Age-Related Decrease in Striatal DA Produces Cognitive Deficits in Male Rats
Bibliographic record
Abstract
Aging is a process that presents various alterations in physiological, behavioral and neurochemical processes. It causes impairment of CNS functions which lead to changes in memory, cognition and other behavioral performances. Reports have shown that aging causes neurochemical alterations in various physiological functions. The aim of the present study was to evaluate the cognitive changes in relation to process of aging. For this 20 male rats were taken, 10 young (4-6 months) and 10 old (18-22 months). Morris Water Maze (MWM) test was performed to monitor changes in learning and memory while Object-Recognition Task (ORT) was performed to evaluate changes in cognitive function. After behavioral assessment decapitation was done and rat brain was dissected to isolate striatum. Then neurochemical analysis was performed by HPLC-EC to monitor changes in striatal DA and DOPAC levels. Results of behavioral tests showed that aged rats exhibited a significant impairment of long-term memory. While cognitive ability assessed by ORT was also impaired in aged rats. Neurochemical results showed that there was a significant decline in striatal dopamine (DA) concentration while its metabolite DOPAC was significantly increased in aged rats. Hence aging has a significant negative influence on cognitive functions. Age-related behavioral deficits may occur as a result of decline in DA levels in striatum leading to changes in memory and cognitive performance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".