team keeping clean all the rumors were true because when it was announced yesterday that the Ravens were having a presser today a lot of people figured it was gonna be Sam Cooke retiring I thought he either Sam Cooke retiring or Jimmy Smith retiring but I don't think this came as a shocker to anybody now it was a it was widely known amongst pretty much everybody I mean we all figure what was gonna go down when the Ravens drafted Jordan Stout in the fourth round when they took a pun in the fourth round it was like okay these boys ain't about to cut no fourth round pick now he was a fifth round pick they might cut that cuz you know what fourth round pick no they pretty safe so when they took took him it was like oh well we know that Sam Cooke is gonna be on the way up out of here but it's nice that Sam Cooke gets to go out on his own terms and I wonder because I didn't watch the presser I didn't get a chance to watch the presser yet so I'm not sure if he said that this was something that he had been thinking about for a while and he let the Ravens know I'm sure he'd probably let them know ahead of time so they could draft accordingly I'm sure he wouldn't just leave them in the dog like oh okay I'm retiring now y'all good luck finding the punner but now I'm sure he ain't do that but one thing shout out to Sam Cooke because they did say that he is retiring from the game but he's still gonna be around the game because he's gonna be a special teams consultant so Sam Cooke was like he ain't hit Jordan with that Ryan Tannehill like it ain't much out of the train he ain't worried about you man worried about me now Sam Cooke was he's sticking around and he's gonna work with Jordan Stout and what not to help him come along in the NFL and it's I think it's very important and it should help make the transition that much smoother because before it was the long snapper you know the Wolfpacks is they they losing another guy first was Morgan Cox who was the long snapper he would snap the ball to Sam Cooke who was the holder and then Justin Tucker would kick it and they did that so many times through so many different situations and they had that chemistry but now they they lost one they lost one a couple years ago with Morgan Cox they cut him and they decided you know what we're gonna roll with the young boy Nick Moore a long snapper he's been doing this thing there hasn't been any hiccups anything like that everything's been a okay maybe he should have taught some of the sentence had a snap the ball anyway so now they lose another member of the Wolfpack and Sam Cooke so now they lose the holder so Jordan that that's gonna be his job but what better person to teach him how to do the job of a holder for those kicks and Sam Cooke himself like what better person like he's been doing this for like literally forever like he I saw something that said he was teammates even with Jonathan Ogden this dude was teammates with Jonathan Ogden and you know Jonathan Ogden Hall of Fame left tackle and he you know for the Hall of Fame in order to get to the Hall of Fame you have to be retired for at least five years and then you're eligible for the Hall of Fame so Sam Cooke not only played with Jonathan Ogden he saw Jonathan Ogden retire the five years past for Jonathan Ogden to retire Jonathan Ogden into the Hall of Fame and Sam Cooke was still playing way after that too shout out to him Sam Cooke has been around literally for forever forever ever ever ever ever ever ever and like a few people have pointed out yeah he is the Ravens most accurate passer in history more accurate than Lamar Jackson more accurate than Joe Fleckle more accurate than Kyle Bowler I know that probably wouldn't be too hard but shout out to Sam Cooke man but yeah now they enter a new era of punting with Jordan no pressure no pressure but there is some pressure because you will be relied upon to pin pin the ball deep hopefully get it inside the 20 maybe he could unlock some of them you know have madden did a little little challenges doing your your franchise mode and you punt it inside the 20 I got my first one like the other day when I was playing my franchise mode and I didn't even know those existed till a couple days ago been playing franchise mode for years and been playing franchise mode all this year but just found out that when you kick it inside the 20 you get the little the little upgrade or whatever I was like wow I guess I'll be kicking inside 20 why don't be putting a lot either anyway so this is a this is not even necessarily good news just it's a transition it's a transition and this is the second person and the second key special teamer that is making the transition from playing to helping with coaching of course Anthony Levine was the other one he was a key special team a special team captain by the way and he's still gonna be around helping with a scout and I believe so that that's really cool I love seeing players get opportunities after football and I love seeing them get different opportunities because and it's one thing if these players go and they like oh you know what I'm gonna be a coach for a high school team a little league or whatnot and that's cool those are those are great positions because you are you are teaching a lot of the youth through football you teach them a lot of lessons through football and they I think with that a lot of them may they may not get the lessons until they may not understand the lessons fully until later on down in life but anyway for Anthony Levine and Sam Cook it's cool to see them go from players to on staff because for them to be on the staff they and we these guys like Jamel McLean of course Zachary or Anthony Weaver is another one it's been different plenty of guys that have done it but I would love to see more not only just on the Ravens but in a league period to where because this gives them an opportunity to continue to grow and this gives them an opportunity to one day they may be coaching against John Harbaugh as a head coach you just never know how this thing could work out but the fact that the Ravens give them the opportunity to make that transition good stuff Baltimore we love it we love it love it so yeah special teams they they they took a blow but I'm sure they'll recover because that's one thing that the Ravens do a great job that is recovering on special teams when they the whole kicker situation remember the kick is before Justin Tucker but again I know everybody remembers Billy Cunder for the bad but Billy Cunder was not always bad he just had the very very bad moments in that last year the year before and even some during that year he has some really good moments good kicks and whatnot but that year everything and I think the Ravens even gave him a contract extension I believe but that year just everything fell apart in the following year undrafted rookie free agent kicker Justin Tucker from Texas they're like yeah get this guy shot see what he's got still booting kicks like 90 yards they weren't that far but he had that leg and the thing with Justin Tucker he showed them like alright I got the power I got the accuracy but he also had the clutch too and that's something that he had already but it's something it's one thing to have it in in college but to have it in a pros that's a whole another ball game so that is a commendation to Justin Tucker himself and his preparation but it's also a commendation a commendation to coaching staff as well with special teams to be able to bring him along in this again a real undrafted rookie free agent undrafted nobody picked this guy any is a kicker so it's harder for kickers to get picked but nobody picked this guy remember Robert Aguayo I think that was his name we got picked in like the second round by the Bucks I think it was by the Bucks remember him I don't know what he had now but anyway um Janet Kowsky I think Janet Kowsky was it was he a first or second round pick I think what are your first I forget but anyway kickers don't really get picked get picked like that I know the bingles they picked McPherson in the fifth round and I know Browns they picked the kicker this year I want to see us in the fifth round too but either way Justin can't get picked and I just took the best kick in the league so Raven they did something right there with the special teams did something right so um with uh with stout I'm sure and again with Sam cook being even if Sam cook wasn't there I wouldn't be worried about Jordan stout but with Sam cook being out definitely ain't worried about Jordan so he will be just fine he will be okay so beautiful thing great thing one last thing I haven't seen it from any I haven't seen anything official because and I just we're not gonna talk about it right now but there's been the rumor floating around that the Ravens are interested in T.Y. Hilton and one of the the things they quoted the athletic they said oh it's in this it's in this article in the athletic so I read the article and it did not mention the Ravens being interested in T.Y. Hilton not one time so that's why we ain't talk about that yet but if we see something from somebody and it definitely says Ravens are interested