Hi everyone, Joe for jaspyscasebreaks.com. We did it, thanks everybody. We filled jaspys high end, three box, we love Tops baseball mixer. Random team break number three, featuring three high end boxes. A box of 2021, they're all 2021. A box of icons, a box of Tops sterling and a box of luminaries. Remember that luminaries is a set where I pulled that 50 auto book number of years back. Big thanks everybody here for making this happen. Thanks to the people who bought teams, bought spots straight up and congrats again to the people who won spots. And that, those are the combo teams up top. Arizona, Kansas City, Tampa Bay are comboed up. So there should just be 27 on each list. Let's find out. Let's roll it, randomize names and teams seven times. One and a six, lucky seven times. One, two, yeah we got 27, three, four, five, six and a one, seventh and final time. We've got Brian down to PJ. We might get a phone call. Oh, there's plenty of breaks that feature. How much we love Panini too. All right, so big thanks everybody there. One and a six, seven times for the teams. One, two, three, four, five, six and a one, seventh and final time. After seven, we've got the brew crew all the way down to the Yankees. We're playing right now. They're up seven, six in the top of the ninth on the, no, Mets are up seven, six on the Yankees. The Yankees are threatening here in the top of the ninth. All right, wait, what happened here? Why do I have 28 on here? Sorry, thought I got that randomizer right. What are we comboing here?  So hang on, let's redo that randomizer to make it a proper 27 spot randomizer. So Rays, Marlins, Royals, and Diamondbacks. Let's abbreviate those by city. Arizona, Kansas City, Miami, and Tampa Bay. Jam myself up Rex. If only you were here to tell me that there were 28 items on that list. Now this is the proper list, 27 items, seven times. One, two, three, four, five, six and the real seventh and final time. Giant sound of Phillies. There we go. All right, Brian, you have the Giants, PJ with the Brewers and the Mets, David with the combo spot, Arizona, Kansas City, Miami, and Tampa Bay. Carrie with the Cubs, PJ with the White Sox. Sean with the Pirates, Jeremy with the Orioles and the Cardinals, Bennett with the Braves, Nancy with the Rockies, William with the A's, Jonathan with the Twins, David with the Yankees, Jeremy with the Tigers, PJ with the Red Sox, Jeremy with the Mariners, Mikey with the Nats. PJ, you got my Dodgers. Josh with the Indians, Mikey with the Rangers. Kim with the Padres, Nancy with the Blue Jays, the Angels and the Astros and the Reds. All lined up there together and PJ with the Philadelphia Phillies, the Fightin' Fills. All right, let's sort this by column B by team and we're gonna pause the video. When we come back, we're gonna see if there's any trades and then we'll have the break. Stick around, BRB. All right, welcome back, folks. No deals were done here. In Jaspy's three box, high-end Wheel of Tops at Baseball Mixer. Here on Sunday the 12th, thanks for spending a bit of your Sunday night with us. That list right there remains the same. Thanks, everybody, for getting in. Appreciate it. All right, so we're gonna start with diamond icons and we'll go to top sterling and we'll close out with luminaries. All three excellent boxes. Thanks, everybody, for making this happen. Ooh, look at that. What is that? It's a preeminent pieces relic card. Might be a piece of the cleat. That is awesome. You really think they'd fire David Ross after like a season or two? Maybe. All right, let's see what's here. I think let's flip it this way right here. Good luck, everybody. We've got nice start. Five out of five, Cal Ripken Jr., red ink autograph, remember? Out of five and under, get the world famous train whistle. That's gonna go to the Orioles, Jeremy Port. Jeremy. All aboard the Big Hit Express. Woo-hoo. We've got a redemption. It's Ken Griffey Jr., Mariners. That'll go to Jeremy Port with the M's, two for two. First one was with the, both of them are actually with the spots that he won in the filler breaks. Next up is Nolan Ryan, Angels edition. Two out of 10, going to Nancy, who also won that spot. Four out of five, Pedro Martinez, PJ with the Red Sox, gets the out of five and under. Remember, it gets the train whistle. All aboard. Nice, good start. Then here we have another train whistle. The guys in the chat were talking about how maybe Ryan Sandberg, future coach of the Cubs? Why hasn't he been, has he done any coaching at all? That goes to Kerry and the Cubbies, nice. Piece of his lumber. The old Cubs jersey, right, old Cubs colors right here. Five out of five, nice on-card autograph. Coaches in the Miners. All right, maybe his time might be coming. Kerry, all aboard the Big Head Express. Woo-hoo. All right, we've got Joey Bart, 12 out of 25, red ink autograph for the Giants who look like they're about to wrap up this division. That's crazy. As a Dodger fan, Brian with the Giants. And we've got some Braves, Dale Murphy, nine out of 25. That's right, Sandberg did manage the Phillies for a bit. Bennett with the Braves. There's Juan Mirachal, nine out of 10, red ink autograph. Another giant for Brian. And then, oh, one more and then the thick card. Ooh, we got a cut autograph. What a box, three out of four, that's Ted Lyons. Ted Lyons, old White Sox pitcher, Ted Lyons. Ted Lyons. Ted Lyons lived from 1900 to 1986, played with the White Sox from 1923 to 42. And then back in 46, and then a couple years as a manager, he was an all-star two-time AL Wins Leader and AL ERA Leader and a Hall of Famer, eighth ballot Hall of Famer, got in in 1955. PJ has the White Sox, old White Sox legend, out of four, cut autograph. That's a nice cut auto too. Solid text, centered nicely, no other texts or anything like that around there. Pretty nice, PJ, all aboard the Big Head Express. Woo-hoo. Now what have we here? This is usually a piece of a cleat, I think. You can see a little bit of the cleat right there. Wow, that's a one-of-one game use memorabilia. And it's gonna be Paul Goldschmidt. Goldy, nice. And you can see the scuff marks out on the bottom of the cleat as well. Definitely game use. That is awesome. Preeminent pieces. That is for the Cardinals. Jeremy Port with the spot that he won in the filler. Jeremy, all aboard the Big Head Express. Woo-hoo. That is awesome. I guess we'll have to find a, maybe we'll just reuse this box for it, but we'll set that over there for now. But wait, there's more. All right, we got two here. We've got MVP award winners and Rookie of the Year winners. Let's go with Rookie of the Year award winners first. And it's gonna be another train whistle. Wow, one out of five, quad relic and autograph. Also commemorating the 37 stolen bases he's had in that 2019 season. I feel like someday, if they let him, I don't know if they're gonna let him keep stealing, but if they let him, I feel like he can have a 40-40 season someday. Nice. That's Bennett who bought a spot straight up, got randomized the Braves and gets the Ronald Acuna Junior out of five. Bennett all aboard the Big Hit Express. Woo-hoo. Let's see what we got here. We'll use that sponge maybe to protect that cleat part too. Next one is another out of five, another train whistle. Two-color patch and autograph Miguel Cabrera. Detroit, Jeremy Port with a spot that he won in the filler gets the Miggy all aboard the Big Hit Express. Woo-hoo. Rex is saying, this is a serial number break. Yeah, there's been three one so far. Imagine if those are in a random number block. All right, final one here, 2021 luminaries. One in case autograph or autographed relic. Good luck everybody, thanks for the fill. It took a little bit of time, but I think the weight was worth it. The weight was worth it. The last one here, maybe it goes this way. So we've got the luminaries logo down there. Maybe we go down this way. See the top of this person's head first. Got another train whistle, it's out of five. You can see it right there, three out of five. Ooh, a Yankee. It is Alex Rodriguez. That's pretty cool. Autograph Hip King's card, number two career hit total as Yankee's third baseman. Yankees, David Ames with a spot that he bought straight up gets the out of five A-Rod. David, all aboard the Big Hit Express.  I mean, this break was exceptionally good. These mixers have usually been pretty good, but it's almost, it is worth doing a recap. The out of five Miguel Cabrera, the out of five Acunia, the out of four Cut Auto. You got old school Juan Marichal, Dale Murphy, the future Joey Bart, Ryan Sandberg, Pedro Mart, Ryan Sandberg out of five, Pedro out of five, Nolan Ryan, Ken Griffey Jr. redemption, and we started off with a Cal Ripken Jr. out of five. Oh, and let's not forget the piece of Paul Goldschmidt's cleats. That's pretty awesome. Pretty great break, folks. Thanks for getting into it. I'm Joe for jaspyscasebreaks.com. That was our three box high end. We love tops. Baseball Mixing, this is why we love tops. I'm Joe for jaspyscasebreaks.com. We'll see you next time for the next one. Bye-bye.


