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Cited by 324

The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.

Mechanoreceptors in the anterior cruciate ligament contribute to the joint position sense

Open access
Adachi, Nobuo, Ochi, Mitsuo, Uchio, Yuji, Iwasa, Junji, Ryoke, Koji, Kuriwaka, Masakazu·2002·Acta Orthopaedica Scandinavica

Abstract

We have investigated the correlation between the number of mechanoreceptors in anterior cruciate ligament (ACL) remnants and the joint position sense just before an ACL reconstruction in 29 patients. The number of mechanoreceptors was evaluated histologically, using the Gairns gold chloride method. Mechanoreceptors were also found in patients who had a long interval between injury and the operation. A joint position sense test was done within 3 days before surgery. We found a positive correlation between the number of mechanoreceptors and accuracy of the joint position sense, suggesting that proprioceptive function of the ACL is related to the number of mechanoreceptors. Therefore, we should consider preserving ACL remnants during ACL reconstruction.

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Metadata

Authors
Adachi, N., Ochi, M., Uchio, Y., Iwasa, J., Ryoke, K., & Kuriwaka, M.
Venue
Acta Orthopaedica Scandinavica
Published
2002-01
Volume
73
Issue
3
Pages
330-334
ISSN
0001-6470 (ISSN-L)
OpenAlex
W1988105081
Cited by
324
References
8
FWCI
2.72
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Mechanoreceptors in the anterior cruciate ligament contribute to the joint position sense. https://app.cochat.ai/papers/10.1080/000164702320155356
The paper
Adachi, N., Ochi, M., Uchio, Y., Iwasa, J., Ryoke, K., & Kuriwaka, M. (2002). Mechanoreceptors in the anterior cruciate ligament contribute to the joint position sense. Acta Orthopaedica Scandinavica. https://doi.org/10.1080/000164702320155356

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.