in T.Y. Hilton this a coach and some other teams interested in T.Y. Hilton but it did not name the Raven specifically the only time that I saw a name the Raven specifically in that article from the athletic was um we talked about last year when Ravens offered money until I was like oh I almost went to the Ravens but then I turned it down because Jim Ursa and the coach they came through with this last minute pushing I came back home then he got hurt again but anyway team keeping clean I love y'all so much I appreciate y'all um and yeah man just like Sam Cookie is when it comes to being a member of Baltimore Ravens oh one last thing I was about to say I'm out buying out yep I know there have been a lot of people who watched the video Eric DeCosta and they've been like oh because I know my boy Mark is he hit me up another one of my guys hit me up about it too I forgot who it was my apologies to you know I love you but a couple people hit me up they say oh hey did you see Eric DeCosta you saw Eric DeCosta's hoodie y'all so you saw you saw you saw him with the uh with the Lamar Jackson hoodie on ho ho Lamar locked in baby let's get it and me I'm like uh that was nice it was cool nice gesture shout out to Eric DeCosta wearing Lamar Jackson's hoodie his apparel and whatnot but nothing's official till it's official so I yeah we'll see how things go with Lamar Jackson in that contract I still ain't expecting anything to be done this year but yeah we'll see so Eric DeCosta you keep on wearing that Lamar Jackson appear I actually got to get me once Eric thank you EDC for more to me motivated me to get a Lamar Jackson one of them a wild dog hoodies man so I appreciate it shout out to y'all shout out to you team keeping clean appreciate y'all thank y'all for watching thank you for supporting and just like Sam Cookie is now we out


Okay, so this is a quite interesting video and I think it's very topical at the moment Of course we get all these results from vaccine trials and when you read these trials You'll see a lot of them expresses the efficacy of The vaccine now in order for us to determine efficacy. We look at the relative risk So this video I'm going to show you a notebook two notebooks in actual fact I'm gonna use our just to explain the language for for statistical computing Just what relative risk is and how we then use it to calculate efficacy And we're also going to look at a specific trial in South Africa There was a small trial as far as the AstraZeneca vaccine was concerned and it showed very poor efficacy And because of that the vaccine was withdrawn from South Africa Which of course is a very big decision was the first vaccine It was supposed to go to healthcare workers such as myself and the vaccine was withdrawn because of the poor showing So we I'm going to show you how they got to this very bad efficacy level of only 21 percent And of course, it's not only about that. It's about this the confidence intervals around that efficacy And that's what I want to explain now, of course with doing that was a very difficult decision And it wasn't only the clinical data. There was some data as well And I'll talk a little bit about it about the neutralizing antibodies, etc A lot more went into the the decision not to use the AstraZeneca vaccine in South Africa So it's all about relative risk and then in this video, I'll show you just how How a relative risk works how you can calculate it and how from that we get the efficacy So here we are on my art pubs website You can view all the documents that I upload you can view them here And of course the original the rmd files are available on github and the links to all of these things will be In the description down below. So we're just going to look at uncertainty in relative risk So first what is risk what is relative risk and how do we express uncertainty in that? And of course, it's very topical with the vaccines these days in the pandemic And we express the efficacy of these vaccines. I want to show you just just how to do that So in this first notebook, we're just going to talk about what risk is and what relative risk is And then what efficacy is and then how can we express uncertainty just due to randomness? We do one trial But there is a lot of other trials that if if we could do it we could do it over and over and over again And this one trial that we have is just one of the possible outcomes And we need to look at where the actual efficacy lies and it'll be in some range That we can simulate around this one This one Study that we've done. So let's first have a look at what risk is And you see then equation one It's just the number of positive outcomes divided by the total in the group Now we've got to talk about what a positive outcome is And we say positive outcome, but it doesn't sentimentally have to be positive The outcome can be quite negative and in this instance It might be well develop the disease and certainly that's not positive But we just use this term. That's the positive outcome that the outcome that we are interested in in an investigating So if we have a bunch of participants in a study A certain number of them will develop this positive outcome the outcome that we're interested in as I said, which might be quite a negative thing But if we just take that ratio that fraction the number of positive outcomes divided by the total number in the group That is the risk Now if we've got two groups one group for instance, I received a placebo intervention and one group received a treatment intervention We can just look at this Difference in the risk between the two So we'll calculate risk as per equation one for both of them And we just take the difference. So the risk in the control minus the risk in the treatment And what we're assuming here is that the risk in the treatment will be lower Because the other name for risk difference is absolute risk reduction ARR absolute risk reduction That's just the difference in the risk And that's a very good way to express A difference in risk between a control group receiving the placebo and the treatment group getting this active intervention So just that difference So you've just got to just watch out if the risk in the treatment ends up being higher than the risk in the control Of course, then we cannot talk about absolute risk reduction Or we still can't talk about absolute risk reduction. We just got to say that being in the placebo group Gives us a reduction in risk for this positive outcome that we're talking about You see there the number needed to treat that is just an equation three there We're not going to discuss it. I've just put that in for you. So what we really want to do is talk about relative risk You'll see our our risk ratio relative risk That is The fraction of the risk of the intervention over the risk of the control So we've worked out the risk in both groups very simple calculations the positive divided by the total the positive divided by the total And for these two we'll just Um We'll we'll just take the ratio Now what we're hoping for you, of course is that the risk The positive outcomes that fraction will be lower in the intervention or the treatment group than in the control group And if that is so this fraction of course will be less than one And if it's less than one it means The risk is lowered by being in the intervention or treatment group So that's when we express this idea of efficacy So let's imagine here in this piecewise defined function On the top row here for efficacy that the risk in the treatment group is lower than the risk in the control group that it was good to develop this because fewer people Fraction wise for the individual groups Was lower if you were in the treatment group than in the control group That means this relative risk will be less than one It'll be a fraction of one And what we do is we subtract that relative risk from one so one minus the relative risk And that gives us the efficacy Now i've put the second part in here, but we really don't use the second part I just want it's just to to Keep your mind or to to simulate your stimulate your mind a little bit Imagine that the risk in the treatment was higher Then we can't really talk about efficacy anymore In as much as if this positive outcome was a negative thing and we want the treatment to lower that risk But now it's going to increase that risk. So we just say relative risk minus one But I warn you there then we can't really talk about efficacy anymore The efficacy is really just for that first line One minus the relative risk. So let's look at some coding examples. So we're going to simulate a study We're taking 41,100 people in our study Which is when these vaccine trials were developed, what is the power? We need to to see how many people need to be in there so that we reach a sufficient Power to this to to to find this significant difference between the two So we say here now control group that were 20,500 people and in our treatment group There were 20,000 six 20,600 people And we're saying in this trial 350 people in the control group develop the positive outcome. So this is just thumbs up numbers Not from a specific trial And 115 in