Did We Overestimate the Potential Harm from Microplastics?

Over the past years there have appeared in the media increasingly more alarming reports about micro- and nanoplastics (MNPs) and the harm that they are causing not only in the environment, but also inside our bodies. If some of the published studies were to be believed, then MNPs are everywhere inside our bodies, from our blood and reproductive organs to having deeply embedded themselves inside our brains with potentially catastrophic health implications.

Early last year we covered what we thought we knew about the harm from MNPs in our bodies, but since then more and more scientists have pushed back against these studies, calling them ‘flawed’ and questioning the used methodology and conclusions. Despite claims of health damage in mice, institutions like the German federal risk assessment institute also do not acknowledge evidence of harm to human health from MNPs.

All of which raises the question whether flawed studies have pushed us into our own Chicken Little moment, and whether it’s now time to breathe a sigh of relief that the sky isn’t falling after all.

Measuring Many Tiny Things

One of the problems with making statements about the amount of MNPs in the body pertains to the way that this is measured. Rather than sliding samples under a microscope and doing manual counting, the typical method involves a method like pyrolysis-gas chromatography-mass spectrometry (Py-GC-MS). For biological samples you first want to remove the organic components before pyrolysis, lest the subsequent mass spectrometry step produces false positives rather than an objective polymer analysis.
A ThermoQuest Trace 200 gas chromatograph–mass spectrometer (GCMS) with open door. (credit: Polimerek, Wikimedia)
Py-GC-MS involves rapidly heating the sample in an inert atmosphere or vacuum. This cleaves large molecules into smaller fragments which can then be separated using a gas chromatography column and classified in combination with a mass spectrometer. With both results combined, the likely original materials in the sample can thus be deduced. This means that you are not literally counting MNP particles in the sample or measuring them, but quite literally vaporizing said sample and analyzing the debris cloud. Obviously this comes with some major asterisks.

A 2024 paper by Marthinus Brits et al. as published in Microplastics and Nanoplastics explored the use of Py-GC-MS for determining the amount of MNPs in human blood. Using whole blood samples they found mostly polyethylene (PE) polymer, with a mean of 268 ng/mL of MNPs across all 68 samples, with a call to investigate the health impact of this finding.

In response to this paper a correspondence by Bianca Wilhelmus et al. was submitted to the journal, in which one of the complaints was a lack of detail on the Py-GC-MS fingerprints using which the polymers were purportedly detected. It was also noted that with sub-micrometer MNP particles you’d need millions of them in a sample to really register, which is far above what had typically been found in human body fluids.

To this Brits et al. replied with among other things the admission that the quantitative analysis of MNPs using Py-GC-MS is still in early stages of development. To the issue of quantity it was noted that most of the MNPs are significantly larger than a micrometer, so they were still fairly confident of their findings.

It’s important to note more recent studies here, such as the 2025 study by Cassandra Rauert et al. in Environmental Science & Technology, in which also a study on using Py-GC-MS for detecting MNPs in blood was performed. Its conclusion was that this detection method has trouble detecting PE and PVC polymers, and the estimated exposure concentrations are testing the detection limits of this technique.

Contamination

One of the problems with trying to measure MNPs in a sample is that of environmental MNP contamination, as MNPs are being shed and distributed all around us, whether it’s from e.g. polyester clothing, plastic surfaces and tools, or carried in from outside. This makes it a real chore to make sure that in a laboratory setting such contamination does not ruin the findings, as with a recent study on MNPs in bottled water by Qian et al. in PNAS.

Rather than Py-GC-MS, this used stimulated Raman scattering, but also led to accusations of contamination due to improper procedures, with the finding that the ultra-pure filtered Milli-Q water that was used for a blank (i.e. control) contained as many MNPs as the bottled water. This and other issues were suggested as invalidating the findings. While Qian et al. acknowledged that using the Milli-Q water as a blank was resultingly improper, they disagreed with the premise that this invalidated the study’s findings.

Another type of contamination can come from the aforementioned biological tissue, such as in the early 2025 study on MNPs in the human brain and other organs by Nihart et al. as published in Nature Medicine. This analyzed tissue samples from human cadavers using, among other methods, Py-GC-MS, leading them to conclude that especially our brains are full of PE polymers, with major implications for Alzheimer’s and dementia research, for instance.

