Ancient building techniques are an excellent subject to explore if one wishes to understand just how advanced our hidden ancestors were. Additionally, it allows one to get a true insight into the contradictions currently upheld by academic institutes the world over. There still exists an extraordinarily diverse array of building techniques. Some, interestingly, appear to overlap even older advanced methods. For example, a stone boring technology, seemingly used upon many ancient monuments, in many cases it appears to have been deliberately used to slightly damage these ancient stones, leaving them etched with uncanny marks, possibly in an attempt to also leave their mark to prove their past existence, later to be realized by us, now laying within their very distant future. We feel that these marks, along with many other aspects of these ancient sites, indicates that many ancient civilizations have been and gone here upon our Earth. Ancient metal clamps used to seat enormous stones, precision machine-cut blocks, some left within quarries, clearly indicating machine manipulation, impossible block building, effortlessly fitting random-sized blocks perfectly together. Yet the most enigmatic of these ancient building features, which many suspect, was indeed somehow connected to the construction of said sites, has to be the protuberances. Rarely mentioned within history books, yet these protuberances are present on many of the most ancient of block structures, which can be found all over the world. No one seems to know what these protuberance were placed upon these structures for. The biggest of these, undoubtedly carved into the still, in situ, regoliths at Yangshan Quarry, a feature we have previously noted and pondered over. Not only do these enigmatic notches suggest a past, world-going, highly advanced civilization having once prospered here upon our planet, but a feature known as the Boss Mark, found deep within the Great Pyramid of Khufu, may link, for the first time, the builders of the Great Pyramids to ancient structures found elsewhere on Earth. Furthermore, the methods used by the pyramid builders are, interestingly, the same methods used by builders of the other sites containing protuberances. This strategic building method, meaning that their ruins have outlived, we feel, many other ancient civilizations now lost to history. Their capability to move such mind-bogglingly huge stone blocks, and their ability to create such erosion-resistant structures, indicate to us that the builders of these sites may have lived an unimaginably long time ago, and probably chose to create such Earth-shifting structures in a bid to indeed survive the eons. Were they doing so in an attempt to leave their legacy on our planet? Or maybe they were, and are, still trying to tell us something. Only time will tell. There are many mysteries to be found within ancient Egypt. Unexplained, seemingly impossible mysteries, which litter the caverns, tunnels, flooded underground layers, and indeed the once inaccessible passageways only recently explored using advanced modern technology. However, some of the most perplexing mysteries lay in plain sight. Not only the great pyramids themselves, an obvious enigma for academia to explain the construction of, but many anomalous features which can be found within objects often leaving academics baffled as to an explanation. The Chiops sarcophagus being one such anomaly. Although these pyramids are entered and explored by millions of people every year, and indeed this mysterious sarcophagus shown to many of these inquisitive explorers, what many of the funded academic tour guide often leaves absent from their explanation of this supposed tomb is how exactly it arrived at its current location. As we have explored and exposed previously, the casing stones that can be found on many of the pyramids are to us not only indicative of another phase of construction work, once having been undertaken upon these structures, but due to the erosion present and the different styles featured, are in fact indicative of more than one attempt to conserve these marvelous structures for future generations. Thus, one must conclude by more than one now extinct advanced civilization. As such, the age of the sarcophagus of Chiops could be immense, so it is not surprising that it has encountered not only grave robbers, but has been vandalized also at points within the distant past. Furthermore, and perhaps most intriguing and frustrating, is that the sarcophagus lid is missing, a lid that could have explained the past contents of this mysterious box, or like the Tomb of Pakal, exposed extremely controversial illustrations of possible past technologies. Unfortunately, however, or rather most conveniently for academics, this lid has never been discovered. Yet what is most perplexing regarding this diorite box, notably one of the hardest workable stones on earth, is that no one seems to know how the original builders managed to transport the box to its current location deep within the bowels of Chiops. The diameter of this supposed tomb being too large to have traveled down any of the known tunnels, which have so far been discovered within the ancient pyramid. This leaves us with two likely possibilities. One, that the diorite box was placed there, and the pyramid built around it, which is a mysterious and confusing hypothesis, mostly due to the lack of markings of significance found upon the sarcophagus, or indeed the lack of any dedicated markings found anywhere else surrounding it. It is as though the box was placed there without much effort to indicate any importance to its existence. Yet, to cut such a box, which has since been discovered to have been cast from one single block of diorite, would have taken tremendous effort, a feat that modern man would only accomplish with the use of diamond-edged power tools, not to mention the effort that would have been involved in moving this multi-ton stone into its found location. The second hypothesis regarding how this sarcophagus found its way into its current location is that the box itself was transported to its found location through tunnels and passageways we are yet to discover, possibly hinting at the fact that within this great pyramid there are indeed many more hidden layers and cavities we are yet to explore or discover. Maybe the placement of this seemingly inanimate box was placed there to suggest exactly this. Furthermore, what was on the lid of this supposed sarcophagus? Why is it known as the sarcophagus of Kufu, when Kufu was not discovered within it? In fact, nothing was discovered within it. And why is the lid mysteriously absent? Where did the lid to the sarcophagus go? Why, if destroyed by grave robbers, was it not left where it lay? Did this lid contain controversial information, possibly pertaining to the original contents or indeed purpose of the great pyramids? We find the diorite sarcophagus of Kufu and indeed its unexplainable journey into the center of the pyramid, highly compelling. During the past few years we have covered many aspects of Mankuri, Kafra, and Kufu, the three great pyramids of Giza. We have explored numerous amazing facts regarding these structures which have remained secret for many years. As the interest has grown regarding these three amazing structures, more people with suspicions, hypothesis, and technical and intellectual talents are fortunately beginning to approach these mysterious and wonderful structures in more explorative ways. We are experiencing the beginning of an ancient Egyptian renaissance thanks to the gift of modern technology. At the beginning of this year, an international team of researchers began investigating the buildings from afar, gazing at them with unusual cameras. Using state-of-the-art infrared heat detection technology, they have discovered some surprising anomalies regarding the heat signatures visible on their faces. What these thermal anomalies reveal are undiscovered shafts, more than likely leading to additional and undiscovered secret tombs deep within these amazing pyramids. The thermal scanning that they have successfully completed has revealed that there are many of these temperature fluctuations in many areas undocumented as containing anomalies. Thus, what the team has done is pinpoint unexplored shafts dotted across the pyramids. The team also found a particularly impressive anomalous signature located on the eastern side of the Khufu pyramid, very close to ground level. From the beginning, the team had always maintained that they would publicly disclose their findings. All of the staggering finds were made public by Antiquities Minister Mamdoul El-Damati. During a press briefing, quote, there is something like a small passage in the ground that you can see leading up to the pyramid's ground, reaching an area with a different temperature. What will be behind it? said El-Damati. The scanning was done throughout a 24-hour period, allowing the researchers to monitor subtle temperature changes as the pyramids heated up and then cooled down during the day and night. Though the huge granite and limestone blocks which make up most of the pyramid, this technology was capable of recognizing the slight differentials in their temperature. By monitoring the speed of this heating and cooling, thanks to these miraculous cameras, the researchers were able to isolate several persistent anomalies. Thus, they may have just unlocked more of the pyramid's secrets in one day, using state-of-the-art technology than Egyptian antiquities or archaeologists worldwide have in more than 100 years. While the difference in temperature between most adjacent limestone blocks was between 0.1 to 0.5 degrees Celsius, the largest of heat anomalies discovered on and within the Great Pyramid was an impressive 6 degrees warmer than the surrounding bricks. So far, there are plenty of theories being put forward as to what these heat anomalies might indicate. Not surprisingly, with the leading assumptions being that of just empty areas, a hypothesis I'm sure some would like to make a reality. The good news is that the study, which is called Operation Scan Pyramids, will continue. Next, the researchers intend to use cosmic particles called radiographic muons to create a 3D reconstruction of the Pyramids of Giza in an attempt to map all the secret chambers and passageways within the Pyramids.  