[timr]

This paper came up as a pre-print. You can't make the extrapolation that the headline is making - they're using gas chromatography to estimate quantities from 1-2mg samples, and then extrapolating to get to these scary sounding whole-organ estimates. If you look at the paper [1], you'll see that the microplastics in in situ samples are not discernible by light microscopy, and that there was a ~25% variation in within sample measurement of the GC [2], indicating a great deal of uncertainty in the precision of the fundamental measurement (the authors brush this off; see quote below).

Basically, you've got an extremely sensitive measurement system being used to make tiny measurements, and then they extrapolate these measurements by a huge factor to get to ug/g estimates. Further extrapolating (to the weight of an organ, say) when you know that there's 25% inter-sample variation, is just guaranteed to be nonsense.

[1] https://www.nature.com/articles/s41591-024-03453-1

[2] "Both analytical laboratories (UNM and OSU) observed a ~25% within-sample coefficient of variation, which does not alter the conclusions regarding temporal trends or accumulation in brains relative to other tissues, given the magnitude of those effects."

[userbinator]

IMHO the more important part is they used pyrolysis gas chromatography, which breaks down all polymer chains.

Besides man-made plastics, guess what else has long hydrocarbon chains, occurs naturally in humans and other biological matter, and behaves similarly under pyrolysis...

https://en.wikipedia.org/wiki/Fatty_acid

Here's an interesting related article: https://www.oaepublish.com/articles/jeea.2022.04

Analysis of saturated, monounsaturated and polyunsaturated fats was demonstrated to form the same pyrolysis products as PE

[timr]

To their credit, they do discuss this in the results. I suspect the reviewers had the same concerns.

Their response is not especially convincing, IMO, but they do at least discuss it.

[rthomas6]

Well, it still tells us something. What are the upper and lower bounds of whole brain microplastic content, given that 25% variation?

[timr]

I couldn't begin to tell you [1]. It's not a 25% variation, once you've extrapolated from the samples by 10,000x (or whatever). The 25% inter-sample error was on a few replicas of teeny tiny measurements. The post-extrapolation error bars are so wide that they're meaningless.

The Smithsonian magazine article is garbage. Ignore it. The paper is saying that they see longitudinal trends in plastic bioaccumulation in various cadaver tissues, and this is plausible. But no, you don't have a plastic spoon in your head. That's just panic porn.

[1] Actually...I just asked Gemini and it reminded me that the expected variance of a draw from a distribution, scaled by factor C, should have a variance of the scaled sample distribution that grows with C^2. So, if we scale up the measurement by a factor of 10,000, we'd expect the variance of the scaled estimate to be proportional to 10,000^2.

[edouard-harris]

I may be misunderstanding you, but it sounds like you're claiming that they had e.g. 10 tiny samples of tissue, that their measurements had an average 25% variation across those 10 samples, and that therefore the whole brain estimate (mass 10,000x that of a single sample) therefore has a much greater uncertainty. But doesn't the standard error of the mean get reduced by the square root of the number of samples? i.e. if you had 10 samples with 25% variation across samples, and you're taking their mean, the error of that mean should be 25% / sqrt(10) = 8%. And that should be the relative error for the scaled up whole-brain microplastic concentration as well. Or is there some other source of variation that I'm missing?

[timr]

You're talking about reduction in statistical variance due to replication of measurement (and then averaging). I'm talking about what happens when they extrapolate from that value by a huge factor (which is what they've done, and the silly article does egregiously).

The paper isn't clear what they mean when they said "~25% within-sample coefficient of variation", so I can't directly address what you're asking, but it's tangential to the point I'm making. My naïve interpretation is that they did an ANOVA, and reported the within-group variance, or something similar.

All I'm saying in my footnote is that, whatever the final point estimate, scaling it by a factor of C will affect the variance of the final sample distribution by C^2. So for example, if you have an 8% variance on the measurement at ug/g, and you scale it by 1300 (for 1300g; what the interwebs tells me is the mass of a standard human brain), then you'd expect the variance of the scaled measurement to be 1300^2 * 8%.

That makes a ton of assumptions that probably don't hold in practice -- and I expect the real error to be larger -- but illustrates the point.

[myrmidon]

I think there is some kind of mixup, you can not scale up the variance percentages quadratically:

If you do a small-scale measurement, say you get result of 5g, with a standard deviation of 0.2g. That means the variance is 0.04 g^2.

If you then scale the setup up by 1000 (=> getting 5kg as expected value), then the variance scales to 1000^2 * 0.04 = 40000 g^2.

BUT the standard deviation is still 200g. The relative uncertainty is NOT increasing quadratically!

(another sanity check: if you change the units by a factor of 1000, your variance must not increase, relatively).

But maybe I misunderstood your point?

[timr]

> If you then scale the setup up by 1000 (=> getting 5kg as expected value), then the variance scales to 1000^2 * 0.04 = 40000 g^2.

They didn't "scale the setup". They made a small-scale measurement, then extrapolated from that result by many orders of magnitude. They didn't grind up whole brains and measure the plastic content.

Imagine the experiment as a draw from a normal distribution (the distribution is irrelevant; it's just easier to visualize). You then multiply that sample by 10,000. What is the variance of the resulting sample distribution?

[drawkward]

...so you are saying that the probability distribution indicates that there is a 50% probability that there more than a spoon's worth of plastic in our brain?

[drawkward]

Why yes, i think i will believe the random internet commenter.

[LoganDark]

Practically every internet commenter is random.

[drawkward]

Which is fine in plenty of contexts. Rebutting this particular article? Nah.

[robertlagrant]

Evaluate things based on reasoning, not source.