This assessment subsequently got challenged (full article) by Monikh et al. in a November 2025 published commentary, with the authors noting that Nihart et al.’s samples from the human liver, kidney and brain all have in common that they contain significant amounts of fatty tissue (lipids), which when subjected to pyrolysis produce fragments that are easily mistaken for PE polymer fragments.

When it comes to detecting polymers in such biological samples, it is absolutely essential to strip away the biological material, without affecting the sample that will ultimately be analyzed. In this case the processing method appears to have been flawed, leading to subsequent contamination. This was acknowledged by the team, in a reply by some of the study authors.

Empirical Correlation

Although it seems like we can at least conclude that our brains aren’t overflowing with PE polymer fragments, but that they are just filled with phospholipids in particular, this doesn’t necessarily take away all our concerns. After all, didn’t some studies find real, empirical evidence for MNPs causing actual damage? Especially since it seems harmful in mice, according to a 2025 study using starch-based plastics.

As highlighted by Baroni et al. in a September 2025 review paper on MNPs in the brain as published in Nanomaterials, the enduring problem that we are dealing with right now is one of a lack of information, a scarcity of standard detection methods and a total lack of longitudinal studies in humans.

Although we have health databases that span decades in countries with strong public healthcare systems, trying to figure out whether certain health trends are due to MNPs using their data is borderline lunacy, as you cannot realistically account for all confounding factors. Thus we are mostly stuck at this point trying to figure out how to actually effectively measure the presence of MNPs.

Methodology

The aforementioned Py-GC-MS and SRS methods are two tools available to us here, but clearly moving from measuring MNPs in water to measuring them in biological tissues is still a challenging topic. When we look at the established science of MNPs in water, we got a range of options, as illustrated by this application note by ThermoFisher Scientific:

In order to measure not just the relatively large microplastic particles, but also the much smaller nanoplastics which are more likely to interact with biological systems, you are pretty limited here already. With only Raman spectroscopes applicable for such fine analysis, it’s little wonder that Py-GC-MS is being applied to biological samples.

Maybe once we have figured out the right methodology for Py-GC-MS and potentially other approaches will we be able to tell with some certainty how many of these polymer fragments are in our bodies right now, and how much of it will simply pass through rather than take up permanent residence. On the bright side, there’s no clear epidemiological evidence of MNPs being actively harmful to us, yet.

Although the sky hasn’t been confirmed to be falling, it is still looking somewhat unsteady. For that reason alone it is probably in our own best interest to use the precautionary principle here, as it’s better to have begun today to find ways to reduce and prevent the spread of MNPs, rather than to regret not having done so tomorrow.

hackaday.com/2026/01/29/did-we…

L’estasi dell’ignoranza. La tradizione occidentale della non conoscenza

Perché un lettore crede a racconti palesemente falsi? Vuole evitare notizie scomode? Come fanno i fedeli religiosi a credere nella scienza e contemporaneamente affidarsi al mito? Si tratta di scelte razionali, strategie collettive oppure difesa privata e personale di un nucleo emotivo che altrimenti finirebbe in pezzi? Sono queste le domande che affiorano, con risposta annessa, nel libro del politologo Mark Lilla che per Luiss University Press ha pubblicato «L’estasi dell’ignoranza. La tradizione occidentale della non conoscenza».

A dispetto della moderna logica mediatica che obbliga tutti alla trasparenza, alla conoscenza, alla condivisione di informazioni e intimità sui social, Mark Lilla elabora una ricostruzione storica e filosofica del volto contrario di questa modernità, cioè dell’ignoranza intesa come volontà di non sapere. Strategia adattativa piuttosto che euristica vitale, l’ignoranza descritta da Lilla viene dissezionata nei miti antichi, come quello di Edipo, che non voleva sapere di essere giaciuto con la madre; passa per le Confessioni di Sant’Agostino che dubita della sua fede; arriva da Nietzsche il pazzo fino a Freud e alla sua teoria della rimozione, per ricostruire i tabù della verità, la delusione della curiosità quando si osa strappare il velo di Iside, fino alle cedevoli illusioni di innocenza personale, colte nelle loro forme quotidiane e talvolta penose.

