Age-related blunting of serial sarcomerogenesis and mechanical adaptations following 4 weeks of maximal eccentric resistance training
Bibliographic record
Abstract
Abstract Background During natural aging, muscles atrophy, which is partly accounted for by a loss of sarcomeres in series. Serial sarcomere number (SSN) is associated with aspects of muscle mechanical function including the force-length and force-velocity-power relationships; hence, the age-related loss of SSN contributes to declining performance. Training emphasizing muscle lengthening (eccentric) contractions increases SSN in young healthy rodents. However, the ability for eccentric training to increase SSN and improve mechanical function in old age is unknown. Methods Ten young (9 months) and 11 old (33 months) Fisher344/BN F1 rats completed 4 weeks of unilateral isokinetic eccentric plantar flexion training 3 days/week. Pre- and post-training, the plantar flexors were assessed for maximum tetanic torque (ankle angles of 70° and 90°), the torque-frequency relationship (stimulation frequencies of 1-100 Hz), the passive torque-angle relationship (ankle angles of 110-70°), and the torque-angular velocity-power relationship (isotonic loads of 10%-80% maximum). Following post-training testing, rats were sacrificed, and the soleus, lateral gastrocnemius (LG), and medial gastrocnemius (MG) were harvested for SSN assessment by measuring sarcomere lengths with laser diffraction, with the untrained leg used as a control. Results In the untrained leg/pre-training, old rats had lower SSN in the soleus (–9%), LG (–7%), and MG (–14%), lower maximum torque (–27 to –42%), power (–63%), and shortening velocity (–35%), and greater passive torque (+62 to +191%) than young. Young rats showed increased SSN from the untrained to the trained soleus and MG. In contrast, old rats had no change in soleus SSN between legs and experienced SSN loss in the LG. Pre- to post-training, young rats saw modest improvements in isometric mechanical function, including a 13% increase in maximum torque at 90° and 4-11% increases in 10-60 Hz torque. Old rats, however, had reductions in maximum torque (–35%), shortening velocity (–46%), and power (–63%), and increased passive torque (+24 to +51%) from pre- to post-training. Conclusions Eccentric training induced serial sarcomerogenesis and improved mechanical function in young rats, while old rats exhibited dysfunctional remodeling that led to impairments in muscle mechanical performance following training.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".