Investigating local and systemic Innate Immune Responses in Skin and Oral Mucosa in vitro
Bibliographic record
Abstract
Skin and oral mucosa both function as barriers to harmful environmental factors. However, clinical observations suggest that these tissues react differently to exposure to environmental insults. Metal exposure in the oral cavity is known to activate the immune system and in some cases results in skin inflammation. Clinical experience has shown that skin exposure can lead to sensitization whereas exposure in the oral mucosa often leads to tolerance. Limited literature is available on oral mucosal immunology. In general, when mucosal immunology is described it is actually referring to gut immunology which has an immunosuppressive character (“tolerance”) compared to the more inflammatory character of skin. The goal of the research described in this thesis was to gain more insight on the local innate immune responses in skin and oral mucosa and to develop a multi-organ approach to study systemic toxicity caused by oral metal exposure. Previous results in our lab have supported the possibility that the innate immune response in the oral mucosa is prone to respond to pathogen exposure acutely and efficiently and thereby eliminate imminent threats immediately as opposed to being tolerant. LC are generally known as immune stimulatory cells whilst there is strong evidence that they can have a more immune regulatory role as they are key players in induction and maintenance of tolerance. Perhaps oral mucosa immunity is not more tolerant or more immune stimulatory but simply differential to skin immunity and supremely adaptable in its response to exogenous insults. In Chapter 2 we describe the most promising organotypic in vitro skin models that are commercially available or being used in a laboratory setting for hazard assessment of potential sensitizers and for investigating the mechanisms behind allergic contact dermatitis. Environmental microbes do not only modulate the immune response initiated upon antigen exposure, a positive effect of microbes on wound healing (via macrophage, dendritic cell and T-cell activation) has also been described. In Chapter 3 we studied the wound healing potential of human saliva in an open wound model setting (fibroblast scratch assay and keratinocyte epithelialization model) and a blister wound setting (freeze wound in RHS and RHG). Titanium is one of the widely used metals in dental restorative materials as well as a white pigment (titaniumdioxide) in toothpaste and food products. It is thought to be inert and hypo-allergenic, however, cases of suspected titanium allergy occur. In Chapter 4 we used our reconstructed human skin model with integrated MUTZ-3 derived LC to determine whether titanium salts have an irritant or sensitizing potential. The field of organotypic modeling is rapidly evolving and several successful multi-organ-on-a-chip models have been developed. Still, to investigate in vitro how an oral metal exposure can result in skin inflammation is a major challenge. A method is needed that allows us to mimic the biological events that occur when a chemical breaches the oral barrier and exerts a toxic event in skin. In order to do so, a multi organ approach with incorporated immune cells with a stable dynamic flow in a closed circuit is required. In Chapter 5 we describe the first multi-organ-on-chip approach to study systemic toxicity and LC activation. Perhaps the biggest limitation of our model is the missing vasculature and lymphatics. Incorporating vasculature and lymphatics with circulating immune cells into the multi-organ-chip systems would allow us to further investigate the mechanisms involved in immune sensitization and immune tolerance and greatly contribute to our knowledge that may ultimately lead to improved oral desensitization strategies and the increased efficacy of vaccine delivery.
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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 | 0.001 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".