I have noticed that the more I've been pushing away the masculine energy, the less dudes I've been attracting. So I was like, I've been attracting a hell of a lot more guys in my masculine energy. But now that I'm like moving on a different wave, it's crickets. It's crickets right now. And I'm okay with that honestly because right now I'm just really focusing on being a better woman. So right now you feel like you need a man. I wouldn't say need. I wouldn't say need, but I do desire to have a significant other. Explain the difference to me. Need would be, from my perspective, it would be like, there's something that I want a man to do for me that I don't want to do myself. Or I just need someone to feel in space on times while I feel alone. Or I want somebody to take me to go get that pedicure instead of me having to do it for myself versus me wanting someone that will come fit my lifestyle. Or someone I can bounce all ideas off of a connection. Do you think black men need black women? Explain. Because honestly, as individuals, we can really do everything ourselves. Because I feel like a lot of black men say they need a woman. They think about cooking and cleaning and stuff like that. But to sustain life, I don't think black men need women. I'm going to give you my opinion in a second, but I want to explore it a little bit. Do you think that's a productive way of thinking? If black men are on this corner saying we don't need women and black women on that corner saying we don't need men, do you think that is a productive paradigm? No, it just sounds good. Why do you think it's not productive? I don't know. I'm lost in this question. Why do you think it just sounds good? Because in the black community, that's how we all feel like I don't need a man. I don't need a woman. People say they do, but deep down inside, all you gotta do is trigger a button and it'll come out instantly. Oh, I don't need these females. I don't need them. I don't need a man. I don't need them. You hear it from every angle. As soon as someone gets upset about something, it's on. But for you, do you feel like it's a problem? Do you feel like it's an issue? Honestly, if you don't, that's fine, but do you think feel that it's an issue? Of course. Why do you think it's an issue? There's no love. Like, why are we so bitter?  It just doesn't make sense. How can you hold both those thoughts simultaneously? The thought of it's not good. It's not productive and I don't need a man. How do you hold both those thoughts? To be honest, I don't know. This is a tough question. I think it's tough. The term is cognitive dissonance. The stories we have to tell ourselves so we can sleep it at night. But the other part of ourselves knows that it's bullshit. We know it doesn't stand up to scrutiny. I can agree because I've been that person that's like, I don't need a man moving in my own way. And then after a certain point, I get into my late 20s, I'm just like, I've been moving in my masculine energy. And then I'm just like, I should have a man in my life. Having a man in my life is beneficial. Even whether he's just a friend, our brother, a significant other, like we all really actually do need each other regardless. So I think this is an important, I think what you said just now is really important and I want to explore that because the I don't need a man narrative is very prevalent, right? It's common. It's not new. What do you think men are good for? What do you think is on ministry? What do we bring to society, civilization, women's lives? What is the importance of men?  And I don't think people really understand what that means. I think they just think that means being strong, you know, like physically, but it's all mental also. And even spiritually, we need men to protect us because as women, you know, one of our biggest gifts is intuition. And when we out here being a woman and just being ourselves, that means that we're being vulnerable. We're relaxed. So it's the man's job to protect our vulnerability. So you think what men bring is like an energy? So how do you reconcile? I'm trying to move away from my masculine into my feminine. I don't need a man. And I don't know any women who are good examples of femininity. How do you make that make sense? It doesn't really make sense. You know, it's one of those things, like when you're trying to figure it out, it's always a question mark.   So there is, there's this concept in psychology. It's called the Joe Harry window. And it's a, it's a matrix, I think is the technical term, but it looks like one of those cartoon windows, like a square with X in the middle, right? And it's broken up into four quadrants. And, you know, at the top it says things that I know about myself, things I don't know about myself. At the side it says things other people know about me, things other people don't know about me. Now, one of the squares is things I don't know about me that other people know about me. So an example would be like, you got broccoli in your teeth. You might not be able to see it, but I might be able to see it.  