the treatment group develop the positive outcome So in the case of a vaccine We have 350 people in the control group. They just received a placebo They developed the disease and only 115 then in the treatment group who got the active vaccine Develop the positive outcome which is developing the disease So we're just saving that also as some computer variables. So we've got a underscore control and underscore treatment And if we just divide those 350 divided by 115 That's not something that we would express but just for interstate then There are three times more positive cases in the control group than the treatment group now There is no denominator in here. So if I had lots more people in the placebo group Then in in the treatment group that value was going to change So that's not a valid expression really of what is happening here. It's just expressing in this Nearly equal groups that we had There were three three times more positive cases in the control group. What we interested though is is is the risk So let's see what the risk in the control group is which I'm going to call risk underscore control here So that's a that's the control. How many got the disease divided by how many was in the control group So that's going to be the 350 divided by 20 500 and we see a value of 0.017 Now what you would commonly see is this multiplied by a thousand So you can say that the risk of developing the disease would be if we multiply that by a thousand the one two three That'll be 17 people per thousand people So you'll always see that per thousand per ten thousand per hundred thousand depending on what makes sense Now let's do the same for the treatment group. So that's the A underscore treatment That's how many got the disease in the treatment group and divided by how many there were that's just the risk And we see a much lower risk here of 0.005. So there'll be five and a half people per thousand people Develop the disease Was it the risk then of developing the disease and now we're just going to do the relative risk So it's the risk of the treatment over the risk of the control And now we see it's 0.32 multiplied by a hundred. That's about that's 32.7 So we want to express efficacy though So we're going to subtract it from one. So one minus that one minus the relative risk and we get the efficacy 67 So we can say the efficacy of this Of of this vaccine was 67 And that is how much it lowered the risk really that is what we're expressing But as I said before that is just one study we did And if we started a week later, we would have had other people in our study if we could do this over and over again We would get different results every time So this one result this one efficacy that we found this is one of many possible ones And what we are interested in is not only this 40 41 100 people in our study We want to infer these results because it's just a sample On the larger population. So what is the true efficacy in the population as a whole because eventually we want to inoculate everyone So we need to express a confidence interval around this efficacy And how do we go about that? You know, so in different papers, you'll see different methods of doing this There are different equations for doing this clopper Pearson There's some other ways of doing this as well But what we're going to do here is something that I like to do and that is just to do resampling From the results that we found And in that way we're going to build up simulate a bunch We're going to do a thousand As if we're doing our study a thousand times over that gives us a distribution of poor possible Efficacies and we can then calculate the 95 percent confidence interval Now remember what confidence interval means. Maybe I should should keep quiet now When we get to confidence intervals when we've calculated the confidence intervals, I'll just remind you exactly what that means So here in our we've created a little function. I'm going to call it simulate underscore group It is a function. It takes two parameters n and p Now what we're going to do is create this Local variable inside of the function. It doesn't exist in the Global space. So it's just internal to our function. I'm using the our unif function random uniform So we're going to draw a random number from a uniform distribution uniform distribution Remember is that every element in the sample space Of of this distribution has an equal likelihood of being chosen at every time we run the experiment So the random uniform is going to draw From zero to one in that interval on that interval zero to one. It just draws a random value So it will then throw that value back in the bin so that the next time around we do it that number is It is possible to draw that number again But every value from zero to one has an equal likelihood of being chosen a uniform distribution It's not bell shape that certain values are more likely to be chosen at random. It's uniform And now what we're going to do is we're going to look at this number That is chosen and we're just going to sum them up if That value is less than p the probability Now that p that we're talking about here is actually the risk remember There were a certain number of people who got the disease inside of that sample of people And if you think about that that the risk that is if we do that division The number got positive divided by how many there were That's in essence a probability of this p that we're talking about here in our function the parameter that we've called p So we're saying we're going to simulate this And we're going to say that a random person We're just simulating this random person. They get this random value And if that value is less than this p p value now, I'm not talking about a statistical p value not the famous p value I'm just saying this risk If that was smaller than that when then we're going to start summing them up And that's a simulation because anyone can get from from zero to one And this value that was chosen there and we only sum them up We only sum it up When it is less than the numbers that are come out less than this p value the risk in in actual fact And what we're going to return is this k divided by in The in that we supply to the function the sample size So let's let's look at that. So I'm storing p now as In this instance, we're going to take the risk in the treatment group. So the number got positive And divided by the total number. They were that's our p And now we're going to run a single simulation So we're just going to say in treatment p and we just run that And now we have not seeded the seed of random number generator here So every time you run this code, you're going to get a different value But in this instance, I got 0.0055 Now we're going to use list comprehension and you'll see early on this notebook. I just I just Loaded this comprehend our Package because it contains this function to VEC And it's going to allow us to do list comprehension or in this instance vector comprehension So I'm just going to simulate this thousand values all in one go So that I just have this vector of a thousand possible instances I'm going to store that as t So we're just going to simulate this risk in actual fact over and over and over and over again So sometimes The value is going to be more than p and it won't be summed and sometimes it's less than p and it will be summed From what we've done way up there So if we do that, we get these thousand values and we can draw this kernel density estimate plot And it shows us this distribution of risks simulated risks There we go for these thousand times as if we could do the study a thousand times over And there you see the distribution of risk a lot of them here by 0.05 just over that open of 0.05 three thereabouts four And that was just simulating that over and over again Now one way that we can express this sort of range of values The measures of dispersion would be standard error And what we've done here is just to take the standard error. That's the standard deviation of t in this instance and we can see it there And because we've got this distribution now we can we can calculate the From all these values these t values we can calculate these cut-off values So for that i'm going to use the quantile function And i'm just passing that 1000 values to it And i'm saying calculate for us these intervals that will be five percent cutoff at the bottom 95 percent cutoff at the top. So if you look at this basically it's going to cut off The bottom five percent and cut off the top five percent and that gives us a 90 confidence interval then and the values within this 1000 values of ours that gave us that was 0.00475 to 0.0064 So then we're saying a 90 percent confidence interval around this Around this risk of ours the the the Mean risk Was going to be these values. So you're not necessarily interested in this single one. We want the relative risk So we're going to create another little Equation here another function. I should say and it's just going to do what we've done before twice For the control group and for the treatment group this time so that we can have this efficacy as one minus The relative risk Risk two that's