Preventive Action of Kai Xin San Aqueous Extract on Depressive-Like Symptoms and Cognition Deficit Induced by Chronic Mild Stress
Bibliographic record
Abstract
Kai Xin San (KXS), a traditional Chinese herbal medicine, has been used clinically for the treatment of depressive disorders and cognitive impairment for centuries. However, the effects of KXS on cognitive dysfunction induced by depression have not been evaluated scientifically. The present study aimed to explore the antidepressant-like and nootropic effects of an aqueous extract of KXS (at doses of 0.3, 0.9, and 2.7 g/kg/day) using chronic mild stress (CMS) as a model of depression. Depressive symptoms were analyzed using the sucrose-preference and novelty-induced inhibition of feeding tests. Cognitive function was evaluated using a two-way active avoidance task. Serum corticosterone and adrenocorticotropic hormone (ACTH) levels, acetylcholinesterase (AChE) protein expression in the hippocampus, and monoamine neurotransmitter concentrations in the prefrontal cortex and hippocampus were also determined to elucidate the neurochemical mechanisms. Experimental results showed that KXS aqueous extract significantly ameliorated the CMS-induced depressive symptoms, including the reduced preference index and prolonged latency to novelty-suppressed feeding. Simultaneously, KXS significantly reversed the CMS-induced decrease in the numbers of active avoidance and active movement distances and increase in the numbers of the passive avoidance and passive movement distances, thereby producing nootropic effects in the two-way active avoidance test. KXS also inhibited the increased AChE expression in the hippocampus, up-regulated the decreased monoamine neurotransmitter concentrations of both brain areas and reduced the elevated ACTH concentrations in the serum induced by CMS. Taken together, these results indicate that KXS exerts its antidepressant-like and nootropic effects in the CMS model by modulating the HPA axis, monoamine neurotransmitter and cholinergic systems.
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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 | 0.000 |
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".