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Record W4407286905 · doi:10.1093/jcag/gwae059.246

A246 EXPLORING THE ROLE OF LUMINAL PROTEASES IN NOCICEPTION MODULATION FROM PATIENTS WITH ACTIVE AND REMISSIVE INFLAMMATORY BOWEL DISEASE

2025· article· en· W4407286905 on OpenAlexaff
Henry M. Wood, Kristýna Blažková, Franco F. Faucher, Prameet M. Sheth, S Vanner, David E. Reed, Matthew Bogyo, Alan Lomax

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2025
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Eye Disorders
Canadian institutionsQueen's University
Fundersnot available
KeywordsInflammatory bowel diseaseProteasesMedicineNociceptionModulation (music)Internal medicineDiseaseChemistryBiochemistryEnzymeReceptor

Abstract

fetched live from OpenAlex

Abstract Background Abdominal pain poses a significant challenge for individuals with inflammatory bowel disease (IBD). Despite current treatments that target inflammation, IBD-associated abdominal pain often persists even in the absence of inflammation, negatively impacting patients’ quality of life. This persistence suggests that factors other than inflammation may be at play. Our previous research suggests that bacterial proteases can directly influence the excitability of dorsal root ganglia neurons, many of which are pain-sensing. Building on this, we hypothesize that proteases, both of host and bacterial origin, play a role in pain modulation during the active and remission phases of IBD. Aims Determine whether luminal proteases in IBD fecal samples induce changes in pain signalling. Methods The effects of fecal supernatants (FS) from patients with active or remissive IBD and healthy volunteers (HV), on pain-sensing neurons were assessed using ex-vivo single-unit afferent nerve recordings from mouse colons. A protease inhibitor cocktail (PIC; 1:1000) and a protease-activated receptor (PAR)-2 antagonist (GB83; 10µM) were independently applied in the bioassay to determine whether these inhibited the excitatory effect of the FS. In addition, the participant FS were tested for proteolytic cleavage of the N-terminal domain of protease-activated receptor PAR2 using a novel enzymatic assay. Results FS from HV [N=5] had no effect on afferent nerve excitability (p>0.05). FS from active IBD patients [N=15] increased action potential discharge from colonic afferent nerves by 85% (p<0.0001) and selectively increased the activation of high-threshold units, which are putative nociceptors, by 44% (p<0.01). A protease inhibitor cocktail and PAR2 antagonist both independently inhibited the excitatory effects of IBD FS (p>0.05) on afferent nerve activity. In contrast, FS from IBD patients in remission [N=15] did not excite colonic afferent nerves (p>0.05). Interestingly, these findings were found to be consistent when IBD was split into disease subtypes: Crohn’s disease and ulcerative colitis. Furthermore, when normalized to total protein content, active disease yielded significantly greater PAR2 cleavage activity (p<0.05), while the remission samples were not significantly different than the HV (p>0.05). This PAR2 cleavage activity was found to be correlated to neuronal excitation (R2=0.4721, p<0.001). Conclusions Our findings suggest that active IBD leads to the generation of luminal mediators, including proteases acting on PAR2, that activate visceral nociceptive neurons. These luminal mediators are less abundant when inflammation is in remission. These data suggest that targeting proteases could offer a promising therapeutic approach for pain management in IBD. Funding Agencies CIHR

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.005
GPT teacher head0.208
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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