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Record W4386947409 · doi:10.1016/j.jaut.2023.103110

The cancer-associated glycan polysialic acid is dysregulated in systemic sclerosis and is associated with fibrosis

2023· article· en· W4386947409 on OpenAlex
Lamia Khan, Tahlia Derksen, Desiree Redmond, Jan Storek, Caylib Durand, Robert Gniadecki, Benjamin D. Korman, Jan Willem Cohen Tervaert, Ana D’Aubeterre, Mohammed Osman, Lisa M. Willis

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Autoimmunity · 2023
Typearticle
Languageen
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsMedicineDermisFibrosisInternal medicinePolysialic acidScleroderma (fungus)Autoimmune diseasePathologyCellDiseaseNeural cell adhesion moleculeBiology

Abstract

fetched live from OpenAlex

OBJECTIVE: Systemic sclerosis (SSc) is a rare but deadly disease characterized by autoimmunity, vasculopathy, and fibrosis. Fibrotic complications associated with SSc correlate with severe morbidity and mortality. Previous studies in SSc have identified fibroblasts as the primary drivers of fibrosis; however, the mechanism(s) promoting this are not well understood. Aberrant glycosylation, particularly polysialylation (polySia), has been described as a prominent feature of aggressive cancers. Inspired by this observation, we aimed to determine if polySia is dysregulated in various forms of SSc. METHODS: All patients with SSc met the 2013 ACR/EULAR. Patients were sub-classified into limited cutaneous (lSSc, N = 5 or 46 patients for polySia quantification in the dermis or serum; respectively), diffuse cutaneous (dSSc, N = 11 or 18 patients for polySia quantification in the dermis or serum; respectively), or patients with dSSc treated with an autologous stem cell transplantation (post-ASCT, N = 4 patients for quantification in the dermis). Dermal polySia levels were measured via immunofluorescence microscopy in 10 μm dermal sections, quantified in each group (healthy volunteers (HC), lSSc, dSSc, and post-ASCT) and correlated with skin fibrosis (via the modified Rodnan skin score (mRSS)). Similarly, serum polySia was quantified in each group, and correlated with the mRSS. RESULTS: Dermal polySia levels were highest in patients with dSSc (compared to HC < 0.001), and correlated with the degree of fibrosis in all of the groups (P = 0.008). Serum polySia was higher in all SSc groups (p < 0.001) and correlated with the severity of mRSS (p < 0.0001). CONCLUSION: Polysia is more abundant in the skin and sera from patients with SSc and correlates with the degree of skin fibrosis. The aberrant expression of polySia highlights its potential use as a biomarker in patients with progressive forms of SSc. Dysregulated polySia levels in SSc further emphasizes the cancer-like phenotype present in SSc, which may promote fibrosis and immune dysregulation.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.442
Threshold uncertainty score0.592

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.263
Teacher spread0.236 · 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