Apoptosis and autophagy are both tightly regulated biological processes that play a central role in tissue homeostasis, development, and disease. The anti-apoptotic protein, Bcl-2, interacts with the evolutionarily conserved autophagy protein, Beclin 1. However, little is known about the functional significance of this interaction. Here, we show that wild-type Bcl-2 antiapoptotic proteins, but not Beclin 1 binding defective mutants of Bcl-2, inhibit Beclin 1-dependent autophagy in yeast and mammalian cells and that cardiac Bcl-2 transgenic expression inhibits autophagy in mouse heart muscle. Furthermore, Beclin 1 mutants that cannot bind to Bcl-2 induce more autophagy than wild-type Beclin 1 and, unlike wild-type Beclin 1, promote cell death. Thus, Bcl-2 not only functions as an antiapoptotic protein, but also as an antiautophagy protein via its inhibitory interaction with Beclin 1. This antiautophagy function of Bcl-2 may help maintain autophagy at levels that are compatible with cell survival, rather than cell death.
Exercise has beneficial effects on human health, including protection against metabolic disorders such as diabetes1. However, the cellular mechanisms underlying these effects are incompletely understood. The lysosomal degradation pathway, autophagy, is an intracellular recycling system that functions during basal conditions in organelle and protein quality control2. During stress, increased levels of autophagy permit cells to adapt to changing nutritional and energy demands through protein catabolism3. Moreover, in animal models, autophagy protects against diseases such as cancer, neuro-degenerative disorders, infections, inflammatory diseases, ageing and insulin resistance4-6. Here we show that acute exercise induces autophagy in skeletal and cardiac muscle of fed mice. To investigate the role of exercise-mediated autophagy in vivo, we generated mutant mice that show normal levels of basal autophagy but are deficient in stimulus (exercise- or starvation)-induced autophagy. These mice (termed BCL2 AAA mice) contain knock-in mutations in BCL2 phosphorylation sites (Thr69Ala, Ser70Ala and Ser84Ala) that prevent stimulus-induced disruption of the BCL2-beclin-1 complex and autophagy activation. BCL2 AAA mice show decreased endurance and altered glucose metabolism during acute exercise, as well as impaired chronic exercise-mediated protection against high-fat-diet-induced glucose intolerance. Thus, exercise induces autophagy, BCL2 is a crucial regulator of exercise- (and starvation)- induced autophagy in vivo, and autophagy induction may contribute to the beneficial metabolic effects of exercise.
In a longitudinal clinical study to compare two groups, the primary end point is often the time to a specific event (eg, disease progression, death). The hazard ratio estimate is routinely used to empirically quantify the between-group difference under the assumption that the ratio of the two hazard functions is approximately constant over time. When this assumption is plausible, such a ratio estimate may capture the relative difference between two survival curves. However, the clinical meaning of such a ratio estimate is difficult, if not impossible, to interpret when the underlying proportional hazards assumption is violated (ie, the hazard ratio is not constant over time). Although this issue has been studied extensively and various alternatives to the hazard ratio estimator have been discussed in the statistical literature, such crucial information does not seem to have reached the broader community of health science researchers. In this article, we summarize several critical concerns regarding this conventional practice and discuss various well-known alternatives for quantifying the underlying differences between groups with respect to a time-to-event end point. The data from three recent cancer clinical trials, which reflect a variety of scenarios, are used throughout to illustrate our discussions. When there is not sufficient information about the profile of the between-group difference at the design stage of the study, we encourage practitioners to consider a prespecified, clinically meaningful, model-free measure for quantifying the difference and to use robust estimation procedures to draw primary inferences.
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