Personal Agent Mitochondrial Biogenesis MET Flux Skill

Zero-dependency PGC-1alpha transcriptional induction modeler, CaMK vs. AMPK pathway partitioner, and 80/20 polarized mitochondrial density training optimizer.

Architecture

flowchart TD
    WorkoutSession[Session Type, Duration, Average HR, Max HR] --> PathwayModeler[Biochemical Pathway Modeler]
    PathwayModeler --> CaMKBranch[Low-Intensity Zone 2: CaMK & p38 MAPK Volume Signaling]
    PathwayModeler --> AMPKBranch[High-Intensity Sprints: AMPK Acute Depletion Signaling]
    CaMKBranch & AMPKBranch --> PGC1aScore[PGC-1a Transcriptional Score & Biogenesis Tier]
    WeeklyCardio[Zone 2 Minutes & HIIT Minutes] --> PolarizedOptimizer[80/20 Polarized Training Optimizer]
    PolarizedOptimizer --> Prescription[Mitochondrial Volume & Cristae Efficiency Balance]

Quickstart

from client import PersonalAgentMitochondrialBiogenesisMetFlux

agent = PersonalAgentMitochondrialBiogenesisMetFlux()
res = agent.model_pgc1a_transcriptional_stimulus(session_type="zone2_endurance", duration_minutes=50.0)
print(f"PGC-1a Score: {res['pgc1a_transcriptional_score']} | Pathway: {res['biochemical_signaling_cascade']}")