Evidence for a Potential “Knee-Eye-Brain Axis” Involved in Mobility and Navigation Control: Knee Injury and Obesity May Disrupt Axis Integrity
Bibliographic record
Abstract
Humans depend on the coordinated activity of their lower extremities for mobility, an essential feature of Homo sapiens. In addition, they use vision to use this mobility to successfully navigate through their environment. During development, mobility appears to mature first, and then it is coordinated with navigation. Thus, the two, mobility and navigation are likely interdependent in function. Recent studies have indicated that compromising the integrity of the knee, a central element of the lower extremity motion segment, can lead to molecular alterations in both the cornea including the central cornea where light passes, as well as the interior of the eye (the vitreous humor). Not all insults to the knee lead to reproducible alterations in the eye, indicating some specificity in the response. In addition, it was recently reported that alterations to the cells in the vitreous humor occur following dietary induction of obesity in a rat model. As humans with obesity, as well as arthritis of the knee are at risk for ocular involvement and exhibit altered gait characteristics, the clinical and preclinical data raise the possibility of a “knee-eye-brain axis” to control or regulate mobility and navigation. Better delineation of such an axis could have implications for variations in control during maturation, and well as during aging when vision and mobility can be compromised, with increased risk for serious falls and failure to successfully navigate the environment.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".