 So actually, I'm going to uncharacteristically raise questions and not have any opinions. So I sort of covered the three broad areas of the overview that Laura outlined, really just raising some of the things that I think have emerged during the first year of what is an incredibly successful and enlightening network. I think at its start, I would say that that's something that all of us feel. We've really learned a huge amount from coming together around Bill's leadership and anesthesiast leadership to really build something that I think we all feel could be the way forward, not just for undiagnosed diseases, but for all diseases. And I think if there's any theme that I would take from my involvement, it is that most of the diseases that we look after in clinical medicine are truly undiagnosed if you really look at them carefully enough. There are whole hosts of elements of the data collection that I think are quite interesting. I know actually Bill and Dr. Karshats both brought up the importance of pattern recognition in the initial assessment of the importance of clinical diagnosis. It's interesting that there's very limited structure in the clinical data at the moment. What you realize is most of what we do in medicine is essentially an 18th century aggregate of voodoo and some scattered objective data. And in fact, one of the most interesting things about beginning to implement phenotypes has been just how subjective, even some of the subjective components of phenotyping really are. The whole host of discrete data elements that we try and capture, the ontology, related phenotypes in family members, almost all was a function, the extent of the family history, and a sort of series of intermediate steps where you're relying on other people's ability to document what you think is part of the problem. In fact, one of the things that we found in our site is how important the expertise of the individual taking the family history is in defining whether that family history is relevant or not. Genomics, functional genomics, exposures, another element that was outlined. And one of the key things that I think, as a community, we all believe we're missing, most genes is very tough to imagine how you're ever going to be able to understand the relevance to a disorder if there's even one conditional exposure, which you're not measuring. Most of clinical medicine measures three, maybe four, exposures in a good day with a falling wind. And then at the end, the paucity of gene or pathway-specific biological assays that are actually in clinical utility. One of the first things I know that we did for Anastasia was to list all of the phenotypes that could potentially be built to the NIH. There are 10 to the four phenotypes, if you include absolutely everything, in common use across the US. When you look at 10 to the nine genotypes in the average genome, you realize just how much the information content mismatch is that exists between genomics and clinical medicine. Data interpretation, I think, and other slew of questions there. There are some very distinctive approaches that we use in different parts of medicine and, traditionally, Occam's razor refining to look for the thing that the single most likely explanation. Yet, in fact, when we're looking at many of these cases, we're grasping for a single feature that might give us an inference about which, among a range of candidate genes, might be important. I do think we need to learn from process and we need to begin to think about how to document more precisely each of the nodes in that decision-making process. I think two of the things, again, that have been raised this morning that are really important is how do you establish causality in an individual patient or family? How are we actually going to do that when you don't have the definitive segregation and you don't have a biological assay? And then, similarly, if you're going to do that, you need to be able to do it at a resolution that will actually change management in real time. And then, finally, the last, on this brief slide, the scope of the clinical impact. We're looking at it from the standpoint of the individual patient. All other patients with that specific condition, all other undiagnosed patients may be relevant. Then, ultimately, we should think about how we could extend this to all patients. Couple of very quick points on the organization of the evaluation. When do we do the data collection? How do we organize the clinical input? Do we undertake the assessment in series as a team or through virtual approaches? The timing of the expert clinical evaluation, we found, for example, that it might be very relevant to know which particular pathways you're going to study in the patient when they're admitted or seen as an outpatient so that you can collect the right tissue or tissues for a molecular analysis. And then, ultimately, something we've all struggled with, but I think is really one of the strengths of this consortium is orchestrating the scientific expertise, either the knowledge, medical knowledge around that particular pathway or gene, and then the modeling knowledge that would allow you to move forwards through either in-person evaluations, grand rounds, virtual grand rounds, or crowdsourcing. And then on the last side, some elements for expanding beyond individual sites, traditional exchange, a shared clinical baseline. If we had a barcode for the phenotypes, we could then use that as a screen for everybody on the planet to understand when exactly it would be feasible to or even worthwhile undertaking an exam like this, moving beyond NF1 to phenotype identified pathways, thinking about the phenotypes we bring to the table, thinking about the animal modeling, repurposing or identifying novel therapies, and finally, a semantic framework and potentially infrastructure for all of the above. Thank you, Callum. And our next speaker is Cindy Powell. Cindy is a professor of pediatrics and genetics at the University of North Carolina at Chapel Hill. She's a board-certified clinical geneticist, pediatrician, and genetic counselor. And her interests include dysmorphology, genetic syndromes, and ethical issues of genetic testing and newborn screening. Cindy? Thank you.