BDNF Is Expressed in Skeletal Muscle Satellite Cells and Inhibits Myogenic Differentiation
Bibliographic record
Abstract
In skeletal muscle, brain-derived neurotrophic factor (BDNF) has long been thought to serve as a retrograde trophic factor for innervating motor neurons throughout their lifespan. However, its localization in mature muscle fibers has remained elusive. Given the postulated roles of BDNF in skeletal muscle, we performed a series of complementary experiments aimed at defining the localization of BDNF and its transcripts in adult muscle. By reverse transcription-PCR, in situ hybridization, and immunofluorescence, we show that BDNF, along with the receptor p75NTR, is not expressed at significant levels within mature myofibers and that it does not accumulate preferentially within subsynaptic regions of neuromuscular junctions. Interestingly, expression of BDNF correlated with that of Pax3, a marker of muscle progenitor cells, in several different adult skeletal muscles. Additionally, BDNF was expressed in Pax7+ satellite cells where it colocalized with p75NTR. In complementary cell culture experiments, we detected high levels of BDNF and p75NTR in myoblasts. During myogenic differentiation, expression of BDNF became drastically reduced. Using small interfering RNA (siRNA) technology to knock down BDNF expression, we demonstrate enhanced myogenic differentiation of myoblasts. This accelerated rate of myogenic differentiation seen in myoblasts expressing BDNF siRNA was normalized by administration of recombinant BDNF. Collectively, these findings show that BDNF plays an important regulatory function during myogenic differentiation. In addition, the expression of BDNF in satellite cells is coherent with the notion that BDNF serves a key role in maintaining the population of muscle progenitors in adult muscle.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".