No other ruins anywhere on our planet is surrounded with more controversy than that of the Great Pyramids of Egypt, or indeed its accompanying plateau. There are many factors to consider when it comes to Egyptology. In academic fields, there are many no-go areas of study. Although hard work and research within permitted areas has taught us a great deal about the previous 4,000 years of the site's inhabitants, yet regardless of the most astute academic thesis, there remains three proverbially large elephants in the room. When it comes to a full or even a mere fraction of an explanation in regards to the origin of these seemingly impossibly huge Pyramids remains patiently absent. No accounts, illustrations of any kind from the era exists. It is simply illogical, especially when one considers the sheer feet these structures must have been. We have presented many previous features, polygonal masonry being present on the Pyramids. They eroded yet younger casing stones protecting inner megaliths, clearly of a tremendous age. Salt sediment found encrusting the lower chambers, and so on, suggesting not only that the Pyramids are much older than currently claimed, but were pre-flood ruins. Thus, questions arise. Just how old are the Great Pyramids? In addition to our study of the Pyramids, we have also, in the past, asserted that the Sphinx was originally a lion, which interestingly correlates to the following hypothesis with fascinating accuracy. The Orion Theory The coincidence with Pyramids aligned with Orion's belt and other significant constellational positions, Baval and Hancock support the theory believing the Great Sphinx was begun in 10,500 BC, creating reference to the constellation of Leo and the orientation of the entire complex with the Nile River and even Milky Way, claimed by them as connected respectively. Zeptepe, using similar methodology, put the age at over 13,000 years. These are clearly astonishing proposals, but the current paradigm for their chronology, we feel, is far too short a time span, and due to our own research, which has uncovered evidence indicative of pre-flood origins, copper tools for such an accomplishment a mere insult to intelligence. Yet thankfully, due to these various takes on events, their age remains highly contested, and to us, a mystery, which is incredibly compelling. One of the most enigmatic, mysterious, and least understood ancient structures to be found anywhere on Earth. Although many academic institutions and funded individuals throughout the years have maintained that these structures were tomb sites built for ancient Egypt's greatest leaders, the severe lack of evidence supporting such claims, along with the lack of any hieroglyphic recording of the enormous undertaking that these structures would have been, contradicts this explanation. Particularly Cheops, the largest of the three Great Pyramids, and the only one constructed to in fact have eight sides. The only one with tunnels, the only one with shafts, most notably the shaft which led to Gatton Brink's door, long thought to have been air shaft, due to its steep incline and minuscule scale. And although it is the only one to possess such features, they were installed perfectly. These tiny shafts were not only perfectly aligned throughout the structure's internal stonework, built with unimaginable skill and accuracy. But these were somehow hermetically sealed during the Pyramids' original construction. This would have been required to avoid them becoming blocked with dust, with the exterior shape of the Pyramids, built with such astounding precision. The subtle indent creating the eight sides is so slight, it is only visibly detectable under certain light angles, often requiring modern technology to actually measure the perfection these ancient feats were. As mentioned, Gatton Brink's door, leading from the King's chamber, was for many years assumed to be an air tunnel. However, after attempting to inspect the shaft with an intention to consider utilizing the structure's own design to aid in fresh air circulation, it was realized that this shaft led instead to a blocking door, the doorway to an undiscovered chamber within the bowels of this most mysterious of ancient remnants. However, after several years of apparent reluctance to explore this hidden chamber, along with the mammoth challenge Gatton Brink encountered attempting to develop a robot capable of reaching the blocking door, capable of traversing the obstacles within the shaft to eventually penetrate this inner sanctum. As the discovery came to its ultimate culmination of actually seeing what was hidden behind this door, within this hidden chamber, a shaft deliberately designed to be near impossible to discover without modern technology, thus clearly a room of great importance. The media was blocked, a blackout descended upon the Giza Plateau, and the investigations remained guarded for a considerable amount of time. When it was eventually opened up to the world, the supposed tomb found in situ within the chamber was conveniently empty, without any distinguishing evidence to suggest the chamber's past function. Many people would be forgiven to suspect a conspiracy ensued, one in an attempt to conceal whatever was found in the supposed tomb of Osiris. What are the Egyptian authorities and even other influential countries' governments concealing regarding this mysterious chamber? Thankfully, it seems that this was not the last chamber to ever be realized. Two more chambers have now been discovered to still be buried, hidden, within this great pyramid. One which is located above the Grand Gallery is said to be of a significant size. The question is, what could be hidden in these two remaining rooms? Will advancements in penetrative radar allow its true contents to be revealed to the world before the Egyptian government have the chance to hide its contents? These are astonishing ancient structures, undoubtedly one of the most incredible wonders on earth. As such, they are highly compelling.


The narcissist wants to be you. I have never seen anyone talk about this topic, but this is definitely something that I have noticed in my own experiences, where the narcissist has tried to be more like me. When the narcissist first meets you, they are in awe of your qualities, abilities and talents. They admire them. They are amazed with everything that you are.  In my own experiences, I noticed that narcissists would try to become more like me. They would engage in the same interests and activities that I enjoyed. They would like the same cars or clothes. They would take an interest in veganism. They would listen to the same music to the point where it almost became an obsession. But this is just what narcissists do. This is what a narcissist is. At a young age, they accepted that who they really were was not enough. They abandoned their true self and created a false self who is everything they wish they could be. This false self is constantly changing. It is always adapting to whoever it is around or whatever environment it is in. Whatever will make them appeal to those around them because all they are really looking for is attention and admiration. Narcistics apply. They want to feel like they are worth something. They want to feel like they are enough. And when they look at us, we look pretty appealing. They like what we're about. So they desire to be more like us. They feel like what they're doing isn't really working. It isn't getting them the supply that they need. So they begin to mimic us. They become an imitation. They observe what we are doing. And then they try to replicate it. But it isn't real. And it was never what they were really about. They've just imitated us in an attempt to get the attention and admiration that we receive. But by doing that they have then abandoned their own identity. They have lost who they really were. And now they're nothing more than a second right version of who you are.  You're the original. They're just trying to be you. And by doing that they end up losing who they really are. Which is where their true power was anyway. But by trying to be you they have lost their true power. And now their survival depends on to get attention and admiration from the people around them. By trying to be a second right version of you. And this isn't just something we're seeing in narcissists. This is so common these days. So many children these days lose their identities at a very young age from watching their favourite celebrities. Whether it's Kylie Jenner or Justin Bieber. They want to be more like them because they see that they're getting a lot of attention. And maybe these children never got the love and attention that they needed from their parents. And maybe that's why they felt the need to become more like a celebrity instead of being who they really are. You've only got to look on social media to see that everyone is just an imitation of someone else that they admire. They're not really being themselves. And they may think that it's working for them. They may think that they're getting more friends. They're getting attention from the opposite sex. But none of those people really know who you are. Because even you don't know who you are anymore. When you've abandoned who you really are to become an imitation of someone else. It's just fake attention. Fake admiration. Because it has nothing to do with the true character and personality. But that's just how it is these days. There's no value in authenticity. It's all about how many likes you can get. It's all about the attention and admiration. People will even go into the knife. Just become more like a celebrity they admire. Because they really see no value in who they are. They believe that they're not good enough. So they try to imitate someone else. Because they think that will get the attention and admiration they need it. But even then no one's really admiring them. They're just admiring who they think they are. So it's all fake.  Every friendship, every relationship is built on a house of cards. Which means that it could collapse at any moment. Because it isn't real or genuine. It's built on lies and fabrications. It has no foundation. It has no underlying basis or principle. It has no real meaning or purpose. Other than someone just trying to use a situation to get what they want.  Which is very narcissistic. And can only result in failure in the end. Because it was never real or genuine. It was built on lies and fabrications. If you want to build something real and genuine it has to be generated from within. Your worth has to come from within. You have to believe in yourself before you expect anyone to believe in you. You can learn from other people. You can let them inspire you. But you cannot be someone else. And you shouldn't try to be either. You were put on this earth to be you. And that's where your true power is.  You just have to realize it. And not listen to anyone else who tells you otherwise. Because anyone who tries to make you believe that you're not enough hasn't realized their own power. And you may not see it. But they're probably trying to be someone else. Because they believe that they're not enough. You have to be real with people. You have to present who you really are and what you're really about. Some will resonate with you. Some won't. That's life. But it does not mean that something is wrong with you. You cannot please everyone. And you shouldn't try to. All you can be is who you are. And you shouldn't try to be anyone else. If someone doesn't accept you as you are then maybe that friendship or relationship just isn't meant to be. But it does not mean that you need to change who you are or what you're about just to please them. You should only change yourself if it's something that you want to do. If it's something that truly resonates with you it has to come from within. Or it will never be a permanent change. It will just be something that only exists on the surface. Because it's not something you're really about. It's not something that really resonates with you. In this life we can only be ourselves. You can try to be someone else but you will never succeed. And people can try to turn you into someone else on their own agenda. But they will never succeed either. So while the narcissist may want to be you they will never be you. They will only be a second rate version of you. It's superficial. There is no underlying support or foundation. So it will crack under pressure. It will never last. It will never withstand the storms of life. And it will only result in disaster in the end.


