Targeting angiopoietin like-2 positive senescent cells improves cognitive impairment in adult male but not female atherosclerotic LDLr−/−;hApoB100+/+ mice
Bibliographic record
Abstract
(ATX) mice-a model exhibiting vascular dysfunctions and cognitive impairment-the role of senescence was investigated by targeting angiopoietin-like 2 (angptl2), a senescence marker. Adult ATX mice of both sexes received AAV1-sh-angptl2; cognition was assessed via the Morris Water Maze, cerebrovascular functions were evaluated in vitro and in vivo and hippocampal transcriptomic signatures were analyzed using single-nuclei RNA-sequencing. Sh-angptl2 restored delayed memory retention in male mice, but impaired learning and short-term memory in females. Sh-angptl2 had no effect on cerebrovascular functions. Transcriptomic analyses revealed sex-specific responses: endothelial senescence pathways were predominantly activated in male cells and repressed by sh-angptl2. In contrast, sh-angptl2 up-regulated senescence pathways in all cell types in females. Key impacted senescent cell types were neurons, choroid plexus epithelial (CP-epithelial) cells, and oligodendrocyte precursor cells (OPCs), not endothelial cells. In male neurons, CP-epithelial cells and OPCs, gene-related pathways induced by sh-angptl2 revealed enhanced neuronal energy metabolism but reduced synaptic pathways, higher synaptic formation with reduced intracellular signaling, structural remodeling and reduced synaptic development. In female cells, sh-angptl2 disrupted GABAergic signaling despite promoting neuronal growth, up-regulated stress-response and decreased gene and protein processing, leading to inefficient neurogenesis. Although neuroprotective ApoE was upregulated in both sexes, males had higher expression of ApoE receptor subtypes, supporting better synaptic resilience. In conclusion, accumulation of non-vascular senescent cells contributes to cognitive impairment in male ATX mice, not females, highlighting the need for sex-specific senotherapies strategies in cardiovascular diseases.
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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 | 0.001 | 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) | 0.002 | 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".