102 Nutrition Affects Tendon Healing In A Rat Model
Bibliographic record
Abstract
Introduction We have previously shown that human and rat tendon cells produce insulin and secrete it upon glucose stimulation. Moreover, the level of tendon insulin production is affected by the amount of glucose taken up by nutrition [Lehner, 2012]. We now hypothesise that nutritional glucose affects tendon healing in a rat model. Methods In 60 female Lewis rats full thickness defects were created in one Achilles tendon and left unsutured. The rats were randomly assigned to three groups, one was fed a high glucose diet, one a diet with low glucose/high fat and one a control diet, for 2 weeks each. Before surgery, one and two weeks after, gait analysis was performed using a NoldusTM catwalk system. After two weeks the animals were sacrificed and tendon size was measured and tendons were biomechanically tested an evaluated by various histological methods. Results Gait Analysis revealed a significant difference between the three groups one week after surgery. The intermediate toe spread (the range between second and fourth toe, a measure for the load on the limb) of the high glucose group is significantly increased one week p.o. (0,49 cm ± 0,07; n = 20; p < 0.01) compared to the control group (0,42 cm ± 0,08; n = 19) and to the high fat group (0,40 cm ± 0,12; n = 20) (Figure 1). Measurement of length and thickness of the newly formed tissue revealed a significant (p < 0.001) difference in tendon thickness of the newly formed tissue between the high-glucose group (4,26 mm ± 0,29; n = 20) and the control group (3,66 mm ± 0,39; n = 19) as well as between the high glucose and the high-fat group (4,32 mm ± 0,20; n = 20). Biomechanical testing revealed no significant difference between the groups in maximum tensile load, however, the new fibrous tissue from the glucose group is significantly (p < 0.05) stiffer (20,82 N/mm ± 8.08; n = 14) compared to the control group (15,07 N/mm ± 4.32; n = 14) (Figure 2). The stiffness of these tendons was similar to the stiffness of intact tendon tissue of the control group (20,63 N/mm ± 10,96; n = 14). Discussion Newly formed tendon tissue quality is affected by nutritional glucose. This finding is relevant for understanding diabetes related tendinopathy. Nutritional parameters may account for the interindividual variation of tendon quality and regeneration. The underlying molecular mechanisms will be examined. Reference Lehner et al. Horm Metab Res. 2012;44:506–510
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".