Strain pattern of each ligamentous band of the superficial deltoid ligament
Bibliographic record
Abstract
Abstract Background There are few reports in terms of detailed biomechanics of the deltoid ligament, and no reports have measured the biomechanics of each ligamentous band, due to the difficulty in inserting sensors into the narrow ligaments. This study aims to measure the strain pattern of the deltoid ligament bands using a miniaturization ligament performance probe (MLPP) system. Methods The MLPP was sutured into the ligamentous bands of the deltoid ligament in 6 fresh-frozen lower extremity cadaveric specimens. The strain was measured using a round metal disk (clock) fixed on the plantar aspect of the foot. The ankle was manually moved from 15° of dorsiflexion to 30° plantar flexion, and a 1.2-N-m force was applied to the ankle and subtalar joint complex. The clock was then rotated every 30° to measure the strain of each ligamentous band at each endpoint. Results The tibionavicular ligament (TNL) begins to tense at 10° plantar flexion and the tension becomes stronger as the angle increases; the TNL works most effectively in plantar flex-abduction. The tibiospring ligament (TSL) begins to tense gradually at 15° plantar flexion and the tension becomes stronger as the angle increases. The TSL works most effectively in the abduction. The tibiocalcaneal ligament (TCL) begins to tense gradually at 0° dorsiflexion, and the tension becomes stronger as the angle increases. The TCL works most effectively in pronation (dorsiflexion-abduction). The superficial posterior tibiotalar ligament (SPTTL) begins to tense gradually at 0° dorsiflexion, and the tension becomes stronger as the angle increases, with the SPTTL working most effectively in dorsiflexion. Conclusion Our results provide a better understanding of the biomechanical function of the superficial deltoid ligament and could help in improving repair and reconstruction procedures.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".