So, thank you. This is my first genomic meeting here, so just to back up, there's been a lot of references to the VA. I think it is the best example to the NHS or anything. It's a wonderful system. There are about 23 million veterans alive with seven millions who are expected to receive care this year. So, it's a very large healthcare system, over 60 million yearly visits. There are 153 medical centers, and then there are a lot of outpatient clinics. So over 1,400 total sites of care. All systems do use the same electronic medical record system, but actually they're not integrated across. We can finally get remote access to other ones, but there are about 180 separate servers involved, so that's a different issue. From my point of view as a clinical geneticist, the VA kind of lagged in delivery of genetic care behind a lot of other health provider organizations, because we didn't have pediatrics, and I did a pediatric genetic fellowship, and 20, 30 years ago, dysmorphology was a very big piece of genetic care, and then it evolved into something very different, and so an academic center is now obviously involved in oncology and neurology, but the VA kind of lagged. Back in 2006, then Secretary Peake really established the first genetic medicine program advisory committee with the goal of using genetic information to optimize clinical care, but also recommending processes and goals for the development of a VA genetic medicine program. So two years later, the committee was formed. There was genetic care in the VA. There are 120 and round numbers of the VA's have academic affiliates. Obviously there are high class providers in all of these places, and they were providing care, one off in a neurology clinic, in a cardiology clinic, in an oncology clinic. There were four actual board certified clinical molecular, clinical geneticists delivering care, and Los Angeles developed a center, but really we only started capturing genetic workload. The VA didn't even use the workload to capture systems. This was integrated into research very quickly within the VA after this was announced. Sarah and I will be talking as soon as I finish as fast as I can here. I think describe a lot of the HSR&D programs as well as the MVP, and those are incredibly large research programs, but the clinical program really lagged. So I was hired in I think 2009 as the national director, and I quickly realized there was no service. So you know, it's a little, it sounds great until you realize that you have nothing to do. I hired the first actual clinical provider as a clinical geneticist in 2010, excuse me in 2011, and one of the key points in providing a centralized integrated genomic service within the VA was an agreement between the VA and well an understanding with the Joint Commission that we could cross credential people across all of the 153 medical centers. So that's at least possible getting it done through the bureaucratic web was interesting. So we hired our first counselor in 2011, and in March 2011 we got the first memorandum of understanding between two facilities. And then there was, there are now 29 stop points that we've identified in the process of delivering care. Telehealth has really made this possible. The VA bought into telehealth in a very big way. The goal is to have 50% of all patient encounters done by telehealth. A lot of these are between the local VA medical center and what are called the community based outpatient clinics or CBOX, there are about 1,000 of those. And so the images of the mothership and then the little outpatient clinics, it keeps the veterans from driving 150 miles, they don't have to drive 20 miles, great place. They can get specialty care there. A lot of it is telemental health. But I think the idea of genetic counseling where you're using a specialist as the primary care physician and then a genetic counselor and a backup medical geneticist really works well and is integrated well into that potential model. Another program, I mean I'm really surprised, there's a big ICU program with TELA ICU where rural hospitals have an ICU, but they can get support from, with a little robotic interface from an intensivist at a much higher acuity hospital. So we really built a centralized service in Salt Lake City. This is where we were one year ago and here is where we are now. So we're delivering care in, actively I think in 47 or 48 places. We have over 60 memoranda of understanding signed to deliver care. But the IT infrastructure lags. You have to get permission from each hospital and get integrated into their system. My counselors have to log on to each medical center every 30 days to maintain their passwords. We have an encrypted log. So if you can imagine trying to keep track of 153 user IDs and log-ins just to be able to deliver care, there's got to be a better way. We're going to work on that. Here's the setup. These are actually two counselors talking to each other. But it's just done through a nice setup. And here's the way the workload has increased through the first quarter of this year. So we're just, we're exponentially increasing, which is really fun. And here's the agreements with TSAs. A lot of this has been through the telemedicine capacity over a third of it. About a third of it is e-consults. And a lot of the driver of that is from pathology. We get consults from, I think well over half of the e-consults are from pathology saying is this test appropriate? How do we handle this? The pathologists in question a lot of times are not certified molecular pathologists. There are more than a handful of excellent certified molecular pathologists within the VA. But a lot of these go to the regional lab. They're just saying in the VA if you've seen one VA, you've seen one VA. They're kind of entrenched. And so the test lands at a local VA medical center that may not have anybody skilled in molecular pathology. So we handle those. We also just do a lot by telephone. As soon as we have the memorandum of understanding signed, we can get in there and legitimately contact the veteran. And then we're emailing encrypted notes, but it does work. We have gotten referrals from every department and division within the VA with the sole exception of the emergency room. And I imagine that's going to happen one of these days. So we've really made inroads into every place. Usually when we get into a site, we give an in-service. The big users are oncology, women's clinic, which also includes breast cancer, obviously, GI. So the needs and gaps, I'm trying to close here, everything that we've heard today is I think there's a tremendous consensus in the room about what the needs are. Clearly integration with EMR is the big one. The one thing that hasn't been mentioned yet is the structured family history. And if you're looking at Amsterdam or Bethesda Criteria, you're looking at BRACA Pro, you want to, if you're going to computerize that for decision support for some busy primary care physician at the point of care, you really need to have a structured family history. I know there's a conference a little later this week that might address some of that. I'm going to the conference in San Francisco on disparities of care. But building computerized decision support all the way through and making this seamless has got to happen. There's no way that any of us who are, no matter how good we are and how long we've been doing this can keep track of all the polymorphisms. I think the processes, this was just eluded, the idea that there should not be a genetic exceptionalism either in the ways we order the test or anything, it's just another test. And it's just more medical information. How can we use that? How are we going to run this into, how are we going to build this in the large scale? There are 3,000, I think, or very close to 3,000 individual genetic tests performed commercially in the United States right now. And then as we approach whole genome sequencing or exome sequencing or Regulome or whatever it is, how are we going to divide that? There are also, so these are sort of the more external issues. I think the internal issues, building a service within the VA, I was at a meeting in DC a little less than a year ago, and they were suggesting words that describe the VA as flexible and responsive. And those of us from the field were saying glacial, monolithic, bureaucratic and working this through so that we can get access to the high-quality molecular labs and centralizing those so that we can work with IT, which is a local issue, work between all the medical centers, all of those are issues. But I think, you know, I can just go back to that trajectory slide. So I also work in research, and so I'll turn over now to my colleague from ORD, but thank you.


Going on everyone, Sam here with late in sports cards we've been 22, 23, Penini court Kings, basketball hobby, eight box, half case break, number two, pick your team style got a list of our names in our teams, Aaron L with the Sixers, Anthony C Warriors, C's R.A. Sons, Chad H. Cavs, Charlie S. Bulls, Chun Wai W with the Grizzlies, Edward P. Lakers, Elton L, Timberwolves, Felix N, Nets Wizards, H. Lee with the Jazz, Hank B. Pacers, Howard T. Bucks, Jasper D. Clippers, Jerry J. Spurs, Joe D. Celtics, John M. Nicks, Joral S with the Magic, Jose V, Hawks, Luke M. Pelicans, Matt B. Thunder, No G. Raptors, Orioles C. Mabs, Paul G. Nuggets, Thomas C. with the Pistons, Tom B. Rockets, Victor F. Hornets, Y. Zhao with the Heat, U-Show L with the Trailblazers, and Zach Astor, the King, Zach, thank you for selling us out, buddy. Let's get into it, everybody. Gotta sell out the next one, everybody, number three coming up next, number three. Let me drop you guys a link to that really quick. Pistons gone in seven, thank you there, Jonathan. All right, thank you there, Donnie. Donnie's gonna go ahead and drop you guys the link to number three, just gonna get it open as well. Bunch of teams on sale there as well. George Booker, there's A. Anthony Simons to not numbered. There he is, worked out well to 199, Keegan Murray. Congrats on that, Zach, that paid off for you, my friend. There we go, nice Keegan Murray coming your way. Let's go, dude, that's awesome. That is awesome, Keegan Murray, fresh paint. We've got James Wiseman, Art Nouveau for the Warriors, that is a game-worn Wiseman, now a member of the Pistons, of course. We've got Jake Laravia, rookie. First steps, Benedict Matheran for the Pacers, nice one there, congrats, Indiana. Got David Arati, rookie, level one, and Benedict Matheran, level two. The Pacers as well, box two, good luck. Let's go, Zach, congrats, man, picking up a Keegan. That's awesome, dude, very happy for ya. Yeah, very nice sit on the Keegan right there, Keegan Murray, very nice, very nice, very nice. Yeah, literally just pulled a Keegan Murray, just pulled one there, Timothy. Jaylen Green, there's a Maestro, is it Yanis? Two, 49, man, what a break we've got going here, guys, so 199, how about a Benedict Matheran now? Two big rookies, let's go. Congrats on that one, that is sweet. Benedict Matheran coming your way, I think that was Hank with the Pacers, if I'm not mistaken. Got a Trevor Keels, rookie jersey, going to the next, nice one there at New York. Picking up a Keels, we've got Jaylen Green, Maestro's. Watercolor is Kyrie, for the Nets, we've got a Patrick Baldwin, and a Patrick Baldwin, level three, nice one there for the Warriors, Warriors sweeping the rookies right there. Again, guys, few teams to go, still on number three, we gotta get that sold out as well, if we wanna keep our night moving. Jaylen Duran works in progress, that is two 149, haven't seen one anywhere. Yeah, I don't think we've pulled an Aurora yet, Pethora, nice one here too, to 99, Jeremy Sohan, that's going to the Spurs, nice one there, Spurs. Congrats on that, rockets gone in number three, we're down to nine, guys, we're down to nine, nine to go, Terry Eason, going to the Rockets on the rookie expressions, nice one there, another tiered spot came in, thank you Larry, we've got Jayden Ivy, Maestroce, for the Pistons, we've got Watercolor, Steph Curry, there's a Jeremy Sohan, level one rookie, and a Jaylen Duran, level two rookie for the Pistons, nice ones there, everybody, thanks again, level four, our box number four, not level four, technically we are on level four of this break though, if you think about it, bit of a stretch, but