Before I get started here, actually, you know how when people publish journal articles, they have to disclose their conflicts of interest first. I actually have a disclosure to make. I have returned to veganism, and I'm actually being serious. I've been a vegan for the past three hours, and I feel fine. So if that's going to bias my information, I'm very sorry. I felt like I should be honest. Anyway, seriously, I thought about tidying this presentation something different. Is that in the art of being wrong sometimes? Because I feel with any pursuit of knowledge, one of the most important things we can do is not just question other people's beliefs, but also question our own. In fact, that might even be more important. And one fantastic way to do that is to try to see yourself and your beliefs and your worldview through the eyes of someone you disagree with. And so enter the plant-based diet people. Clearly, some of our sworn enemies in this community often seem to be hating us as much as we hate them, and so there's often this war going on. But for today, I want to present something kind of devil's advocacy and actually look more closely at the results and how they may have achieved them. And so we're going to be looking at a very specific kind of plant-based diet, and that is the one espoused by these dapper young gentlemen. We have John McDougal, who's the author of The Start Solution, Neal Bernard, who you might have recognized from a debate with our very own Chris Masterjohn recently, and Caldwell Esselston, who's known for his dietary treatment of heart disease.  No, seriously, he actually doesn't have a lot of clinical research, if any, backing up his particular brand of plant-based diet. So I'm not going to include him in this case here. And so for the maning people, the diet-based spouse is pretty consistent. It is under 10% of calories from fat, no added oil whatsoever. Starch-based, low in salt, low in refined sugar, low in high fructose corn syrup, and generally low in refined grains as well. And on top of that, there's little to no animal foods allowed in these programs. With the exception of some early research done by Caldwell Esselston, where he did allow skim milk. So then he met T. Kong Campbell, who convinced him protein was evil. And so he dropped that from his program. And I do believe Ornish is actually using supplementary fish oil in his program now. So in the past, I have rationalized the success of these diets based on their overlap with the ancestral community. And those include areas like excluding high omega-6 vegetable oils, which brings their proof intake very low, limiting refined grains and sugar, using whole foods instead of processed foods, and there's always the option of it being some kind of healthy lifestyle overhaul that masks the perhaps negative effects of their diet by compensating with more exercise, ceasing smoking, so on and so forth. And I'd like to take this moment to apologize, because I think I have jumped the gun on justifying it with only these items. And I feel I have not in the past looked closely enough at the success of these people and some of their rationale. So I was, for the prepping of this presentation, I actually found quite a few things that shocked and disturbed me and made me realize I have been wrong about some things. So I'd like to apologize for anyone who has taken my word as gospel, which I hope no one has. But if you have, I would like to present a slightly different version of events today. And that is not a joke. So there's more to the story. So to start off, I want to dig into some research into some people that are not well known, but they're from the past and they have some great information to explore. So this is our current generation of dietary doctors, and some of us may be familiar with them. But before any of these guys, and serving as the inspiration for many of them, was a man named Nathan Pritikin. Who's heard of Pritikin? Good, lots of hands. So short story, he was an engineer who had heart disease, was able to reverse it using a low-fat vegan diet, and then started a longevity clinic trying to do the same for other people. He also happened to be quite buddy-buddy with George McGovern, the guy who gave us the 1977 Dietary Goals. Don't you love that heart? Got to text Nathan after my Senate meeting. Love him. So this duo here, they also had quite a bit of influence on the direction of our national dietary guidelines. But before Pritikin was somebody else, a guy named Walter Kempner, and he would have heard of him. Much fewer hands. He is fascinating, and we're going to talk about him. So this was a German guy. He was actually a German refugee who was Jewish. As soon as the environment in Germany became hostile towards Jews, he left for America, and he started working at Duke University. And that is where he started something called the rice diet. Anyone heard of the rice diet? Few more hands, good. This is very interesting. So 1939, after he had been experimenting with usually animal tissue to find potential cures for kidney disease and kidney failure, he came up with a theory that kidney failure might be able to be treated using a very low sodium, very low protein, very low fat diet. And so he ended up testing this theory on humans. He came up with this diet that was essentially based on rice, rice with every meal, usually in the range of 700 to 1300 calories of rice alone each day. Unlimited fruit, unlimited fruit juice. And if you have any rotten tomatoes, please prepare them for launching, because he also allowed unlimited sugar. In the range of about 100 grams a day on average, 400 calories, some patients were eating as much as 400 grams of sugar. Out of the bag, this is pure white table sugar, about 2,000 calories worth a day. So the composition of his diet ended up being 565 grams of carbohydrate a day on average. Only 25 grams of protein, 5 grams of fat, very, very, very low sodium. The reason he excluded vegetables was actually because they had too much sodium for his theory. And it's important to note that this is not a low calorie diet. People were eating between 2,000 and 2,400 calories a day, which is for this kind of diet trials of this variety, that's actually quite a bit. It was not a super low calorie diet. So what happened? Did they all have insidious weight gain? Did they all die? Actually, the results were kind of shocking. Here's two files, or two pictures from Kempner's files at Duke University, just of two patients. In the course of 11 months, this gentleman lost 112 pounds. This lady lost 121 in the same amount of time. On top of that, this was not an anomaly. In 1975, Kempner published a study of 106 patients, just a sample of the thousands that he had, that had lost an average of 140 pounds on this diet. And shockingly, to some of us, diabetics were going off their insulin or even reducing, in most cases, they're definitely reducing their amount of insulin they needed. In many cases, they could actually completely go off their insulin, even if they hadn't lost weight. This is important because we know that any diet that creates negative energy balance will probably be beneficial to diabetics. And because these diabetics were going off insulin, regardless of whether they're eating fewer calories, this is kind of big, it's kind of awesome. Abnormal EKGs and heart disease patients normalized on this diet. We're not even talking just about a short-term period either. He followed many of his patients for years, in some cases, decades, eating this diet. It was, by the way, supplemented with vitamin, if you're wondering how they didn't die. And it ended up working, being very effective for not only renal failure, but also congestive heart failure, diabetic retinopathy, people who were going blind from their diabetes could see, again, after they started eating this diet and stayed on it. And it's important to note that this low-fat diet, this was going on 14 years before Ancel Keys even made his six-country graph and supposedly started the low-fat movement in America, 14 years before Keys. We like to think that he was the guy who created all of it. We like to blame him for single-handedly changing America's direction and introducing the idea that fat is bad. He was actually a latecomer. Stuff was going on way before him. So something else quite fascinating is that as patients were eating this diet for a number of years, as their conditions were stabilizing, reversing, seeming to be cured, they ended up adding back foods slowly, very, very slowly, foods that were not allowed on the diet back into their eating plans. And if they did it gradually enough, they were able to maintain all of the benefits that they got on that diet without a recurrence of diabetes symptoms or a recurrence of heart disease symptoms. So essentially, they were more or less cured. And the reason this is really important and in my mind really fascinating is suppose we take a low-carbohydrate diet and we put a bunch of diabetics on that. We're gonna see some awesome success with many people, but it's only gonna last as long as people stay on that diet. It's a Band-A treatment, essentially. And for some people, not to trivialize people who have had success on low-carb diets, but some people love the Band-A treatment. They're fine with staying on that program for the rest of their life. Oh, look at my awesome Flintstone neon pink Band-A at all, wear it proudly. But in the case of this type of diet, there's actually a reversal of the disease itself and the ability to regenerate normal glucose metabolism, which is kind of fascinating. So of course, there were confounders. One being that this diet was obviously very hard to stay on because social reasons, psychological reasons, taste reasons, probably physical reasons, too. So what Kempner did, being the typical German he is, he used to whip his patients with an actual whip to get them to stay compliant. And this erupted into a giant scandal shortly before his death in the late 90s. And his response when people asked him why he did this, he just said, I have whipped people in order to help them. And because they say they want to be whipped. Whether or not that's true, I do not know, but we can view it in that sense as perhaps an early incarnation of the biggest loser just with less TV and more sadism. So regardless, that is important to consider because this was not an easy diet for people to stay on. And it did take drastic measures in order to help them do so. But of course, Kempner was not the only person in the middle of the last century who was doing this kind of thing with low fat diets, not the whipping, but the diet. So of course, Pritikin again, engineer, had cured his own heart disease and was very interested in helping other people do the same. So he started this clinic, which you can see a vintage picture of down in the bottom. It used to be an old hotel. He opened the Pritikin longevity center and tested the diet on others. If I had more time, I would list out some of the results that he found, but he can easily do a Google scholarship search and find some of his findings. He had great success treating not only heart disease patients, but also again, diabetics and people who were overweight. Quite a few conditions seemed to improve on his very low fat, oil-free vegan diet. And what gets very interesting to me is the rationale he had for why excess fat was bad. His first point was that it interfered with carbohydrate metabolism, which we can look at it from that perspective and see that as kind of valid. Elevating cholesterol, that's an obvious one. He was definitely a cholesterol man who wanted to keep that very low. But the very interesting thing that we don't discuss very often was the idea that eating large amounts of fat might produce tissue atoxia, basically when the tissue is not receiving oxygen. And for Pritikin, the first idea that sparked that third bullet point was a study with hamsters. Hold your disbelief, I know it's a hamster study. We're gonna talk about why this is important later.  