The role of nutrition, food allergies, and gut dysbiosis in immune-mediated inflammatory skin disease: a narrative review
Bibliographic record
Abstract
PURPOSE OF REVIEW: This review focuses on the emerging roles of nutrition, food allergies, and gut dysbiosis, and their influence on pediatric skin conditions such as psoriasis, hidradenitis suppurativa, and alopecia areata. As the prevalence of these conditions increases, understanding the underlying mechanisms and potential therapeutic targets is crucial for clinical practice and research. RECENT FINDINGS: The review covers 32 recent articles that highlight the significance of the gut microbiome, nutrition, and gut dysbiosis in the pathogenesis and progression of inflammatory and immune-related pediatric skin conditions. The data suggest that food allergies and gut dysbiosis play a crucial role in disease pathogenesis. SUMMARY: This review emphasizes the need for larger-scale studies to determine the effectiveness of dietary changes in preventing or treating inflammatory and immune-related skin conditions. Clinicians must maintain a balanced approach when implementing dietary changes in children with skin diseases like atopic dermatitis to avoid potential nutritional deficiencies and growth impairments. Further research into the complex interplay between environmental and genetic factors is warranted to develop tailored therapeutic strategies for these skin conditions in children.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".