again, guys, now down to nine to go, teams are on sale, definitely check it on out, nine to go, Porter Jr, there's a Keldon Johnson, Purple 249, for the Spurs, we've got nice one here too, 199, Max Christie on the heir apparent, going to the Lakers, heir apparent, we've got a Clay Thompson, nice one there for the Warriors, game used Clay, game worn Clay, we've got a Palo, works in progress rookie, followed by Zion Maestroce, we've got a Christian Brown, level one, and a level two Chet Holmgren, for the Thunder, nice Chet, Luca Jokic, James Hardin, there's a Colin Sexton Pink, 299, for the Jazz, got 2199, Caleb Houston, nice one there on the Fresh Pain Auto, yes, yes it is Johnny, yes it is, we've got, going to the Wizards, Johnny Davis, Art Nouveau, Rookie Jersey, for Washington, we got first steps, Jalen Durin, for the Pistons, we've got Maestro Scotty Barnes, second year, we've got a Caleb Houston, level one, and a level two, Mark Williams, for the Hornets, box number six, Bama DeBio on the red, that is gonna be 2149, Bama DeBio, and guys, nine to go still, nine to go on the next one, 199, Kenneth Lofton Jr., on the Rookie Auto, Kenneth Lofton Jr., got nice one here, Andrew Nemhard, Rookie Expression Jersey, going to the Pacers, what's up Joey, how you doing buddy? We've got a Patrick Baldwin, works in progress, a Maestro's Dean, level one, Benedict Matheran, hey thanks Johnny, appreciate you buddy, and another Benedict Matheran, level one and two, King's gone, now we're down to eight to go guys, thank you there Johnny, appreciate you buddy, very nice, thank you, thank you, down to eight to go now, drop guys that link again, we got just eight left, PYT style, there's a Maestro's Jomerant, that is to 149, for the Grizzlies, nice one here, Rookie Auto 2, 199, Oseman Zhang, that's going to the Thunder, I appreciate that Aaron, that's a lot of fun man, getting guys just eight to go on the next, E.J. Griffin, Art Nouveau for the Hawks, my guy, love me some E.J. Griffin, got a Yanis, nice one there, watercolor for the Bucks, Rookie Marjan Bochamp, level one Nicola Jovic, and a level three, that is Shaden Sharp, nice one there, you got it Spencer, no problem buddy, and the last one here. Is there a case in this or are they all just SSPs? What do you mean? It's like all the short, oh just SSPs yeah. I know there's like case in here. Yeah, cause there's like three or four different like case hits, case hits, they're just super short prints. Right. Chris Middleton, that is going to be not numbered, I think I can Joey, we've got the 49, Brooke Lopez, for the Bucks, nice one here, got a Steph Curry on the artistic endeavors, that is Gameworn Curry, very nice. That's on that Golden State, very nice. We've got a Osemane Jang works in progress, a Ja Marantz on the paint by number, that is a super short print, congrats on that Memphis, paints by the number baby, and I forgot to bring my paint brushes in, kind of pissed about that, nice super short print, congrats on that one, that's sweet. We've got J Dubb, level one, and a Wendell Moore Jr. level two. That'll do it for the break guys, we'll do a quick recap here. We've got a AJ Griffin, Andrew Nemhardt, Johnny Davis, Clay Thompson, Terry Eason, Trevor Keels, James Wiseman, Steph Curry, Brooke Lopez, Osemane Jang, Kenneth Lofton Jr., Caleb Houston, Max Christie, Jeremy Sohan, Benedict Matheran, Anna Keegan Murray, really good break right there, a couple of big rookies, as well as the Ja paint by number. We'll get those right out to you guys, thanks again, let's fill up number.


In the previous video, we saw how to compute average value of a function. It's fairly simple. It's just the value one over b minus a times the integral of f from a to b. That's all there is to it. And so as long as the integral is easy to compute, average value is fairly simple to compute as well. But why is one interested in average value? Like if you're looking for what's the average homework score, you can see that you're trying to find what's the middle of all the homework you've done and that has consequences, perhaps on a final grade in a calculus class or something like that. And the average value of function is trying to do the same thing. It's trying to find what's the center of the function? What's the center of the data? Now, this idea of average value we talked about is related to the mean value theorem we saw in calculus one. The mean value theorem from calculus one tells us that if a function is differentiable, then there exists a value of x, such that the derivative is equal to the average rate of change of the function. That is, there's a moment where the instantaneous rate of change matches the average rate of change. A similar question actually applies in the following context. Is there a value of x for which the function obtains its average value? And for a continuous function, the answer is going to be yes. And so what we want to do is restate the mean value theorem, not for derivatives, but for integrals. If f is the continuous function on the interval a to b, then there exists some number c that sits between a and b, such that the average value, which we defined earlier, is actually equal to f of c. So the function obtains its average value at some location. Now, if you take this equation right here and you times both sides by b minus a, you've got to do it on the left-hand side as well. Then you get the integral, like you see right here. The integral is equal to f of c times b minus a. Now, this second equation has a very interesting geometric interpretation, so I want to give some explanation about that. So if you look at the left-hand side, the left-hand side right here is the area under the curve. So if your function f is given right here, you see that the area under the curve is this region colored in right there. The right-hand side, though, is factored. It's f of c times b minus a. Because we have a product to two numbers that's equal to an area, this makes me think that this is likewise an area. And as it's a product of two numbers, I think it's the area of a rectangle.  So if we find the guaranteed point f of c right here, that doesn't look like a c. Try that again. If we take the guaranteed point f of c, is the point on the graph which has the same value as the average value of the function. In this situation, if we take a height that and we take the thickness, so here's a and here's b, if we take this rectangle right here whose width is b minus a, whose height is f of c, what we're saying is the mean value theorem for integrals tells us is that the area under a curve is actually equal to the area of a rectangle. And the height of the rectangle is the average value. So basically how we wanna take this geometrically here is the average value is saying if we re, to redistribute the area under the curve in a uniform distribution, it will form a rectangle the height of the rectangle is that average value. So why does such a point exist? Well, like we saw in calculus one, what we can do to kind of prove this argument is we can introduce a integral function, a function f of x defined as integrate from a to x, the function f of t dt. So when we talk about the fundamental theorem of calculus, we can define functions using integrals where the upper limit is itself a variable. All right, then the average rate of change of the function capital F on the interval a to b is gonna be given by the following capital, the delta capital F over delta x right here. Well, this will look like f of b minus f of a, and these are capital F's, not lowercase f. This will sit above b minus a, that's just the average rate formula there. Now as capital F is itself an integral, f of b is the integral from a to b of f of t dt. And f of a is the integral from a to a of f of t dt. Like so, this all sits above b minus a. Now notice that second one right there, the integral from a to a, that's gonna be a zero. If you integrate from a to a, that's always gonna be a zero. And so the numerator is just gonna be the integral. And if we rewrite this thing, you're gonna see that we get one over b minus a times the integral from a to b f of t dt. And now if this feels like deja vu, it's not quite that. This is, we've seen this before, this is the average value of F. So what we see here is that the average rate of change of capital F, the anti-derivative of little f, is the average value of little f. So we see that relationship right there. Now what we also know by the fundamental theorem of calculus, so by the fundamental theorem of calculus, FTC, we do know that capital F prime of x, this is gonna equal, well, if we write out the details, d dx of the integral from a to x f of t dt. What we know from the fundamental calculus is this is gonna be little f of x, like so. And so if we apply the mean value theorem for derivatives to this capital F, right? So we apply the mean value theorem from calculus one to capital F. What this tells us is that there exists some number C such that the average rate of change, delta F, delta F over delta x is equal to the derivative of capital F at this number C, right? But the left-hand side is just the average value, which then proves the argument we're trying to look for, that there will be some location where the function obtains its average value. Now, to see that, let's take the example we saw in the previous video, take the function F of x equals one plus x squared, we consider the interval negative one to two, and as we saw previously, the average value here was exactly two. Where does this function F obtain this value two? Well, just solve the equation one plus x squared equals two, I replace the x with a c here. But if you take one plus x, c squared equals two, subtract one from both sides, you're gonna get c squared equals one, taking the square root, which notice there are two square roots, the positive and negative one, we get that c equals plus or minus one. And so if we look at F of one or F of negative one, those will both equal two. Now, notice that there were two values, and this mean value theorem guarantees there's at least one. There could be numerous, right? There could be 12 dozen, there could be 5,280 numbers that obtain the average value. But we know there's at least one. But I do wanna draw your attention to the fact that if we look at the interval, negative one to two, the mean value guarantees that there will be at least one number in this interval between negative one and two that obtained the average value. And there does turn out to be two. Negative one's on the boundary and one is in the middle somewhere. So we do get multiple values that do that. And if we look at these numbers geometrically, we see those points right here. When x equals one, the y coordinate is two. When x equals one, negative one, or when x equals one, this is x equals one, we see the y coordinates equal to two. And if we look at the area below the curve, we look at the area below the curve right there, we see, we calculated earlier that this area was equal to six. And so, if you notice the length of the interval right here is equal to three, the average value is two. If we look at this rectangle right here, this rectangle likewise has a volume of six, not volume, an area of six, excuse me. So this rectangle has the same area as the area under this curve from negative one to two. And this is a rectangle whose width is the length of the interval and whose height will pass through these guaranteed points, these average values of the function. So we can always turn the area under a curve into a rectangle using the average value. And that actually brings us to the end of our discussion of average value. It's a really short section. It's cute and adorable, but that's it. If you have any questions, like always, please, please, please, you can post your questions in the comments of this video below. Now be aware that if you're watching this video through a learning management system like Canvas, you might have to actually open up the YouTube page. Of course, if you're on YouTube already, you can see the comments. Post your comments below. I would, your questions or comments, I'd be glad to address them, answer any questions you have with any of these videos. If you like what you're seeing, please click the like button, subscribe to see new videos in the future, and I will see you next time. Keep on calculating everyone, bye.


