High Dietary Folate in Mice Alters Immune Response and Reduces Survival after Malarial Infection
Bibliographic record
Abstract
Malaria is a significant global health issue, with nearly 200 million cases in 2013 alone. Parasites obtain folate from the host or synthesize it de novo. Folate consumption has increased in many populations, prompting concerns regarding potential deleterious consequences of higher intake. The impact of high dietary folate on the host's immune function and response to malaria has not been examined. Our goal was to determine whether high dietary folate would affect response to malarial infection in a murine model of cerebral malaria. Mice were fed control diets (CD, recommended folate level for rodents) or folic acid-supplemented diets (FASD, 10x recommended level) for 5 weeks before infection with Plasmodium berghei ANKA. Survival, parasitemia, numbers of immune cells and other infection parameters were assessed. FASD mice had reduced survival (p<0.01, Cox proportional hazards) and higher parasitemia (p< 0.01, joint model of parasitemia and survival) compared with CD mice. FASD mice had lower numbers of splenocytes, total T cells, and lower numbers of specific T and NK cell sub-populations, compared with CD mice (p<0.05, linear mixed effects). Increased brain TNFα immunoreactive protein (p<0.01, t-test) and increased liver Abca1 mRNA (p<0.01, t-test), a modulator of TNFα, were observed in FASD mice; these variables correlated positively (rs = 0.63, p = 0.01). Bcl-xl/Bak mRNA was increased in liver of FASD mice (p<0.01, t-test), suggesting reduced apoptotic potential. We conclude that high dietary folate increases parasite replication, disturbs the immune response and reduces resistance to malaria in mice. These findings have relevance for malaria-endemic regions, when considering anti-folate anti-malarials, food fortification or vitamin supplementation programs.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".