We got off to a great start. We're defensively minded. We came out, we made shots, but we left it to the defense and that made our plays on offense. We'll speak on that defense. You guys are able to hold them down to 40% shooting for the game. What was the key there? Scout report. Can't eat those guys. They do their work. They put it up for us to go out there and execute it. We did a great job tonight. Talked about your improvement in the off-season headed into this year. We talked about it with Keras. New guys on this team. Deeper roster. How dangerous can you guys be? Man, it's too early to tell. But like I said in the pre-season, guys gotten better. Guys have that business-like approach. More prepared for playing and winning more. And guys want to see other guys do well as well. So we're all in as a team. Thanks a lot.


Good afternoon, this is Dr. Jean Jenkins and welcome to our second webinar in the JNS series of presentations about the articles that you can find in the new genomic special issue published online, February 1st. We're very excited to have Yvette Conley talking with us about current and emerging technology, which is in genomics today. You have the opportunity to post questions, and those will be addressed at the end of the session. You are on mute, but you can also raise your hand and comment by way of typing in. We will be recording the session, and we will now start the recording. Also if you are representing more than just yourself in attending today, could you please note for our records by typing in how many people are actually in your room or working with you as part of listening to this webinar. And just a reminder that our next webinar will be March 5th. It will be a dual webinar from 3.30 to 4.30 with two topics, one by Dr. Xiufen Wang on cardiovascular genomics, and the other an overview of the genomics and metabolic syndrome by Anne Cashin, Jackie Taylor, and their colleagues who were also involved with writing the paper. So thank you so very much. I'm going to turn over the introduction to Dr. Kathleen Calzum. Well, good afternoon, everyone. We're delighted to have Dr. Yvette Conley speaking to you this afternoon. She has her master's in genetic counseling and a PhD in German genetics, both of them from the university to be her. And she's a tenured faculty member and associate professor with a primary appointment in the School of Nursing, as well as a secondary appointment in the Department of Human Genetics, all at the University of Pittsburgh. She's been managing and directing molecular genetic laboratories for over 20 years and is fully equipped to, and has a fully equipped laboratory that's actually in the School of Nursing that's focused on molecular genomics. Her research has focused on using a variety of genomic approaches to understand the biologic basis underlying variability in patient outcomes. She's had funding from the National Institutes of Health, the Department of Defense, the Alzheimer Association, and the Oncology Nursing Society. She's also director of an NINR-funded T32 titled Targeted Research and Academic Training of Nurses in Genomics, and continues to be a primary faculty member for the National Institute of Nursing Research Summer Genetics Institute. And she's a standing member of the NIH Nursing and Related Clinical Sciences Studies subsection. So there's really no one who's sort of more uniquely positioned to speak to technology and how it applies to genomics and its application for nursing practice. So we're delighted to welcome Dr. Connolly. Okay, thank you very much. I want to start off by thanking all of the attendees and also thanking my co-authors who's on behalf I'm presenting today. And the co-authors include Leslie B. Beesacker and Stephen Clesalves from the National Human Genome Research Institute, Carrie Merkel from the University of Arizona, Maggie Kirk from the University of Glamorgan in the U.K., and Brad Lizarat at the University of California, San Francisco, are my esteemed co-authors and without whom I would not be able to talk about all of these things. So let's move ahead. I'll tell you a little bit about what I'm hoping to talk about during the webcast. So I want to briefly discuss the approaches that are introduced in the manuscript. So those being genome sequencing, genome-wide association studies, epigenomics, and gene expression profiling. Now I do want to point out that I'm not going to be covering details on how to conduct these types of studies or the various platforms that you can use to conduct these types of studies. I think we just don't have time to cover all of those things, but the information I'm going to provide is more about how these approaches are emerging and being utilized and increasing in utilization for both research and clinical applications. So don't worry, we've provided in the paper and I'm going to address some of these towards the end of the talk. We included a lot of online resources in the paper to assist with some of this information. I'm also going to address implications for nursing practice and research, and then I will, time permitting, take you guys to some of the databases and resources that are out there online. And then we'll have a question and answer session. So as far as genome sequencing is concerned, what we're interested in with sequencing in general is we're interested in determining the order of nucleotides. So with that, the order of G's, A's, T's, and C's in the DNA. So in the past, sequencing has been around for a long time. In the past, what we did was we did sequencing. We figured out the order of G's, A's, T's, and C's for a very focused piece of DNA.  And then we had technology to help you focus in on that particular spot in the DNA that you wanted to sequence. And you would collect that data, that focused data, one base at a time using methodology that gave you one base at a time information data collection. That's all changed. Now I have to say those old school methods of collecting, sequencing data, one base at a time, and focusing in on a particular piece of DNA that is still useful today. But now we do have, through advancement of technology, the ability to sequence many pieces of DNA simultaneously at the same time, so to collect these data in parallel. And it's also possible to not have to focus on a particular piece of DNA anymore. You can actually look across the entire genome and sequence the genome now. Now this idea of in parallel sequencing many pieces of DNA at the same time is referred to as next generation sequencing or massively parallel sequencing. Those are equally correct terminologies to use and a lot of folks will say next gen sequencing. And what they're referring to is the ability to collect DNA with this higher throughput technology that collects sequences, many pieces of DNA at a time. So as you could imagine, having the ability to actually look at greater sequencing coverage and to the extent that you could look at the whole genome from a sequencing point of view. And you can do this in a lot less time and simultaneously the cost of doing this has come down. It makes genome sequencing way more appealing for research and clinical utility. So it is something that's out there being used and it is on the forefront of being adopted by a lot of research and a lot of folks doing clinical research and then looking to translate that research to clinical applicability. We'll talk a little bit more about that. So whole genome sequencing basically is you're sequencing the entire genome. Now, there could be gaps in what you're able to collect from a data collection point of view, but for the most part you're capturing the sequence of the entire genome. Whole exome sequencing, so an exome is that piece of the gene that goes into the coding, that's the coding region of the gene.  And so we also have the ability to sequence the whole exome of the genome. So you're not doing the whole genome, but what you're doing is you're focusing in on the exome, which represents about 1% of the genome, but is likely to contain about 85% of the variability that influences the phenotypes that we're interested in to get a lot of bang for your buck out of whole genome sequencing. You're only sequencing about 1% of the genome, so it's a little bit quicker to do and a lot less expensive than whole genome sequencing, but you're capturing a lot of usable data. So why would one even want to entertain doing a genome sequence? Well if you take a step back and think about what your areas of interest are, probably the phenotypes or the traits or the conditions that you're interested in are not single gene conditions. These are probably conditions where there's multiple genes involved, maybe even gene environment interaction, and you would like to be able to look across all genes or regulatory regions of the genome, and you would like to know a little bit more about how that genome, the variability that that genome holds for telling you about your phenotype of interest. And because a lot of the conditions of high public health importance are going to be conditions where there's more than one gene, more than one variation in the genome that is impacting that condition, genome sequencing becomes very appealing. So one real advantage to genome sequencing is that it captures rare as well as common variation. So as far as changes to our DNA that can impact our health, there are, you know, there's a lot of folks out there who believe it's rare variation that's going to be what tells us, you know, the most about our phenotypes of interest. There are folks who believe that it's going to be common variation. There's a lot of us who believe it's probably a mix of both, but genome sequencing satisfies both camps of thought because you actually will capture all of the variability in someone's genome by doing the genome sequencing. So you can see where there would be appeal to that. So it's a very powerful approach. This is something that is, you know, very much if you can do it gold standard. You're getting the DNA sequence of an entire genome of an individual. So a couple of things that folks conducting research, folks who are looking at