Iqisha kwa nasu Securaun, kukipu mwake nmitu mwake mmuneya. Waqutu mwakutu isu. Kwa mwaksimia wajafu, kufu mei nusibutu na kwa kwa mwakawek. Tata wewa kukipu mwakawek wa kwa hwadu mwakawek iqisha mwasa. kwa mwakawek wa kwa mwakawek wa kwa mwakawek. Kwa mwakawek wa nusibutu na kwa mwakawek na kwa mwakawek wa kwa mwakawek. kwa mwakawek wa kwa mwakawek wa kwa mwakawek. the nature of this conversation, I am joined by Moses O'Mondi. He has an interesting story. He's a born cancer survivor. He's a youth of course and I'm a team member for the Global Week for Action on Non-Kunikable Diseases. Right here in Kenya. Banna Moses, Karibusana, yo well. I'm good. Thank you for finding time to join me this morning. And as always, we appreciate your feedback from wherever you're watching us from. The hashtag as always is why in the morning at Ramaguko is where you can find me at Michela Shearer, my colleague's handle. The station handle is at Y254 channel. The hashtag as always is why in the morning. Get over to Facebook also if at all you'd like to be part of this conversation and drop in your comments on the comments section because we've made a post there on Facebook on the comment section below, regardless of whatever you have been posted there, just be part of this conversation. Remember, we shall sample your feedback as you continue with this particular program. It is matters health. Now, Moses, before we talk a lot and touch base on so much, tell us about what you do. And I'm really interested in getting to your story also. How did it all start? It's quite interesting because it is in the year 2014 when in form two that he was told that, hey, you know what? You've got cancer. Imagine if it was you who you're finding in me. Moses, tell us. Okay, for what I do, I work at an Uncommunicable Disease Alliance of Kenya. It's an umbrella organization for the groups that deal with the Uncommunicable Disease. So we host cancers, diabetes, they're all under Uncommunicable Disease, Alliance of Kenya. And I'm part of the team there. And for this month we have an activity. It's called Global Reconfaction that we've been planning. And for my story I can say that I was diagnosed back in 2014 when I was still at a young age, still in high school. So I had a lot of questions, like why me, you know? At such a young age you have this disease that at the back of your mind all along. I knew that this was a disease for the rich, you know? That's what you believe? Yeah, that's what I used to believe back then. But cancer is a disease for the rich? Yeah, yeah. So I was wondering why me. I had a lot of questions. Back then I was under the care of my parents, so I used to go with my father for clinics. So all the information I passed through him. So if I get you right, you're informed too? Boding or... It was at the school? At the school. Roraka High School. And how exactly did you get that information? Test for being done in school, what led to you actually getting such kind of a diagnosis? Okay, at first it just started like a simple pain around the near sharp pain. So one day while at this assembly, I fainted. And then I was taken to a hospital and X-ray was done. From days when I was referred to Kiambu Hospital, then to Kenyatta, a long process. And when the doctor saw the results, biopsy test was done. Just to know, to be sure what was going on, it took like a month. And then when they... Together results. Together results. So I was in the hospital and then discharged. By then I was at Kenyatta Hospital and then discharged and then I went back for the results. And now days when the news was broken to us, I was with my father and I was told that your son has cancer and the only solution is amputation because the swelling was big. So Moses, I thought part of the knee did you feel that you are pain? Okay, the front part. But it used to affect the whole knee. So both legs? The right side. So it used to swell and the knee used to... Irukwenakuji na kwa fupi. Fupi? The swelling in a kwa kubu and the knee gets shot.  What do you say in a kwa fupi in terms of the length from your hip to your toe? Yeah, in terms of the length because now all the masses, all the skin, Irukwena stretch. So when it stretches outside, it comes in a kwa fupi. So some kwa fupi kwa fupi kwa gini? It reached a point that I couldn't even walk. So I used to... My father, I can't jengia like a crutch that I used to walk around with because the right knee, Irukwenakuji na kwa kubu. Now this was before you went to a hospital? Yeah. And meanwhile, how was the reception especially from your father and your relatives, friends and family upon such news? How was it? Okay, I can say that they were very supportive, especially my family because they were there with me the whole journey. My mother used to work in Westlands. So she used maybe to sacrifice her time on a daily basis to come and see me in the hospital. Same with my father. So my father took the initiative of caring for me, going to the hospitals, the clinics, all those. It was my father who did that. So I can say that the support was great because my siblings were still in high school. So they used to come during the weekends, maybe on Saturdays and Sundays. You and your siblings are all in high school? At then, I'm the third born. You're the third born? I'm the third born. I'm a family of six. So they held a brother and they would come as a shule. But from our second born, I think he was informed for, I was informed too, and the others were behind me. So the only time that they could come was during the weekend. But they were supportive, very, very supportive. Same with my colleagues, my friends from school and the teachers, they were very, very supportive because they used to come during the weekend also. Even after I was discharged and I went home, they still continued coming, just visiting, giving me that amount of support. And how was it for you, getting such kind of information, especially at that point when you were told that they have to amputate your legs? Did you expect that kind of information, considering in a furra, in a shrink, in a furra, in a shrink? And at what point did you get the information? Was it when you were admitted, while still in the hospital bed? Okay, at first I went and when I was admitted, they did the biopsy test. And the doctor told us that the results will take a while. So we don't want your hospital bill to pile. So we'll just discharge you, go home, and when the results are out, you can come back. So you're not fully admitted? I was not fully admitted for three months. The results were done, the biopsy test was done, and then I was discharged. And then I went back. So when I got the results, it was when I was 10 and I was admitted in the hospital. There is when the results were given to us. It was shocking news. At Sanchayang, age being told that you were diagnosed with cancer, bone cancer. So all sorts of things were running through your mind? Through my mind. I was depressed, I started crying.  It's just the start. The important thing is that you'll be alive. And for something like a leg or an arm, you can get a prosthetic, you'll be okay. So just go through it. And there's when I got the courage and I went through the operation. Because I'm sure coping up was difficult? Very, very difficult. Because all your life you've been used to living in a particular way. But now you have to adapt and change. How was it coping? It was very, very difficult. In fact, after amputation and I was okay, I went back to school. At school where you were the only person who was amputated. The others are okay. You see now the challenge there. You walk in this corridor, someone is looking at you like they are wondering what is happening. So it was very, very stressful and depressing. But as time went by, I got used to eat and make classmates. They were there, they were supportive. They used to help me talk to me. You know, the moral support. And that is what got me through that. You know, for many, they go through stigmatization. The stigma that is there.  There is always a look at you. And I don't know if that was true for your case. They look at you and you can be able to read. It's like they are talking through their eyes. Yeah, I've experienced that. It was very, very difficult. But the good thing is I accepted myself. That's the first step. If you accept yourself, it's when others will accept you. But if you don't accept yourself, you'll be depressed. And you know, for many who are watching, there are some who have cancer and are watching it today. What would you tell them? Regardless of the environmental factors, because for you it was good that you had parents who were supportive and you had friends who were supportive. But there is someone there who doesn't have any of the two. True. And first I can say that maybe it was a blessing for me to get this cancer. And that's why I am here today to give hope to someone else out there. So what I can say is that just be strong. Be strong. Cancer is not a death sentence. Just be strong. Have that courage. Talk to someone. You know, if you are able, just join a support group because that is what worked for me. I joined several support groups that we used to talk, share your story.  You let everything out.  And you'll get that hope and you'll be. Like just share, just open up, talk to someone. And that's why we talk about these NCDs. Just talk to someone. Like for mental health cases, people are depressed, people are dying. If you can just find someone to talk to, have a conversation with open up, everything will be okay. Now, and that's what we have this week. And that's what we have this week. So what is this week? What exactly are we planning for this week? What should we be looking out for? Okay, this week will be celebrating. It's a global week for action on NCDs. It just says on its own, global week for action on NCDs. Like it's a global event that there will be a lot of action and activities. Or a visit should we be looking out for? So for global look of action, it's all about trying to reduce the burden of NCDs globally. Those are non-communicable diseases and increase health and equality. So for this week, we have several events. We'll be having the radio interviews, TV interviews, just talking about the week. And also we'll be having a webinar on 9th. So people come this week on 9th. That will be on Thursday. So people can join us on that. If you want more information, log on to our social media pages. That is NCD Alliance. All across the social media pages. And for global look of action, we have something called voice of change. Or that? Voice of change is you go there, you express what you want the government to do for you or what you want to see changing. So we have a competition on that. So you just log on to actonncds.org and just express what you feel about uncomfortable disease. Anybody can do it. Anybody can join. You can just express, you can just have your voice of change there. And for that, you can take a screenshot and share all along your social media handles. And there is something good at the end of that. So it's all about getting the information out there. You know, everyone coming to just talk about the same thing from the different perspectives. Globally. Globally. So it's a global event. It's a global event. Nancomunicable disease and also Kenya is part of that. So it's a GWA. Global week off for action on NCDs. Now as we wrap this conversation up, I would like you to speak to that Kenyan youth who is watching it today in regards to all of this just in a nutshell.  