Amyotrophic lateral sclerosis-frontotemporal dementia (ALS-FTD) is a neurodegenerative disease characterized by progressive neuronal loss and motor decline. Recovery remains beyond therapeutic reach, and even complete neurogenesis does not ensure preservation of memory capacity (defined as the strength of synaptic connections). Freshwater planarians, capable of whole-body regeneration and associative learning, provide a tractable model to study the relationship between neuronal damage and behavior. Their "single-circuit" centralized nervous systems allow evaluation of oxidative stress, a key driver of ALS-FTD pathology, which was induced via hydrogen peroxide. In this study, 180 planaria underwent three phases. Phase 1 established baseline memory using a 28-day operant conditioning protocol with a light-based training device. Success was determined by the proportion of planaria in concentric circles defined as zones (A-C) with a respective gradient descent of light concentration. Phase 2 determined hydrogen peroxide (H2O2;) concentrations sufficient to induce oxidative stress that triggered regenerative signaling and neuronal damage without lethality. Phase 3 applied the optimal concentration, allowed regeneration, and retested memory. The optimal concentration of hydrogen peroxide was 5 ppm, triggering blastema formation and neuronal damage while preserving viability. Zone occupancy analyses utilizing prior found concentration revealed measurable post exposure shifts: Zone A increased initially but trended lower post-exposure, Zone B increased, and Zone C decreased significantly. These results indicate that while memory capability persists after neurogenesis, the quality of memory decreases. In accordance with this study, current treatments for ALS-FTD that focus solely on neurogenesis will not fully restore cognitive function.
Uncovering Code Insights: Leveraging GitHub Artifacts for Deeper Code Understanding
arXiv:2511.03549v1 Announce Type: cross Abstract: Understanding the purpose of source code is a critical task in software maintenance, onboarding, and modernization. While large language models

