<i>Plasmodium berghei</i> infection ameliorates atopic dermatitis‐like skin lesions in <scp>NC</scp>/Nga mice
Bibliographic record
Abstract
BACKGROUND: Atopic diseases are more prevalent in industrialized countries than in developing countries. In addition, significant differences in the prevalence of allergic diseases are observed between rural and urban areas within the same country. This difference in prevalence has been attributed to what is called the 'hygiene hypothesis'. Although parasitic infections are known to protect against allergic reactions, the mechanism is still unknown. The aim of this study was to investigate whether or not malarial infections can inhibit atopic dermatitis (AD)-like skin lesions in a mouse model of AD. METHODS: We used NC/Nga mice which are a model for AD. The NC/Nga mice were intraperitoneally infected with 1 × 10(5) Plasmoduim berghei (Pb) XAT-infected erythrocytes. RESULTS: Malarial infections ameliorated AD-like skin lesions in the NC/Nga mice. This improvement was blocked by the administration of anti-asialo GM1 antibodies, which are anti-natural killer (NK) cells. Additionally, adoptive transfer of NK cells markedly improved AD-like skin lesions in conventional NC/Nga mice; these suggest that the novel protective mechanism associated with malaria parasitic infections is at least, in part, dependent on NK cells. CONCLUSIONS: We have experimentally demonstrated for the first time that malarial infections ameliorated AD-like skin lesions in a mouse model of AD. Our study could explain in part the mechanism of the 'hygiene hypothesis', which states that parasitic infections can inhibit the development of allergic diseases.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".