So these hamsters were fed a cream meal, just a pure, heavy cream.  It was not terrible. It was probably still out of those beautiful glass jars. And then their cheek pouches were observed.  And basically what they found was that the erythrocytes started clumping together a few hours after the ingestion of fat. The blood became latexant.  And many of their capillaries began becoming blocked. And what's interesting is the plasma oxygen level dropped to about 68% of what it was originally. So again, it's just a hamster study. I know what you're thinking. We are not hamsters, maybe we wish we were because they are so freaking cute. We're humans. So they repeated the study with humans. This is the best part of the presentation which is to listen up very carefully. So basically in 1955, again, middle of the last century, milk was probably not contaminated with a lot of horrible things yet. Some researchers took 14 patients with angina, which is chest pain related to advanced heart disease. And they had them fast overnight. They were not allowed to smoke, weren't allowed to eat or drink anything else in the morning of this experiment. And then they drank on an empty stomach a glass of heavy cream. Big ol' glass of heavy cream, nothing else. And then they waited. They waited six hours. They were monitored, given EKGs. Their blood was taken samples of, and what happened? Again, there was the influx of chylomicrons to be expected. There's also reduced oxygen carrying capacity in their blood after about five hours. Platelets and urethrocytes started clumping together. And at the peak of all of this happening when the fat was hitting the bloodstream at its most severe peak, there are 14 angina attacks. And EKGs, they were indicating that the heart muscle is not giving enough oxygen. Again, this is advanced heart disease patients. So you might say, okay, maybe that happens after anything they eat. How do we know? So the experiment was replicated using a fat-free drink. Exact same calorie content and volume bulk-wise. It was just nothing but protein powder and some refined carbohydrate as the macronutrients, which maybe from our whole foods perspective is a much worse option than a glass of wholesome cream. Again, weighted, weighted, weighted, we're tested, we're monitored. What happened after five hours? Nothing. Why? So, of course, there are a lot of confounders in this very small experiment. One being angina patients are not representative of the normal population. They're not, they may be more likely to be ApoE4 carriers who we do know may have a different form of fat metabolism and cholesterol metabolism that could make them react differently to glass of heavy cream. In addition, if they had been adapted to say a low carbohydrate diet, if they'd been eating a ketogenic diet, maybe their reaction would have been different and would have been less severe. There's of course the question of what the long term versus the short term effects of this very short experiment were.  And then I was thinking this, and oh, wait a minute. I don't, I'm not trying to scare you and I'm not just saying at all that this is a harmful practice if you're a healthy person. But there is at least one small but well designed and fascinating study that is already, what, 60 years old that did show if you have heart disease and you consume a large amount of dairy fat in one sitting, that essentially your vascular environment becomes much more conducive to having a heart attack. We haven't looked at this. So moving on, of course there's been additional experiments showing very similar things using low fat diets to treat heart disease. And again, the problem is they're always very confounder-ridden, but nonetheless, I think they're worth looking at and trying to prune apart to see why they're working. We have Esselstyn who's famous for his oil-free vegan diet that he used on Bill Clinton to, you can see Clinton down here. So he made Clinton heart attack proof apparently and also turned his hair gray. Yeah, good job. And so he used, in addition, to keep his patients' cholesterol below 150. If diet alone could not get it that low, he would put them on statins. So that's another confounder. And nonetheless, his first study did show that he halted progression in 100% of his adherent patients and reversed, had actually reversed heart disease, showed some signs of that in 73% of his patients. Unfortunately, those percentage points might not mean a lot because he only used 18 people. So that has been a big criticism of Esselstyn for a long time and a reason that both myself and many other people have not taken his study all that seriously. Lo and behold, June 2014, just a couple months ago, he came out with a new, bigger study. This time he used 198 people. 177 were adherent and the other people just couldn't stick with his diet. So the cardiac event rate for his adherent group was only 0.6%. 62% of the people who didn't follow his diet but were enrolled in the program ended up getting either a stroke, heart attack, or something else along those lines. So that's a pretty big difference. And again, it's so hard to say whether this was due to the fact that his diet was low fat, that it eliminated animal products, that it eliminated refined grains, that it was low in Pufa, that people were not smokers. There are many, many, many variables here. But one of the key points we might be able to take away from this is that all of this reversal or halting of progression happened despite the fact that his patients had very low HDL that was not improved by the vegan diet and also had very high triglycerides. And so that doesn't really make sense with our current world view. We usually think, okay, the low fat, high carb diet that creates this horrible LDL pattern B where the LDL is very small and dense and more prone to contributing to heart disease. Doesn't it raise your triglycerides? Isn't that really bad? Doesn't it cause low HDL? Doesn't it spike your insulin? And if you adhere to the idea that you can get a tired pink race, you know, that's a bad thing. I don't personally believe that but it's definitely a theory that's out there. And so this is kind of a head scratcher. Why is this going on? How come his version of the low fat diet as well as the other people who are kind of preaching the same message, how come they're having success? Isn't, don't we have a lot of studies showing low fat diets don't work? And here's the problem.  Any of these low fat plant based diet doctors will tell you that this is not low fat. This is moderate fat if anything. It's far too high to achieve the kinds of effects that they've been seeing with their patients. And they will also tell you that once you hit that point around 10 to 15% of the diet being fat, something happens. And there's a very consistent message going on with people who are of this persuasion. The ones we have often included myself, considered the enemy, considered wrong, considered illogical, considered blind, considered dogmatic. They all have many, in many cases independently, come to the same conclusions by working directly with patients. So with that in mind, even Walter Kempner noticed way back in 1949, he said smaller minimal additions to the diet may spoil the entire therapeutic effect. You had to stick to the diet 100%, be so, so super low fat in order to see results. Even a tablespoon of oil in Kempner's diets would make the diabetics go back on their insulin. So with that being said, I've developed a very scientific diagram here. So here we have a spectrum of percent of calories as fat. And I know it's not peer reviewed yet one day. So we as the ancestral community have often focused, where's the clicker thingy? To pretend I'm shining in a green light on the upper end. Oh, here we go. So we've focused up here. We've looked at ketogenic diets very intensively. We've looked at low carbohydrate diets. And we haven't really looked at this end of the spectrum. And large part in my opinion because butter, because bacon, chocolate. Nobody wants to give up those things. It's not fun down here. This is where all the good stuff happens. Nonetheless, I have come to the idea, the hypothesis theory, whatever, that perhaps there are two unique metabolic states that can be achieved by manipulating macronutrient ratios. And when we're up in the swamp land of, I'm gonna call this the macronutrient swamp land that exists between these two extremes, research seems to corroborate that you can tweak fat levels, you can tweak protein levels. It's gonna have very minor effects, if anything. Going from a diet of 35% fat to 30% fat, which we've had a lot of low fat diets don't work, studies that do exactly that. It's not gonna show very much result. We're not gonna see anything beneficial happening there. It's not until you get way down to one of the end of the extremes that something unique happens. I'm gonna call it magical. There's probably an actual biochemical explanation for it, but I haven't seen it investigated thoroughly yet, at least on the lower end. We have ketosis on the upper end, I'm gonna call it carbosis on the lower end. And if you actually think about it in terms of human history and evolution, perhaps there was an advantage to being able to survive on a very high carbohydrate diet for periods of time when animal foods were scarce, when plant fats were scarce, they're very hard to find in the wild. So why not be adapted to two ends of the spectrum here when that fit perfectly with human history and evolution? Just an idea. And what we do know is when we get down to this low end of the spectrum, and again, it has to be below 15% more or less of the calories, usually below 10% is when the best results are achieved, we see increased insulin sensitivity and glucose tolerance regardless of weight loss. And we do have quite a few studies that are showing that at this point.  