 Thanks, Paul. And then our final speaker will be Wendy Chung. So I'm gonna take a somewhat provocative stance but to try and emphasize that I think the UDP needs to skate to where the puck is going to be, not to where it is now. And so when I think back to when Bill started this eight years ago, it was absolutely necessary to have something like this, but increasingly as genomic diagnostics has become, I would say, almost standard of care at least in some of the academic medical centers. I think the UDP or UDN needs to really think about what it can do that adds incremental value beyond what's going on with that. And so in thinking of that, you know, insurance is clearly an issue, but I think many of you know SIGNA already now has guidelines in terms of what is a covered benefit, you know, what indications we'll cover, for instance, exome sequencing. So with that as being the first of the insurance companies to come up with, you know, I think very rational guidelines for this, I think others are going to follow suit within that. And when you see that happening, I think what's going to happen is this now comes out of the center of sort of just even the geneticist or the geneticist at top tier academic medical institutions to geneticists and then to the other providers. So whether they be ophthalmologist, cardiologist, gastroenterologist, increasingly it's going to be, let's get beyond the diagnosis and let's get on to something more interesting than that. The diagnosis is going to be done by the laboratories. It will be done as many as us have seen now within days. So no longer even for instance weeks or months, but within days to do that. And I would venture to say that this is going to be done either in terms of neonates, largely who are symptomatic or presenting with problems, but even back up the bus, it's going to be even done prenatally. And so when you think about that, I think in terms of at least on an exome basis, that's going to be what the standard of care is when it's going to come up time for renewal for this. So what I look to the UDN for is, so what can you do that's even pushing the envelope further than that, right? What are the added things that you can do beyond that? And you have the luxury of being able to now think very creatively and test things out in terms of seeing what the added value is. I don't know the answer to these questions, but as I was sitting here listening today, I was thinking to myself. So what is the added yield that you get from doing the metabolic evaluation? I have no idea. Is it 1%? Is it 10%? But knowing that empirically is what we need to know, right? If you do think about being able to do, because your accessible tissue is blood, at least when I've done these experiments, it adds a little bit, but it doesn't add as much as you'd like because it's not always either the tissue or the developmental time point that you'd like to be able to have. But I don't know the answer. How much does it add when you do that? When you add a genome instead of an exome. If I had to guess, I would guess the yield is going to be about 5% to 10% today over what we can get from an exome. But again, I don't know. You guys have the ability to answer those questions. And I think for those of us in the trenches, we'd like the answer to those questions in terms of knowing what the next steps. What I worry about though is in terms of really increasing the yields, when I look at the cases that I bring in, for instance, if I take familial cases that clearly have a monogenic condition with standard of care exome sequencing, we bat about 50-50, right? So I can tell you, you know, it's because it's clearly to me going to have an answer. We can get the answer about 50% of the time just with a standard clinical exome. If we bring that in and reanalyze it using some of our more sort of pushing the envelope tools and, you know, we'll look at deleterious missent variants or splice variants, we can get another 10%. But we're still, there's a gap that we're missing there, right? So the question is what's going to fill that gap? I would venture to say that it's not going to necessarily be the modest numbers you're going to have from the UDN. It's going to be about scaling this. So we're talking about in terms of reference exomes or genomes to do this, you're getting into the hundreds of thousands. When we get up to those numbers, which will come with precision medicine, with things that are going on internationally for doing this, I would venture to say that's when the yield is going to start increasing, because you're going to start seeing the patterns that you can't by seeing in the ends of ones, but you can see when you start getting to the ends of tens or hundreds to do this. And so I think the question is how can you be prepared to be able to use all of that information in the aggregate that's going to be out there? And what I would look for to NIH is because you can actually leverage the investments that go across your different programs, how can you do that? So between the programs that are the CSER programs, between what you've got in DbGaP, between what you've got in NICHD and INDS, you know, all of your institutes, how can we do that? And as I look to being able to get access, for instance, to some of those data, for instance, and you'll sort of don't bash the messenger, but DbGaP is impossible to be able to get the data from, right? So in terms of being able to do that and make use of the money that you've invested in doing that, that's not a solution, I think, for the field to be able to move that forward. And so what is the answer to that? How can you leverage the investment? You're sinking lots and lots of money in terms of being able to do this, but that yield is going to increase tremendously if people could simply get their hands on the data, still protect patient privacy and being respectful of that, not, you know, sort of jeopardizing that, but being able to increase the yield. And so that's, as I think about it, you know, those are, I think, the opportunities. Then comes the question, as we have already heard about the functional studies, and that clearly, I don't know how to get around it. That's the rate limiting step. I don't know how to scale that besides even with throwing more money at this, but clearly at some point that becomes a big issue. And I would love to see, again, in terms of a community of the basic science researchers, everyone volunteer, you know, be able to get NIH again to leverage your investments in doing that, get your army of researchers that would love to have a human disease to be able to be associated with the gene that they love, be able to actually make that happen. I don't think it's really all that difficult to do, but I do think those are sort of the easy, you know, take the cream off the top in terms of quick wins that you could get in doing the investments. So, thanks.