AdipoRon Treatment Induces a Dose-Dependent Response in Adult Hippocampal Neurogenesis
Bibliographic record
Abstract
AdipoRon, an adiponectin receptor agonist, elicits similar antidiabetic, anti-atherogenic, and anti-inflammatory effects on mouse models as adiponectin does. Since AdipoRon can cross the blood-brain barrier, its chronic effects on regulating hippocampal function are yet to be examined. This study investigated whether AdipoRon treatment promotes hippocampal neurogenesis and spatial recognition memory in a dose-dependent manner. Adolescent male C57BL/6J mice received continuous treatment of either 20 mg/kg (low dose) or 50 mg/kg (high dose) AdipoRon or vehicle intraperitoneally for 14 days, followed by the open field test to examine anxiety and locomotor activity, and the Y maze test to examine hippocampal-dependent spatial recognition memory. Immunopositive cell markers of neural progenitor cells, immature neurons, and newborn cells in the hippocampal dentate gyrus were quantified. Immunosorbent assays were used to measure the serum levels of factors that can regulate hippocampal neurogenesis, including adiponectin, brain-derived neurotrophic factor (BDNF), and corticosterone. Our results showed that 20 mg/kg AdipoRon treatment significantly promoted hippocampal cell proliferation and increased serum levels of adiponectin and BDNF, though there were no effects on spatial recognition memory and locomotor activity. On the contrary, 50 mg/kg AdipoRon treatment impaired spatial recognition memory, suppressed cell proliferation, neuronal differentiation, and cell survival associated with reduced serum levels of BDNF and adiponectin. The results suggest that a low-dose AdipoRon treatment promotes hippocampal cell proliferation, while a high-dose AdipoRon treatment is detrimental to the hippocampus 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) | 0.000 | 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 | 0.001 |
| 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".