And this is something good that we are expecting this week. So within just 30 seconds, have a final word. Okay. My final word I can say that to Kenyan youth, now it's tough. NCDs are on a rise. So just take care of yourself. Be active. Just do a lot of exercise. Watch your diet because those are some of the risk factors for NCDs being inactive excessive conception of alcohol and tobacco. So let's be active, let's watch our diet and together we can reduce the burden of NCDs in Kenya because no action is small and no action is big. You know, it's quite interesting what you said there. People don't know how their lifestyle can actually affect their overall welfare. Yeah. You know, your health is the number one office. If you're not okay, you can't do anything. Watch your health. Wonderful. If you're a healthy nation, healthy people is a healthy nation. A healthy people is a healthy nation. Moses, thank you so much for finding that journey. And I'm sure there's so much that you've not touched on, but I wish you the best whatever you're doing, keep doing it. You know, at the end of the day, we are reaching out to so many people out there and we are changing the perspectives, the mindsets, the stigma, the fear and the panic that is outside there. We are bringing that influence. So keep it up. Thank you so much. And if you want more information on that, just go on our social media pages, NCD Alliance. Twitter is NCD Alliance Kenya, Facebook NCD Alliance 2013 and Twitter is NCD Alliance. NCD Alliance. You'll get all you need. And are you on social media? Yeah. How can we find it? I'm on social media, Facebook is mosesmoses. For Twitter is mosesomond101. Wonderful. And for IG is moses.omondy underscore. Understood. Understood. Thank you so much. God bless you for coming. I appreciate it. That means that to the end of this conversation on this particular issue on cancer awareness, head over to their handles as they have said and their website and follow, catch up with the conversation, join in this particular event and let us create awareness. Thank you so much for being part of the conversation. Keep it going on our Twitter handle. The hashtag is all in the morning at Ramaguko and that Y244 channel. We still have more insta for you. Meenawal, we're taking a short break. We'll be back in a bit. This is all in the morning.


Introduction to Proteomics, Protein Identification, Quantification and Statistical Modeling. Before diving into this slide deck, we recommend you to have a look at the following. Proteins are macromolecules that have many important functions in a cell. Protein-coding genes are transcribed into mRNA, which is translated into amino acids. The amino acid chain forms secondary, tertiary and structures to obtain a functional protein. One gene may generate different proteins due to alternative splicing and post-translational modifications. Therefore, the proteome level shows a higher molecular complexity. The proteome is defined as the entirety of proteins expressed by a genome or by a cell or tissue at a given time. The study of proteins is important as their identity and abundance is only partially predictable from DNA and mRNA information. This is due to alternative splicing, post-translational modifications, protein turnover and subcellular localization. Mass spectrometry is the standard method for proteomic analyses of complex samples. In the classical bottom-up approach, proteins are enzymatically digested into peptides. Peptides can be analyzed with high sensitivity and throughput in a mass spectrometer. The peptide mass is measured as mass-to-charge ratio. Only charged peptides can be measured in the mass spectrometer. Tens of thousands of mass spectra are generated per sample. Each spectrum consists of many mass-to-charge and intensity pairs. Different mass spectrometry-based proteomic techniques exist. The most common one is explorative or shotgun proteomics. It aims to identify as many proteins as possible from a sample. It comes in two flavors, data-dependent acquisition, DDA, and data-independent acquisition, DIA. A second technique is targeted proteomics. It measures only a predefined set of proteins with very accurate quantification. A third technique is mass spectrometry imaging. It measures the spatial distribution of peptides or proteins in thin tissue sections. Plenty of software for DDA, DIA and mass spectrometry imaging are available in Galaxy. Here is an overview of all proteomics tools installed on the European Galaxy Server. Other public Galaxy Servers offer a similar or complementary proteomic tool kit. The Galaxy proteomics tools and training materials are constantly expanding and improving. This presentation will focus on explorative proteomics via the traditional DDA approach. Proteomics experiments consist of three main steps. First, the sample is prepared for the analysis in the mass spectrometer. Then the sample is measured in the mass spectrometer. Last, the obtained data is analyzed. Typical sample preparation steps include protein extraction, reduction and alkylation, tryptic digestion and desalting. Before tryptic digestion, disulfide bridges are reduced and cysteines alkylated. This ensures that tryptic peptides are separated from each other and allows their mass-based identification. Trypsin cleaves the amino acid sequences terminal of arginin and lysine. Desalting is a clean-up step to protect the instrument from contamination and clogging. Sample measurement in a mass spectrometer consists of different steps.  It separates the injected peptide mixture according to their hydrophobicity. The peptides elute from the LC column into the mass spectrometer within several minutes to hours. This reduces sample complexity and gives the mass spectrometer more time for the measurement. The acidic LC buffer charges the peptides positively at their end terminus and the basic lysine or arginine amino acids on the C terminus. The LC column is directly connected with the iron source needle. There, high voltage and heat are applied to evaporate the ionized peptides into the gas phase. This process is called electrospray ionization. Inside the mass spectrometer the mass analyzer separates peptides based on their mass-to-charge ratio. The detector detects the peptide ions. Typically explorative proteomics is performed via liquid chromatography tandem mass spectrometry, LC-MSMS. While the sample elutes from the LC column, thousands of mass spectra are acquired. First, a mass spectrum of all peptides at this time point is measured. These mass spectra are called MS1 spectra. From these spectra the N most abundant peptide peaks are determined. These top N peptides get fragmented. N is typically between 3 and 20. This example shows a top 3 method. The filter unit of the mass spectrometer, a quadrupole, allows only these peptides to pass. One after the other is selected in the filter unit and then fragmented by collision with neutral gas molecules. This fragmentation breaks the peptide bonds and generates peptide fragments. The peptide fragments are measured again via the mass analyzer and detector. These spectra are called MS2 spectra. After all top N peptides were fragmented and measured, another full MS1 mass spectra is acquired. MS1 and MS2 spectra are acquired in this way during the elution of the sample from the LC. The analysis of the acquired mass spectra comprises several steps. First peptides are identified via the MS2 fragmentation spectra. From these peptide identities the corresponding proteins are assembled. The MS1 spectra are used for peptide quantification. Peptide quantities are summarized into protein quantities. The information about protein identity and quantity allows following statistical analyses. This was the overview of a typical explorative tandem mass spectrometry workflow. Now we will dive into more details of the data analysis part. Many tryptic peptides of an organism have same or similar masses. Therefore, MS1 spectra don't allow reliable peptide sequence identifications. MS2 spectra allow peptide identification via the generated peptide fragments. The N terminal fragments are called B ions and the C terminal fragments Y ions. The differences between the fragment masses correspond to the mass of an amino acid. This allows manual interpretation of the spectra. However, this is a tricky procedure because in reality the MS2 spectra contain more noise and side product peaks than shown here. Also, in explorative proteomics tens of thousands of spectra are acquired and make manual interpretation unfeasible. The manual interpretation process is automatized with so called de novo sequencing software. These algorithms have improved in the last years. No information about potential protein sequences in the sample are needed. The default software for peptide identification are so called search engines. They require information about all protein sequences of the analyzed organism as faster database. From this they generate in silico spectra which are then matched to the measured mass spectra. This process is often called peptide spectrum matching. It starts with a protein sequence database of all protein sequences of the analyzed organism. Analogous to the procedure in the sample, the protein sequences are in silico digested. This means that the sequences are cut after each trypsin and arginin. These in silico tryptic peptide sequences are then in silico fragmented. All amino acid bonds may potentially break and generate peptide fragments. Therefore, all possible fragments are generated in silico. From each in silico peptide fragment, the mass is calculated. In case of amino acid modifications the mass of the modification is added accordingly. Fixed modifications are added to each occurrence of the amino acid on which they occur. Variable modifications may not occur on every amino acid and therefore two masses, with and without the modification, are calculated. These in silico generated mass values are matched to the mass values from each measured MS2 spectra. A matching score allows to find the best identifications for each MS2 spectrum. Potentially false matches may occur, therefore the false positive rate is controlled. This is done by adding decoy sequences to the protein sequence database. These sequences are generated by reversing or shuffling the real sequences and will not exist in the sample. In case such sequences are considered a good match to an MS2 spectra, this is a false match. One option to control the number of false positive matches is via a false discovery cutoff that includes the best matching scores with only 1% wrong decoy matches included. The protein sequence database is stored in a faster file. This is a text-based file to store DNA, RNA or protein sequences in a single letter code. Each entry contains a header line and the sequence. The header line starts with a greater than sign and is followed by a unique identifier. A proteome is the set of proteins thought to be expressed by an organism. Only proteins that are present in the faster file can be identified, but the more proteins are present in the faster file the higher the chances for false identifications and the longer the computation time. Sources for proteome faster files include Unipro, Nexprot, NCBI or DNA and RNA sequencing data. After having identified peptides, they need to be reconstructed into proteins. This step is called protein inference and is not trivial. Unique or prototypic peptide sequences belong to one protein, but other peptide sequences may belong to several