Type 2 Immunity at the Interface Between Helminth Infection and Stunting
Bibliographic record
Abstract
Early life, defined as before the age of two, represents a critical development window. Many development-associated issues, like stunting, arise from suboptimal conditions during this period. Stunting, defined as two standard deviations below the height-for-age median, affects almost 30% of children under five. While many factors contribute to stunting, epidemiological evidence emphasizes that early life helminth infections, combined with undernutrition, may be major drivers. Helminths induce a potent type 2 immune response, which, potentially favoured in undernourished conditions, can modify systemic metabolism linked to development. Despite their prominence in developing countries, no publications have reported the early life interactions between helminths, undernutrition, and stunting. Thus, we seek to elucidate a potential relationship between these variables. We hypothesize that undernutrition increases the anti-helminth type 2 immune response, exacerbating early life stunting. Mouse pups are weaned onto an undernourished or control diet and are subsequently infected with a well-characterized helminth. Two- or four-weeks post-infection, immune cells and antibodies are quantified using various imaging and quantitative methods. Our lab has established a murine stunting phenotype reliant on both helminth infection and undernutrition, and our data suggest that a type 2 immune response may drive stunting. While mice are valuable models for studying this interaction, they possess temporal developmental differences from humans. Our preliminary data suggest that our stunting model depends on a type 2 immune response. This is the first study examining this response in an interplay between undernutrition, helminth infection, and stunting—an initial step towards addressing determinants of childhood stunting.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".