the research for potential clinical utility, and folks that might be using this down the road for clinical utility, some things that you need to keep in mind is that it is an error-free. And as the technology advances and as we start collecting more data and as we start to get better at managing the data, collecting the data and viewing the data, we'll probably have error rates go down. But right now, the average error rates for next gen sequencing is about a half a percent to two percent. So there's a lot of call in the genomics community for labs who are reporting this sort of data, this genome sequencing data, or exome sequencing data that you need to when you're doing these reports, you need to say what genes or what exons or what regions of the genome that were not adequately assessed while you were collecting those data. And that could be because you didn't get any data from a particular piece of DNA or you got data, but the quality just wasn't high enough for you to feel comfortable with that. The people who are getting the report on the other end need to know that that's something that came out of your laboratory. The other thing is the genomics community is calling for, because this is a newer technology. And anytime there's a newer technology, comparing that to our more traditional technology that's been validated is something that we try to do for a while until we feel more comfortable with the newer technology. So there is a push out there for anything that you find with next gen sequencing that it's a good idea to validate those findings with a more traditional method to validate those findings. The other thing that I wanted to make sure we brought up was the idea of incidental findings. And this is a pretty hot area in genomics right now. It's an ethical, legal, and social issue that has come up in the genomics community. And you can imagine how you set out to look at someone's genome. And you're looking for variation that's involved with your phenotype of interest. Because you're going to get a lot more information about that person's genome than what impacts your phenotype of interest. What if you were to find variation not involved with your phenotype of interest, but that has clinical importance not related to your phenotype? What do you do? When you uncover that information, what do you do? What are your obligations to the participant, the person whose genome you're looking at? And this is a very hot area right now. Over the past year, genetics in medicine has produced quite a few papers on this topic. And genetics in medicine is a product of the American College of Medical Genetics and Genomics. So I would bring you out to look at some of those articles about the topic. And they've even coined another ome. There's lots of omes and lots of omex out there. But the incident ome is basically the genome, the information that you find out about an individual by looking at their genome sequence. But it's stuff that you weren't expecting to find. And what are researchers supposed to do when they find an incidental finding that has potential clinical importance? But the samples that they're using are de-identified. The samples that they're using are from a biobank. The samples that they're using, those subjects were not consented to go back and give information to them. It's really raising a lot of interesting dilemmas. Because once again, what's happened in the genomic community is our ability to look at the genome, characterize the genome, our technology, to do all these things far surpasses and is far ahead of what we deal with, the massive amounts of data that we have. And so I think that once again, technology is much further ahead than what we can deal with when we're talking about doling out findings to folks. So very common issue right now that we're dealing with. And I would recommend that you look at some of those manuscripts that have been published in Genetics and Medicine. OK, so genome-wide association studies, or GWAS, as it's affectionately known. So this has, this is an approach that's been around a lot longer. You may have heard more about it. So genome-wide basically meaning that you're collecting genotype data for polymorphisms that span the entire genome. So up and down, every chromosome are polymorphisms that are spaced on that chromosome. And you collect genotype data for each of those polymorphisms that span the genome. You then take those data and you analyze it statistically using an association approach. So by association, this is no different than statistical associations that you would look for in data that isn't genetic data. So you're looking for a relationship between two variables that make them statistically dependent. Now in this case, it's your allele or your genotype of interest and your phenotype of interest. So you're looking to compare what someone's genetic material looks like to your phenotype and seeing if there's a relationship. So at the very basic level, what you could do and what people do do is they will analyze each polymorphism to see if there's an association with their phenotype of interest. And what you do is you run a multitude of simple association tests. Now we do have more sophisticated analyses that are available to us. For example, there are ways to look at gene-gene interactions so you can look to see not only is this particular allele or this particular genotype in this gene associated, but in reality it's an allele in this gene and an allele in that gene and an allele in this gene. And when I look at them in an additive way, I'm actually seeing that there are interactions between those genes and I have a strong association. So it's a little bit more sophisticated. Pathway analyses where you take genes that are known to interact with one another in a biological pathway and you look to see do those genes synergistically together have an association with your phenotype of interest. And so those are some very robust ways of looking at GWAS data. So the types of polymorphisms that are used most often in a GWAS are your single nucleotide polymorphisms. And most people today who are conducting GWAS experiments, they are collecting data on anywhere from about a half a million SNPs to about 2 million SNPs. So the reason why a GWAS works is this idea of linkage disequilibrium. So it turns out that if you think about how you get your genetic material from your biological parents, you do not get that material one base at a time. You get your genetic material in chunks called chromosomes. Now, it's true that when your biological parents made gametes, there was recombination and reshuffling amongst those chromosomes that they have. But once they donated that genetic material, then that material was inherited as a chunk. And so these chunks or blocks of linkage disequilibrium are very helpful to us. It turns out that let's say there's 300 polymorphisms in a particular chunk of DNA, a particular block of linkage disequilibrium within our DNA. And if you were to genotype all 300 of those polymorphisms, you would find that if you had genotype just one of those polymorphisms, you probably could have predicted the genotypes for almost all of those other 299 polymorphisms in that chunk of DNA. So it turns out, luckily for us, that we just look at one highly informative polymorphism in that chunk, in that block of DNA. And those are the SNPs that are then chosen for a GWAS. And so when you talk about a half a million or two million SNPs up and down all the chromosomes, those don't represent all the polymorphisms in the genome, but it represents a subset that help us capture the majority of the variability in the genome. And so you're looking for association with a chunk of DNA when you do a GWAS analysis. Now the most common design is a case control study. And so you could think of this like any old case control study, you have people with a particular phenotype of interest compared to a group of folks without that phenotype of interest. And you look to see, do those two groups differ significantly based on allele or genotype or haplotype frequencies for any of these polymorphisms? So the biggest advantage to a GWAS is that it gives the investigator a nonparametric way of evaluating the genotype-phenotype connection for that phenotype. So what I mean by this is you have all these polymorphisms that are up and down every chromosome. You then collect the data for those polymorphisms. You take that data, you analyze it, and you look to see what SNPs or what chunks of DNA look to be associated with my phenotype of interest. And only then do you look at, OK, well, this one is significantly associated. Let me see where in the genome this polymorphism that I have an association with. Let me see where that's hanging out. And if it's hanging out in the gene, then you can look and see, OK, well, what gene is that hanging out in? Sometimes you're going to say, oh, that's a very logical gene. But a lot of times, and the benefit here is it could be a gene or set of genes that you weren't even thinking about would be associated with your phenotype of interest. So that's what I mean by big advantages is you collect the data and you let the data tell you what might be interesting from a biological point of view for your phenotype of interest. And that's a huge advantage when you think about the fact that most of us, the phenotypes that we're interested in, we'd be fooling ourselves if we tried to say that we understood everything about that phenotype. So this gives us a way to circumvent the fact that we may not have all the knowledge that we need to a priori say what genes we would look at. We're just going to look at them all and let the data tell us what looks interesting. So that's a big advantage of a GWAS. So some considerations and potential drawbacks. So it does require a large number of subjects to conduct these studies. So if you think back to when I said folks are looking at a half a million SNPs, two million SNPs, you might be thinking to yourself, wow, that's a lot of data. And that would be very true. So multiple testing is an issue when you're looking at that many variables. And so you need