proteins. These peptides are called shared or razor peptides. Most protein inference algorithms assign them to the protein that has the most other peptides. In the depicted example peptide 2 would be matched to protein 1 which is for sure present in the sample because it has one unique peptide. Different quantification approaches exist in mass spectrometry-based proteomics. In explorative proteomic approaches relative quantification methods are applied. They compare the amount of proteins between different samples. Label-free and label-based methods exist. Labels add specific mass tags to the peptides of different samples via metabolic or chemical ways. In label-free approaches every sample is measured separately. Afterwards the protein amounts are compared between measurements. Chemical labelling techniques add a mass label to the digested peptide. Afterwards the samples are mixed and measured in one run. The different masses of the added labels allow distinguishing the origin of the proteins during data analysis. Depending on the labelling technique up to 16 different labels exist. In metabolic labelling amino acids with heavy isotopes are added to the cell culture medium of one condition. During cell growth these amino acids get incorporated into proteins. Thus proteins of the heavy condition can be distinguished by their normal counterparts via a fixed mass shift. For label-free quantification all peak areas in the MS1 spectra are integrated. Peptide abundances are summarized into protein quantifications. This requires decisions about which peptides to include in the summarization. Only unique peptides. Only proteins with or without modifications. Last the protein abundance may be computed by taking the median, mean, weighted mean or some of all its peptides. MaxQuant is the most popular non-commercial software for quantitative proteomics experiments. It performs protein identification via its Andromeda search engine. Protein quantification of label-free and many label-based methods is supported as well. MaxQuant accepts raw data in vendor-specific formats. Typical follow-up analyses include visualization, network and go-enrichment analysis. Finding differentially abundant proteins between different groups requires statistical analyses. MSStats is an open-source software for statistical modeling of quantitative proteomics data. It is compatible with complex designs of label-free and isobaric labeled quantification experiments. First several processing steps are performed. Then MSStats applies flexible linear models to detect differentially abundant proteins. MSStats takes identified and quantified spectral peaks from common proteomics software such as MaxQuant as input. For DDA data MSStats starts with peptide-level data. It applies several feature selection and processing steps in order to account for proteomics-specific data properties. Afterwards MSStats calculates new protein abundances and performs statistical modeling on them. In addition to the results of the proteomics software an annotation file is needed as input. In this file the experimental design is described. It specifies conditions and biological and technical replicates. In case MaxQuant results are used as MSStats input, an additional column with a label type is needed. In a DDA experiment the value is L for all conditions. First, the input data is converted into an MSStats compatible table. For this step several parameters to filter and adjust the input data can be selected. Log transformation brings the peptide intensities into a close to normal distribution. Normalization aims to make the intensities of different runs more comparable to each other. The default normalization method is called equalize medians. It assumes that the majority of proteins do not change across runs. It shifts all intensities of a run by a constant to obtain equal median intensities across runs. Feature selection allows the use of either all or only the most abundant peptides for protein summarization. The table represents the intensity values for the peptides of one protein. The dark gray fields represent missing intensity values of peptides. Missing values and noisy peptides with outliers are typical in label-free DDA datasets but influence protein summarization. For a reliable and robust statistical analysis, missing value imputation is recommended. Missing values in maxQuant mean that they are missing because they were below the limit of detection. This means the values are not missing for random, but for the reason of low abundance. Therefore, the values are only partially known and called censored values. This may also be the case for very low intensity values, which might not be reliable and can be imputed. Censored intensity values are imputed via an accelerated failure time model. Alternatively, they may be replaced with a value obtained from the other measured intensities for the peptide and all the run. Protein summarization is by default performed via 2 keys median polish for robust parameter estimation with median across rows and columns. The calculated run-level protein summaries are used for statistical group comparison. Any two conditions can be compared to find differentially abundant proteins between them. MS stats uses a family of linear mixed models for this. The model is automatically adjusted for the comparison type according to the information in the annotation file. This means MS stats accounts for technical replicates, paired designs or time-course experiments automatically. Thank you for watching.


Hey guys, it's Nate, A.K. The Foot Accountant. Welcome back to the channel. In yesterday's video, I told you guys that I'd be surprised if Icon Swaps 3 came. And guess what? Here's my shocked face. Because Icon Swaps 3 was dropped yesterday with a loading screen about six hours before it was dropped. And of course, everybody right now is on this game grinding the insane Icon Swaps. This is like the best value for time, for when it's been released in the game Icon Swaps I think we have ever had. The players are great, the packs are great, and the icon upgrade, player picks and packs as well, are absolutely fantastic. So, no complaints from me. There is a lot to grind on this game right now. And of course, what we also have to talk about today is the market, because the market is just rising, right? The fact is that people are starting to buy some of those cards for their teams, and the panic selling is just kind of ending. That's also where this market rise is coming from, right? One example, just looking at right now that I see on footpin over to my left is Jordan Henderson, who was like 380,000 coins two days ago is now 430,000 coins. I got countless examples of cards that are moving up in price, and it's probably gonna continue that way throughout this week unless EA do something crazy. So we're gonna talk about all of that in today's video. The icon swaps, maybe the best value. There's so many options. And of course, look at today's content on Tuesday, because Champions League is back, and we have live items with upgrade potential and markets moving. Once again, probably some more TOTS warm-up series packs today. I don't know if I would expect a really, really big day of content, because of course, EA knows. They just yesterday dropped an insane grind for a lot of people with the gameplay for the objectives for icon swaps three. So what might be a bit of a quieter Tuesday, we will have to see. So if you're enjoying the videos on the channel, as always, make sure to thumbs up and subscribe if you're new. Let's start off by talking about the market. Let's take a look at some prices, because a lot of cards that I see right now are starting to trend upwards. The market is rising from those panic selling moments that we had over the weekend. Not every single card, but most cards are up. Remember in last night's video we saw Marco Royce for 330, 340,000 coins? My guy is back to almost 370K. Dempsey was 150, he's now back to 170. You know, Unberg is back up 40K. Mingz was like 245, 250. He's now 280,000 coins.  Like, let's see. Ben Yetter was 820 last night. I bought one, he's about 840 right now. Still pretty rare to 870. So not everything in the whole entire game is up, but a lot of stuff is starting to trend in that way. Foot birthdays as well. You know, Paqueta has been a card that we've been looking at a lot. I saw just a couple hours ago, Paqueta was actually over 500K, and now he's back down a little bit. But you know, we look at this guy like every single video, and you're like Nate, stop looking at Lucas Paqueta. But he's kind of, he's risen up a bit, right? I would not be surprised if he's over 500K pretty consistently. After today, he's only got one page to be there. You've got other cards like Roberto Firmino, 760K. So this guy was like 720,000 coins a couple days ago. Now he's 760, so he is on the rise. Fakir is starting to rise back up. Again, I could continue to look through players upon players on this market, and a lot of them just continue to slowly rise. Now, like this Tony Cruz at 320, that's a bit of an undercut right there. That's still decently low. There are still cards that are kind of low-ish, or cards that haven't really moved that much. So saying the market is rising does not, of course, encompass the entire market as a whole. But a lot of cards can be put under that umbrella that are rising up. Now, one exception yesterday was Pedri. And now Pedri is back up. But for whatever reason, there was some panic selling on Future Stars Pedri yesterday. And this guy was like 1.05. It was a tremendous opportunity to buy this card. He was literally down 100,000 coins. Now he's back up to kind of where he was. So if you got in on that, GGs, there were some other cards that were down yesterday. I know two examples just from the top of my head are both Future Stars. Adam's Farron Torres was like 460. And I believe now he's back up to almost 500K, 485. So both of these cards for Future Stars for him were pretty low. So as it goes for the market in general, with these cards really starting to bounce back and with these player prices starting to rebound over the week this week, if you've bought cards, are you selling them? Not really, not yet, right? All the cards that I invested basically 22 million coins on my account into out of pack special cards, I'm not looking to sell these cards this week. Maybe one or two of them. Maybe I'll take the cash on if I feel like the rises are just simply too much in such a short timeframe. And I wanna have some coins for this Friday. Look at Kempembe, incredibly rare, but 460, 500,000 coins from where he was at 430. That just might be a moment of rarity. But again, yeah, he was 490 earlier today. So a lot of these cards are just bouncing back. And as you take a look at prices on the market, that is a very, very consistent trend. It's because the panic selling is ending. People are starting to buy cards for their teams. And this week is kind of a slower week of content. So again, there's really not a reason to sell. And that's why you've seen, that's why you have seen all the prices dropping over the past few weeks, is because people had reasons to sell, right? All of this time where we were getting panic sold since the start of April, down, down, down, down. It reached the low point. We had another low point this weekend. And now cards are starting to rise back up again.  