going to be the treatment divided by risk one, which is going to be the control So we've got to pass four parameters there So the p-value that we are going to ask for it to count below As the p1 will be the controls risk and the p2 will be the treatment arms risk And then we just simulate that once And it'll give us back one possible efficacy 65.9 percent Now again using this two-vec function, I'm going to create this vector of a thousand Efficacies all in one go calling this function of our simulate trial And the simulate trial remember it calls the simulate underscore group function twice one for each of these Two groups of ours And if we plot the kernel density estimate there, we see that we have this Range of values possible values. We just simulated So we resampled based on this finding that we had for this specific study And then we see the mean efficacy of the 1000 simulator trials was 0.67 our actual one was also 0.67 That's where it's going to work out. So if we want a 90 confidence interval for that We just pass those thousand values to the quantile function And we set a probability cut off the bottom 5 percent the top 5 percent What were the values within t2 Which is where we saved a thousand values would be 60.8 to 72.7 So we can say the efficacy of this study for this drug or this vaccine was 67 percent 90 or 90 confidence intervals 60 to 72 Or about 61 percent about 73 percent So that's 90 confidence intervals And now let me just remind you what confidence intervals is we we're not saying that we are 90 confident That in the globe as a whole if we gave it to everyone And we are 90 it's not to say that we're 90 percent sure that the true efficacy in the Will population as a whole will be this. No, that's not what it means. It means if we ran the study 100 times over Just imagine what that would cost now long that would take but if we ran it 100 times over Every time we're going to get slightly different confidence intervals in 90 percent of those The true population Will be True population efficacy will be within the confidence Intervals that we set so we're not saying that's true for the specific one is if we could do it 100 times over in 90 of them 90 of them will capture within its bounds the true population efficacy Now that we've done that let's go and see the trial that was done in South Africa with the astrazeneca trial And now this trial i'm going to warn you i mean from the time of this recording It's just on as available the pre-printed was not Not accepted by a journal yet not peer reviewed yet And on the space on the evidence of this very small study The the vaccine was withdrawn from South Africa So there was about a million doses available. This was the first doses Of any vaccine to land in South Africa It was ready to be distributed amongst healthcare workers And it got pulled On the strength of the study now the study has more than one component So what we're going to look at is just the clinical side of it Looking at the relative risk and the efficacy But it was also about it was about more than that there was Part of the analysis was also on the neutralizing antibodies And whether they could were effective against the the the variant that's prevalent within South Africa So it's not just based on this But i want to show you What what the what relative risk does in efficacy what it would look like at least the Uncertainty in the value when we're dealing with a small trial and how difficult it becomes In a small trial where the risk is relatively low. So let's look at that So you can click on the link there to find the pre-print of this article And there were some potent points So the primary endpoint and i've just listed them here the primary endpoint was this efficacy of Confirmed symptomatic COVID-19 more than 14 days after the second dose So waited 14 days after the second dose then start looking at whether people develop confirmed symptomatic So the primary for the primary efficacy analysis only per Perperatical seronegative participants were included And the vex vaccine efficacy ve was calculated as one minus the relative risk and 95 percent confidence intervals were calculated Using the clopper Pearson exact method as reported. So that's not what we're doing. We are using resampling Which is what i like to do There's a bunch of these tests and they have their strengths and weaknesses and debate about You know, whether they work or not and when they should be used and when not My feeling on the matter use use resampling So with a thousand and ten participants received vaccine and a thousand and eleven received placebo And in the end there was a lot of exclusions You can read the paper as to why in the end though remember our Simulated study before had over 40,000 people in them 20,000 more than 20,000 each arm Yeah, there was only seven hundred and fifteen in the vaccine group. There was analyzed in seven hundred and seven fifteen vaccine In seven seventeen in the placebo group. So very small now and Other problems with the trial and and i don't say that's problems. The trial was correctly done Is this we want to infer that to a larger population the population out there and of course The participants in the study were not representative of the population as a whole. It was only representative of certain people In the population because the median age was very young was only three one years 56 and a half percent were male And then there was a racial distribution as well All 42 endpoint cases were graded as either mild or moderate. So there were no severe cases Following this trial. So even in the placebo group, there was no Uh, severe cases and we can see in the vaccine group 15 Mild and four moderate and then 17 mild and six moderate So there are no cases of severe disease or hospitalization in either arm So that makes it very difficult because half of these people receive placebo To infer the results to the larger population So let's just see You know if we do the relative risk And we look specifically at the uncertainty around the relative risk. That's what this is all about So there was 717 in the control group 750 in the treatment group 17 plus six that's the mild plus moderate I got the disease in the control group and 15 plus four that's in the treatment group So we're going to work out the risk in the control group Which is just that very simple ratio and the risk in the treatment group so that we can express the relative risk And the relative risk as you can see there that was lower than 1 So we subtracted from 1 and we get the efficacy and that was the headline. It was only 21 effective Only 21 effective and of course Mostly you'll see that we're looking for at least 50 efficacy in these but here comes the problem And we need to express our uncertainty In this 21% efficacy And so again, we're going to create our two functions the one that just simulates again from a random uniform distribution Just as we did before only counting those That was lower than this risk value And then we're going to simulate it The two risks and we express the efficacy again as 1 minus The risk 2 over risk 1 so risk of the treatment divided by risk of the control group NLP values here again remember that just taken from the outcome of this actual study The two risks and then we're going to simulate it and I've run a simulation just this once And we get a negative value We get a negative value And now this becomes very difficult to interpret And let me show you why because now we're going to simulate it a thousand times using this two-vec function So we can do list or vector comprehension So in one go we get our thousand values And here I've used plotly and not the inbuilt r plotting So we can see here this distribution around the around the efficacy And you can see how it tails off below zero Now how do we interpret that? So I'll leave that for you in the comments to interpret that Because if you think about it, we're actually back in the real realm of the vaccine actually increasing the risk Okay, and that's the way that the values are going to come out And you can see this bump here right at the top It is at about About 21 22 23 percent and the efficacy And what we're interested in now is the 95 percent confidence intervals So we said the efficacy of this study of the astrazeneca Vaccine was only 21 and now you see the 95 percent confidence intervals around that From negative 50 percent to about 59 percent So it's quite possible that the efficacy of this The efficacy out in the population just based on the study that the efficacy of astrazeneca vaccine out in the population Is somewhere between there So this is bizarre on this side, of course And as I say leave your thoughts in the comment what this negative values would really be but This is we're still within the 95 percent confidence intervals almost 60 percent efficacy of the astrazeneca so Very difficult to make decisions based on a small study like this Where our risk is very low The risk is very low for someone to develop the disease both in the placebo arm and in the treatment arm and The efficacy they've The the two risks were very close to each other meaning the efficacy was only 21 percent But because these values are so small and we simulate a thousand of these when we express our uncertainty in this 21 percent you see that this uncertainty is quite big and as I say this The the the idea behind the study was not only looking at this to make the decision to withdraw the use of the vaccine Astrazeneca vaccine in South Africa because a part of the study was also about neutralizing antibodies, etc There's a whole other parts to that But see how difficult it is How difficult it can be if you've got relatively small sample sizes and the risk is also small Then you are going to struggle to just make a decision Because your uncertainty in your efficacy is not going to be very good There's going to be a wide confidence interval in the efficacy So I hope this was interesting for you. Leave some comments down below Remember to like the video You can read this these notebooks here on our pubs or follow the link down below to download the rmd files the our markdown files if you've got our studio You can just import that and you can play around with these values Maybe simulate some more draw some pretty graphs, etc And I hope this really helped you to understand the idea a very relevant example of understanding relative risk and efficacy