La fuga dalla realtà è la chiave di questo viaggio intellettuale nella volontà di ignoranza. Certo, sull’ignoranza e sull’errore molto è stato detto, da Gianrico Carofiglio in Elogio dell’ignoranza e dell’errore, a Umberto Galimberti con Le contraddizioni della Verità e l’attitudine tutta binaria a pensare semplice senza troppo complicarsi la vita, come pure in L’età dell’ignoranza di Fabrizio Tonello, ma questo testo si misura sulla volontà di non conoscere quale strategia di sopravvivenza intima, nascosta e personale, per rendere la vita odierna più accettabile. Una scelta che è alla base di questioni tremendamente attuali, dagli effetti della disinformazione al cospirazionismo politico, dal pensiero magico alle semplificazioni scientifiche. In fondo, in fondo, il trionfo dell’ignorante è l’estasi del potere.

dicorinto.it/articoli/recensio…

Ask Hackaday: How Do You Digitize Your Documents?

Like many of you, I have a hard time getting rid of stuff. I’ve got boxes and boxes of weirdo bits and bobs, and piles of devices that I’ll eventually get around to stripping down into even more bits and bobs. Despite regular purges — I try to bring a car-load of crap treasure to local hackerspaces and meetups at least a couple times a year — the pile only continues to grow.

But the problem isn’t limited to hardware components. There’s all sorts of things that the logical part of me understands I’ll almost certainly never need, and yet I can’t bring myself to dispose of. One of those things just so happens to be documents. Anything printed is fair game. Could be the notes from my last appointment with the doctor, or fliers for events I attended years ago. Doesn’t matter, the stacks keep building up until I end up cramming it all into a box and start the whole process starts over again.

I’ve largely convinced myself that the perennial accumulation of electronic bric-à-brac is an occupational hazard, and have come to terms with it. But I think there’s a good chance of moving the needle on the document situation, and if that involves a bit of high-tech overengineering, even better. As such, I’ve spent the last couple of weeks investigating digitizing the documents that have information worth retaining so that the originals can be sent along to Valhalla in my fire pit.

The following represents some of my observations thus far, in the hopes that others going down a similar path may find them useful. But what I’m really interested in is hearing from the Hackaday community. Surely I’m not the only one trying to save some storage space by turn piles of papers into ones and zeros.

Take a Picture, It’ll Last Longer

Obviously, the first step in digitizing physical documents is image capture. The most obvious way to accomplish this is to simply use a flatbed scanner, and in some cases, there’s a solid argument to be made that it’s the best approach. Indeed, many of the documents that I’ve already filed away digitally were created this way. But it’s a tedious enough process that you may want to consider alternative methods.

If you’ve got a decent camera, you can get a couple of lights and put together a nice overhead photography rig without spending too much money. Put your document down under the camera, snap a picture, and keep it moving.

Imaging doesn’t get any faster than taking a picture, and so long as you’re not using some point and shoot from the early 2000s, the resolution should be more than sufficient. This method is particularly appealing if you’re planning on digitizing books or anything else that can’t be laid perfectly flat on a scanner.

The major downside with this approach is the setup itself. It’s one thing if you’re digitizing documents and books on a daily basis, but for occasional use, putting something like this together is a big ask. A flatbed scanner certainly takes up a lot less room, and you don’t have to worry about getting the lighting right, mounting the camera, and so on.

Casting Some Magick

Whether you used a scanner or a camera, once you have the image of your document, you’ve technically digitized it. Congratulations, you’re now an amateur archivist.

If you’re looking to keep things simple, you could stop here. Stash the files someplace and be done with it. But depending on the type of content you’re working with and what your goals are, there’s a good chance you’ll want to touch up the images a bit. Luckily for us, the incredible ImageMagick project has many of the functions we need built-in, from cropping and resizing, all the way to image enhancement.

Consider the image below. It’s clear enough to read, but the text is rotated and the lighting isn’t consistent across the entire page.

