Bibliographic record
Abstract
International classification of diseases-11 (ICD-11) classifies chronic primary pain conditions like temporomandibular pain disorders and fibromyalgia syndrome under Chapter 21 ("symptoms, signs or clinical findings, not elsewhere classified"). such conditions lack well-defined etiology and diagnosis. Our understanding of chronic primary pain conditions is incomplete, and these conditions are not just limited to anomalies in sensory perception of pain but involve multiple systems. The immune system is one of those contributors to the pathophysiology of chronic primary pain. This thesis explores the role of the immune system in pain modulation. Specifically, we will focus on two chronic primary pain conditions: temporomandibular disorder (TMD) and fibromyalgia syndrome (FMS). Chapter I would summarize the literature on the general involvement of the immune system in enhancing and resolving pain, and how immune cells and neurons interact due to neuro-immune molecular overlap. Chapter II will describe my first research project representing an important example of reverse translational research in the area of pain genetics and immunology. Here, we found an association between an inflammatory mediator, epiregulin (EREG), and chronic TMD through statistical genetics approaches. TMD, a major cause of nondental pain in the orofacial region, is characterized by craniofacial pain involving the joint, masticatory muscles, or muscle innervations of the head and neck. We found that loss of function EREG genetic variants are associated with chronic TMD and chronic pain intensity. Next, we found that the same genetic variants are analgesic during the acute stages of pain development. We then validated these associations in the large independent cohort. Finally, we were able to confirm this dichotomous role of EREG in pain through animal pain models. Chapter III deciphers the role of the immune response in another chronic musculoskeletal pain condition-fibromyalgia syndrome (FMS). FMS, a common rheumatic disease, is characterized by chronic widespread pain, fatigue, and, sleep and cognitive difficulties. Pathogenesis of this syndrome remains elusive leading to a lack of objective diagnosis and specific treatment. Although the immune system's involvement in FMS is irrefutable, the specifics are yet to be deciphered. Furthermore, numerous studies have described the presence of small fiber neuropathy in FMS patients, but the mechanism of development of this neuropathy is unknown. In chapter III, we investigate peripheral blood mononuclear cells (PBMCs) through flow cytometry and differential gene expression in a case-control manner. We found that the FMS cases have fewer circulating natural killer (NK) cells. Furthermore, these cells were activated and exhausted in FMS patients. Co-culturing these cells with HLA-/- cell line (an activation stimulus for NK cells) showed that the NK cells from FMS patients are hyperactive compare to controls. Lastly, skin biopsies from an independent cohort showed increased expression of ULBP (NK activation ligand) and recruitment of NK cells on the peripheral nerves of the patients. In summary, this thesis advances our current understanding of the immune system's involvement in chronic primary pain conditions. Firstly, it demonstrates the dichotomies role of EREG in pain development being protective against acute pain but contributing to chronic pain. Secondly, we found the contribution of NK cells to FMS through its association with peripheral nerves in FMS. Both of these findings are novel steppingstones on our understanding of the pathophysiology of chronic pain and have therapeutics implementations in the treatment of chronic primary pain conditions
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".