| Integrated Damage Model (proposed) |
ba(t) = P(t) Ā· (1/Nr) Ā· ā«[fresp(u) / f(m,e)] du |
Refines Escalaās theory by integrating respiration cycles over time, adjusted for species-specific maintenance (f) and life-phase acceleration (P). Can explain aging inflections and outliers like bats. Mechanistic and time-continuous. |
| Escalaās Respiration-Cycle Law |
tlife ā Nr / fresp |
Proposes organisms undergo a nearly fixed number (~10āø) of respiration cycles per lifetime. Supported across ~300 species from microbes to mammals. Unifies metabolism and lifespan. |
| Entropy Generation Model (Silva & Annamalai) |
ā«Ļ(t) dt ā constant |
Connects aging to total entropy generated over lifetime. Predicts human lifespan from heat dissipation per kg. Conceptually links thermodynamics and aging. |
| Reliability Theory of Aging |
Vitality(t) = V0 - kĀ·t + noise |
Models aging as loss of systemic redundancy. Predicts rising mortality even when components have fixed failure rates. Supports late-life mortality plateaus. |
| Kleiberās Law |
B ā M3/4 |
Basal metabolic rate scales as body mass to the 3/4 power. Foundational to metabolic and lifespan scaling laws across all taxa. |
| LifespanāMass Allometry |
tlife ā M1/4 |
Empirical observation that lifespan increases with body mass. Follows from Kleiberās law and constant energy-per-mass assumptions. |
| Rate-of-Living Hypothesis (Rubner) |
Elife/M ā constant |
Suggests that organisms expend the same amount of energy per gram over a lifetime. Holds across mammals but breaks down across classes (e.g. birds). |
| GompertzāMakeham Law |
Ī¼(t) = Ī±Ā·eĪ²Ā·t + Ī» |
Classical model of mortality where death risk grows exponentially with age and includes a constant background risk. Very good empirical fit but not mechanistic. |
| Gompertz Law |
Ī¼(t) = R0Ā·ebĀ·t |
Simpler form of GompertzāMakeham. Predicts exponential rise in mortality with age. Used widely in demography and aging studies. |
| Weibull Mortality Law |
Ī¼(t) = kĀ·Ī»Ā·tk-1 |
Predicts mortality using a power law. Used in reliability theory and some species. Less common for biological aging. |
| DNA Methylation Clock (Horvath) |
DNAmAge = Ī²ā + Ī£(Ī²iĀ·CpGi) |
Uses weighted DNA methylation levels at CpG sites to predict biological age. Highly accurate. |
| Phenotypic Age (Levine) |
PhenoAge = f(albumin, WBC, etc.) |
Combines standard blood biomarkers to predict mortality risk and biological age. |
IMMORTALITY