And if you think about things like the potato diet, the potato hack that I know a lot of people have been trying in order to kickstart the weight loss, improve blood glucose levels, is it really working just because of resistant starch? Or is it also because those diets are extremely low and fat and inducing some kind of special state here? So my takeaways are again, I'm definitely playing devil's advocate and I could argue against every position that I've taken on the podium today from another angle. So I don't want you to think that I've really jumped off the deep end here. It's just to inspire some cognitive dissonance that will get us thinking. But one option that I've been pondering is perhaps going on an ancestrally adapted low fat diet for a while, temporarily, whatever, perhaps that can be used therapeutically when people are not doing well on high carb or high fat diets. You know, there are people who go into ketogenic diets and have fabulous results treating whatever condition they're aiming for and there are other people who do the same thing. They're LDL skyrockets without a concurrent rise in HDL. They're feeling worse, bad things are happening. Maybe there are other options for them. So the people who might do best on this very low fat kind of diet, again, just maybe temporarily, people who are high amylase producers who have better starch tolerance than others, people who are ApoE4 carriers who might respond less favorably to high fat diets. And of course, this can be adapted to ancestral food sources.  You don't have to drink fruit juice if you don't want. You don't have to use gluten. You can create a diet like this based on entirely ancestrally acceptable food sources. And the most important benefit in my mind from looking at all of this is this kind of diet might actually be able to heal and restore glucose tolerance, which is something that generally does not happen again on low carbohydrate diets. And as a final take home point, I just think that this kind of thing, you know, in this community elsewhere, in the universe at large, I think this is just a general philosophical point that we should always consider other options and never close our minds completely to other people being right. We have to ask ourselves at some point, is our goal to own the truth and hoard it, or is it to seek the truth? Because you really can't do both things at once. Thank you. Any questions? All right, yep. So I think Denise is probably willing to stay as long as she needs to to answer questions.  But you're free to leave for lunch. We're gonna gather again at 2.05 here for the next talks and also at Bancroft Hall at 2.05. Go ahead. Hi there. I think it's amazing your message, you know, to keep questioning, but is it not true that some options are so impractical that they're useless? So, I mean, you could say this about global warming as well. We could just all stop having babies and that would solve the problem. Or with this option, you know, I could just fall on my sword and that would solve the high HD LDL2, right? But so it's just not useful because it's not practical. I would say that's definitely a possibility, but the fact that we have had so many people being successful in this kind of diet, it shows at least a portion of the population may have the motivation and the incentive to stick to that kind of diet. Like, I mean, I ate a low-fat raw vegan diet for a year and, you know, I had to stop because I was falling apart, but I was able to stick with it because that motivation was there even though it was very impractical lifestyle-wise. So I think basically, yeah. Yeah, it's all a matter of the motivation. Okay, thank you. Yeah, thank you. Hi, hi. This is less of a question, more of a potential comment for Future Avenue of Research. Sure. Is that human beings have developed in different areas of the world for different time spans. So do you think it's maybe possible that some people are evolutionarily more adapted to one of these versions versus the other depending on where they evolved? I think that's absolutely possible and it's probably how it's working out. Even if you look at Caldwell-Assistan studies, you'll see that there are always at least a few people in his group, especially his larger one, where their health just deteriorated. He had one stroke in his really big group of people. So there's clearly gonna be people who are gonna react adversely to that kind of diet and I think it might be what you're saying. It could be a genetic thing, it could be just where your ancestors have herald from. Definitely plays a role. Thank you. Great talk. Thank you. You made one really interesting observation about the Kempner diet, which you said that after they achieved these great benefits, they could maintain them after you, if you gradually reintroduce normal foods. That seems kind of implausible to me because you think after some point of time, right, you would get back to the beginning state but if that's true, why would that be true and why would that not be the case with the low carb or paleo diets? You know it very well could and I just haven't seen that explored or demonstrated yet but with Kempner's diet, the one caveat there is that they couldn't go back to eating how they were before necessarily is more of an expanded, lowish fat vegetarian diet. They could add back some lean animal products but probably eating a fatty steak was never gonna be in their cards for the future. Thanks. Dr. Gonzales talks about a spectrum of diets for different people. And one of the things he talks about is that there are very few people who do very well in his opinion on the plant-based diet. No meat at all. And other people at the other end who do meat three times a day and thrive. Yeah. So, but the interesting thing to me was that some of those people on the plant-based, low-fat diets would be people like Nathan Pritikin and people like William Kelly. They both killed themselves. Relations and causation but... They healed their incurable illnesses. Right. Absolutely. But then they were feeling so bad they killed themselves. Well, that's a good point too. I mean we do know with very, very low-fat diets that may affect the brain for some people if not everybody adversely. Although I would say it's definitely not a universal thing. There are people who are gonna react differently. Some people have alleviated their depression going on a MacDougall-style diet. But with the case of Pritikin, my understanding was that he had lymphoma due to being exposed to radiation when he was younger and he had actually kept it at bay for about 27 years longer than his doctors predicted. And eventually it went to the point where his, I think as chemo treatment, it was shutting down his organs and it was just such a miserable existence that he did kill himself. But that's always a good point to look at the mental health effects too because that's so important. Kind of thing, it's like it'll cure one thing but then there's another problem. How do we get the right balance? Exactly. Great point. I think it was a great talk. It highlights the complexity of the human organism and how it can move in ways that we don't anticipate. The thing I would remark is that you show some of this data which only has one or two metrics like weight or reduced whatever they're called, heart attack events. I would suggest that what's really necessary is a whole lot more biometrics. And just two that come to mind would be cortisol and say HDH because high sugar is gonna suppress all the HDH. So you may be thin on the outside but you're not getting any growth hormone. So I'm just saying that I think you have to look at the whole universe of complexity. Right. And so I don't know if you have any thoughts on that. Yeah, that's a fantastic point. I would add to that too just total mortality data because if you're dying less of heart disease but dying more of cancer that's also a point to consider. Definitely a global perspective is necessary. Thank you. So the debate seems to have been framed between high fat animal-based diet and high carb plant-based diet. But that's just of course how it was framed. And then there's like what actually happened. And I don't think I heard much about the potential for the high carb diet actually being low protein that may have been protective maybe by up regulating autophagy or something to that extent. So do you know what the protein intake was? Like were they eating tofu like gangbusters or was it really just leafy greens? The best of my knowledge a lot of the protein sources for plant foods were also kind of fatty like tofu. And so those were eliminated as a byproduct of that system. So I think that I actually wanted to talk about glycine and methionine and I just didn't have enough time in this presentation. But I think the protein perspective is another really important issue to look at that we can also glean information from that might be relevant to the ancestral health community. Yeah. So I really loved your chat. Thank you. Your talk was really, really interesting. So I was curious, there's been a lot of talk about the ketogenic diet and how wonderful it is, but primarily seems to be focused in men. Men get great results, but with women it seems to be a little bit more all over the place. Just any thoughts about anything you've come across with women when they do a ketogenic tends to be more adrenally taxing. I think it could definitely be something along those lines. I haven't looked into that research very thoroughly, but I know based on just emails I get, I know this is anecdotal. It's exactly as you say, there's a very strong gender division between reactions, not only to ketogenic, but to the paleo diet that's maybe even a little bit higher in carbohydrate and not ketogenic. So I would say there's definitely something either hormonal interaction or could be that, gosh, I really don't know, but you know, I've gotten that question so many times, it's probably about time to research it. Thank you. A, I love the open-mindedness. I think that we are always evolving and unfolding and adding new information to what we learn from previous generations. So my area of focus in nutrition is primarily in supporting birth and postpartum, and I have done a lot of research, specifically reading a lot about Dr. David Barker's research in how the, I'm sorry, we're going to have to quit because the audio video people need to leave. Thank you. We can, if you want to continue these last two questions, talk to Denise. Yeah, you guys all hang out here for a while. Please come and talk to me or I like hugs too, so come hug me. So we'll see you at lunch.