to look at large numbers of subjects to offset the fact that you're going to have to correct for multiple testing if you're going to conduct these types of studies for the most part. And that large sample set requirement does turn some people off from doing this approach. The other thing is there are some phenotypes where you would really struggle to get large numbers of subjects. And by large numbers, I'm thinking most folks are saying you're anywhere between 1,000 to 2,000 cases compared to 1,000 to 2,000 controls. But the larger the better. You could think of some phenotypes where you would really struggle, and maybe over the course of your lifetime, maybe not be able to collect all those subjects. But then there are some phenotypes that are amenable. And this is why I see a lot of consortiums popping up for GWAS studies because people need to pool their resources. They need to pool their subjects in order to do some of these more non-parametric approaches. The focus is on common variants. So unlike the whole genome sequencing where you're going to capture rare and common variants when you do a GWAS by design, you are collecting data on common variants. But one thing that I do want to point out is when you have an association with a chunk of DNA that's in linkage disequilibrium with your polymorphism that you have an association with, be mindful that that chunk of DNA could house a rare variant. And what's happening is you have an association with this common variant, but it's a surrogate for a more rare variant that's hanging out in that block of DNA. It is an association. So sometimes you have to remind folks that an association is not mechanism. And so when you have association, you need to be mindful you have an association with a chunk of DNA, which may actually have an association with a surrogate marker for something else that's going on in that chunk of DNA. And so your work really isn't done. You need to characterize that chunk of DNA or chunks of DNA a little bit better. And you may need to figure out, well, what's the function of the variability that I'm seeing in that chunk of DNA if you're going to get a little bit closer to mechanism? But a lot of times when we talk about conducting candidate gene investigations, a lot of times the data that goes into what candidate genes you investigate, a lot of times that data comes from a GWAS and the data pointed to some very high priority candidates for us to look at for a particular phenotype. So gene expression profiling. So again, gene expression profiling been around for a while. And the whole basis of gene expression profiling is based on the fact that in every gene, I'm sorry, in every cell of your body, you have all the same genes represented. So every somatic cell in your body, whether it came from lung, whether it came from skin, whether it came from the lining of your mouth, whether it came from the lining of your gut, doesn't matter. If we took those cells and extracted DNA, every gene is represented in those cells. But not every gene is needed in every cell. And so not every gene is expressed in every cell. And so what we do with gene expression profiling is we actually look to see can we characterize what genes are actively expressed in a particular cell, a particular tissue of interest. Now why would that be interesting? Well, if you think about comparing genes that are differentially expressed between two different phenotypes of interest, that could tell you a lot about the underlying, the biology of the underlying phenotype. So what differentially expressed genes are there that you can characterize that can tell the difference between your phenotypes of interest could be clinically useful. So an example, so if you had a phenotype of interest, you could look at tissue from an individual that has the condition compared to that same tissue in an individual that doesn't have the condition. You compare the gene expression profiles from those tissues and genes that are up-regulated or down-regulated, differentially between the two, it's gonna say a lot about what might be, what concert of gene regulation might be going on that's leading to your phenotype of interest. For example, you could even look at the cellular level even within an individual. For example, you could compare healthy tissue within an individual to unhealthy tissue, so tumor tissue. So what genes are up or down-regulated in tumor tissue versus normal margin? And you could capture a lot of information about that tumor by looking at what genes are up or down-regulated. Now we actually exploit this gene expression profiling clinically already, and while I don't want to talk about a lot of different commercially available assays and things like that, suffice it to say that there are gene expression profiling arrays that are being used clinically. One particular example for risk stratification, for prognostication, for tailored intervention, a really good example is in breast cancer where a woman who has presented with breast cancer, her abnormal cells involved with her breast cancer, those are taken and clinically characterized using gene expression profiles. And being able to say what genes are up or down-regulated in that woman's tumor tells us a lot about what type of breast cancer she has. Breast cancer is very heterogeneous. So what type of breast cancer does she have? What is her potential prognosis? What therapy? What type of chemo or other adjuvant therapy might work best for that individual with breast cancer based on the biology of her tumor? We are already doing this. This is already being done clinically. For those of you who are involved in oncology, you're well aware that we are using gene expression profiling, not just in research to figure out what genes are important to what cancers, but we're actually using them clinically to make some very important decisions for these patients. So gene expression profiling relies on RNA. So the sequencing that I talked about, GWAS that I talked about, in those situations we are looking at the bases of the DNA. Here we're looking at RNA. So, and when you're talking about looking at RNA, you can look at a particular type of RNA from a particular candidate gene, or like a GWAS, you could actually look at the level of gene expression for every gene across the genome. And what you can do there is you can actually, at the most basic level, do what you did with a GWAS. You could look at every piece of data that's generated across the genome for gene expression. And you could look at each piece of data. You could say, okay, I'm looking at this level of expression for this particular piece of RNA, and I'm looking to see if it's associated with my phenotype of interest. And again, if it is, then because you looked at it, you looked at all the genes, you looked at it from a whole genome point of view, a nonparametric point of view. You might see expression of genes that are up or down regulated from that whole genome approach that you expected to be altered in its expression. Or you might find some novel genes or novel pathways of genes that you wouldn't have expected to be involved with your phenotype of interest. So that's, again, one of the benefits of the nonparametric evaluation. And just like GWAS, you can look at those individual pieces of data for gene expression, or you could look at how genes might, expression of one gene or a whole host of genes taken together might impact your phenotype of interest. So a couple of other things that I wanted to point out that are emerging. MicroRNAs are becoming very, we're learning more about them. We don't claim to know everything about them at this point in time. But they're very interesting. They are definitely involved in gene regulation. Not so much involved with, like messenger RNAs are with taking that template and translating it into a protein. These RNAs are not involved with making protein. They're involved with gene regulation. And what they are is small pieces of RNA that are transcribed and they are the antisense to messenger RNA for another gene. And the antisense RNA from the microRNA hooks up with the messenger RNA from that other gene and basically prevents it from being translated into a protein. So you can imagine how these microRNAs are impacting gene regulation. It's another level of gene regulation that you can assess. Now what's interesting is if you do these whole genome gene expression data collections, a lot of the standard platforms and technologies that are out there now for you to do the whole genome expression evaluation includes most of the microRNAs that we know about. You'll simultaneously not only evaluate expression of annotated genes, but you'll also evaluate expression of these microRNAs also. So again, lots of advantages to doing a whole genome expression. Couple of things that I did wanna point out because we're talking about RNA here not DNA. So things that you have to be mindful of when you are conducting this type of research or when you're evaluating publications of this type of data. And when you're thinking about clinical utility of this data, DNA is very hardy, extremely hardy. RNA is not. So folks who are working with RNA need to stabilize, appropriately stabilize their RNA. That's an important factor to consider because if you are looking at a publication and you're not, you don't feel confident that they stabilize their RNA, then you have to call on the question, how valid are their findings and then how applicable are those findings ever gonna be to the clinic? Other issues with gene expression. So gene expression differs across tissues. So if you remember what I said, take a lung cell, you take a kidney cell, you take a gut cell, take a skin cell, those genes are all there. The polymorphisms are gonna be the same amongst those cells. But what isn't going to be the same is gene expression. So when you're talking about doing a gene expression profile or you're talking about doing research, using gene expression, you need to give a lot of thought to what tissue is most appropriate for your phenotype of interest and that you are comparing apples to apples when you're comparing