National Center for Biotechnology Information

So vitamin D3, endogenous melatonin produced during the day from near-infrared light, these are all things that touch on so many systems in the body.

And it's just so obvious to me, especially if you look at the literature like PubMed, NCBI, Nature, they have all these papers available for people to look at, but people don't, look at it either because they're not really scientifically minded or in the case of medicine, you just have reductionist specialties that are not willing to look at other specialties.

And that's, I think, a large part of the problem too.

You guys know I love my GLP-1s, peptides, HRT, all of it, but none of them replace the foundational things that keep your body strong and resilient in midlife.

Advances in Audio Classification and AI for Respiratory Health in Swine, Biology, 2026, https://doi.org/10.3390/biology15020177.

Monitoring of Respiratory Disease Patterns Using AI and Aggregate Samples: SoundTox Field Study, https://pmc.ncbi.nlm.nih.gov/articles/PMC11512249. Audio-Visual Multimodal Coughing Pig Detection, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11598093. Biosensors in Precision Livestock Farming in Dairy Production, Invited Review, 2026, https://pmc.ncbi.nlm.nih.gov/articles/PMC13089215. Penn State Extension, Precision Livestock Farming: Dairy Technologies, https://extension.psu.edu/precision-livestock-farming-dairy-technologies.

Effects of PLF Notification Mechanisms on Canadian Dairy Farmers, Springer, https://link.springer.com/chapter/10.1007/978-3-031-06371-8_16. IoT Sensors in Dairy Cattle Farming: Adoption Barriers Review, https://pmc.ncbi.nlm.nih.gov/articles/PMC11545371.

Thank you for listening to this HackerNoon story, read by Artificial Intelligence.

It kind of depends on the type of species.

So, you know, some species mammals, for example, there's a lot of genomic information that's readily accessible on NCBI and others share it.

So you have your completed reference genome.

And if you don't have capacity to generate RNA-seq data to use for annotation, you can use publicly available resources on NCBI, or you can just use other annotations of close relatives to kind of annotate your own reference assembly.

So you can certainly do that.

But if it's a species that isn't well studied, for example, we've sequenced a couple of them that are in like the deep Pacific.

So what does success look like? Like when we've done the whole project, what are we going to actually do with these sequences when we have them? And how is that going to be able to inform success? Canadian communities, Canadian research, research globally? You know, we mentioned just now that we can use these sequences to help sequence other organisms, but is there anything else that we can use as a measure of success for this project?

Yeah, so there's a couple different, I guess, ways that we could measure success.

1.3 life-threatening reactions per 1 million vaccines.

vaccination so if we give 44 million more vaccinations we'll have 57 life-threatening reactions per year it doesn't mean that these 57 kids die it means that if they didn't get emergency care at that point they probably or possibly would but those are the severe immediate anaphylactic type reactions what about non-serious reactions well they did some research on that and now they found that 19 percent of people who got vaccinated children got vaccinated had some kind of reaction and this would be something like a fever or nausea or a swelling at the injection site or aches and pains so if we give 44 million more vaccinations we have 8.4 million mild non-serious reactions and this was one study that found the 19 we don't really know because according to this study which was on NCBI on national institute of health as a government site these things are usually not reported people get their vaccine if nothing happens right then and there they go home and if the kid gets a little fussy they don't really worry about it but is it possible that out of these 8.4 million that some percentage might have some residual effect that they don't resolve 100 that there is some down the road problem because of that something unknown I would say that that is very likely so this makes it a judgment call right if you're a high risk group then that might be a good idea but maybe it's not such a good idea across the board another difference we want to be aware of is the way that the body is exposed to the virus which is the vector of entry that normally if you breathe it in or you get it on your skin or you eat it or something then it's going to encounter the virus the pathogen is going to encounter an immune barrier It's going to encounter skin or a mucous membrane or intestinal lining and in the gut it's going to come across GALT.

And GALT stands for gut associated lymphoid tissue.

You have the majority of your immune cells in the gut.

And that That assumption doesn't apply when you think about genomics databases.

So like NCBI's GenBank or RefSeq databases, which many of us use routinely, I think are often thought of as a reference database, as a gold standard.

But there have been numerous publications over the last decade, and they're always improving.

And I have something to say about NCBI.

I'm not trying to throw shade at them.

They're always improving, but there have been a number of issues around the traceability, the quality of the data, mis-annotations, things that have been assigned to the wrong taxonomy.

And as the AI becomes a bigger part of biological research, is there anything that you would like to see change about how we generate and share biological data?

I mean, Yeah, I would say for me, one of the biggest issues around public data...

Like I said, I'm sure there...

I know there are hundreds, but these three that I read through were published by PubMed, ScienceDirect, and the National Center for Biotechnology Information.

There's a mouthful there.

There are hundreds of peer-reviewed studies that link glyphosate to autism, neurological disorders, reproductive harm, liver and kidney damage, poor gut health.

That's a simple multicellular organism.

And this source comes from NCBI data.

You notice here you have tardigrades also.

It's a salt grain, the smallest plant, amoebas.

And for that, you need high quality data.

As, as the saying goes on in AI, like if you put garbage in, garbage out, okay? There are a lot of publicly available data, like we have NCBI and everything, but things are not connected there, okay? There's thousands of genome available in NCBI, but in most of the cases, it's very hard if you, you'll not get those particular, say you have the genome of your organisms, but it'll be hard to get that particular genome, uh, particular organism.

But whether it's A, uh, ATCC or other, uh, biorepository, there you have the physical material, and at the same time we are generating all this data, so you have the data set.

So you just put together and get your results.