Everybody welcome back to the Photoshop tutorial in this one going to show you how to change the color of an eye like a pro Here we go I'm going to show you step by step first step get your footage in or get your image in now You want to go to your toolbar and select the pen tool We're going to draw a mask around the eye just like this and it doesn't have to be perfect because we're going to Be doing some feathering, but you know make it as good as you can something like this And I would normally zoom in a little bit more, but hey, you know what this is just to show you the technique Okay, zoom in. Yeah, it's pretty good doesn't have to be perfect Like I said now right click on it and make it into a selection feather the radius by as many pixels You see fit for me I'm going to go with four pixels for this one because I want a nice feathered edge Okay, good because that way it dissolves off into the distance. All right good enough now The next step is we're going to go down here and we're going to create a new solid color Adjustment layer go to solid color and now we're going to select the color we want for this one I'm going with a darker green. We're gonna make a nice dark green eyeball. All right Good left click on okay now holding down the alt key or the option key We're just going to clip it to the mask below Although that's not necessary. It's just a old habit and now let's drop the opacity down to about 60% that's kind of in the ballpark, but again, it doesn't look natural yet not to worry select the blending mode right here Go from normal go to color now. You're going to see what we're working with now We're really close if you want to go a little further click on this mask and then adjust the feather as you see fit For example, I like to feather it up quite a bit something like that's a bit too far Something like that looks pretty natural and it's got some blue kind of going into the green there And as a last effect if you really want to go down the rabbit hole You can grab a brush like this make sure that you've got a soft round brush like this select it Opacity flow 100 and then you can actually go around the edges if you wanted to get rid of some of this green Tin if you're painting with black like I am you'll see that I'm removing some any any external any extra green This is not a necessary step, but it is something you can do. Thanks for watching


What's going on, everyone? Sam here with late sports cards. Rippin' 22-23, pretty impeccable basketball hobby, three box case break, number 36 tiered random team style. So look again at your random results. As always, you can find those on the websites, under the results tab, as well as the link in chat. Five on TikTok, oh boy. What's up, JT? Legal and Shane together and at the national, that's scary, man. Hello, boys. That is a trash list, like, convention right there. Hey, Donny, you want to see me do the grouchy, Sean? No, here you go. Stop naming moves after me. Oh, you did it, you did it, okay. Everyone's a steamer, except for me. 99 of 99, Devin Booker. Standless stars for the Suns. Nice one there, Suns. Here we go. That is going to be a Cam Thomas, 25-75 for the Nets. And Kelden Johnson, 32-49. Oh, man. Devin Vasell, that is 25 of 99. First hit is going to be going to the Celtics. Dino Raja, nice one there, 46 of 99 on the Estravigans. Estravigans. Got Musa Diabate, three of 10 on the Rookie Auto. Nice one there for the Clippers. Nice tier two hit there for Brent. That's Brent. Musa Diabate. Next up, we've got going to the Wizards. Johnny Davis, 95 of 99, Rookie Auto. Terry Eason, that is going to be 63 of 99. Nice one there for the Rockets. And nice one here. Going to Bradley Yard. Chet Holmgren, 18 of 25. Two colored RPA. Congrats on that one, Bradley. There you go, buddy. Bradley with the thunder. Gorgeous, Cade.  Congrats, buddy. Nice chet there. That was what, four Rookie Autos. Back to back to back to back. That's kind of nice, too. Yeah, congrats on that, Bradley. Very nice one coming your way. That is a silver card.  Where's that from? Is it the new ones? Well, they're in the back. And of course, you said they use them. All right. So, here. Well, let's see how the sticker looks on. 70 of 99, Chet Holmgren on the Metal Card. Nice one there. Stainless Stars, I should say. Stainless Stars. All right, Desmond Bain, 5 of 49. Drew Holiday, 13 of 75. Got Donovan Mitchell, 6 of 99 on the base cards there. First up on the hits is Trevor Keels, 5 of 10. That's a pretty nasty RPA. Congrats, Nix. Oh, that's cool. That's really nice. That's going to Chase and A. Yeah, Chet is like 70-pound soaking wet, dude. Chet Holmgren's a skinny dude. Could take something my way if he wants. Bernard King, 41 of 75. Illustrious Ink, again for the Nix. Nice one here. Immortal Ink for the Pistons. Joe Dumars, 6 of 99. Congrats on that one there, Pistons. Joe Dumars. Next up again for the Nix. That is going to be a Jalen Brunson. Elegance, Jersey Auto, 15 of 99. That is going to be Game Worn Slash Use Material as a member of the Dallas Mavericks. Very nice one there. We'll use our yellow card. This red card is the Redemption. That is going to be Elegance Veteran Jersey Autographs. Card number four, Steph Curry. Let's go, man. Going to the Warriors. Adam Kay, congrats, Adam. Good job, Adam. Elegance Veteran Jersey Autographs of Mr. Chef. There you go, TikTok. Take a look at it right there. Look at it. Look at it. Adam, congrats, buddy. Big cards at the end of the back-to-back boxes right there. We had the Chet in the last one. Curry in this one. Very nice. Now, Curry, that's all right. That'll work. That'll play. That'll play right there. It's okay. All right, we've got our bar card.  All right, we'll do the bar card last. I don't know what came out of that box. That was weird. Carboard, Sam. Carboard came out of that box. Thank you, Donnie. You're welcome. Hope your mystery is solved. Thanks to you, I would say yes, it is. It definitely is. Sweet. Dyson Daniels, 33 of 75. Elegance as well as a Boyan McDonovich, 3 of 75. For business. That's a Jason Tatum, 69 of 99. Nice. Tatum for the Cs. Coran Butler, going to the Wizards. That's sick. 67 of 99, Yukon legend right there. Coran Butler. That's Washington. Dallan Terry, Rookie Otto, 61 of 99. Foe, the Chicago Bulls. That's Bulls. Next up is for the Hawks. That is going to be Deandre Hunter, 17 of 35. Hunter. Hunter. Tom with 3 and 20, Bowman. Thank you there. I appreciate that one, Tom. That's awesome, man. Appreciate it. Jazz, we've got 10 of 14. John Stockton. There you go, Bradley. Bradley R. Congrats, man. 10 of 14, 14 assists, 14.5 assists per game. 89 to 90, that's awesome.  This is going to Rory. Rory C, how about Nicola Jokic? Six of four. Six of 25, a live Joker. Holy cow, man.  Shet RPA to 25, then a curry redemption, and then a Nicola Jokic to 25 in one case. Unbelievable. That's awesome. A lustrous ink, Nicola Jokic. 3,000. So sick. And now the bar card. He's going to look good in a black ring. Oh, yes. That is going to go into the Raptors. Christian Coloco, 13 of 20. One Troy ounce of Bon Silva. Christian Coloco, 13 of 20. Congrats, Raptors. Nice one there. Tier two for Adam Kay. All right, guys. Quick recap here. We had the John Stockton. That is going to be DeAndre Hunter. Dallin Terry. Hey, Koran Butler. Jalen Brunson. Joe Dumars. Bernard King. Trevor Keels to 10. Nice RPA there. Terry Eason. That is Johnny Davis. Musa Diabate. Dino Raja. We had Mag Cards, like I said. Really, really, really good break overall here. That is going to be Christian Coloco, 13 of 20. One Troy ounce of Bon Silva for the Raptors. We had the Chet RPA, 19 of 25. Chet Holmgren. We had Step Curry. Elegance Veteran Jersey autographs for the Warriors. And then we had a Nicola Jokic, 6 of 25. That is going to the Nuggets. That will do it for the break, guys. Thanks again for the filp. Up next, we've got Leaf Pearl. Nice.