I think there are still cards that are gonna continue to bounce back more in price, for sure. I would stick to the out-of-pack special cards and I would stick to stuff that is rare and popular. Like I bought some of your rentays at 340, 350 on some undercuts. Ooh, that Tela's is looking pretty cheap there at 108. That actually just got upgrade updated. So I will go ahead and take a look at this card right here. I do think that some cards are kind of out of reach and probably are not at their good prices anymore. Is this sitting there at 108? You know what, I'm just gonna let that sit. Maybe somebody will undercut that and throw up something cheaper because that is a pretty low price for Mr. Alex Tela's. But, and this is something you can do late night.  Oh, it's just gonna sell. Sometimes you let cards sit up and then Footman will catch those undercuts and then people will list below that and that's great stuff. So I am not really selling too many things. I did just sell the Suarez that I bought at 367 or something like that. Not a lot of profit there, but I think that there's gonna be some community tauts leaks probably in the next couple of days and I think Suarez is gonna get in. So I'm just kind of taking the safe cash on that just because I don't wanna risk his price dropping with some leaks of him potentially being in community tauts which I do imagine that he would be. So that's the state of the market right now. Cards rising back up a little bit. Still think they have more to go. So just buckle in, watch the cards rise up. Again, the only thing that would contradict that rise would be some content from EA Sports that would be crazy content. I think we still have not seen the 85 times five e-figs upgrade pack yet. So whenever that drops, that might be a little bit more of an expensive SBC that could cause maybe a slight dip in some prices. I wouldn't expect it to be a huge dip by any means and I need to do these times 11 SBCs or I'm gonna forget. So mental note to do these and save them for the league tauts of course but I don't think there would be anything super crazy today. Maybe a campaign bag player pick. We've seen those consistently on Tuesdays and Wednesdays. Maybe one of those coming out pretty soon. But other than that, I don't think there'd be a crazy day of content today on Tuesday as well as the potential for UEFA Marquis matchups. And we didn't see that last Tuesday there was Champions League like two weeks ago I think and even last week in general. We did not see that. So I'm not sure if we're gonna get UEFA Marquis matchups this late, because there's only of course one game today, Real Madrid versus Manchester United. Huge game and I've got some bail once to watch is on my transfer list. Hoping that he maybe rises up a little bit today pre-game and then I'll take the cash on those probably to sell in the hype. I would love to get 281. I would love to get like 300K because he is really, really rare. Not that many cards at 290. So if he does have a bit of a rise, I'll try to get him out at like 300K. That would be a nice bit of easy profit right there of course. So there's gonna be more live items on the line with upgrades on the line today as well. Guys like Márez, guys like Kyle Walker and Gareth Bale. I think those are the only live items today that are having upgrades, pending on this outcome of the game. Although it would not of course, the cards would not upgrade until after the second leg. This leg would just be the first leg, but it would and it probably will impact prices on the market. So it's probably gonna be a bit of a quieter time on the market, being completely honest, right? What's the main grind right now in this game? The main grind is the icon swaps that EA dropped yesterday, right? Icon swaps set number three. Now again, we didn't have any leaks. We had literally zero leaks. Not even the, there was a couple leaks, maybe right before content drop about what the objective requirements were gonna be, but this is just such a W. And in my opinion, it's basically the best icon swaps for the time of the game that we are in. The rewards that we get for how many tokens you have to turn in. Think about casuals on this game. Five tokens for an icon moments goalkeeper, right? Seven tokens for an icon moments dog leash. I think this icon swaps is tremendous value.  And what set of icon swaps have we seen in the past year that has been like, wow, I really wanna grind for the players? Icon swaps set two, there was a few in there, right? But literally every single one of these choices for the amount of tokens that they are for players, hold it at 17. Okay, it's not the moment, but it's still good. Mateus is awesome at 14. Etto is great, Vest is great. Roberto Carlos is insane. Like literally an end game, one of the best left backs in the game for eight tokens. That's it. And an icon moments goalkeeper that will be at mainstay and you're starting 11 for the rest of the year for five tokens. Tremendous, tremendous dub. The 84 times 25, the 85 times 20 pack. I know a lot of you guys are maybe even grinding for this for like a first set of tokens. That's the only L with icon swaps, right? That you can only get the first nine tokens. And then I think it's almost, it's like 28 days from now, we will be able to get the second set of nine. So you can't get anything higher than the 93 plus icon moments pack or George Best technically with all nine swap tokens from this set of objectives that are dropped. So nothing past George Best can you get until the May 23rd timeframe. So it is going to be a little bit of a wait if you're wanting to go for the 94 plus, the moments player pick or the 93 plus attack or midfielder moments player pick. But again, there's just so many angles that you could take a look at this and say, wow, this is great value. Can we just note that last year an icon swaps three, which came out during team of the season, by the way, this came out during La Liga Tots. So like three weeks after or four weeks after right now, we had not moments best, just prime best. We had moments Schweinsteiger, who we've already had as an SBC and FIFA with a better card than this one for like three weeks. We had Puskas, we've already had an SBC four for a while and we had prime Viera as the best card 17 tokens and we've had a prime moments Viera SBC for a week now. There was an 84 times 20. No, so there wasn't even an 85 plus. There was a 93 plus icon moments player pick and now this year we have a 94 plus pack and 93 plus attack or midfielder pack. So if you compare last year's icon swaps three to this year's right now icon swaps three, it's unbelievable. So GG is the EA, gotta give credit where the credit is due because this is an incredible grind. And again, like I said, especially for a guy like me who loves taking these packs, I'm gonna get all of the packs that I can for team of the season. I'm gonna get the 84 times 20, or sorry, 85 times 20, the 84 25, the 83 times 25, probably gonna take all of these and even the 82 times 25, right? That is literally 95 players that I'm gonna be getting all 82 and above to craft SBCs to do a lot of that content that will be out during team of the season. And I know you're like, Nate, why wouldn't you just do VaynerSar as well? Yeah, I might end up doing VaynerSar. I might do all the packs and then with leftover tokens do VaynerSar. Of course I could do anything up to dog leash, the mid attack mid pack or VaynerSar but VaynerSar would just be great for the team. So probably gonna do that if I end up grinding all the tokens, which at the moment it's just a perfect time to grind and that's what everybody is doing is getting the swap tokens. And I think that's a great idea with the lack of crazy content that we have right now in this game. It is a very, very good idea to be going in here and getting these icon swaps done. Now I have not been claiming these because I was unassigned with gold rare meta or not gold rares out of packs, informs and special cards, investing all of my coins in for a market rise there, but I'm not unassigned anymore so I might start claiming some of these. But I have gotten, I got the Serie A done, Bundesliga, Ligue 1, and then I'm working on the squad battles games at the moment. I'm doing silver MLS Brazilians, which those and some English MLS Silvers are up big time as well. So I was buying Brazilian MLS Silvers for like 10,000 coins yesterday and I do believe they're probably cheaper now. And I paid nine to 10K and they're probably down. But that's the slight price you pay.   Wow, they're still like 9K.  All of Indicates 630, that was bought at 570, big moves. That's what I would do right now with the swaps. Take this time of the lower hype week of content to get some of this stuff done. Evidently I have Silver Beast going in here too. I need to maybe work on this. You can get a lot of objectives done. You can actually combine the Tots Warmup series. Like you see here, I did League One, Sierra and Bundesliga all of those 81 times 11 packs and then the 75 times 15 for League One. I did all of those while doing icon swap. So if you hadn't finished any of those, nice little double up there that you can do for some of those. It's a great time to grind gameplay this week and I think that's the focus for a lot of people. And also getting rivals games in to finish out the season, which I need to take control of and start doing pretty soon here as well, trying to get at Leete for the last set of rewards for the season. So again, that icon swaps grind is just a tremendous dub. If I had to give you a best value out of my opinion for what swaps was, I would have to say, I think with, I know icon moments cards, yes, icons are just, they're not as hype this year, right? That's a fact that I think we can all basically agree on is that icon moments cards are just not as hype. Icons in general, they're cheaper. The stat boost for moments were pretty solid and they're still really, really good cards. But with the way the power curve has progressed with just the special cards that we have in this game, a lot of those outshine icons. And I think that's gonna be continually the case during the team in the season. So it is very tempting to go for, like Roberto Carlos and to get Edward Vaynerstar in my team. But I think I'm just gonna go with Vaynerstar and then I'm gonna go for a lot of packs because all of the SBCs that are gonna be out during team of the season for players that I want to craft, upgrade packs and stuff like that. And then I'm gonna be able to use the fodder that I get from this and put it into other icon moments players that maybe I want to do, that instead of trying to get a gamble pack to go and get them through, I can just go and finish an SBC for way cheaper than it would cost buying players off the market because crafting is so good. I'll be able to get a lot of icons in my club still through that manner. So last call for Oxley Chamberlain, by the way. If you wanna get that done, that SBC is expiring today on this game. The league one challenge, the 81 times 11. And I think we will be re-upping the 83 times five. I think this should be re-upped today. I don't know. I'm not entirely sure though. I've done that twice I think. Hopefully we're able to do it another time today on Tuesday. So other than that, there's really not any leaks. There is actually one leak. Now that I think about it, but it doesn't relate to any content that is coming out right away. At least it seems. There was some code and we'll talk about this really quick to end the video. There was some code added yesterday about cross play being tested in FIFA 22. Now the code is very interesting because it's all over the place. This is completely different code than what we're used to. Cross play disabled enabled, cross play notification title, cross play pending invite. You know, it's all these messages that are maybe gonna pop up in game. So again, we do not know. And as foot sheriff said here for his leak, he said probably won't be on Ultimate Team but definitely coming to FIFA 23. And it looks like it's gonna somehow be tested in FIFA 22. I don't know if that's gonna be in like seasons or pro clubs or Volta, I don't know. But it doesn't, I wouldn't imagine that it would be coming to the Ultimate Team. Who knows, we'll have to see. But I would expect some more information along the lines of that. And maybe they're dropping that stuff in the code right now because they're actually gonna do something for team this season with that. Who knows. So that's just something that we're kind of keeping in tune to and just kind of watching what's happening on the game because that would be very, very interesting if we had cross play enabled at the end of FIFA 22 this year. So again, the story right now in the market is that cards are going up because again, the pain excelling has kind of bottomed out. If you bought cards, if you bought cards this weekend like a lot of us did, then you're making coins really quick to talk about fodder. Fodder's just kind of chilling. There weren't really big SBCs yesterday. I think that if you're holding fodder still today could be a day where you see some cards reach maybe some peaks. Today, tomorrow, probably gonna be some peaks, especially if you have another gamble pack, some other type of coin drain SBC.  