Interactions between skin-resident dendritic and Langerhans cells and pain-sensing neurons
Bibliographic record
Abstract
Various immune cells in the skin contribute to its function as a first line of defense against infection and disease, and the skin's dense innervation by pain-sensing sensory neurons protects the host against injury or damage signals. Dendritic cells (DCs) are a heterogeneous population of cells that link the innate immune response to the adaptive response by capturing, processing, and presenting antigens to promote T-cell differentiation and activation. DCs are abundant across peripheral tissues, including the skin, where they are found in the dermis and epidermis. Langerhans cells (LCs) are a DC subset located only in the epidermis; both populations of cells can migrate to lymph nodes to contribute to broad immune responses. Dermal DCs and LCs are found in close apposition with sensory nerve fibers in the skin and express neurotransmitter receptors, allowing them to communicate directly with the peripheral nervous system. Thus, neuroimmune signaling between DCs and/or LCs and sensory neurons can modulate physiologic and pathophysiologic pathways, including immune cell regulation, host defense, allergic response, homeostasis, and wound repair. Here, we summarize the latest discoveries on DC- and LC-neuron interaction with neurons while providing an overview of gaps and areas not previously explored. Understanding the interactions between these 2 defence systems may provide key insight into developing therapeutic targets for treating diseases such as psoriasis, neuropathic pain, and lupus.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".