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Record W2405209802

Protective role of interleukin-6 in systemic sclerosis gastrointestinal tract involvement: case report and review of the literature.

2015· article· en· W2405209802 on OpenAlexaff
Tracy Frech, Marie Hudson

Bibliographic record

VenuePubMed · 2015
Typearticle
Languageen
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsJewish General Hospital
Fundersnot available
KeywordsMedicineImmunosuppressionScleroderma (fungus)ExacerbationGastrointestinal tractSystemic sclerodermaSystemic diseasePathogenesisDiseaseImmunologyConnective tissue diseaseImmunopathologyAutoimmune diseasePathologyInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVES: Systemic sclerosis (SSc, scleroderma) is characterised by complex multi-organ pathogenesis, including gastrointestinal tract (GIT) disease that remains poorly characterised. Immunosuppression is commonly used to treat inflammatory manifestations of SSc, including the skin, lungs and joints. There is a paucity of data on the effects of immunosuppression on GIT disease in SSc. METHODS: This case report and review of the literature presents two clinical cases in which interleukin-6 (IL-6) antagonism was used for early, diffuse skin disease. RESULTS: In these two cases, IL-6 anta-gonism was associated with an exacerbation of GIT symptoms. CONCLUSIONS: We postulate that IL-6 is important in the repair of GIT mucosa and further studies are warranted to better understand the effects of immunosuppression on SSc-GIT disease.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.038
GPT teacher head0.238
Teacher spread0.200 · 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 designCase report
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

Citations10
Published2015
Admission routes1
Has abstractyes

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