0.000); and laboratory parameters such as  PCV (r 0.371, p=0.000); urea ( r 0.527, p=000 ); creatinine (r 0.625, p=0.000) and uric acid  ( r -0.419, p=0.000). Conclusion The present study has revealed a high prevalence of CKD amongst patients with SCA in this region. Various clinical and laboratory predictors of eGFR were also identified. Monitoring and detection of early stages of these groups of patients may allow for interventions which may delay progression into advance stages and ESRD

Transfer learning based histopathologic image classification for burns recognition

Burn is one of the most leading devastating injuries affecting people worldwide with high impact rate in low-and middle-income countries subjecting hundreds of thousands to loss of lives and physical deformities. Both affected individuals and health institutions are faced with challenges such as inadequate experience/well trained workforce and high diagnostics cost. The demand of having efficient, cost-effective and user-friendly technique to aid in addressing the problem is on the rise. Deep neural networks have recently attracted the attention of many researchers and achieved impressive results in many applications. Therefore, this paper proposed the use of off-the-shelf Convolutional Neural Network features from two ImageNet pre-trained models (GoogleNet and ResNet152), VGG-Face. The features are used to train Support Vector Machine (SVM) and Decision Tree (DT). 100% identification accuracy was recorded using ImageNet model and SVM