It's not like someone who's thinking about starting a business has to go all into their business on day one, right? But what would you tell someone who's just a bit of a little hesitant starting their business or maybe even doing it full time? Yeah, I mean, I think the hardest part is the patience and I completely get it. You know what I mean? That's the hardest part. And I keep telling myself is how many basketball players are there and then how many up and coming basketball players are there and then, you know, people who aren't even born yet. It's not going away. It's not going away.  You know what I mean?  That's the hardest part, though. I get it completely. You know, so when you have a family, I completely get it. So that's it. But in fact, if you're young, find mentors.


Ok, da smo povrdujati, da smo se povrdujati o vrštivnih vrštivnih in elektroferetnih patenji. Tako, da so tudi izvajte, da so smo vrštivnih in začali, da smo vrštivnih, kako so vse organizi, kaj je Kristian Mikkelejti in da so vlasti vrštivnih. So smo da v Davida Mikkelejti, pa je dnev vrštivno z Andrei Stasiak in Luka Tobijana. And the title here hopefully you get an idea of. We used this title, so we had a selection between titles and we said, yes, we want to use this title because we want the reader to say I want to understand what the hell is topological friction after reading this paper. So let's see whether we can get there. So one thing that will be important for the talk is that DNA is highly compact v svoj biologičnih vseh. To je nekaj, ki se všem izgleda in izgleda v nekaj vseh izgleda Edimbroscijnji festival, tako da počnem s kvizami, ki na pop-kvizami. Vseh, ki ne boš, nekaj se prišli v mene. To je, da se počnem, kako je kompatne DNA. Zato, ki smo počnem, kaj je DNA v svoj bolj, in kaj smo počnem, kaj se počnem, kako je zelo, kaj se počnem, kaj se počnem v Edimbro, in se da se koristina, ovo bo v glasglu, Na njer vse izgleda je, Na vse, ne zvom dissolve, dobro lahko všivno, tako da so tko si plut, njega zelo, s njih nekdo, to je pošlišnji, updated iz vse pošlišnji, da se zelo v taj pluto in s lega vsah, vse zelo prist, od SOEV neko tega pisila z 10 mikronov, kaj sem od 103 kg of the 13 cell, it reaches about that much. At all level, so this I think is quite an impressive number and if we now look more scientifically at each different organism, you would see that this is a micrograph of a DNA inside a bacteriophage which will be important for the first part of the talk. Vseh, kakje je vrstav na obrstav, zelo je 15 nm in DNA je 10 mikron. Kaj je zelo, da vrstav na obrstav in zelo se, da je ina, zelo je tko zelo. In in in v Nuhmanj, tako bila spremno prej, DNA je zelo vzelo. Takaj, čas je veči inoč, zelo se početnjo vstav, nekaj ne se vrstav prizat, neko za to, da je oto početnjo vzelo. So, I will start. So the first part of the talk will be on the physics of DNA inside bacteriophages, so physics of DNA within these viruses. And the second part of the talk will be trying to understand with a simple model how experimentalists can tell which not is which. So thinking about bacteriophages as I said to you before, this is the capsid, so this is the container, you can think of a sphere where you stuff in the DNA of the virus, which has to infect the bacteria. So, there has been a number of experimental studies of this system, because it's perhaps the simplest living organism that you can think of. And the DNA inside, so there has been a few key papers about ten years ago, which shows that at least in the outer layers, so close to the capsid wall, the DNA is arranged in a spool-like fashion. At least, so these are the reconstruction that the experimentalists need. So this will have some importance of what we'll say after. So this is the bacteriophage, it's about an icosahedral, so it's made by proteins. This is the DNA inside. These are many of these viruses. So this is for images. You can also study the DNA notedness. And it will come as no surprise that since the DNA is so compactified, it will be highly noted. So for instance, this is P4 virus. So if this is P4 virus, sorry, this would have about 10,000 base pairs of DNA in. And people have measured how much the DNA there is noted. And you can see that in the wild type, so this is the wild type, 47%, so it's about half of the DNA molecules that were looked at experimentally by arsuaga and co-workers, yeah, are noted. And if you have some mutants, so the trick that the P4 has in order to infect the cell is that it will keep one of the ends of the DNA rooted, so you've got a sphere, you've got an opening, and one end of the DNA is rooted, so it's easy for the virus to attack the bacterium. So this is the wild type. And if you have a Taylor's mutant, so this routine is lost, so both DNA ends are inside the capsid, and as a result, you have many more knots. I should point out here that in order to define a knot for a physical string, which is not closed, that is open, you can, for instance, keep it fixed as it two ends. So, for instance, if I have my extension cord, they are often noted, so this one is noted, for instance, you've got two knots, so this is not a closed string, but it's clear enough that it's noted, because if I keep the two ends fixed, I will not be able to undo it. If they can rotate, and if they are free to move, I cannot undo the knot, but it still makes sense to think that if I have two ends, I can close it and then I can ask myself how many times when I close it I will have a knot. So in this case, we can give a meaning to the notion of an open knot. So this is what happens if we have a bit untidy and we store our headphones cord in the pocket, for instance. When you take it out, it will look a little bit like that, especially if you have two or three, and good luck if you want to see which kind of knot it is or if it is a knot or knot, that's a monster. It's very difficult to characterize. So there are a couple of things that I want to tell you about knot theory, which are important for the first part of the talk, which I should just review. So these are the simplest knots in Tate's table. So this is the unknot. This is a trifoil. This is a full one. So these are the two knots that I have here. We are just looking at the number of crossings. So for instance, this is a full one, because it's in its minimal projection. So this is this one. It's got one, two, three, four crossing. And this is a knot, which appears quite often if you have extension calls, indeed. And then you can go on in the 5-1 and the 5-2. So if you have five crossings, you have two types of topologically inequivalent curves, so you cannot convert one into the other. So that's why they give the name 5-1 and 5-2. So all this I want to also remind you of something that will be important for us is that we have two important classes of knots. One is the torus knot, which are these red curves here. This is 3-1. This is the pentafoil. The next one up would be the 7-1. And there are many other knots, which are torus and which are more complicated than this. And the blue guys are twist knots. So these are knots, which come up very often in an extension cord. And we'll discuss them a little bit more just now. So torus knots are knots that you can draw on the surface of a torus. So that's how you can draw the trifoil, for instance, here on the surface of a torus. Or if you want, you can do that on a donut as the editor convinced us to do in this physics world paper that we had. So these are the torus knots, the 3-1, the 5-1, 7-1, and so on, and so forth. So this would be important for the rest of the talk. So if I look, so this is my extension cable in Edinburgh. This is longer than the one I have here. Yet you see, so this is got, for instance, if we just review what we've been saying. This is 1, 2, 3, 4 crossing. This is a 4-1, so it's a twist knot. And this is 1, 2, 3, 4, 5. So this is a 5. It's actually a 5-2. So all these knots appear quite a lot because, so here, for instance, I got a 3-1 and a 4-1. And the reason they appear so often and the reason they are called twist knots is that you can easily do them by mistake if you make a plectonym, so you twist up a string, and then just by mistake you take one end and you put the hoop here, you create a knot, and this will be a twist knot. An important thing about this knot is that they have a knot in number 1. So if I just undo one crossing, I have an unknot. So this is different from the torus knots. So the unknot in number is the number of crossings that you have to undo in order to go from a knot to an unknot. So an important property of the twist knot is that you have unknot in number 1. So if you undo this crossing, for instance, you will undo the knot. That's why this is a twist knot. So one question that was always puzzling for us is how experimentalists can use their techniques to be able to tell so accurately one knot from another one. So you will know that they do by gel electrophoresis, but I think still that it's quite remarkable. So what is done here is that these are a series of twist knots, and these are the knots that are in a phage, in a bacterial phage. So this is again from the paper by Arsuaga and Muriel and co-workers, where they characterized by gel electrophoresis the complexity of the knots inside the phage. So what they did basically, they ripped the capsid open, so this is the virus, remember, they took the knot or the piece of DNA which was there, ligated it, and then ran it through a gel, similar to the one that Matthew was showing to you before in this first part of the talk. And then different knots migrate at different speed. I will say much more about this after. So what is remarkable is that you can tell quite a few of the simple knot up to ten cross in a list just by looking at how fast they move. So if it moves as fast as a trefoil, it will be a trefoil. So you don't need to look at it. If you do a calibration. So this is quite impressive, I think, that such a simple technique, just telling you how quickly you go through a gel can tell you about the knot type. It can tell you also about