tissues because you can't necessarily compare a lung tissue to kidney tissue with gene expression because just because they have different jobs to do, they're gonna have different genes expressed. So you have to be mindful that there's gonna be variability from tissue to tissue. The other interesting thing about RNA that is distinct from DNA is that it is dynamic. Gene expression is gonna change. It's gonna change in response to exposures. It's gonna change in response to, there are temporal changes to gene expression. There are genes that are expressed in early development that are shut off and no longer needed in the adult. So there are a lot of changes in gene expression. It's very dynamic, which is not something that we see when we're looking at the basis of the DNA. So these are things that need to be taken into account when you're either conducting a RNA-based or gene expression-based study or evaluating those types of studies out there in the literature. Okay, so a little bit about epigenomics. So our sequencing and our GWAS, we were interested in DNA. Our gene expression, we were interested in RNA. With epigenomics, for the most part, we're back to looking at the DNA. So epigenomics is different. When you get back to the DNA for epigenomics, you're not interested in the basis, like you were with sequencing and GWAS. We're not interested in what the GSAs, order of GSAs, Ts, and Cs are. We're not interested necessarily with the polymorphisms that are there. What we are interested in is how that DNA is chemically modified or packaged. Now the chemical modifications and packaging impact whether or not a gene is expressed. So when we talk about gene expression, there's something going on mechanistically to impact that gene being expressed or not. And epigenomics explains a lot of variability in gene expression. So it's one of the mechanisms behind gene expression variability. Now, a lot of times people automatically associate epigenomics with DNA methylation. And I think that there's a good reason for that. And I think it's because looking at DNA methylation is something that we've moved along with DNA methylation is the form of epigenomics that has gained the most research in clinical applicability. There are some DNA methylation assays that are being used clinically. Again, mostly in oncology. But I do want to call your attention that there are many types of epigenomics, including histone modifications, chromatin structure, non-coding RNAs. So for example, some of the micro RNAs would fit here, and DNA methylation. And so I just wanted to point out that there are many different ways that the DNA can be chemically modified or packaged under this category of epigenomics. So I am actually going to spend some time talking more about DNA methylation because that is where most of the research seems to be happening. And it's certainly where most of the clinical utility for epigenomics has occurred. So with DNA methylation, you're talking about chemical modification to the DNA. You're talking about addition of methyl groups, but not just anywhere in the DNA. Methyl groups are added to GC-rich regions of DNA. So where you see a lot of repetitive GC, GC, GC, GC nucleotides, those are called CPG islands and CPG island-rich regions of the DNA are susceptible to DNA methylation. So when a region of the genome is hypermethylated, you're basically shutting down that region of the genome. So when the promoter region of a gene is hypermethylated, that gene is not gonna be expressed. When you get hypo methylation of a gene that's supposed to be methylated, you have activation of that gene. So you can see when we talk about DNA methylation being dynamic, you can see what we're talking about here.  You take it away, you reactivate it. And because DNA methylation is key for temporal gene regulation, as well as tissue to tissue variability and gene regulation, you can see how genes can be turned on and off based on their chemical modifications. So epigenomics does share some of the methodological issues with DNA polymorphism-based approaches as well as RNA-based approaches. You're back with the DNA, so DNA is stable. And for example, if you are looking at DNA methylation, the methylation stamp that's on that DNA is also stable. You can extract that DNA and you don't have to worry about the instability that we have to worry about with RNA. But what makes it a little bit like RNA-based gene expression is that it does matter what tissue you're looking at because the methylation stamp that's on the genome of a particular cell is gonna be different than the methylation stamp on a cell from a different tissue. So like gene expression, you do have to be mindful of what tissue you're looking at. And you do have to be mindful of exposures because it is dynamic. So one of the things that can make DNA methylation evaluation a little bit messy is, it's impacted by exposures, both endogenous and exogenous. But I think what draws a lot of us to looking at epigenomics and in particular DNA methylation is that exposures do impact epigenomics and DNA methylation. And to that extent, we're interested in how our genetic material interacts with our environment. Now, be mindful that we can only talk about what we know about today. And when I was a graduate school, we did not know much about epigenomics. We knew that some DNA was methylated. We knew about imprinting, but we didn't know the extent to which our genetic material interacted with our environment. And that actually could impact methylation of our DNA and the epigenome of our DNA and how our DNA is packaged. So with an epigenomic approach, you could look at one gene of interest. You could look at the methylation status of one gene of interest. You could look at the methylation status of a pathway of genes. There are assays out there to do that. Or like GWAS and whole genome expression profiling, you could look across the entire genome.  And in a non-parametric way, take a look at, well, what regions of methylation differentiate my phenotypes of interest? And so you can mix and match some of these approaches. And they overlap a lot, but there's little nuances about each of these approaches that the researcher and the person who's thinking about using these approaches clinically needs to be mindful of. So I do wanna talk a little bit about implications for nursing practice and research. And so I'm gonna pull directly from our paper. We have a table in our paper that deals with how across all four of these different approaches that have discussed how it impacts practice and research. So a couple of things that I wanted to point out, some of the highlights. So when we talk about genome sequencing, it is interesting to think about the fact that you could collect an entire genome's worth of sequence. And you could even do this with antenatal testing, for example. A lot of folks are thinking that what we could do is move towards whole genome sequencing clinically and have that whole genome sequence sitting there so that when it's time to prescribe a particular medication, our healthcare provider can take a look and see, okay, there's key genes that regulate metabolism of a drug that we're thinking of giving you. So in addition to all of the things that we normally would take into account when prescribing a medication, we're also gonna take into account your genomic variability. And so it would be there for us to take a look at and make appropriate recommendations for therapy, for example. And it sounds kind of futuristic, but there are a lot of folks who believe that at some point in time, we are probably going to have our genome sequences entered into our medical record and how we could utilize those data. Genome-wide association studies, again, particularly advantageous for common complex disorders, where you're thinking more than one gene is probably involved. Gene expression profiling, I already hinted at some of the things that we're using gene expression profiling for clinically, and certainly in the breast cancer population, we are using specific gene expression profiles of tumor samples to help us with accurate diagnosis, prognosticating, figuring out what would be the best treatment for that individual, and then post-treatment surveillance. For example, when some oncology patients go back in for follow-up biopsies and follow-up surveillance, we can look to see, are we seeing what we would expect to be a quote-unquote normal gene expression profile, or are we starting to see some genes abnormally expressed and is that cause for concern? And then with epigenomics, we have some clinical utility where we do have some methylation assays out there for key genes of interest. We know that loss of methylation and of oncogenes is a reason for some types of cancer and can help us differentiate certain types of cancer. So some of those DNA methylation assays can do for us in the oncology patient what we're doing using gene expression profiling in the breast cancer patient, for example. So lots of avenues for clinical implications and lots of possibilities down the road as these technologies continue to emerge and have more utility. From the point of view of implications for nursing, I think I'm probably preaching to the choir. You're all participating in this webinar, so chances are you need more education. But I think that you need to spread the word. No doubt there needs to be education efforts made. And I think that this webinar series is a huge step in the right direction. As far as research, clinical care, public health nursing, ethical practice, and then, of course, nurse leadership, there are already leaders amongst us that are looking to translate all of the new knowledge that is being brought to us through these emerging technologies and then how are we gonna use them clinically? And then what sort of ethical, legal, social issues might actually arise from conducting some of these technologies. So lots of implication for nursing, I'm sure this was the tip of the iceberg for the paper and I'm sure you guys could be thinking about additional implications. So for maybe a couple more minutes and then I'll stop and take questions, I