So for these lower tier cards, definitely think about listing those for Lazy's if you've invested and maybe taking the coins on some of those. For your higher tier ones, I haven't really sold the cards that I still had. Like Han Danovich is 39K, that's where I bought them at. Jose Fonte is 47, that's where I bought him at too. So we're technically in the mud a little bit and losing only tax on a few of these cards right now but the higher ratings are just not in demand. So unless EA surprise us with some sort of SBC this week, like another icon upgrade pack, not a player pick, then those cards are probably just gonna maintain their value and just kind of chill at their prices where they're at on the market and probably just be pretty stagnant and maybe drop a little bit as we get towards Friday. So that's gonna be a bit of a waiting game if you wanna wait that out a bit which I am currently doing with the Fonte that I have. But I'm gonna keep listing up my special cards for Lazies, man, because I feel like the prices that I got and a lot of these cards were really, really good. Again, we were looking at this on stream. Here's another example of a card that banged. This Chalmeny I got between 460 and 470 and no shot, is this guy 540? Wow, 540, this Chalmeny continues to rise as a French CDM, very OP out-of-packs card. And that's where you're seeing the market rise up right now the most is on those items. I still have some Dempsey's I got in the 140s. He's like 170. MLS objectives maybe helped him out a little bit today, not too much. And I still have a lot of stuff in the club too that I set in there. So just selling cards that I think have risen up a lot getting some quick flips, gonna regain some coins back for the weekend of cards that have bounced up really quickly. But that's the thing, right? Just keep watching the market bounce back up. We'll see if anything content wise today changes the market in that aspect and we'll just be grinding some more icon swaps. Good luck getting your swap tokens. Good luck playing your games because that is the central focus of what is going on on this game right now. So if you enjoyed today's video make sure to hit the thumbs up on it. Comment down below if you do have any questions and of course, subscribe if you are new. It has been Nate the Foot Account and I'll catch you guys later. Peace out.


Well, thank you so much Don and the organizers for the, it's a real honor to be participating in this symposium. I got a notice on my screen. Can everybody hear me? We're fine. Yeah. Okay. Yeah, so I'm going to tell you that my foray with Mortirella really began with this culture here on the right. I was in Reedus Vilgalee's lab and we had the opportunity to sequence some genomes. We had three genomes and so we wanted to maximize phylo diversity. So we picked a Bacidio mycete, an Asco mycete, and a Zygomycete. And the reason we picked this, the Zygomycete is because it was common in a lot of our next gen sequence data sets. It was common in the soil microbiome and these genomes were for metatranscriptomes of forest systems. And so we thought it'd be important to have this one. These TEMs are from Kerry O'Donnell's graduate studies at Michigan State University. And this last one is a TEM of the bacteria living in the hyphae of this genome. So when we got this genome back, there were two genomes. We got the fungal genome and the bacterial genome. So we were excited. We called it TOOFAR. So I'm going to give a little bit of background on the ecology, the biology, and then about the phylo diversity of this family or sub phylum, if you will. I'm going to, the third part's going to talk about the bacteria and then the fourth part's going to talk about morterella plants interactions. So these fungi are almost as charismatic as Kabir's, Sewillis, and Betsy's endophytes. If you've cultured fungi from soil, you've most certainly come across this rosette pattern of growth, which is distinctive of most of the genera in this family, though the form of the rosette is dependent on the diet of the fungus. There's been a lot of history on this group since the mid-1800s. Linamon was one major, made a lot of contributions looking at the sporangia forms for differentiating a lot of the species as well as some of the macro-morphological characters and described a number of species of morterella. However, there's other genera in the family, and so I had to bring it back to the phylo, and so this is from Roland Daxter. He isolated desophora from woodmouse dung in Cambridge, and he had this culture alive for years, but during his travels in the West Indies, it died, but he still had prepared slides, and he described this new genus, desophora. Lobo sporangium is another genus in the group with its distinctive sporangia shown here. Meredith Blackwell and Gerald Benny placed this in the morterellaaceae, and it's only been isolated three times. So these fungi are all synesthetic, though they can make cross walls, and they often wall off old parts of their mycelial network. They're characterized by bi-directional cytoplasmic streaming, and you can see that here. This is a genus that we described, Beniella erionia, which is shown with these kind of chained chlamyto spores. In the family, there's at least 200 species, and likely more, and the species can either be sexual, homothalic or heterothalic, so some of them can self and others need to out-cross. And following up on Matt, here's one of Matt's interesting finds in South America. This is moticellarineiformis, which is a sporocarpic morterellaaceae fungus known only from South America. That's species. We have a species in North America, and there's a third in New Zealand. So about the ecology of morterellaaceae, it's still really understood. Peter gave a good overview that they might be implicated in a kind of necromass turnover in soils. For sure, morterellaaceae are a core part of the soil microbiome. Nutritionally, they can utilize simple sugars. They're very good at utilizing chitin in their genomes and protein, their genomes are enriched in protease enzymes. A number of the groups have been shown to be endophytes and plants, and in some cases can promote plant growth. And these are industrial fungi. They're used in lipid production commercially. So my first PhD, the first PhD student in my lab, Natalie Vandepole, recently published this work, which used phylogenomics and a combination of phylogenomics and multigene phylogenetics to try to resolve what was known as morterella, the genus, which was a polyphyletic genus. And so we used monophily as a way to try to describe these different genera. So we can better ascertain maybe what their ecology is and their distribution. So we used the low-coverage genome sequencing of 70Taxa to have a highly resolved tree, which we then expanded with the use of multigene phylogenetics with a six loci. So we kind of had this super tree approach. We constrained the backbone. And so you see up top, here's Beniella, the sister group of Modicella. Here's DeSophora, which is related to Gamziella. And here comes Lobosperangium out on a branch. Morterella alpina group, polycephalus, the type species, so that we retained the genus morterella for the alpina clade. Linnomania is what we would call morterella elongata. So a lot of my talk is now talk, I'll use the new name Linnomania. And Podella in orange is another plant-associating group. So Podella, morterella, and Linnomania are often isolated from plant rhizosphere. Now morterella ac are known to associate with bacteria. In fact, nearly 20% of isolates will harbor bacteria, either external or internal. And so here is kind of a little bit of a meta-analysis that combines data from our lab with those from Aliska Okrasiska and Takashima, who recently published on these endobacteria. So in blue, peribercal dairea, these are kind of facultative endobacteria associated with the hypo-plane there in mucora, umbilopsis, and morterella ac. Teresa Palauska talked about rhizopus and their bacteria. These are pink here, myceto-habitins, and those are endobacteria. And the AMF in green here is shown candidate as glomerobacter. These are in the gigasperaceae, gigaspera and scutelospora. And then in red are those bacteria that I'll be talking about, peribercal dairea related. These are mycoavidus, and there's three main clades of that. We might call them species, but they're actually quite diverse. So how do you know they're endobacteria? To really demonstrate this, transmission electron microscopy, or fish, are used to confirm this. And so here's two different groups that we show from Alessandra D'Zero's work. And then fish is shown here from the Takashima and all paper in 2018 showing these bacteria inside the hyphae and inside sporangia spores. So we've gotten a number of genomes back. And if we take their genes out and align the orthologous genes, then we can look at a kind of presence absence. And this is kind of a little bit of a crude way to look at it. But what's fascinating to me, so the first one here, mycoavidus species 3, this one actually appears to promote the growth of the host. So when the host has this bacterium, it grows a bit faster. The two below it, one of those is from Linomania elongata in North Carolina. The other one is from Linomania elongata, same host, but isolated from Japan. And so here we have the endosymbion of the fungus. And if you look at it, they're not completely the same. But wow, there really is a lot of conservation here, which to me is kind of amazing. We never detected any plasmids. Their genomes are kind of small, 2.5 to 2.8 megabases with a little over 2,000 genes. We've been able to use some associative mapping techniques similar to what's used in GWAS to look at genes under positive selection in these bacteria. And there's not a lot. We had a short list. But of those that we found, they tend to be involved in energy and amino acid metabolism. I