other topological things, but the knot will be most important for us today. And if you look here, and if you calibrate your gel electrophoresis experiment correctly, we see that you find the knot. So there's this spot here. This spot corresponds to the trefoil, and then you have a very faint spot which corresponds to the full one. So in these bacteriophages under high confinement the twist knot, which appears very often with the extension cable, appears very rarely in the DNA inside the capsid. And we'll be interested to understand if you can understand the mechanism why this twist knot is not present. The five knots, there are two kind of knots. One is the five ones, the pentafoil. This is the torus knot. And the other one is the one which I showed to you with the extension cable. That's a five-two, that's a twist knot. So again, so this is more difficult to discriminate, but you can do that with gel electrophoresis. So the pentafoil here it is, and here you have a missing spot for the five-two. So what is happening is that we seem to have more torus knot than twist knot. And actually you can do more careful experiment. So this was a groundbreaking experiment a few years ago, about ten years ago, but many more have been done and they all confirmed this remarkable thing that you don't have many twist knots within a bacteriophage. So within a bacteriophage the DNA is no different than in solution, but in solution you find a lot of these four one knots, not in the bacteriophage. So the confinement has to have something to do with this peculiar finding. Okay, so roundabout at this time we got quite interested, and I'll tell you, so I'll be more interested in the ejection, but I need to tell you a little bit about the knot spectrum because otherwise it would be difficult to follow what I say after. So we wanted to understand, we wanted to understand whether we could design a simulation to understand the knot spectrum so the kind of knots that are formed within a bacteriophage. So the first go that we had was very, very simple. This was done with Monte Carlo kinetics, with a kinetic Monte Carlo model, which only consider the fact that the DNA, the bits of DNA have a thickness, so if you are hydrated, the DNA has above the thickness of 2.5 nanometer, compare it to the 15 nanometer that is the sphere that it is confined in. So we have two lens scale there, and we got another lens scale which tells us how stiff the DNA is. This is the persistence length, which is the length of which thermal fluctuation will buckle your fiber, and which is again 15 nanometer. So it's quite remarkable that the persistence length is very similar to the size of the container that you are in normally, and indeed this is of some relevance. And so we did the first simulation only as thickness and persistence length. So we put a piece of DNA with the right stiffness inside the sphere and wanted to see what happens. And this is what happens. So you have a messy structure which is resembling a bit of a very messy spool. That's not, yeah, some kind of spools would look like that, but it's very, very messy, so it's a horrible structure that will be highly entangled. And the deep reason, well, the physics reason why this appears is indeed the fluctuation of the DNA which you can think of as persistence length are about the size of the container. So if the container was very small the stiffness would be, the DNA would look very stiff, so it would order more. Here the DNA looks relatively floppy at that scale, so that's why you get a disorder structure. And if you run this simulation which we did for realistic confinement you can put or not electrostatic, it doesn't matter much. What will matter is something that we will see in a few minutes. You cannot even, we were able to identify essentially none of the knots which we generated. So these are almost certainly noted, but we don't know what they are. They might be the unknot. It's very unlikely. We don't know what any of these knot is because they are not identification routines which are available. They struggle if you go to a very high number of crossings. So they can do very well until you have 16 crossings, perhaps a bit more if you simplify, but not if you have these monsters. So the bottom line from here is that if you take a simple model where you only have a semi-flexibility and thickness, so you have a very honest model of DNA which works pretty well in solution. It works very well there. If you put it in a sphere, it doesn't do a great job in the sense that clearly the experiment shows that we can see some simple knots because we have a very nice spot for the unknot, nice spot for the trifle, and there is nothing here which is so simple. And also it does not resemble the spool-like ordering that we saw in the micrographs. So people were finding pictures like this in six years or so ago. And one theory which was out there is that the micrographs were actually overdoing the kind of symmetry so they were making the DNA look like more order than it was. So people thought about this for a while. And we actually thought about this for a while. So we then tried to put in a simple interaction with the idea that maybe the simulation is not right. Maybe we are missing something. So the idea here is that DNA strands are chiral, and if you want to write a simple model which does that in solution you might get away without worrying about that, but not in confinement. Because if you have strands, so if you have chiral objects that we use to demonstrate this point when you lock them at very close packing they will lock at an angle. Which depends on the groove details of the fusilli in this case and it will do that in DNA as well because you have grooves there and you have a helicity. It turns out that this is actually something which is well known in DNA physics. People have done experiments and shown that the molecules can form a liquid crystalline solution which is exactly what this is. So when you tweak the concentration you can undergo a transition from anisotropic to anematic or a cholestetic phase. So in practice if we remember what Slobodan was saying today if you have chiral objects you expect a cholestetic but the pitch is so large that within the confine of the capsid is very similar to anematic so the angle is about a few degrees. So here comes this interaction, let's see what happens. There you go. So this is a movie from Christian that we had in the first paper on this. And you see that if we have p4 like DNA with this interaction where the parameter were tuned on the basis of this liquid crystal DNA experiment you form nice pools there very different physics from a very simple interaction. And these cases which will look exactly the same so I will go on from now. So this interaction would not be very important in confinement because it only kicks in when the strands are very close together so it will not be very important in solution so in an unconfined situation but it will be very important in confinement when you force the DNA strands to come close together in this angle. So these are the configuration that we get. Again they are very order, there is a very high level of liquid crystallinity and there are some have in defects as we call them like this. DNA is a liquid crystal that doesn't tell the head from the tail. And this is what we would expect for a liquid crystal in polymer. So now the surprising thing perhaps is that with this kind of interaction the situation changes a lot. So this is surprising perhaps up to a certain extent but nevertheless it's quite pleasing that if you look at the so this is a system which, so this is a collection of a couple of hundred simulations where we repeated for each simulation the packaging process so we had a sphere and we fed the DNA in this is in principle a non-equilibrium process so we didn't want to worry about the glassy autocollabation time in this case because every time we had a single different simulation and we just recorded how many times in this case we found a trifle how many times we find a full one and so on and so forth. So this is a thermodynamic system is only that it will get stuck in a metastable state so you have to do it many, many times if you want to sample correctly the distribution. So the results are interesting because you see that you can now, first of all you can characterize the knots because before we couldn't do it without the interaction we have a lot of trifle a lot of pentafoil so we have some 7-1 so relatively large amount of knots that are simple that we know and we know that they are appearing in the gel electrophoresis or the phage as well. The 4-1 is present but it's very, very suppressed the 5-2 is another twist knot it's very, very suppressed so at least within the simulation we can understand that we can understand how this bias comes through so this is through DNA-DNA interaction which you would not have considered in a simple course-grain model for DNA. So our view is that they come from a line in interaction which gives some liquid crystal in order and if you want you can understand this by thinking that if you with liquid crystal interaction can stabilize somehow a spool like the spool that sailors use to put away your harpoon so these pools are very ordered and they resemble a bit a torus so if you can't form a knot there it will be more likely to be a torus knot so this is a very simple mind explanation why this torus knots appear so now so the bottom line from here is that we can just by tweaking the potential a little bit so just by putting some more detail that we would have thought at the beginning simple model to understand the knot spectrum so which knots form within a phage so now the question that we had at the beginning of the project is given that knot's form and we know that more than 90% of the mutant p4 is knotted in order now for the bacteriophage to kill the bacterium it has to make so that the DNA will go inside the bacterium so it has to eject properly and if you have a knot like the ones that I had before you could imagine that the knot would form