You might not be able to see, even though it's a you thing, but I might be able to see it. So I say that to say it's very important that we seek insight and perspective from the other, the other side, whatever the other side could be. And with this conversation, the other side is black men. But typically black women don't care about what black men have to say. So this is an opportunity for us to change that paradigm. So what are your questions about femininity that I might be able to shed some light on? I think the question I have is what portion of our childhood should that have been the most important to learn? So I read somewhere that 97% of who we become as human beings, like as adults, is dictated by whatever happens between the time you're born and like seven years old.  And that's because in those early years, kids are still taking in cues. They're watching adults and things like that to figure out how to interact with the world. Like what does a happy interaction look like? What does a sad interaction look like? What is an angry interaction? And they're just recording. They're just tape recorders, right? Unfortunately, a lot of our people grew up in not just poverty, but also generational trauma. So a lot of times those years were compromised. And it's very hard to come back from that. But as adults, it is our responsibility to heal our inner child. And I'm glad you said that. I'm so glad that you said that. Because there's so many adults that are bitter and angry and upset at their parents. And I get it. I get it. But they got to understand that our parents did the best they could. And some parents will acknowledge that a lot of parents won't. And I think a lot of people will sit in bitterness and pain and trauma and constantly blaming the parents, either being distant or acting out instead of rolling up their shoulders, looking in the mirror and saying, hey, this is my life. Let me figure out how to fix it. And I think the most important part about that is it's not necessarily a parent you need to forgive.  You felt like it's because of me. If I wasn't here or whatever, then things wouldn't be like this. And at the court, that's really what it is. And that's what's sad. Because a lot of times when that goes unaddressed, you literally just repeat the cycle.  So I think it's about, and for some people, that's very painful to do that, to peel back those layers. And that's why I recommend therapy. But it starts there. Yeah, I can agree 100%. Ask me something else. Do men really desire feminine women, like they say? Or do they really like masculine women more? Because a lot of men tend to complain about masculine women. But if they're presenting women more feminine women, they don't know what to do. I think masculine women are easier to have sex with. Interesting. And men, we are very sexual creatures, very visually driven creatures. So we see the utility for the masculine energy. But ultimately, we know that's not what we want. That's not what we want inside the house. That's not what we want 20 years down the line. That's not what we want raising our kids, our sons, our daughters. We know that's not what we want. Now, the deeper answer to that is you have to decide on the life you want to live into your old age, and then decide on the type of companion that's going to make sense for that life. So for most men who've self-actualized and done the work and who are top 1% guys, they want peace. Another nigga in the house doesn't bring you peace. That's so true. I grew up with four brothers. Because I got to go out with my shield every day. I got to go out with my full armor. I want to be able to take that off when I get home.  But ultimately, the masculine woman is not going to win. And for me and I assume other men who have wisdom and understanding, we can make the distinction. This girl you play with. This is a girl you build with. Because I don't need what I already have.  What I need yours for. That's so true. Yeah. And I think it's interesting because I think women understand it on some level because I've heard girls say, you know, I met this dude. He was so fine. He was six foot whatever. And he had a jaw line and all this. But as soon as he opened his mouth, I lost interest. And it could be because his voice was light. It could be because he wasn't articulate. It could be because he was just goofy as hell. So women understand it works that way.  