would like to talk to you a little bit about some of the databases and resources. One of the things that myself and my co-authors believed very strongly was, if we're writing a paper about emerging technologies, particularly in the field of genomics, you know the paper's gonna be out of date, probably by time it's published. Or how useful is it gonna be a year or two years down the road? Well, to add to the potential half-life of this paper, one of the things that we decided to do was to embed in the paper a multitude of online, reliable web-based resources that are kept up to date. So that even if our paper gets a little bit out of date, readers would have resources to go to, to bring themselves up to date, to learn more about the technologies, not just how we describe them in the paper, but going forward, what's happening with those technologies, going forward, what data has been collected and stored in these databases. A lot of effort has been put into developing these databases and folks, we need to use these databases, we need to use these resources. So again, a couple of the resources that I wanted to point out, I did wanna point out Clint Seek, so Dr. B. Secker, who is a co-author on our paper, is the leader of the Clint Seek project at NIH, and so I wanted to give a call out for that because these folks are looking to develop clinical utility for whole genome sequencing. And so if you would like more information about Clint Seek, you can go to their website. I highly recommend you take a visit to the database of genotypes and phenotypes. So when we talk about GWAS studies, for example, that have been conducted, and I'll see if this will actually take me out to this website, when you take a look at what's going on here, you could go to DVGaP and you could type in, if your area of interest is cardiovascular, I'll just put in cardiovascular. You can see there are 95 studies that have dumped into this database, GWAS data that's publicly available. Now, some of this data's embargoed and you may not have access to it right now, but a lot of it is available and those that are embargoed will eventually be available. But you can take a look and see, your framing hand had 14,000 subjects in this study and the GWAS data and phenotype data is available to investigators through the DVGaP. The Jackson-Hart study, large epidemiologic studies that folks have seen in the literature for years, Women's Health Initiative, Cardiovascular Health Study, I would highly recommend that you guys go surf around on the DVGaP and see, put your phenotype of interest in and see what GWAS comes up that you might be able to tap into. Gene expression omnibus, or affectionately called GEO, is a clearinghouse for gene expression data. If you wanna know more about epigenomics, you can go to this website. If you would like to see databases of epigenomic data, mostly what's in there is DNA methylation data as well as some chromatin precipitation data the epigenome project is very interesting and contains epigenomic data from quote unquote normal individuals that you might find helpful to your research in particular for comparison group. And then just a couple of others that I threw up here and this is just a smattering of those that are in the paper. The paper has way more online resources for you to use. Genetic test registry and OMIM, very high clinical utility for you guys. I'd highly recommend you surf around on some of these websites. And just to put a plug out for the next webinar and I think we have time to take some questions. So thank you, Yvette. There has been one question posted so far if I can get to it and read it. Clarification, can you give an example of an incidental finding and how it was handled? Is it like LCM, is it related to research on that was not consented to? Okay, okay. So as far as incidental findings. So the idea of incidental findings, that's not a new concept. It's newer to us in genomics, but for example, in the field of imaging, incidental findings has been a problem. So if you do an image on someone because you need more data to clinically assist this individual, what do you do when you see something on an image that you weren't expecting and has nothing to do necessarily with the problem that your patient is having? It's the same situation. So an example would be, let's say I do whole genome sequencing because I'm interested in looking at an individual for, let's say I have a host of genes that I wanna look at variability in to say what their risk would be for cardiovascular disease or hypertension. And because I'm getting whole genome sequence, what if as I sequence through the Huntington gene, I find a run of trinocleotide repeats that are indicative of this person having the mutation that at some point in time if they live long enough, they're gonna develop Huntington's disease. What do I do with that incidental finding? It's not of interest necessarily to my phenotype, my index phenotype, but I know that there's clinical importance to that finding. What do I do? Now what do I do if this is a data identified sample? How much effort as a researcher do I now put into figuring out who is that individual? Because remember, a lot of the samples are de-identified for a reason. If you know, if you can trace back to the identity of that individual, would that individual even want to know that information? That's not necessarily what they signed up for. I have hypertension, I have cardiovascular disease and that's what you were looking for. Now you're telling me that I have this other thing. Well, I didn't wanna know that. So there's a lot, I don't know if that answers this individual's question, but that's the sort of scenario that we see playing out potentially with the collection of so much data about what someone's genome looks like. So the next question you've had is sequencing is the new light in the room of genomic research. Will future research require a blend of sequencing, epigenetic profile and expression analysis? If so, this could be very expensive and laborious. However, it appears to be the ideal. I think what is most desirable is usually most expensive. So more data is always better. And I think what you described where you're talking about looking at the sequence of someone's genome and then you're looking at the chemical modifications or packaging of that genome from an epigenomic point of view and then you're looking at what genes are expressed as a result of all of the above.  It allows you to start from beginning to end. What do I see in the genome that could be associated with this phenotype and why? So you're getting the how and the why, which are very important pieces of the story. You're absolutely right. But one thing that I would say is we're using a lot of these more global approaches that are more expensive with the idea that as we start to catalog more phenotypes systematically, we're not gonna have to look at everything down the road. We're gonna know for this particular phenotype, we're gonna have to look at this particular group of genes from both variability and epigenomic and a gene expression point of view, but we won't have to look at everything. And so I think that's really what a lot of folks are hoping that we'll eventually get at. I don't know whose lifetime that'll be, but eventually we're hoping to get to the point where we have cataloged enough of these findings for every phenotype that we're interested in so that we can be more focused. And then the cost won't be so high. So I bet this will be the last question and just to let everybody know, this recording will be archived and available on this same Gov site that's listed on Ivette's slide. And this is also where you can register for upcoming webinars. And the links, obviously in the tables are available in her article, which is in the JNS issue. And so the last question, in addition to a very positive comment about how helpful this has been was that for the Jackson Heart Study from DB Gap, do you know whether it includes the genotype or SNPs associated with metabolic syndrome? So, okay, good question. So if you are familiar with the Jackson Heart Study or any of these large epidemiologic studies, if you're familiar with them from the literature, you have an idea of what variables they collected on these individuals. So metabolic syndrome, I can tell you that they have a whole host of laboratory measures on these folks. They, you know, so they have glucose. They have, you know, CRP. They have hemoglobin, HC1. They have BMI. They have, you know, lots of information on these folks. These folks have had a lot of data collected on them over time. You would have access to all the phenotypes that they have. You could then, now whether or not they have metabolic syndrome, I'm not 100% sure, but you could certainly look at the individual variability, individual variables that you would take into consideration to come up with metabolic syndrome. Look at those individually or look at them as a whole, as a syndrome. But those phenotype data as well as the genotype data, now you have to apply for these things. You have to apply to get access. It's no longer available to the public. These things have gone to the point where now you have to ask for permission. But very rarely is someone turned down. The main reason why someone would be turned down is somebody's already looking at that. But if you have a phenotype of interest, you can go and look and see what variables are available. You can go to DB Gap and it'll tell you what variables phenotypically are available and what platform they used for their GWAS data collection so that you would know how robustly covered the genome was in their GWAS study. Thank you so much, Yvette, for doing a wonderful presentation. I'll ask Kathy if you have any last comments. I don't think so. It was a great presentation of that. We really appreciate your time. Thanks, everyone. And for anybody who had additional questions, we will try and follow up with those individually. Thanks, Dr. Conley. We appreciate your time and the slides from Yvette will also be posted on the genome.gov site. Till next month, see you soon. Thank you.