a hindrance so the DNA would not be able to eject properly so what happens if we simulate ejection so these are some selected simulations here so this is a knotted chain out from the capsid so you should imagine that here you got a sphere and you got an opening here so I got p4 DNA and then I let it out through this opening so the entropy would be much larger outside the virus of course so the DNA wants to get out but the question is how it does that and you naively might think that the knot could form a blockage so that if you had a knotted structure it would create some kind of topological friction just to come back to the title and stop the ejection ok so what we are seeing now is another so the knot has come out so this is another complicated torus knot it's a 9-1 so this has got a knot in number 4 so it's quite complicated and still it comes out no problem you see no difference and yes another very complicated configuration is one of the few that we couldn't classify and it goes away no problem again and one thing that I hope you will guess in the end is that if I ask you what kind of knot it is we don't know but I pretty sure bet that this is going to be a torus knot so the reason why all these knots get out so quickly or do not have many problems getting out we at least thought is linked to the idea of knot localization so if you have if you are tying shoelaces or if you are pulling on a knot it will localize so you see the knot will become very small so when you pull on a knot it will localize that's how we tie our shoelaces on the other hand when we compress a knot it will delocalize no sorry I said at the beginning this is knot we have done simulation with Debye-Huckel interactions and these are actually we put Debye-Huckel interaction and they don't make much of a difference because it's so screened in physiological conditions so the shoelaces will help the physics so it will give you a force to push out but it won't change much the topological friction so the knot when you compress are delocalized so you cannot look at a small region say close to the aperture of the capsule and say is it not it or not so there is no local structure that can create a blockage so that's why the DNA gets out whether it is a torus knot so remember that these simulations were all done with a spool so we're all done with a Karel interaction so it's quite remarkable that we've done a few years after we got again at this we try to study more systematically the ejection simulation so you see at that time the ejection is very slow because it's only entropy driven so these are very slow simulations at the time so we were like quite a lot of statistics so that's why we didn't do them straight away so the red guy here so this is the percentage of ejected beads so it goes from 0 to 100 there is again p4 DNA as a function of time in millisecond in kinetic Monte Carlo we can map to a realistic time scale by using stock slot and diffusion and a few more things so I just here give you the time in millisecond it doesn't matter so much though so I would like you to notice the scale so these are the interactions with the Karel bias on so you see that the DNA gets nicely out it's almost linear actually the way it does that whereas with without colostatic interaction it still gets out sometimes three times 50 or so that I'm plotting here it has gone out but it takes a long time it's much slower so this is an example of topological friction because if you were doing a simple theory with a thermodynamic theory it would be very difficult to guess that the DNA so the DNA concentration is the same, the charge will be the same semi-flexibility is the same the only thing which changes is that there are some small interaction in this case liquid crystalline which has favored a conformation with respect to another so in this case perhaps I should speak about conformational friction which has much less friction than the mass as you would perhaps expect and this is something that is difficult to get with a simple theory so this is how you can see it microscopically so this pool is like the harpoon so if you have a harpoon that's why the sailor put it so nicely if you want to put it out it's easy maybe there is a toss not but it still gets out quite easily if this was a mess it would be much more much slower to come out the bottleneck which is created here is purely topological and is due to the conformation so the entangled nature of this structure makes it difficult to make it eject and in particular you see that you need a lot of rearrangement so this suggests to me that you could suggest an experiment whereby in interaction as to make the current interaction smaller or larger you should be able to see differences in the ejection dynamics for instance ok so there is another thing which I think is quite cute is that I showed you only a part of the trajectories first so look at the red ones so now we are considering only the trajectory with the chiral bias so these are the one which work but not all of them start immediately so this is another prediction we have done and that as far as I know is not quite been tested experimentally perhaps because the time scales according to our simulation are pretty small anyway so there is a stochastic element in this ejection so some of the DNA don't eject immediately and that's due to the fact that they are in a dormant state so if you have a look here look at how the spool is oriented and look at this guy here so you see that this spool so the opening is here so this spool has to do a rotation and has to present itself nicely so that the ejection can start so before that happens it will just stay put so it will just stay put and then when it starts it go very fast ok so there is just a two state biphasic dynamic response in the progress of the ejection so if we look deeper so this is so this is quite a simple plot but there are too many things so this is the knot type and this is the probability of the knots and this is the percentage of knots which has been ejected ok so from this plot we can see two things one if you look at this is a small probability so a small percentage of ejected this should say percentage of ejected DNA sorry you can see that you have an unknot you have a 3-1, 5-1 is essentially the same distribution that we looked at before when the DNA was all in so when the DNA starts to get out it's perhaps nice to see and expected but you see that you don't populate the twist knot so you stay in the torus knot so even when you get out you always have more torus knot on top of this you see that the knot becomes simpler as it the DNA ejects as again you would expect but it's nice to see it in the simulation and quantitatively so another thing that you can see you can follow so for instance that we follow here one of the ejection simulation when there was no lag ok and we can look at the percentage of ejected DNA so this should be in milliseconds it goes from 0 to 7 and you can find here what so this is the percentage of ejected DNA so you see that it's not quite linear it's got some small pauses but it goes all the way so at the beginning this guy was one of the complicated knots like the last one that I showed to you that was ejected very happily so it's got more than 30 crossings in the minimal projection but if you wait longer a little bit you see that it will simplify it will have 20 and then it will go on this progression of torus knot from the 9 one to the 7 one to the 5 one to the 3 one then the un knot this is very typical of what happens if you think about the un knot in number the twist knots have an un knot in number of 1 so they can be undone with only one single uncrossing so the torus knots have more uncrossing numbers so basically what this says is that ejection proceeds in a stepwise way whether you undo one crossing at a time it's like you had a big spool and you are slipping away your tether little by little so that you can undo one crossing at a time so you got a large loop here and you are just teasing out an end so that you make the spool simpler and simpler no there are pauses there are not so many pauses but there are pauses and they resemble so there are experiments and people do see pauses and there are several explanations yes the pausing becomes yeah it's yes you have more pauses as you go on I should review that curve but we did have that we did look at that frequency of pauses so some pauses are extremely long so they just get stuck so very few cases of this so this DNA with carial bias get stuck and in the few cases so this is very episodic but in the few cases that we have seen this for instance is one of the few remarkable example of twist knots so the twist knot is slow to get out and if you look at how so this is one lucky case where we could actually find how this evolved and this is a 5-2 it becomes an unknown knot and then it becomes another quite complicated knot that get stuck then so again it's very different from the nice linear progression that you see with a torus knot so the topological friction is much higher, it gets stuck whereas the torus knot so the reason that we think that the knots can be infective so the phages with the knots can be infective is that they form this nice kind of torus knots that can be undone one crossing at a time so they have a low topological friction in the last 15 minutes or so I will discuss some results that we got quite excited last year and we are also working on some generalization right now on the simulation of the gel ecrophoresis experiment so I will go back to that this is trying to understand how experimentalists can say so confidently which knot is which ok so this is one of the other another slide from the talk with the wit so this is how the agarose gel that experimentalist use looks like so it's a bit like Swiss cheese you can think about it like that or a network with holes and you can ask yourself which knot will move faster in this gel will it be the trifoil, the unknot or the most complex knot or there will be no difference at all you want to guess? D, yes, that's right so