But ultimately, to him, it's going to be the same as the light voice dude was to me. But I think unfortunately what happens, and this is where I'm hard on men, we keep incentivizing that type of behavior from our women. Because we stay in their DMs. You know what I'm saying? We stay texting them. We stay taking them on dates. We stay boosting them so they don't feel like there's anything wrong with me. And ultimately the other ones are going to lose. Because those men aren't going to stick around. That's true. I have noticed that the more I've been pushing away the masculine energy, the less dudes I've been attracting. So I was like, I've been attracting. I love a lot more guys in my masculine energy. But now that I'm like moving on in different ways, it's crickets. It's crickets right now. And I'm okay with that honestly, because right now I'm just really focusing on being a better woman. And I think what you just said is really powerful because for men, the challenge for us in life, we do all kinds of stuff to make ourselves better, to peacock, right? So we can attract a large number of women. So a quote unquote high value man is going to attract a lot of women. The difference is a woman who's doing what she needs to do, she's not going to attract as many people. She's going to attract more quality people. So your job is quality, not quantity. Men's job is quantity. And then we're finding it to quality. And the other thing too is I think we don't give men enough credit. Men can see the BS. Men can see the BS, especially the type of men you want. Because for me, while I tell women, the dusty dude shouldn't exist to you. They shouldn't. Because if you're going to attract a woman, you're going to attract everybody, right? But who you choose to entertain is what's saying something about you. Because I hear women complain about men sometimes. I'm like, you know, oh, he was broke and he was unintelligent, things like that. But it was like, well, y'all, he was intelligent enough to hold your attention for six months. Y'all had conversations, the vibes were nice. So maybe you are not as intelligent as you give yourself credit of being because he was able to hold and captivate your attention. That's true. I can agree. You know, ask me something else. I'm liking this.


Broadway's my beat from Times Square to Columbus Circle, the gaudiest, the most violent, the lonesome-est mile in the world. Broadway's my beat with Larry Thor as Detective Danny Clover. The still-brilliant light of a new January drifts down over Broadway, and the pattern it reveals is unchanged. The scalpled edges of piled concrete are still defined against winter sky. Glintzer struck off chrome and steel, and the faces of the mob are already molded back into the old years' anguish. Because still, the vision of duty stands in a doorway at the end of night. And you walk toward it, and you're stopped by the hawker who has another plan for you. You push him aside, keep walking. He stops you again, lays odds you'll never make it, and you never do. And the light filters a corridor you walk with a man who has just been acquitted of the murder of his wife. A man you arrested, testified against, watched as he was given the verdict of freedom. And in his face, no sign of release of joy, only a newer pallor, sudden, intense. You tried, Danny. You didn't make it. The court found you innocent, Mr. Welch. Yeah, didn't they know? You know something, Danny? What? They say I'm innocent. You say it. Me? I still don't know. I was out of the world at the time. I was drunk. That girl, I'd agree.  Fay was... My wife was being killed. I wonder if I had fun. I wonder if I'd had me had fun while Fay was dying. She broke our case, saved your life. You want it? I give it to you. For whatever my life's worth now, take it, deal it out among your friends. Right, Mr. Welch, you're a free man. What's with this free? A man pronounces a word and that makes me free? You look. Fay's dead. The girl I loved is dead. A girl... You know something, Danny? What?  That means someone else did. I'll try. I make you a promise out of the goodness of my heart. I'll get to the killer before you do. Hope to die if I don't. We'll handle it, Mr. Welch. You leave it all to us. You two, Johnny, I want a picture. You and Ida here. Stand close to them, Ida. Come on, come on, get close. Touch his face or something. Get out of here before... Oh, Johnny, Ida saved your life. You don't have to, Johnny, if you don't want to.   