Anemia in children is defined by the World Health Organization as a hemoglobin concentration below 11 g/dl for children (0.5-5.0 yrs) and 12 g/dl for teens (12-15 yrs). 4 ml of venous blood sample was collected in EDTA container. Of the total of three hundred and thirty four (334) subjects, one hundred and fifty two (152) were Females and one hundred and eighty two (182) were Males. Intestinal parasite assessment was done by Direct Smear technique and Formol-Ether concentration methods. Hemoglobin concentration was analyzed using Cyanmethaemoglobin method. Thirty (30) subjects were infested with Ascaris lumbricoides (single infestation), Ninety Five (95) subjects were infested with Ascaris lumbricoides and Hookworm (Double infestation) and Forty Two (42) subjects were infested with Ascaris lumbricoides, Hookworm, Entamoeba histolytica and Trichuris trichiura (Multiple infestation). The Mean ± Standard Deviation of Hemoglobin concentration of the various infestation types against the control subject shows a statistically significant decrease (P < 0.05). Our data confirm that intestinal parasites are associated with anemia irrespective of gender and age in children.

C reactive protein is sensitive physiological biomarkers of sub clinical inflammation associated with hyperglycemia. The aim of this study is to determine the fasting serum C reactive protein level in type 2 diabetes mellitus patients attending diabetic clinic in Benin City, Nigeria. The population sample consists of 142 subjects. 71 patients were known type 2 diabetes mellitus, while the other 71 were age matched control subjects. Fasting glucose and C reactive protein were estimated using glucose oxidase method and ELISA method respectively. The age group that has the highest number of type 2 diabetes mellitus was 41-50 (64% of males and 36% of the females). Our finding revealed that C reactive protein and serum glucose level of type 2 Diabetes mellitus in both females and males show a statistically significant increase as compared with age matched Control subjects, (P < 0.05). An elevation of serum C-reactive protein was demonstrated in both males and females type 2 diabetes mellitus in Benin City, Nigeria. These data support a possible role of inflammatory biomarkers in diabetogenesis.

Our results showed a stronger Th1 cytokine response in HbAA than HbAS and HbSS individuals; this may suggest an immunocompetence of the HbAA individuals in early infection.

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Whereas accelerated attention beclouded early stages of the coronavirus spread, knowledge of actual pathogenicity and origin of possible sub-strains remained unclear. By harvesting the Global initiative on Sharing All Influenza Data (GISAID) database (https://www.gisaid.org/), between December 2019 and January 15, 2021, a total of 8864 human SARS-CoV-2 complete genome sequences processed by gender, across 6 continents (88 countries) of the world, Antarctica exempt, were analyzed. We hypothesized that data speak for itself and can discern true and explainable patterns of the disease. Identical genome diversity and pattern correlates analysis performed using a hybrid of biotechnology and machine learning methods corroborate the emergence of inter- and intra- SARS-CoV-2 sub-strains transmission and sustain an increase in sub-strains within the various continents, with nucleotide mutations dynamically varying between individuals in close association with the virus as it adapts to its host/environment. Interestingly, some viral sub-strain patterns progressively transformed into new sub-strain clusters indicating varying amino acid, and strong nucleotide association derived from same lineage. A novel cognitive approach to knowledge mining helped the discovery of transmission routes and seamless contact tracing protocol. Our classification results were better than state-of-the-art methods, indicating a more robust system for predicting emerging or new viral sub-strain(s). The results therefore offer explanations for the growing concerns about the virus and its next wave(s). A future direction of this work is a defuzzification of confusable pattern clusters for precise intra-country SARS-CoV-2 sub-strains analytics.