Immunological and Anti-oxidant Profiles of Malarial Children in Abuja, Nigeria
Bibliographic record
Abstract
Background: The clinical symptoms, cellular immune response, and serum cytokine homeostasis during falciparum malaria among children living in endemic regions depend on the parasite densities. This study aims to evaluate the CD4+ and CD8+ T cells, leucocytes subpopulations, IL-6, IL-10 and biomarkers of oxidative stress among children infected with varying grades of malaria attending the University of Abuja Teaching Hospital and National Hospital, Abuja, Nigeria. Materials and Methods: This case-control study involved blood samples collected from 165 children (between 5 -12 years). This comprised 45 children with mild malaria, 40 each with moderate, severe malaria and apparently healthy (control). Serum cytokines, ferritin, malonaldehyde (MDA), ascorbate, α-tocopherol levels were determined by Enzyme-Linked ImmunoSorbent Assay (ELISA). Leucocytes differentials and CD4+ / CD8+ T cells counts were enumerated by automated hematology analyzer and flow cytometry, respectively. Results: All malarial children had only Plasmodium falciparum. The male to female ratio of children with mild malaria was 1.5:1 (mean±SD age of 8.5 ±1.9 years). However, other groups had 1:1 male to female ratio and mean ages of 9.2 ±2.3, 9.8± 2.2, 8.5± 1.5 for children with moderate, severe malaria and control, respectively. There was a positive but not significant association of neutrophils and monocytes with the 3 grades of malaria parasitemia (p˃0.05). There was a negative and significant correlation between severe malaria and lymphocyte count (p=0.048; r = -0.647). However, there was positive and significant correlation between eosinophil with moderate (p= 0.03; r=0.994) and severe malaria (p=0.006; r=0.825). There was a significant decline in serum ascorbate with increased malaria density (p˂0.0001). However, there was no difference in the serum α-tocopherol concentration within the 4 groups of children (p=0.182). Serum ferritin and MDA significantly elevated with an increase in malaria density (p˂0.0001). There was a significant decline in CD4+ T and CD8+ T cells counts with an increase in malaria densities (p˂0.0001). Serum IL-10 and IL-6 significantly elevated with increased malaria density (p˂0.0001). Conclusion: Based on these findings, severe malaria was significantly associated with declined CD4+ and CD8+ T cell counts, upregulation of IL-6, and high serum levels of oxidative stress biomarkers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".