Calcium ions in neuronal degeneration
Bibliographic record
Abstract
Neuronal Ca(2+) homeostasis and Ca(2+) signaling regulate multiple neuronal functions, including synaptic transmission, plasticity, and cell survival. Therefore disturbances in Ca(2+) homeostasis can affect the well-being of the neuron in different ways and to various degrees. Ca(2+) homeostasis undergoes subtle dysregulation in the physiological ageing. Products of energy metabolism accumulating with age together with oxidative stress gradually impair Ca(2+) homeostasis, making neurons more vulnerable to additional stress which, in turn, can lead to neuronal degeneration. Neurodegenerative diseases related to aging, such as Alzheimer's disease, Parkinson's disease, or Huntington's disease, develop slowly and are characterized by the positive feedback between Ca(2+) dyshomeostasis and the aggregation of disease-related proteins such as amyloid beta, alfa-synuclein, or huntingtin. Ca(2+) dyshomeostasis escalates with time eventually leading to neuronal loss. Ca(2+) dyshomeostasis in these chronic pathologies comprises mitochondrial and endoplasmic reticulum dysfunction, Ca(2+) buffering impairment, glutamate excitotoxicity and alterations in Ca(2+) entry routes into neurons. Similar changes have been described in a group of multifactorial diseases not related to ageing, such as epilepsy, schizophrenia, amyotrophic lateral sclerosis, or glaucoma. Dysregulation of Ca(2+) homeostasis caused by HIV infection or by sudden accidents, such as brain stroke or traumatic brain injury, leads to rapid neuronal death. The differences between the distinct types of Ca(2+) dyshomeostasis underlying neuronal degeneration in various types of pathologies are not clear. Questions that should be addressed concern the sequence of pathogenic events in an affected neuron and the pattern of progressive degeneration in the brain itself. Moreover, elucidation of the selective vulnerability of various types of neurons affected in the diseases described here will require identification of differences in the types of Ca(2+) homeostasis and signaling among these neurons. This information will be required for improved targeting of Ca(2+) homeostasis and signaling components in future therapeutic strategies, since no effective treatment is currently available to prevent neuronal degeneration in any of the pathologies described here.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".