We can fix both issues with a simple ImageMagick command via the convert tool:
convert input.png -deskew 30% -threshold 25% output.png
We won’t get too bogged down in the details, the ImageMagick documentation can break it all down better than I can. The short version is that we’re telling it to straighten out the image and convert it into pure black and white. The result looks like this:

The values can be tweaked a bit to refine the result, and as you might imagine there are many other ImageMagick functions that could potentially be brought in to clean up the result. Things do get more complicated if you’re working with something more complex than plain text, but you get the general idea.

This sort of post-processing is especially important if you plan on running the images through any sort of optical character recognition (OCR) to capture the actual text of the document. That first image might be perfectly legible to our human eyeballs. You might even prefer it over the stark look of the processed image, but tools like tesseract have a hell of a time picking the text out when the background isn’t uniform.

There’s an App For That

The process described here certainly isn’t for everyone, and that’s fine. If you’re not looking to invest the sort of time and effort it would take to make this work, there’s fortunately a far more approachable solution available. In fact, it might already be in your pocket.

The Google Drive mobile application offers a very impressive document scanning mode that essentially automates everything above. If you give it access to your device’s camera, it will automagically detect documents in the field of view, find their edges, compensate for angle and rotation to straighten out the image, and even run it through filters to make the text pop. It’s fast, works reasonably well, and is exceptionally handy for cranking out multi-page PDFs.

The downside is that you’ve got relatively little control over the process, and being a product of Google, there’s the usual concerns over what they may be doing with the information that’s passing through the system. For these reasons it’s not something I would personally recommend for any private information, and its automatic nature the lack of fine-grained control means it may not be a great choice if your needs venture too far from the beaten path.

Still, the speed and ease of use it offers is admittedly very attractive.

Open to Suggestions

I’d love to hear the community’s thoughts on digitization, whether it’s hardware or software related. There’s surely some slick projects out there that aid in creating bespoke digital libraries, and there’s plenty of areas where real-world experience can help streamline and improve the overall process. For example, what’s your file naming convention look like?

Hackaday readers are rarely shy about sharing their opinions, so let’s hear them.

hackaday.com/2026/01/29/ask-ha…

These Ultra-Cute, Handsfree Walkie-Talkies Are Built For Cycling

Walkie-talkies are great fun, and [RealCorebb]’s bbTalkie project takes the concept a step further by adding some extremely cool features to make a highly refined, self-contained ESP32-based communicator. bbTalkie completely does away with a push-to-talk button by implementing robust voice detection that works reliably even in noisy environments. It was all designed with cycling in mind, so hands-free operation that stands up to noise is a big plus.
Hands-free, wireless, self-contained digital walkie-talkies that can connect in a group. What’s not to like?
The core of communication is done over ESP-NOW, which is Espressif’s own protocol for direct device-to-device broadcasting. This removes the need to involve any sort of external service like SIM cards or internet access to transmit voice. Performance is best with an external antenna, naturally, but ESP-NOW doesn’t actually require anything other than the existing on-board hardware.

We’ve seen ESP-NOW used to make digital walkie-talkies before, but bbTalkie is a really evolved take on the concept, not least of which due to its hands-free operation.

Because volume-based automatic triggers are highly susceptible to noise, voice detection is done with the help of VADNet, a neural network-based model implemented locally on the device. This system can reliably detect human speech, even in noisy environments. This lets bbTalkie switch between transmit and listen modes automatically and hands-free, without false triggers.

Even when doing all that, there’s still spare capability to play with. Further to the goal of making bbTalkie useful for cyclists in a group, [RealCorebb] added a system that can recognize specific voice commands (like “turn left” for example, or “wait for me!”) which trigger synchronized animations to play on the displays of all connected units. There’s even some experimental support for controlling a camera over Bluetooth, though currently it only supports hardware from Sony.

Watch a tour of it in the video below (Chinese language, English captions available). The OLED screens and animations are adorable, and are great visual feedback of what the unit is doing at any given moment.

youtube.com/embed/v0QcsWsoYbw?…

hackaday.com/2026/01/29/these-…