Age-induced nitrative stress decreases retrograde transport of proNGF via TrkA and increases proNGF retrograde transport and neurodegeneration via p75NTR
Bibliographic record
Abstract
Introduction Axonal transport of pro nerve growth factor (proNGF) is impaired in aged basal forebrain cholinergic neurons (BFCNs), which is associated with their degeneration. ProNGF is neurotrophic in the presence of its receptor tropomyosin-related kinase A (TrkA) but induces apoptosis via the pan-neurotrophin receptor (p75 NTR ) when TrkA is absent. It is well established that TrkA is lost while p75 NTR is maintained in aged BFCNs, but whether aging differentially affects transport of proNGF via each receptor is unknown. Nitrative stress increases during aging, but whether age-induced nitrative stress differentially affects proNGF transport via TrkA versus p75 NTR has not yet been studied. Answering these questions is essential for developing an accurate understanding of the mechanisms contributing to age-induced loss of proNGF transport and BFCN degeneration. Methods In this study, fluorescence microscopy was used to analyze axonal transport of quantum dot labeled proNGF in rat BFCNs in vitro . Receptor specific effects were studied with proNGF mutants that selectively bind to either TrkA (proNGF-KKE) or p75 NTR (proNGF-Δ9-13). Signaling factor activity was quantified via immunostaining. Results Young BFCNs transported proNGF-KKE but not proNGF-Δ9-13, and proNGF transport was not different in p75 NTR knockout BFCNs compared to wildtype BFCNs. These results indicate that young BFCNs transport proNGF via TrkA. In vitro aging increased transport of proNGF-Δ9-13 but decreased transport of proNGF-KKE. Treatment with the nitric oxide synthase inhibitor L-NAME reduced retrograde transport of proNGF-Δ9-13 in aged BFCNs while increasing retrograde transport of proNGF-KKE but did not affect TrkA or p75 NTR levels. ProNGF-Δ9-13 induced greater pro-apoptotic signaling and neurodegeneration and less pro-survival signaling relative to proNGF-KKE. Discussion Together, these results indicate that age-induced nitrative stress decreases proNGF transport via TrkA while increasing proNGF transport via p75 NTR . These transport deficits are associated with decreased survival signaling, increased apoptotic signaling, and neurodegeneration. Our findings elucidate the receptor specificity of age-and nitrative stress-induced proNGF transport deficits. These results may help to rescue the neurotrophic signaling of proNGF in aging to reduce age-induced loss of BFCN function and cognitive decline.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".