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S100A8/A9, Exercise, and Creatine in Knee Osteoarthritis

2019· article· en· W3173882853 on OpenAlexaff
Jason Peeler, Pengu Zhang, Stephen M. Cornish, Saeid Ghavami

Bibliographic record

VenueThe FASEB Journal · 2019
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsUniversity of ManitobaPan Am Clinic
Fundersnot available
KeywordsMedicineOsteoarthritisPhysical therapyKnee JointKnee painRange of motionInternal medicineSurgeryPathology

Abstract

fetched live from OpenAlex

Knee osteoarthritis (OA) is a degenerative joint disease characterized by progressive breakdown of articular cartilage, and increasing joint pain and stiffness. Chronic inflammation is thought to play a central role in cartilage degradation, with pro‐inflammatory cytokines such as S100 A8/A9 potentially associated with disease progression and elevated levels of systemic cartilage oligomeric protein (COMP). The purpose of this prospective RCT was to examine the influence of weight bearing exercise and creatine supplementation on S100 A8/A9 levels in patients with mild‐moderate knee OA. Twenty‐six (26) knee OA patients were randomized into 3 groups: (1.) Lower Body Positive Pressure supported treadmill walking exercise, (2.) Creatine supplementation, and (3.) Control. Following radiographic confirmation of OA severity, patients were evaluated at baseline and following a 12 week intervention on the following parameters: (1.) body anthropometry; (2.) knee joint range of motion; (3.) Knee Injury and Osteoarthritis Outcome Score (KOOS) questionnaire for chronic knee pain, joint symptoms, and dysfunction; (4.) acute knee pain during 30 minutes of full weight‐bearing treadmill walking; and (5.) serum biomarkers (S100 A8/A9 and COMP). A longitudinal multi‐level model of analysis was used to evaluate multiple independent variables at the same time. Data suggested that the LBPP exercise improved KOOS scoring on the Sport/Recreation Function subscale, and that creatine supplementation improved KOOS scoring on the Quality of Life subscale. SCOMP levels were also positively correlated with both acute and chronic knee joint pain, joint symptoms, and scoring on the KOOS Activity of Daily Living subscale. Unfortunately, S100 A8/A9 levels were un‐influenced by either LBPP exercise or creatine supplementation, but concentrations were moderately correlated with patient BMI and scoring on the KOOS subscales of Pain and Activities of Daily Living. Further research is needed to clarify what role (if any) pro‐inflammatory proteins such as S100 A8/A9 play in cartilage degradation, and future investigations should focus on examining synovial based biomarkers that are specific to the affected joint. Support or Funding Information Ongoing support provided by the Max Rady College of Medicine, the Pan Am Clinic Foundation, and funding through the Paul H.T. Thorlakson Foundation. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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)0.001
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.229
Teacher spread0.220 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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