So let's go ahead and I'm going to save this for later and I'm just going to say I've got to add that $1,000. So the easiest way to do that is probably to hit the Carat over here and go to the accounting and the chart of accounts is what I'm looking for and go to the accounting and then the chart of accounts and if you're in the Business view by the way the chart of accounts is under the bookkeeping and the chart of accounts and And then We're going to go down to the credit card down to the credit card. There it is. I'm going to look at the register I think that's the easiest way to enter it and open in the register and Then I'm going to enter like an expense. It'll be like an expense charge type of thing I'm going to enter as of the end of the month, which was 08 31 2 2 I think maybe the beginning of the month would be better. I should now note a couple things to note You don't if this is a beginning balance and it was coming from a prior accounting system You don't want to put the beginning balance possibly on the income statement, right? Because it's something that you've already accounted for on the income statement. It therefore the other side you can record to equity equity Or you can record it to like Like an expense account if you're doing it in the prior period meaning if I was starting my books in January 2022 then I might want to enter it as of December 2021 so that if there's any impact on the income statement it rolls into the balance sheet and I'm good to go but I'm just Going to enter it in directly into the equity accounts. I'm going to say 08 08 let's say 0122 and I'm going to say that this is going to be a memo. Let's say beginning balance beginning Balance it's going to be a charge of a thousand I'm not going to put it to the income statement But just directly to the balance sheet account assuming it's from prior activity in a prior period So it shouldn't be on the income statement. So I'm looking for an equity account So if I go down it would be an equity We we could put it to opening balance But you don't ultimately want it in opening balance should be either you would think in owner's equity or in our you know investments Or you know draw I'm going to put it into owner's equity it's going to go into owner's equity and That's it. So I'm going to say okay So boom let's take a look at what happens on the financial statements from that transaction running it running and I'm scrolling down scrolling down scrolling down the visa account if I go into the visa Did I take that the wrong way? It's going to be owners It's going to be the one thousand right here No, because I'm so there it is and if I go into it It's an expense type of account of form that I use go into the credit card as opposed to the checking account Scrolling back up top the other side. I put into equity Instead of the income statement I can't look at it because it won't drill down on it if you want to drill down on that number you could open right click and duplicate you can open a General ledger report so I can go down to a report and say general ledger General ledger. I want to see the detail in that account and they won't let me click on it so I'm going to go to the general ledger and then from let's go from 010122 to 1231 222 run it and Then I can say okay cash accounts receivable inventory blah blah payments equipment Total here's the credit card and draws opening balance and Owners equity so there's the activity for owners equity and there's our There's our thousand dollars so for some reason that well It's not for some reason the reason you can't double click on it Even though you can post to it is because that's the account that income rolls into So for some so you would think you would still be able to click on it But you can't so you can see the detail here though by opening a general ledger report. Okay, so back to the first tab Let's go into our hand boogie and then go down to the chart of accounts again or accounting and Then go to the reconcile tab and let's resume the reconciliation resume and So now I've got the thousand dollars stop showing me these stupid things Boom and now I've reconciled. So now I'm in balance. So we should tie out now. So I'm gonna say okay let's go ahead and and Finish it. So this is the process of reconciling now the reconciliation report will be very Blah, there's nothing to do reconcile this account. How do you want to pay your bills? So now it's asking. There's an outstanding balance in the credit card So I could then pay the outstanding balance right now. I don't want to pay the outstanding balance I'm gonna pay it when I when I want to pay it. So I'm not gonna do it as I reconcile. So I'm just gonna say done


The term liberalism is a victim of what historian Ralph Raco has called conceptual mayhem. From its original use to describe the ideology of private property and freedom for individuals, the term liberalism eventually came to describe ideologies of an entirely different sort. By the mid-20th century, liberal was being used to describe a wide variety of social Democrats and other supporters of government-managed and government-planned economies. Hello, this is Ryan McMakin, and you're listening to Radio Rothbard. According to Raco, liberalism properly understood is, quote, the ideology that holds civil society, understood as society minus the state, by and large runs itself within the bounds of the principle of private property, unquote. Society minus the state, of course, is no simple matter. It is a complex array of civil, religious, social, familial, and market institutions. And according to the liberals, these institutions, if organized according to principles respectful of the principle of private property, could function mostly in a state of cooperative peace. In this view, however, the state is an institution separate from the others because it relies on coercion and taxation, unlike the voluntary institutions that otherwise comprise society. The political economy of these liberals, therefore, then came to reflect a skepticism toward the state, and a preference for a society dominated by non-state institutions like markets, families, and churches. Liberals sought to minimize state power and to devise political institutions that might limit its abuse. Historically speaking, this view of liberalism well describes a theorist commonly regarded as liberals throughout the 18th and 19th century, and even into the 20th. Liberal theorists such as Lord Acton, Gustav de Molinari, Frederick Bastiat, Herbert Spencer, Benjamin Constant, Richard Cobden, Ludwig von Mises, F. A. Hayek, Adam Smith, and the Marquis de Condorcet, among others, all certainly fall within this general description of liberals. Certainly these theorists often diverged as to the extent of their radicalism. But the fact that these theorists varied in their radicalism only shows the broad historical, geographical, and intellectual breadth of liberalism, as it gained influence throughout much of Western Europe and the Americas. But there were limits. Removed from the core commitment to private property and economic freedom, liberalism ceases to be liberalism. For example, in later times, Raco notes, the term liberalism suffered as historians attempted to place more and more theorists of widely diverse views under its banner, theorists such as John Rawls, Carl Popper, John Maynard Keynes, and John Stuart Mill. But if theorists such as these are liberals to be placed alongside men like Molinari, then the term liberalism ceases to have any useful meaning. Much of the confusion stems from the fact that historians have often attempted to classify liberals based on their views in regard to subjects outside matters of political economy. It's true, airsats liberals like Mill and Keynes were in favor of freedom when the idea fostered personal expression through certain religious or sexual practices. But