Lestienne R
Laboratoire de Physique Nucléaire des Hautes Energies, Ecole Polytechnique, Palaiseau, France.
Mech Ageing Dev. 1988 Mar;42(3):197-214. doi: 10.1016/0047-6374(88)90047-4.
"Thermodynamical" foundations of a Gompertzian representation of mortality rate distribution vs. age are reviewed. The two fundamental assumptions of the original model (as developed by Strehler and Mildvan) are: (1) challenges that threaten the lives of organisms of a given species have an exponential distribution in harmfulness; and (2) vitality ("energetic" reserve to be used to counteract the challenges and restore proper function of the organism) declines linearly with age. It is proposed that the external environment should not only be characterized by a "temperature", but also by a "pressure" (related to the average time between successive hits). While recent progress of health sciences have essentially lowered the "temperature" factor, future progress might also lower the "pressure" factor. The effect of this would be to provide only a slight extension of observed longevity in humans. Internal cause(s) of ageing that lead to death are not specified in the model (except that they should be compatible with the linear decline in vitality). It is shown that death cannot be attributed to a slowing down of the recovery machinery that restores the organism's state following a challenge or a disease. A mechanism of this kind would instead lead to a gamma- (rather than a Gompertzian) distribution of ages at death, at great ages. Whatever the modalities of the challenges (they are, of course, not necessarily of a literally energetic nature), the model is shown to assume that death is linked to single, large amplitude challenges, rather than to the conjunction of independent, small amplitude damages. The concept of programmed longevity is proposed and integrated into the model. In this new model, Gompertzian distributions are characterized by the two parameters alpha (slope) and L (longevity) rather than by the two traditional parameters alpha and R0 (mortality rate at birth). This new presentation is more parsimonious than the original one, in that only alpha (not L) is temperature dependent. Models with fixed longevity automatically display a negative correlation between ln R0 and alpha, as was noted by Strehler and Mildvan. There exists a definite lag of time (of 23-29 years) between longevity and the most probable age at death. Assuming that the human species has a maximum programmed longevity of 120 years, this implies that the progress of health sciences will allow the present survival curve to evolve, not towards a rectangular shape as previously believed, but rather to a given limiting curve such as is depicted.
回顾了死亡率分布与年龄的冈珀茨模型表示的“热力学”基础。原始模型（由斯特勒和米尔德万提出）的两个基本假设是：（1）威胁特定物种生物体生命的挑战在危害性上呈指数分布；（2）活力（用于应对挑战并恢复生物体正常功能的“能量”储备）随年龄线性下降。提出外部环境不仅应以“温度”来表征，还应以“压力”（与连续打击之间的平均时间有关）来表征。虽然健康科学的最新进展本质上降低了“温度”因素，但未来的进展可能也会降低“压力”因素。其效果将只是使人类观察到的寿命略有延长。导致死亡的衰老内部原因在模型中未明确规定（除了它们应与活力的线性下降相一致）。结果表明，死亡不能归因于在挑战或疾病后恢复生物体状态的恢复机制的减慢。相反，这种机制在高龄时会导致死亡年龄的伽马分布（而非冈珀茨分布）。无论挑战的形式如何（当然，它们不一定具有字面上的能量性质），该模型表明死亡与单个大幅度挑战相关，而非与独立的小幅度损害的联合相关。提出了程序性长寿的概念并将其纳入模型。在这个新模型中，冈珀茨分布由两个参数α（斜率）和L（寿命）表征，而不是由两个传统参数α和R0（出生时的死亡率）表征。这种新的表述比原始表述更简洁，因为只有α（而非L）与温度有关。如斯特勒和米尔德万所指出的，具有固定寿命的模型自动显示ln R0与α之间存在负相关。寿命与最可能的死亡年龄之间存在确定的时间滞后（23 - 29年）。假设人类物种的最大程序性寿命为120岁，这意味着健康科学的进展将使当前的生存曲线演变，不是如先前认为的朝着矩形形状，而是朝着如所描绘的给定极限曲线演变。
