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Record W7000047023

Efficacy of oral intake of haruan [Channa striatus (Bloch, 1793)] extract versus glucosamine sulfate on knee osteoarthritis

2019· other· en· W7000047023 on OpenAlexaboutno aff

Bibliographic record

VenueUniversiti Putra Malaysia Institutional Repository (Universiti Putra Malaysia) · 2019
Typeother
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsOsteoarthritisPlaceboGlucosamineAnalgesicJoint diseaseTendinitisSynovial fluidArthritisIn vivo
DOInot available

Abstract

fetched live from OpenAlex

Knee osteoarthritis (OA) is the most prevalent degenerative arthritis and currently there are no pharmacological agents that able to retard the disease progressions. Channa striatus (CS) is a freshwater fish and its potential for treating knee OA has been explored but no comparison study has been done with glucosamine (GlcN), which has been widely used to treat osteoarthritis. In vivo study was conducted to evaluate the efficacy of CS extract versus GlcN on histomorphometric examinations in experimental OA rabbit model and a clinical trial was done to assess the efficacy of different doses of CS extract versus GlcN on primary knee osteoarthritis patients in terms of knee OA symptoms based on Western Ontario and McMaster University Osteoarthritis Index (WOMAC), analgesic drug consumption, serum cartilage oligomeric matric protein (COMP), cyclooxygenase 2 (COX-2) enzyme and serum Prostaglandin E2 (PGE2). OA was induced using Anterior Cruciate Ligament transection in thirty three rabbits and were divided into three groups namely: CS, GlcN and control group. The CS and GlcN groups were orally administered with 51.4 mg/kg of CS extract and 77.5 mg/kg of GlcN sulphate respectively based on the dosage used for human study for eight weeks. The articular cartilage was evaluated macroscopically and histologically using semi-quantitative and quantitative methods. One-way analysis of variance (ANOVA) was used to analyse the histologic assessment and Kruskall Wallis test was used to analyse the macroscopic grading. A randomized, double-blind, placebo-controlled trial comparing the effects of oral CS extract at the dose rate of 1000mg/day or 500mg/day, 1500mg/day of glucosamine sulphate and placebo among knee OA patients for 6-month intervention period was conducted. Repeated measures analysis of covariance and variance was used to analyse the WOMAC index. One-way ANOVA was used to analyse the analgesic score, COMP, COX-2 and PGE2 level. The results revealed that the severity of macroscopic score was significantly less in CS as compared to GlcN (p<0.05) group. CS exhibit less severity of semi-quantitative histology score compared to control (p<0.05) in more compartments of the joints compared to GlcN. Both CS (p<0.05) and GlcN (p<0.05) groups demonstrated higher cartilage thickness and area; lower roughness than control group. Moreover, less cartilage roughness was expressed in CS group compared to the GlcN group (p<0.05). In the clinical trial, 153 patients were analysed. Both CS (p<0.05) and GlcN (p<0.05) groups demonstrated significant improvement of WOMAC stiffness and physical function compared to placebo. CS (1000mg/day) (p<0.05), CS (500mg/day) (p<0.05) and GlcN (p<0.05) groups reduced serum COX-2 level compared to placebo. Serum PGE2 was reduced in CS (1000mg/day) (p<0.05) compared to placebo. In conclusion, it was found that based on macroscopic, semi-quantitative and quantitative histological examination, CS extract was superior to GlcN in maintaining the structure of the cartilage degeneration on an ACLT OA-induced rabbit model. In the clinical trial, both doses of CS extract had similar efficacy with GlcN in alleviating the symptoms of knee OA and had an anti-inflammatory effect through the reduction of serum COX-2. CS administered at the dose rate of 1000mg/day was effective in reducing PGE2 level compared to GlcN.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.517
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.230
Teacher spread0.213 · 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 teacher head, not a consensus.

Study designNot applicable
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
Published2019
Admission routes1
Has abstractyes

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