the more complex knots will move faster because they are smaller and they can squeeze more easily in the gel or at least that's what you would think right so this argument works beautifully for sedimentation so even if you have knots going out in a disco gel you can see this beautifully and the reason in that case is that very similar that we have a competition between gravity or something else electric force and the friction so the the force is equal to the friction times the velocity and the stock's drug or the friction becomes smaller if you have a smaller object so a smaller object will feel less friction so it will go faster, that's it that's not the whole story though and that's why we were interested in this so a lot of biologists and biophysicists use two-dimensional gel electrophoresis so the idea is that you can have a little bit better separation so this particular case you have a first direction where the where the field is weak where the knots move according to their complexity so the more complex knots will move faster and then you have another direction so the knot will be moving very slowly there and you've got another direction in which you put a stronger field and in general in the stronger field direction or in general you said in some cases at least you have no monotonic mobility so this is telling you that the unnot is moving faster than say the twist knot the 4-1 ok so as a result if you combine the two you will have an electrophoretic arc and this is indeed the one that was used in phage knots to discriminate and to separate them so if you only do one direction you can't see them all so clearly so we wanted to understand why and in principle this has implication for other things that's what we're interested in now so if you have supercoiling for instance here or if you have no sorry so these are dimers supercoiling is not shown but if you could have denatured loops so this is a DNA which is denatured at several different degrees you could have a DNA which is more or less supercoiled as we have heard today so it's got more ride if it is a loop it will not get rid of the supercoiling or you could have a linked DNA so gel electrophoresis will show you how to separate all of these and it will do that by using so there's been a nice work by Weber et al so this is Paolo de Los Rios and Giovanni Dietrich so there is a surprise there was not too much simulation work on this interesting problem I think and what Giovanni and others did is they found out that it's important when you want to understand the mobility of knots in a gel to understand to account properly for the topological interaction between the gel which is modeled pretty much in the same way as Matthew showed to us this morning and the polymer so this kind of they're not quite you can think of them as threading in a way but it's a little different so these kind of interactions are going to affect the dynamics importantly however in no situation we find some non-monotonic behavior so you could either have that the drift speed goes down with complexity or goes up with complexity but you could never find something non-monotonic so our contribution was to consider something slightly different so in the work by Weber they had a regular gel exactly the same as Matthew showed to us today in the first part of his talk we consider that another gel you could think that another thing might be important so that the gel might not be regular but it might be cut here and there so you could have dangling ends which model agarose filaments which here are completely rigid but we check that even if you make them flexible the results don't change much and this could affect things a bit in principle because they could provide a way so in this case rather than threading so the gel could pierce through a loop and perhaps change its mobility and I will try to convince you that this is probably what happens so in this case p is the probability with which we broke one of the regular sides in the cube so if p is zero we would have a gel made by nice little cubes and if p is different than zero we have dangling ends so I will try to show the results so I will try to go through the results in the remaining five minutes or so so this is a drift speed as a function of the average crossing number this is the N naught the trifoil for one so the not complexity goes higher here and there is no surprise that you go a nice linear result so this is what we have would happen a weak field would you produce the nice linear behavior that you find in experiment however if you run the simulation at a moderate field you find that you have a hint of this no monotonicity so we were quite excited by that and wanted to understand at least in our simulation why this comes about so here the N naught is not the slowest but it's faster than the full one so the full one is the slowest of all in this particular case if in this case in the simulation as I showed there is a bit of irregularity because this simulation takes quite a lot of averaging to do but there is a clear signature that we find in anotrophoretic arc which is very similar to the one that people find routinely in experiment where the zero so in this case the full one is the slowest but you can change this hierarchy by tuning parameters anecdotically we could see that when we did this simulation there were cases in which indeed the danglin ends or the gel were piercing or threading let's use the loops so one important clue to understand what the reason is for the no monotonicity and that it is indeed linked to the danglin end is that we can redo the same simulation at p equal to zero regular gel no danglin ends so this is the case with danglin ends you see that the speed is no monotonic with average crossing number or not complexity in this case we could never like in the web simulation we could never find a single case in which we had no monotonicity always monotonic so there can be some discontinuity but it's always monotonic so again in this particular case we could never find a tight gel and the more complicated nodes always go faster so if you look at single no trajectories this is the position as a function of time danglin ends you see that they get stuck several of these guys get stuck without danglin ends they don't get stuck if you look at the radius of generation that is the size it can oscillate so the DNA has to move and the contract that is goes through the gel but you don't see any signature in the velocity curve and here on the other hand again you get stuck when you get stuck your radius generation increases so this is again all due to this thread in or piercing and we wanted to understand this a bit more quantitatively so we can compute from the molecular dynamics in this case simulation that we did they are very similar to the one that Matthew described today actually so this is the number of hitting events so we can ask how often is that a loop will be impaled on one of the danglin ends and this is the number of these events so the unknot is a bit fatter so it gets impaled a bit more often you see but there is a competition so the unknot would go slower with this because it becomes entangled more often but this entanglement time as a function of average crossing number has the opposite behavior so if you have a simple knot even if it gets entangled it will be able to undo itself quite quickly whereas a more complicated knot will take much longer time and you have to consider the competition between the probability of hitting and the disentanglement time and this is what gives you the non-monotonic behavior in the velocity as a function of average crossing number indeed here we made a simple theory so this is our data and this is a theory where we don't have fitting parameters we have matched the fitting parameters to the ones that we have found in the simulation and we have done a very simple problem in which we have a bias random walk which can hit an impalement and get stuck and can disentangle with a time taken from the distribution probability of times that we measured in simulations so we can fit rather well the results here and this is a predictive data so these are not more ecodynamic simulations in this model we can change the parameter here with the radiation of the unknot divided by the mesh size of the gel so in going from the black curve to the purple curve you are essentially making the gel smaller smaller if you want the polymer larger and larger what matters is the ratio between the length scales so you see that the non-monotonicity can be controlled there physically so if you are stuck you want to the unknot the unknot is not stuck permanently so it will be able to disengage yeah it disentangles from the matrix in the sense that you have a dangling end which is penetrating and then you get out you can maybe call it something yeah so let me go through briefly the main conclusions in the first part I showed you that you can do simulation with a coarse grain model where you take into account the fusilli-like interaction between DNA and which allow you to understand that the knot spectrum should enhance torus knots as a function as opposed to twist knots by simulating ejection you can also see that these torus knots get out more quickly and more easily than twist knot and I hope you like this I would like to describe them as topological friction so the topological friction of these knots is lower than that of twist knot and that's why these phages can still be infective because their knots can get out very quickly and then I showed you some results about how to understand from a theoretical point of view the experiments of gel electrophoresis in particular the non-monotonic behavior which is observed at intermediate strength where the velocity of a knot first goes down and then goes up again so which goes against the normal idea that we have that Stokes law would make faster more complex knots and as I showed to you we have a strong hint or a strong clue that this is linked to the fact that the gel can get entangled temporarily with the polymer thank you very much