Effects of Reactive Oxygen and Nitrogen Species on TrkA Expression and Signalling: Implications for proNGF in Aging and Alzheimer’s Disease
Bibliographic record
Abstract
Nerve growth factor (NGF) and its precursor form, proNGF, are critical for neuronal survival and cognitive function. In the brain, proNGF is the only detectable form of NGF. Dysregulation of proNGF in the brain is implicated in age-related memory loss and Alzheimer’s disease (AD). AD is characterized by early and progressive degeneration of the basal forebrain, an area critical for learning, memory, and attention. Learning and memory deficits in AD are associated with loss of proNGF survival signalling and impaired retrograde transport of proNGF to the basal forebrain. ProNGF transport and signalling may be impaired by the increased reactive oxygen and nitrogen species (ROS/RNS) observed in the aged and AD brain. The current literature suggests that ROS/RNS nitrate proNGF and reduce the expression of the proNGF receptor tropomyosin-related kinase A (TrkA), disrupting its downstream survival signalling. ROS/RNS-induced reductions in TrkA expression reduce cell viability, as proNGF loses its neurotrophic function in the absence of TrkA and instead generates apoptotic signalling via the pan-neurotrophin receptor p75NTR. ROS/RNS also interfere with kinesin and dynein motor functions, causing transport deficits. ROS/RNS-induced deficits in microtubule motor function and TrkA expression and signalling may contribute to the vulnerability of the basal forebrain in AD. Antioxidant treatments may be beneficial in restoring proNGF signalling and axonal transport and reducing basal forebrain neurodegeneration and related deficits in cognitive function.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".