Communication between Mast Cells and Group 2 Innate Lymphoid Cells in the Skin
Bibliographic record
Abstract
The skin is a dynamic organ with a complex immune network critical for maintaining balance and defending against various pathogens. Different types of cells in the skin, such as mast cells (MCs) and group 2 innate lymphoid cells (ILC2s), contribute to immune regulation and play essential roles in the early immune response to various triggers, including allergens. It is beneficial to dissect cell-to-cell interactions in the skin to elucidate the mechanisms underlying skin immunity. The current manuscript concentrates explicitly on the communication pathways between MCs and ILC2s in the skin, highlighting their ability to regulate immune responses, inflammation, and tissue repair. Furthermore, it discusses how the interactions between MCs and ILC2s play a crucial role in various skin conditions, such as autoimmune diseases, dermatological disorders, and allergic reactions. Understanding the complex interactions between MCs and ILC2s in different skin conditions is crucial to developing targeted treatments for related disorders. The discovery of shared pathways could pave the way for novel therapeutic interventions to restore immunological balance in diseased skin tissues.
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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 | 0.002 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".