Neuromuscular Consequences of Diabetic Neuropathy: Motor Unit Loss, Transmission Instability, and Alterations in Muscle Form and Function (P6.252)
Bibliographic record
Abstract
Objective: To investigate how diabetic polyneuropathy (DPN) impacts the neuromuscular system in humans using a comprehensive and novel array of complementary measures. Background: The early stages of DPN typically result in length-dependent sensory impairments, but can eventually lead to dysfunction of the neuromuscular system. However, these DPN-associated neuromuscular deficits are studied less often and are more poorly understood. Our laboratory has undertaken a set of interrelated investigations using decomposition enhanced quantitative electromyography (DQEMG), dynamometry, and magnetic resonance imaging (MRI) to examine neuromuscular alterations in patients with severe DPN. Design/Methods: Patients with DPN (n = 12) were compared with age- and sex-matched controls (n = 12). Neuromuscular parameters related to the tibialis anterior (TA) and dorsiflexion were examined. DQEMG was used to derive: motor unit number estimates (MUNE), standard needle EMG parameters, and measures of neuromuscular transmission stability (e.g. jiggle, jitter, [percnt] blocking). Dynamometry and electrical stimulation were used to assess: contractile speed, muscle strength and endurance during a sustained isometric fatiguing task. MRI provided assessment of muscle quantity and quality. Associations between variables of interest (e.g. MUNE and muscle strength) were examined. Results: Patients with DPN were weaker (-35[percnt]), slower (-45[percnt]) and more easily fatigued (-21[percnt]) than controls (p<0.05). The DPN group featured fewer motor units (-45[percnt]), and reduced neuromuscular transmission stability (-30[percnt]; p<0.05). Patients with DPN were still weaker when strength was normalized to TA total cross sectional area (-30[percnt]; p<0.05). In the DPN patient group, TA MUNEs were negatively related to [percnt] noncontractile tissue (p<0.05; r = 0.72), whereas no relationship was found between these variables in controls (p>0.05). Conclusions: DPN may result in major changes to the neuromuscular system beyond weakness and muscle atrophy. Combined with sensory deficits, these changes likely contribute to decreased functional capacity and impaired mobility in this population.
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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) | 0.000 | 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 | 0.000 |
| 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".