I actually am beginning to worry about this from a scientific publishing point of view. Yeah I know there’s editorial board meetings where articles are discussed for publication, but given that the content is being pushed out increasingly through algorithmic channels (google scholar, social media, pubmed search, researchsquare), I have to wonder how much choices are made to optimise for the channels. What are the metrics editorial decisions are measured by? Does channel performance factor in?
Scientists appear to optimise for citations because that's how they're "measured" against others. The quality and innovation of the research almost doesn't matter if it won't get citations, so you must publish something around what other people are working on, not on what you believe there's more chances of progress.
To get citations, you also need to "play SEO" on those research search engines, of course (which is why every research paper uses as many buzzwords as they can fit in it), or make sure you have mutual agreements with "friends" to cite each other in every possible publication. Most heads of departments require everyone to cite their work on everything they publish.
It's a wonder that with such a idiotic system (ironically coming from our brightest educational institutions) science still manages to make any progress at all.
These results are both interesting and unsurprising at the same time. Firstly unsurprising as the COG proteins are already well known to be important in animals, linked to a whole family of diseases, the congenital disorders of glycosylation.
However, this is interesting because it points to the protein(s) we need to consider to understand the aging process in plants (probably some N-glycosylated protein). I would bet this is some misfolding accumulation defect that takes some time to kill the cells.
I had a go at something like this when my kids were born. We were after names that could be pronounced in both Danish and Gujarati. After grabbing name lists from various websites, I generated phonetic translations of each name, and then looked at the names that had the shortest edit distances in the phonetic representation between both languages. It was a great exercise in taping bits of software together, and I ended up coming down to a shortlist of 7 names. I very proudly showed this list to my wife, and she showed me her list of names that she had written down.
Turns out two of the names were on both the lists, so we went with them. I have a feeling that it wasn’t so important that they were on my lists.
If anyone is wondering, this looks a bit like a syndromic set of phenotypes resulting from the mutation(s) in DHDDS. The mutations are hitting a really bad part in the glycosylation pathways, where I can imagine impacts on a massive number of proteins. I’m assuming this is a hypomorph, as if you lost function of this gene completely, it’s hard to see how any cell can survive.
NDST1 is a funny one in the list. In principle it shouldn’t be out in circulation, so it’s probably a sign that actually what you are seeing is a dysregulation in activity of SPPL3 in shedding of this enzyme from the Golgi.
More on reflection: Looks like NDST1 has a protective effect, so maybe this is reflecting the shedding going up for some reason. Would need to check what is regulating SPPL3 activity.
NDST1 is a bifunctional sulfotransferase and de-acetylase. It’s a gatekeeper enzyme (well as much as it can gatekeep with other isoenzymes), that catalyses a sulfation on heparan sulfate (HS) chains. HS makes up a big chunk of the extracellular matrix, and it is this matrix that various signaling molecules travel through to get to the cell. Reducing availability of NDST1 in cells would likely reduce binding of growth factors etc (or increase it, who knows!). It’s likely a bunch of subtle effects, and maybe this is actually pointing to some whole other thing that is happening. It’s difficult to say without digging into the literature.
I’d be a little skeptical about spraying in a bunch of heparin and hoping it binds enough of the spike protein.
This whole idea is predicated on the binding of heparin (a sulfated polysaccharide) to the spike. It’s known to be a co-receptor on cells for the spike protein, and people have designed very clever flow devices to exploit this binding to perform detection of spike. However, without carefully controlling the sulfation on heparin, I would be worried about all the other binding of proteins, and how effective this would be in real complex environments.
There are also open questions about how you would even retain the GAGs in the mucosal environment, and as I haven’t heard that they bind to mucins/mucus, I wonder how many other proteins they could possibly anchor to.
As far as I know, there’s no receptor for GAGs on cells to mediate their uptake specifically. Usually they hitchhike on some other protein that has a specific receptor/co-receptor. Heparin is actually a sulfated polysaccharide, and not like those other drugs that you might be thinking about.
Does this study will answer the question behind the low-GI food trend, which is (as best as I understand the topic) :
"what are the impact of high, medium, low GI food on our health as non diabetic people" ?
Did they track the cohort meals ?
Very interesting! Many people with T1D wonder, when they get a sensor, what a “normal” glucose chart would look like. I’ve never seen a graph for a non diabetic person. I’ve checked the glucose of friends a time or two and it’s consistently been 85, which was good to know.
I mean if you want to go down the path of indiscriminately competitively binding Siglecs, I would read up about how NeuGc (which is found on meats) gets incorporated on our cells. Of course then you might end up in trouble with inflammation/cancer. No silver bullets here!
Siglecs are SUPER important immune receptors that normally antagonise or induce tolerance in the immune system. Normally they recognise different sialic acids (e.g., the same ones recognised by hemaglutinin in influenza) and depending on the health of the cells you can induce different responses in your immune cells.
We’ve done a bit of work in our lab on these receptors, trying to figure out what their natural ligands are. Crazy that the carbon nanotubes are also recognised. I’ll need to check my notes, but I think that the loops that are recognising the nanotubes aren’t where the binding normally is for sialic acids, so it’s all very interesting!
Additional thoughts: I wonder if anyone has tried throwing viral particles or protein pathogens on a carbon nanotube to check for binding. The other Siglecs don’t interact, but hey, maybe we’re lucky and all these pathogen related sialic acid binders happen to have the right residues in place! The SRR bacterial adhesins off the top of my head might be candidates.
Excuse my ignorance, but how are there carbon nanotube recognizing immune receptors? Do the tubes just happen to fit in the receptors because of their size or shape, or is there something about the tubes that trigger the receptors?
The receptors have these floppy loops which are great for bending into the right conformation to recognise different things. It turns out that if they have a few aromatic residues they just happen to recognise carbon nanotubes. It’s unlikely this is something that evolved, and much more just some bad luck in recognising this particular shape.
Something that tickles me about this idea is that, if you think of proteins recognizing these small molecules as lock-and-key (I know that model is outmoded), this is the equivalent of a self-impressioning attack (like the Bic pen attack on cheap tubular locks).
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