[Symmetry]

Even before Linear No Threshold was a thing scientists were doing experiments showing that dosing fruit flies with radiation all at once would lead to a highly mutated second generation, but spreading that radiation out over the course of a month wouldn't.

[sjmcmahon]

Most radiobiological effects for acute exposures are actually quadratic in dose - this applies to things like mutations, chromosome aberrations, and lethal events.

The quadratic term relates (loosely) to interactions between damage from multiple ionising particles which are present in cells at the same time. When you protract exposures, more damage is repaired before subsequent ionising particles arrive, and you see a reduction in the quadratic term, to effectively a linear form at very low dose rates.

So it's not surprising that spreading the radiation out significantly reduces the yield of biological events, but actually supports a linear trend for mutation yield in low-dose and low dose-rate conditions. (Whether that tracks linearly in turn to cancer risk, on the other hand, is a topic of much more debate.)

[Retric]

> a topic of much more debate.

People who want to step away from linear no threshold seem to ignore the extreme likelihood people will get cancer at some point. Which means for any given population there will be many people who are really close to the threshold of getting cancer.

Studying the effects of radiation on healthy tissue isn’t therefore representative of the general population. You need population level data, and the sensitivity just isn’t there to be able to detect if their model is correct or if linear no threshold is correct etc.

[epistasis]

Cancer cured (in mice)!

Radiation response shown to be sub-linear (in flies)!

[Symmetry]

At the time (the 1950s) evidence from fruit flies was essentially all the evidence there was. But as the article points out we have pretty good data showing it works the same way in humans.

[epistasis]

I do not agree that they have good data showing it works the same in humans. I see a lot of stretching of datasets, a lot of squinting, and above all a lot of hope!