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This Perspective advances a mechanistic framework for understanding burnout as progressive loss of biological reversibility across multiple scales—from molecular receptor dynamics through systems-level network function to clinical phenotypes. We integrate evidence from structural biology (AlphaFold 3 GPCR predictions [38,39]), dopamine neuroscience [20-32], neuroimmunology [57-75], chronobiology [141-164], and clinical observations to propose testable hypotheses about why recovery becomes progressively difficult in chronic stress. This is a conceptual and mechanistic contribution, not a treatment guideline or randomised controlled trial. Clinical patterns described (detailed in Supplementary Protocols S1-S3) serve to illustrate how the reversibility framework maps onto real-world treatment trajectories, revealing biological constraints consistent with proposed mechanisms. These retrospective observations are explicitly hypothesis-generating, providing design templates for future mechanistic trials. Background: Burnout afflicts over 50% of physicians and nurses globally [1,2], driving medication errors, adverse events, and reduced patient safety [3-5]. Despite organisational interventions, treatment resistance remains common, and no validated biomarkers exist for diagnosis or staging. The biological mechanisms underlying burnout's progression and variable reversibility remain poorly understood. Framework: We propose burnout as a progressive loss of biological reversibility across multiple scales—from molecular receptor dynamics through systems-level network function to phenotypic presentation. Chronic occupational stress drives a cascade: dopamine D2 receptor downregulation and desensitisation [27-29] → neuroimmune activation [57-62] → HPA axis dysregulation [51-56] → circadian disruption [147-150] → epigenetic modifications [45-50]. Each biological scale exhibits distinct reversibility kinetics, creating temporal windows where intervention efficacy declines exponentially. Evidence Synthesis: We integrate molecular neuroscience (D2 receptor conformational dynamics [33-37], GPCR desensitization [33-35], AlphaFold 3 structural predictions [38,39]), systems neuroscience (default mode network connectivity [88-95], HPA axis allostatic load [83-86], autonomic dysfunction [76-82]), clinical neuroimaging (amygdala hypertrophy [106,107], prefrontal thinning [102-105], striatal volume loss [99]), epigenetics (BDNF, FKBP5, SLC6A4 methylation [45-50]), and cardiovascular outcomes [11,12]. Recent meta-analyses demonstrate burnout predicts adverse patient outcomes (SMD=-0.68 for safety climate [4]) and cardiovascular disease [11,12], while organisational interventions show no significant association with burnout reduction (Cohen's d=-0.25 [6-8]). Clinical Implications: Qualitative case series (N=3, 24-84 months observation) illustrate the reversibility gradient: early intervention (<6 months) may achieve >75% recovery with behavioral approaches; intermediate stage (6-24 months) requires multimodal treatment achieving 60-80% recovery; advanced stage (>24 months) exhibits treatment resistance with <50% recovery ceiling despite intensive biological interventions. Conclusions: Burnout represents a multi-scale biological state transition with time-dependent irreversibility thresholds. The framework explains organisational intervention failures (scale mismatch), treatment resistance (biological constraints), and generates testable predictions for biomarker-guided staging, precision timing of interventions, and novel regenerative approaches. Early detection becomes a medical imperative rather than a wellness recommendation.