Hi guys, so here we are for another episode of my creative year for June 2018, and the topic this month is space. The prompt this week is who occupies your space. That's a really interesting question. You could take it literally, or you could take it figuratively or philosophically. I'm not sure how I'm going to take it, but I do know that the topic and the prompt inspire a look for my page that I think I want to go forward with. I already have this journal page that I've stuck some of these stickers onto. This is one of my new sticker sets from my Etsy shop, and I think we're going to go with that.  I want it to be messy, so I'm going to go around it two or three times, yeah, and then I think I want to do this, yep.  I'll be right back. I cut it, but I decided to tear it because I don't want any of the edges to be perfect. So now I'm going to pick a paint color, and I think I'm going to pick one of my favorite colors, which is French blue. This is a folk art craft paint, and we're going to need a stencil brush. I have a few stencils in my Etsy shop that have four designs on one stencil, and I took some of them, and I cut them apart, and that way I can just use the one element from that stencil. Maybe I want to use that one, let's see, let's see, shall we? I do think that is the one, or do I want to use this one? I think I want to use this one. So we're going to go around the edges here. The trick to getting a good stencil is to put a little paint on the brush and then tap it off so you have almost a completely dry brush. And then don't push down too hard, then you'll get a pretty good mark. And as you can see, I haven't reloaded the brush, so a little bit of paint goes a long way. I have this arrow stencil that I also think I want to use. I think I just wanted to use another shade of blue, I was going to use that purple, but I don't think I want to do that. This is a lighter blue, this is the blue lullaby. We're going to dry that, and I'll be right back. Now I'm going to take a blue gel pen, this is a PaperMaintink Joy Gel Pen, and I'm going to doodle over the stencils, the stenciled arrows. All the while that I'm doing this, I'm thinking about the question this week, the prompt, who occupies your space, and what that means to me in my mind. Okay, and I'm going to take a Uniball Signo in black. I said last week that these come in colors. Everybody's used to using the white, but don't forget about the colors that they come in. I'm going to color in some of these lines, sketchy lines that I made with the big pen, sort of like that, all the way around. Okay, now I'm going to do some free writing in the center, kind of messily, about what the prompt means to me, or what's going through my mind regarding the prompt. I want to use the other pen moves. I really like the way this page is looking. It's really saying to me something about space and the occupying of space, and what you can do when you're occupying a space. It creates a certain interesting movement on the page. I do like it. I am going to go search through my quote box for something, a focal point, and I'll be right back. Okay, I happen to have this set of words right on top that I think are going to work for this. So the first thing I'm going to do is cut them apart. This came from some magazine I don't remember, or leaflet, or pamphlet, or I pick up stuff everywhere that I go that might have images or words in it I can use in my journals. So I'm apart, make them look a little neater and cleaner, and this way too I can arrange them so they fit better on the page. And I think I want them right in the middle like that actually too. Let's see, we need some gel medium, this one I think, I have these little pots of gel medium I need to kind of try to use up. The trick always is getting it on the crack of the book.  When you have thicker pieces of paper like this magazine page was a little bit on the thick side then it's good to use some kind of medium to glue it down that's also a little thicker and heavy duty like gel medium.  And then I'm going to use some of my lettering stencils. These are from the Office Supply Store, you've all seen me use them before. I'm going to take the medium one. I kind of run and write your space, maybe your space, maybe, oh yeah, maybe, but do I want it this big or do I want it littler? See that's the thing, I got a littler one, I might want a littler one, yep, that one's too big so this is the second smallest, it's not the smallest one. Okay, then I'm going to take a bigger pen like the Uniball Signo Pen, a bigger nib, actually I have a big crystal that's a broad tip, here it is, let's use that one because it's got a bigger nib on it. To fatten up the letters, I like that page, experience, explore, discover your space and what that means to you, I love this page. Alright so I'm going to stop there because I'm really happy with the way it looks and what it says, what does the prompt who occupies your space mean to you, journal about it, create some art about it, I'd love to see what you do, I'd love to see you share it over in the Facebook group my creative year if you're not already a member, if you are by all means share over there, but if you're not a member and you'd like to be, the link's in the description below and it's a great little sense of community and art and exploration that we have over there so I would love to see you all join if you do Facebook. That's it, don't forget the most important thing besides like, share, and subscribe and that is, I'm waiting, y'all know what that is right, why now you should know if you're a regular on my channel, go out and have a great day, do something nice for yourself because you deserve it, explore your space and those around you in your space. That's it for today, see you later, bye guys.


He'll write the GitHub issue. I will write up the code I will publish it. I will do everything they say if I if I am a Do this and I publish a hard-fork patch to delete Fire a bunch of accounts. How many people here would be willing to download and install the update and switch to that chain? I See relatively few raised hands This is called decentralization Do you personally own any cryptic I think like two people gave me a couple of crypto kiddies And I haven't really looked at them since but they're around tokenizing real-world assets, whether they're securities or gold or bonds or like fiat or like I don't know like pixels of some Banksy photo or whatever. I think it's like all Interesting it doesn't seem psychologically that easy for people to make the leap from paying $40 million for a Mona Lisa painting to paying $40 million for a digital private key thing a jig that claims that it has some arbitrary attachment to a Mona Lisa painting and That's like okay fine. I understand that I don't really understand the art world in general anyway when you can just like photo Copy that looks almost identical Yeah Even if centralized exchanges end up having a lot of volume like the better decentralized exchanges are at the base As a baseline kind of the more happy I am because that way we can really like take away this Stupid king-making power that these centralized exchanges have for like where they have this ability to just decide which tokens become big by just deciding to list them and in charging these crazy 10 to 15 million dollar listing fees and Like the more we can get away from that world and into something which actually you know Satisfies the watch in values of openness and transparency the better. I definitely am less optimistic about private and consortium watchings than it was two or three years ago basically because like There's there's there's this bubble and there were a lot of promises and like oh my god IBM makes 200 million dollar savings by putting something on a blockchain and I have No idea what they actually did they probably just like digitize something that was paper before and like great Which other blockages interested by which we could measure of the which are the blockchains Do you actually have private keys for? Experimental reasons or which I do Well, a lot of this is like kind of historical reasons, but Bitcoin Bitcoin cash Bitcoin gold Bitcoin Uranium it's quite bad. It's Bitcoin carbon dioxide No, let's see. I got some doge. I think I think I got some z-cash In all sorts of Ethereum based tokens