Publications by authors named "O Oyebamiji"
Despite the inherent risks associated with waste scavenging, it is surprising to note the age group involved in this activity. This study aimed to assess the motivating factors driving teenagers and youths to participate in waste scavenging, using a sample of 247 scavengers. The data underwent analysis using frequency counts, percentages, and factor analysis techniques.
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- Chronic hypoxia (CH) leads to an increase in pro-inflammatory T helper 17 (T17) cells and a decrease in the suppressive function of regulatory T cells (Tregs), which is linked to the development of pulmonary hypertension (PH).
- In mice exposed to CH, Tregs showed altered gene expression indicating reduced suppressive capabilities, while T17 cells were found to be more prevalent.
- The study reveals that under chronic hypoxic conditions, Tregs may transition into exTreg-T17 cells, further exacerbating the imbalance between Tregs and T17 cells and contributing to the onset of PH.
Background: Nigeria is a significant contributor to the global burden of chronic undernutrition in children under 5 years of age. The undernutrition challenge constrains the productivity of rural households. This study was carried out among beneficiaries of the productivity-enhancing Nigerian Dairy Development Programme (NDDP) to guide incorporation of nutrition into the successor program-Advancing Local Dairy Development in Nigeria (ALDDN).
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- Pediatric osteoarticular infections are often caused by Staphylococcus aureus, but research on how its genetic variations impact these infections is limited.
- A study of 47 children with either skin colonization or infections involved whole genome sequencing and investigation of virulence genes, indicating that osteoarticular infections carry more immune evasion genes.
- The findings suggest significant genetic diversity in S. aureus strains causing these infections, but no dominant sequence types, and imply that pathogenicity may rely more on gene expression rather than mutations.
RNA editing exerts critical impacts on numerous biological processes. While millions of RNA editings have been identified in humans, much more are expected to be discovered. In this work, we constructed Convolutional Neural Network (CNN) models to predict human RNA editing events in both Alu regions and non-Alu regions.
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