Dude, what point are you trying to make? You're nitpicking at data normalization strategies, which is something that is worth considering, but you're completely ignoring the possible sensitivities of the relevant outcomes to what you're saying. We're looking at data that show massive differences (30x) over sample sizes which are different by 2x. The level of wrongness in testing scheme required to make those two line up would be absurd, and there's no reason to believe that it exists. But you're going to stop looking at data there? That's not "pay attention to what the data ACTUALLY says" that's "I don't want to hear it, so I'm going to ignore it."