Mill and Keynes were notably less liberal when it came to larger issues of taxation, trade, war, and labor issues. Similarly, historians have tried to classify liberalism based on criteria divorced from economic and personal freedom altogether. Instead, they grant the title of liberal to those who maintain certain views about the meaning of life or utilitarian ethics. The result was often a definition of liberal that had nothing to do with the private property-oriented political economy that had dominated liberalism from the beginning. In other words, it may be easy to make the case that, say, both liberal historian Augustine Thierry and social democrat John Maynard Keynes were skeptical of the idea of organized religion. To conclude that both were therefore necessarily liberals, however, requires one to ignore the prevalence of private property in the views of influential liberals such as Bastia and Cobdon throughout the 19th century and beyond. After all, if a liberal is defined primarily by hostility to traditional Christianity, say, then how to classify a practicing Catholic and liberal such as Lord Acton? One strategy has been to arbitrarily reclassify men like Acton as conservatives. Another strategy has been to simply redefine the pro-private property position itself as conservative. As Raco noted in one especially egregious case, quote, Elio Jaguaribe, evidently a star of Brazilian political science, describes Hayek Milton Friedman and Ludwig von Mises as, quote, extremely conservative. David Spitz likewise refers to the three thinkers as conservatives, though what he could understand of their views is unclear, considering that he believes that Herbert Spencer was their, quote, unquote, patron saint, unquote. The punchline here is that by virtually any measure, Herbert Spencer was so unconservative that the suggestion that he was the chief intellectual influence on supposedly extremely conservative theorists like Mises and Hayek renders the claim rather absurd. If we use the principle of private property as a central tenet of liberalism as Raco suggests, then we do find a quite plausible foundation for classifying liberals properly.  Mark Thornton recalls an exchange with Raco on the matter, quote, Ralph stepped forward and began to explain that the word libertarian was relatively new. He said that the term classical liberalism was also used to describe libertarianism. However, he explained the phrase classical liberalism was also a modern invention, and then he went on to explain why we should be using the word liberalism to describe the true philosophy of individualism. For Raco, there was no clear distinction between liberalism and libertarianism, nor does the fact libertarianism denote a rather more radical strain of liberalism make it somehow non-liberal. After all, by today's standards, the thinking of Herbert Spencer and Gustav de Molinari were all quite radical, yet few dispute both were liberals. Some historians have attempted to differentiate libertarians from liberals based on minor policy differences, but these attempts fail. Raco notes, for example, quote, Grappling with this issue causes even as accomplished a historian of ideas as Alan Ryan, author of Making of Modern Liberalism, to flounder, Ryan concedes a place to Hayek within the category of contemporary liberals, but denies that libertarianism can be a variety of liberalism on the grounds that even classical liberals did not favor decriminalizing victimless crimes. But not only is this libertarian position clearly implied by, for example, Herbert Spencer's Law of Equal Freedom, it is also the stated view of Ludwig von Mises, unquote. For his part, Murray Rothbard considered libertarianism to be merely a variety of liberalism, and that the history of this ideology extended back at least to the 17th century. In For a New Liberty, he writes, quote, The object of the classical liberals was to bring about individual liberty in all its interrelated aspects. In the economy, taxes were to be drastically reduced, controls and regulations eliminated, and human energy, enterprise and markets set free to create and produce an exchange that would benefit everyone and the mass of consumers. The earliest theoreticians of libertarian classical liberalism were the levelers during the English Revolution and the philosopher John Locke in the late 17th century, followed by the true Whig, or radical libertarian opposition to the Whig Settlement, the regime of 18th century Britain. Moreover, Rothbard considered the American Revolution to be a thoroughly libertarian revolution and an outgrowth of earlier liberal political and intellectual movements. As with liberalism in general, at the center of the conflict was the matter of private property. Rothbard says, There need be no dichotomy between liberty and property, between defense of the rights of property in one person and in one's material possessions. Defense of rights is logically unitary in all spheres of action, and what is more, the American Revolutionaries certainly acted on these very assumptions, as revealed by their essential adherents to libertarian thought, to political and economic rights, and always to liberty and property. The men of the 18th century saw no dichotomy between personal and economic freedom, between rights to liberty and to property. These artificial distinctions were left to later ages to construct." Also illustrative of the liberal libertarian convergence is the case of Ludwig von Mises. Mises was always self-identified as a liberal, and he was clearly a liberal within his own social and political milieu in Austria. He wasn't a socialist, and he certainly wasn't an adherent of conservatism, which in 19th century Austria was, as Ronald Hammouy trenchedly put it, the ideology of the rack, the thumbscrew, the whip, and the firing squad. Indeed, Mises' views outlined in detail in his 1927 book, liberalism, supported political freedom in almost complete laissez-faire in both domestic markets and an international trade. He opposed war, generally supported free migration, and pushed for political decentralization. These views are what we might call textbook liberalism, and Mises' student Hayek held similar views, albeit to a far more mild extent. Notably, both Mises and Hayek are today routinely referred to as both liberals and libertarians. To say that the effect of liberalism on the world has been profound would be an understatement. In English-speaking countries, of course, liberal political movements pushed policy rapidly in a liberal direction throughout the 19th century, and then served as a much needed break on social democratic movements in the 20th century. In France and elsewhere in Europe, liberalism served as a crucial counterbalance to the march of socialists and totalitarians. While liberalism has never dominated French politics, for example, the success liberals have had there has not been without effect. Without the liberals, France may very well have succumbed to outright socialism in the 19th or 20th century. For the past 200 years, liberal activists like Cobden and liberal intellectuals like Ludwig van Mises have remained the voice of reason in the face of relentless competition from socialists, mercantilists, fascists, and warmongers of every stripe. Some critics of liberalism often haroonf that liberalism, that is, libertarianism, is irrelevant because socialists and social democrats continue to be popular in various times and places. But rest assured, Lou Rockwell reminds us, things could be far worse, since, quote, were it not for the efforts of a relative handful of intellectuals who have fought against socialist theory for more than a century, it might have been 99% in support of socialist tyranny. So there is no sense in saying that these intellectual efforts are wasted. Unquote. Moreover, the success of liberalism is demonstrated