should say a lot of them are amino acid oxytrophs. Like for instance, to grow them, you have to supplement with cysteine and other metabolites. So there's a second group of endobacteria that I want to talk about. These are the molecule-related endobacteria. And this was a passion of Alexander Desiro who came to work in my lab as a postdoc. He had worked with Palabonfonte and characterized MRE in our muscular mycorrhizal fungi. And then he discovered them in endogony, which is an ectomycorrhizal fungi in the endogonyllis. And so he was really wanted to know, are they in mortiurelacy as well? And in fact, he was able to demonstrate that they are only in 3% of our cultures. We went through hundreds of cultures, but he found them in nearly every clade at the time, we would call a genus now. And there were three main groups of these endobacteria, molecule-related. It has these beautiful SEM done in Robbie Robertson's lab, where you can actually see the cells dividing. So they are actively growing in these fungi. We've been generating some genomes from these. These are very hard to work with because they are so divergent from each other. But they do have a, there is a clade that is fungal-specific. So this is work of Julian Lieber, where we're looking at, we're doing kind of a comparative approach based on these orthologs. But the challenge is a lot of these are just hypothetical proteins. We just got the Unitig last week of the smallest genome yet of one of these MRE was 326 kilobases. There's between 1,100 to 1,400 genes of these bacteria. They can have plasmids and one isolate has a mitovirus in it as well. If you look at what they are really there, what we know about the genes that are there is a large part of the genomes involved in translation, replication, repair, and protein metabolism. So the question of course arises, what is their impact on the host? And so we've looked at this in a number of different ways. Jesse, Julian published early on or a few years back anyway, showing that when you remove these bacteria, the fungus is a little bit relieved and it grows more fluffy. You get more bio-bass. And so that was in the BREs. We see the same patterns. And it's not for all BREs. As I mentioned, there's one group that seems to promote the fungal host growth. If we look at MREs, we see a similar pattern where, well, actually, we see that morterella, this species here, which is alpina, it actually grows faster, more bio-mass at four degrees than at 22 degrees. And what we see here is it's only at room temperature that there's a change, a statistically difference in their growth rate. And we use QPCR to demonstrate that that's because at this room temperature range, the bacterial population is much higher. So at these low temperature or high temperature, the bacteria don't really, they're not as active within the mycelium. So following up on this in collaboration with Powell Mitchell, we were able to put these isolates cured or not. So we use antibiotics to remove the bacteria cured or not in these chambers for real-time, time-resolved emission analysis. And here's just kind of a cool example, because here we have them and we're ramping up the temperature in the incubator every few hours. So at 20 degrees, you can see, I'm just showing one example here. This is butyric acid, which is a known metabolite from mycoplasmas. And so as you ramp up the temperatures, the activity of these bacteria goes kind of off the charts here, especially at 30 degrees. It doesn't even go up to 37, but they would probably lose that signal. How about the fungal metabolome? So this is using metabolomics. This is an S-plot that is looking at how you can discriminate cured from wild-type isolates. So this is cured here as in red. And these are the metabolites that can discriminate the two isolates. And they're largely, when there's no bacterium, you largely get a lot more acidic polyunsaturated phospholipids. When the bacterium's there, there's a drastic change in the metabolism. It's not just a few metabolites being broken down. There's a huge shift in the fungal metabolism, with stearic acid being particularly abundant in MRE-infected isolates, as well as polyunsaturated phospholipids. Most of these metabolites are not well characterized. So how about mating? So it's been shown, Teresa, yesterday showed that with mycetohabitins, that they are required for mating in rhizopus. We see the opposite here for our burkholderia-related endobacteria. So if they're present, it suppresses, it prevents mating in morterella. And so this is, we showed this in a heterothalic species, litimania elongata. Takashima showed this last year. They published it in a homothalic fungus where it was sterile until they cleared the bacteria out with antibiotics. And then they got zygospore production. So that was kind of cool. And it showed this same thing that our work was showing.  And they are most definitely thought to be vertically transmitted. So this third section, I'm going to talk about some of these interactions of morterella with plants. This is work here. I'm going to highlight from Davis Matthew, who's interested in fisco-mitrium patents and its impact on how morterella interacts with the moss and how the bacteria is, there's a role of the bacteria in this interaction. And I'm just going to tell you that there's not, we didn't see any impact of the MRE or BRE on the host response. However, we did see differential effects of the different fungi on the host. And so Beniella has had more of a parasitic response on the plant. So this is based on plant genes that were overly expressed or significant differences in stress response, immunorespons, apoptosis, where Linemania elongata seem to be more of a mutualist or a friendly interaction with DEGs involved in carbon metabolism, nitrogen growth, development, and decrease in stress. This is, we wanted to see about with flowering plants. So this is work that Natalie van de Pol did with Arabidopsis and morterella. So from the same soil sample, we isolated two fungi, one of them the same species, one carried MRE, the other carried BRE. And what she showed here was there is a phenotype in the seed mass and the total seed number of those plants grown with morterella. We had been using millet and uninoculated, you know, millet not inoculated in no millet and as these two different types of controls. We were concerned that millet might, it can be allelopathic, it can also be a nitrogen sink. So she moved to these plate assays and so there's no millet confounding factor. And what we see is there's a, there's a significant impact. So these are colonized, these are not colonized negative control. The aerial biomass is significantly improved. But again, similar to what Davis found is we didn't see any impact on the endobacteria. And so how does it affect the aerial plant growth? So she did RNA-seq experiments and looked at some of these genes and it appears to be involved something with plant hormones, modifying oxen, ethylene, and ROS response pathways.  And this is work that was done by a postdoc in my lab, Xi'an Du, who's now a professor in Hawaii. They worked on my lab, the lab next to mine worked with micro algae.  So we wanted to see if morterella could help bio flocculate these micro algae. And sure enough, we found that some groups did, especially the linimonia clay, it was very effective. And you can see these hyphae kind of turn green. When you put them in a jar with these algae, they flocculate to the fungal mycelium. Not only that is, this is kind of cool. Clamidomonas has flagella. So it actually swims very quickly to the fungus mycelium when they're put together. And they form this kind of biofilm together. And it's a protective matrix. So we did this experiment with the oxidation where we put bleach on the fungi. And immediately if there's no, if it's just the algae, they bleach in a second. But if they're grown in this biofilm, they don't bleach and they persist for days, still active in photosynthesizing. What's the role of bacteria on this flocculation? We didn't publish this because this was really, our results were different. We come in, they look green, they're flocculating, we come in the next day and they'd be white, they bleach out, and then sometimes they turn green again. We did look into it and it appears that with the endobacteria, there's a higher ROS content. There's a lower viability of the algal cells, less chloroplast. So we think there's a negative response of the endobacteria. But the challenge is, is we have to monitor, we need to use QPCR so we know what the endobacteria population is throughout these studies. If you just grow nanochloropsis alone, it has a smooth cellular surface. But if you grow it in the presence of a fungus, that outer surface is removed and it has these irregular tube-like extensions that actually make contact with the fungal cell wall. And so here you can see the cells all around, flocculating all around. They stick to the mycelium. We did some carbon tracing studies with C14 where we labeled the algae and then put them with the fungus and we did this in a couple different ways. We had a no-contact control where there was a membrane between them that solutions could move between. We also used heat-killed cells, so we weren't lysing the cells, but we would kill them so they're not living. And it turns out that the signals pretty strong in those cells that directly interact and they have to be alive. And the heat-killed cells, those were put in the vial too. So what this means is this is a biotrophic interaction. It's not a saprotrophic decay kind of interaction going on. We did a similar thing with nitrogen where we were able to show that nitrogens move in both ways between the partner. It looks like a little bit more is moving to the algae than to the fungus. In here, we didn't see that a contact was necessary for this exchange. So this is kind of the coolest thing to me was this long-term effect of co-cultivation. When carbon is limited, these algae can become internalized within mortarella hyphae and they can persist for months in this condition. Whether these fungal cells are still, I don't know how much cytoplasmic streaming is going in when they become chock full of algae like this, but the colonies are alive. And we have some nice TEM that kind of show this condition. So here's the fungal cell wall showing continuous, and these are the algae actually living inside the fungi. You can see their chloroplasts are large, they're healthy, they're happy. And here you can see the fungal mycelium has cytoplasm. So it is, this one's alive at the time of sectioning. And as far as I know, I'm not aware of any fungi ever really taking up algae or being shown to do so. So in conclusion, there's now 13 reference genera in mortarella ACE. And these fungi, all of the genera can host bacteria, and they're fairly common. And so this kind of evidence supports this idea of an early invasion. So the fact that these clades, both BRE and MRE are in our vascular mycorrhizal, the glomer amicotina, bucar amicotina and mortarella amicotina, we suspect so it was an early invasion. So let's see, BRE but MRE inhibit mortarella mating. Linomania appears to interact with vascular and nonvascular plants, kind of as a mutualist, and it might be a bio-troth association with algae. But these interactions aren't affected by the bacteria. So with that, I want to thank folks in my lab who did this work, other collaborators, the Zygolife Consortium, and JGI for helping with a lot of this sequencing. Thank you.