ReviewFrontiers in medicine2020
Emerging Technologies and Platforms for the Immunodetection of Multiple Biochemical Markers in Osteoarthritis Research and Therapy.
Review in Frontiers in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
28 citing papers in PubMed, 53 citations in OpenAlex.
- State-of-the-Art and Next Generation Intra-Articular Implantable Biosensors for Osteoarthritis: From Analytical Limits to Operational Stability.Biosensors · 2026Review
- Interpretable machine learning integrates multi-source biomarkers for osteoarthritis diagnosis and mechanistic insights: A temporomandibular joint model.Osteoarthritis and cartilage · 2025Article
- Emerging nanomaterials capable of effectively facilitating osteoblast maturation.Nanomedicine (London, England) · 2025Review
- Intelligent Manufacturing for Osteoarthritis Organoids.Cell proliferation · 2025Review
- Clinical and radiological evaluation of osteoarthritis in knee pain patients and its association with inflammatory markers at MGM Medical College Hospital, Jamshedpur.Journal of family medicine and primary care · 2025Article
- Therapeutic Controlled Release Strategies for Human Osteoarthritis.Advanced healthcare materials · 2025Review
- The Interplay Between Adipokines and Body Composition in Obesity and Metabolic Diseases.Cureus · 2025Review
- Development of a Sensitive Quantum Dot-Linked Immunoassay for the Multiplex Detection of Biochemical Markers in a Microvolumeric Format.International journal of nanomedicine · 2025Article
- The Challenges of Local Intra-Articular Therapy.Medicina (Kaunas, Lithuania) · 2024Review
- Article
- Tissue engineering and future directions in regenerative medicine for knee cartilage repair: a comprehensive review.Croatian medical journal · 2024Review
- Equine Models of Temporomandibular Joint Osteoarthritis: A Review of Feasibility, Biomarkers, and Molecular Signaling.Biomedicines · 2024Review
- Establishment of Reference Intervals for Bone Turnover Biomarkers in Healthy Populations in Northern China.International journal of general medicine · 2024Article
- Evaluation of Cartilage Integrity Following Administration of Oral and Intraarticular Nifedipine in a Murine Model of Osteoarthritis.Biomedicines · 2023Article
- Osteoarthritis, an old wine in a new bottle!World journal of orthopedics · 2023Article
- Generation of Matrix Degradation Products Using an In Vitro MMP Cleavage Assay.International journal of molecular sciences · 2022Article
- Implantable biosensors for musculoskeletal health.Connective tissue research · 2022Review
- Past, present, and future of cartilage restoration: from localized defect to arthritis.Knee surgery & related research · 2022Review
- Harnessing Tissue-derived Extracellular Vesicles for Osteoarthritis Theranostics.Theranostics · 2022Review
- The future of deep phenotyping in osteoarthritis: How can high throughput omics technologies advance our understanding of the cellular and molecular taxonomy of the disease?Osteoarthritis and cartilage open · 2021Article
Corrections and comments
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Authors and funding
12 authors at 5 institutions in 7 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Biomarkers, especially biochemical markers, are important in osteoarthritis (OA) research, clinical trials, and drug development and have potential for more extensive use in therapeutic monitoring. However, they have not yet had any significant impact on disease diagnosis and follow-up in a clinical context. Nevertheless, the development of immunoassays for the detection and measurement of biochemical markers in OA research and therapy is an active area of research and development. The evaluation of biochemical markers representing low-grade inflammation or extracellular matrix turnover may permit OA prognosis and expedite the development of personalized treatment tailored to fit particular disease severities. However, currently detection methods have failed to overcome specific hurdles such as low biochemical marker concentrations, patient-specific variation, and limited utility of single biochemical markers for definitive characterization of disease status. These challenges require new and innovative approaches for development of detection and quantification systems that incorporate clinically relevant biochemical marker panels. Emerging platforms and technologies that are already on the way to implementation in routine diagnostics and monitoring of other diseases could potentially serve as good technological and strategic examples for better assessment of OA. State-of-the-art technologies such as advanced multiplex assays, enhanced immunoassays, and biosensors ensure simultaneous screening of a range of biochemical marker targets, the expansion of detection limits, low costs, and rapid analysis. This paper explores the implementation of such technologies in OA research and therapy. Application of novel immunoassay-based technologies may shed light on poorly understood mechanisms in disease pathogenesis and lead to the development of clinically relevant biochemical marker panels. More sensitive and specific biochemical marker immunodetection will complement imaging biomarkers and ensure evidence-based comparisons of intervention efficacy. We discuss the challenges hindering the development, testing, and implementation of new OA biochemical marker assays utilizing emerging multiplexing technologies and biosensors.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.