in the fact that non-liberals have long attempted to steal the mantle of liberalism for themselves. In the English-speaking world, it is no mere accident of history that social democrats and other non-liberal groups often insist on calling themselves liberal. The effort to expropriate the term liberal in the 20th century was a matter of political expediency. Liberalism was a popular and influential ideology throughout the 19th and early 20th century. So it only made sense to attempt to apply the term to non-liberal ideologies and coast on liberalism's past success. Today, we continue to see the legacy of liberalism worldwide in discussions over human rights, in efforts to increase freedom and trade, and greater autonomy from state intervention. The fact that socialists and other types of interventionists win victories proves nothing about the relevance of liberalism. They only remind us how much worse things would be were it not for liberalism's occasional successes. Moreover, efforts by governments to co-opt liberal vocabulary for purposes of building state power are to be expected. We see this often in the call for government-managed human rights efforts and in calls for globally managed free trade. These measures aren't liberal, but governments know saying liberal things and professing to pursue liberal goals makes for great PR. Meanwhile, the answer to gains made by social democrats and socialists lies in strengthening the intellectual movement that is liberalism, which over time translates into political action. If liberalism is eclipsed today by other ideologies, the fault lies with us who have done too little and with the defeatists who declare intellectual fights to be irrelevant to real life or not worth the trouble. Liberalism, that is libertarianism, has a long and impressive history that is all too often neglected, but it is, as Raco contended, an indispensable part of our own civilization. We do well to know more about its history. Thank you for listening to Radio Rothbard. Have a wonderful day.


The anti-cancer effects of the turmeric pigment curcumin extend well beyond its ability to block carcinogens. The anti-cancer effect of curcumin mainly result from the multitude of ways it regulates programmed cell death. It's estimated that the human body consists of 10 or so trillion cells. That's a million million. Almost all these cells get turned over within approximately 100 days. We're like a new person every three months. We reinvent ourselves physically. And since we're just made up of three things, air, water, and food, those are the only inputs. We are what we eat, literally, physically. In a sense, our body has to rebuild itself every three months with the building materials we deliver to it through our stomach. Our mouths are like the access road to the continual construction site to our body. Trucks roll in three times a day. What do we want them to deliver? Some shoddy, cheap stuff we scrounged around for, or bought at the discount outlets that's just going to fall apart? Or do we want to build our foundation solid? We are each walking around inside the greatest known architectural structures in the universe. Let's not ruin such grand blueprints by consuming junk. Anyway, we only own the biological real estate we're born with, so if we need to rebuild every three months, we also need a wrecking crew, right?  We do that primarily through a process called apoptosis, pre-programmed cell death, from the Greek ptosis, meaning falling, and apo meaning away from. So it's ourselves falling away from our body. For example, we all used to have webbed fingers and toes. Literally, each one of us in the womb until about four months. Then apoptosis kicks in and the cells in the webbing in between kill themselves off to separate our fingers.   What can we do about it? Well, one of the ways curry kills cancer cells is by reprogramming the self-destruct mechanism back into cancer cells. Let me just run through one of these pathways. Just so you can see the complexity.  FAD then activates caspase 8, which ignites the death machine and kills the cell. Where does curry powder fit into all this?  It can also activate the death machine directly, as has been shown in lung cancer and colon cancer. Caspases are so-called executioner enzymes that, when activated, destroy the cancer cell from within by chopping up proteins left and right, kind of death by a thousand cuts. And that's just one pathway. Here's all the other ways curcumin can affect apoptosis, and here's all the different types of cancer cells curcumin can kill. But it tends to leave normal cells alone, for reasons that are not fully understood. Overall, this review showed that curcumin can kill the wide variety of tumor cell types through diverse mechanisms. And it's because curcumin can affect numerous mechanisms of cell death at the same time, it's possible that cancer cells may not easily develop resistance to curcumin-induced cell death, like they do to most chemotherapy. Furthermore, its ability to kill tumor cells and not normal cells makes curcumin an attractive candidate. For supper? Can't make money on some spice you can buy anywhere, an attractive candidate for drug development.


This is the animation minute as always I start with jobs here motion films looking for a mid-senior level 3d CGI animator and animation supervisor. Yeah, he's looking for an animation director as well While Prane Studios is hiring across multiple departments including technical animator He's done a job posting for 3d animators all levels in Sonya games has internships including animation That's it for jobs It's going to news you have only thunder gods tail trailer is out this by Tonko house looks very cool New poster is out for Super Mario Brothers the movie including the trailer is out as well And of course the voice controversy also of course it's in animation houses clip you want to watch that That's all my channel as well and more trailers this time It's a new Ernest and Celestine Celestine Ernest. However, you want to pronounce it to the voyage in Charabi looks super cute And the new trailer for Star Trek Prodigy. This is part two of season one this week on a catch up on enter galactic This looks also super cool There is a making of and one more trailer. This is a prologue trailer for his short looking super cool I'm a scrub for because it is awesome. Check this out. It's really nicely done. What's your whole thing? This is very satisfying to watch. This is for Moss 2. Look at that. I love it Love this too bad guys is an awesome movie and I love progression reels You got the layout pass first pass and more. This is cool to watch Thank you for posting that so you go with you to the animation that is a loop But very satisfying to watch. I'll love to the effects speaking of 2d On Fun is that I love it Yeah, let's scroll down for it. You cuteness. Look at this. How cute and there is more There is this one which I do have on my phone right now. That is cool Come on. I'll love these. It's real loving that is pretty cool. I love that I love these be awesome doesn't three printed colors nice lony desks here aligned kind of creepy just the heads on your desk Come on designs are cool. Speaking of cool. That is very cool. Come on. That would be awesome As a backdrop to Animate these are nice and there is more here. This is a whole thread. So check that out. These are super moody sense of scale fantastic Love it and that is cute too. No idea. This is done, but I love it. That's some AR thing I don't know, but I love it. This would be super cool in the desk again More stuff on my desk and of course pixel art. That's pretty bonkers. That's a lot of work and the turn Come on and last but at least more pixel art. This is super cute You can never go wrong with Zelda and that is that animation minute You can find it every Monday every week on my channel