Come on, Johnny. Ida here, this pretty girl here, handed you back your life on a silver platter. That's what Ida did, all right. Okay, take your picture. And step aside so a picture could be made. A picture of a man, Johnny Welch, his eyes dull, unfocused. The corner of his lips twitching somewhere between pain and hate. The girl looking up at him, unsmiling. And the man with the camera... All right, now, now. Try to look glad about it, will you? ...forced smile, friend. Posed happiness for all the world to see. Okay, got it. Then turn the whole thing over to your memory. Go away. Spend the next two days for routine. Fill in spaces and report sheets. Catch up on the paperwork. Shake a finger at a school teacher from the Midwest who was clapping her blackboard erasers on the runway at Times Square. Speak at a boys' club. Lose three boxes of matches at the poker game in the squad room. Catch up on your reading at home. Then the call comes. Danny Clover speaking. Danny? Guy named Larry Moore. Just got some lumps. What are you talking about, Sergeant? I'll name Larry Moore. Just got slugged. Good. All right. Why did you call me, Gino? Guy that did it to him was named Johnny Welch. Oh. Did you pick up Johnny? No, we're looking. Where do I find this Larry Moore? Same hotel where Johnny lives. Room 305. I don't see why you waste your time, Mr. Clover. I'm not going to bring charges against Johnny. Looks like he went over you pretty good, Mr. Moore. Can you see out of that left eye? What difference does it make? I'm not going to press charges. Why did he beat you up? Between you and me, that's all. Okay. He tried to make me confess. To what? That I killed his wife. I see. I guess you want to know why Johnny would think a thing like that, huh? Yeah, I would. I knew Faye Welch. Know her well? A lot of fellas did. You know, the boys who hung around the bar where the Welchers lived. Then Mrs. Welch used to hang around at the bar pretty much. It came out at the trial. Your name didn't. For what reason? I just played piano for cocktail hours. I did a request for a play them. I just can't understand it, Mr. Moore.  And I don't get mad about it. Why should I? A guy like Johnny... A guy like him, he's upset. He needs to be understood, Mr. Clover. Not arrested. What kind of a guy do you think I am, anyhow? For a moment, consider him. Consider the man whose reaction to the violence done him was compassion, understanding. To have come out of a beating from an embittered man, a man on the prowl dedicated to the killing of his wife's murderer, and still Larry Moore makes no charge against him, wonder about it, and note your own shock that you've stained Larry Moore's compassion with suspicion, and leave with no answer to Larry Moore's question as to what kind of a man he was, anyhow. At headquarters, issue an all-points bulletin for the pickup of Johnny Welch, acquitted of the murder of his wife, because where he walked, walked violence and death, and stripped off the hours of waiting with routine, with talk to Detective Muggum. Isn't it safe for the citizens with that guy loose, Danny? We'll find him.  Right now you can go so far as to call him crazy. Maybe.  This time he just beats up on a man.  We'll find him. Sure we will. Mind if I open the window a little, Danny? It's stuffy. Go ahead. A lucky fella. A lucky, lucky fella. What do you say? Johnny Welch's lucky boy. He just didn't know how lucky. No. Sure, no.  The real killer could... The real killer? Could have killed Faye Welch, planted the gun on Johnny, because Johnny was too gone to know anything. It has to be like that. Because a jury of his peers said so? Well... Because a girl, a Miss Ida Gray hops a boat from England, arrives just in time to telecourt Johnny, was seeing her off to Europe from the hours of 11 to 2, the night his wife was killed? His established Mrs. Welch was killed around one o'clock that night. I'm not fighting it then. Sure was established. Goes back to what I was saying. Johnny Welch is a lucky boy. Comes home from a party drunk, staggers down a hotel hall, meets an old girlfriend, Ida Gray. She takes him with her to Bitter of Bon Voyage. This takes till 2 in the morning, she says. Alibi. Freedom. And Johnny Welch walks the streets... Yes, gentlemen, Danny. Good day to you, Detective McGovern. What came in, General? They found Johnny Welch. They keeping him there for you. Where? Blossoms Bar and Grill on 3rd Avenue. One of them 3rd Avenue joins the dispensed factory with Danny putting up your overcoat. You shouldn't catch cold. Hi, Johnny. I never sit down. How do you feel? How do I feel? Let's get out of here, Johnny. Come on, I want to talk to you. I live here.  I live here. Johnny, you... How do I feel, the man? Simple question, the beg the simple answer. I could say, all right, I feel good. You could say, not so good. Stop me when I get to the answer you wanted. What have you been doing for the last... What's the matter, don't you drink? Grab the bottle by the throat, friend. Pour. And mar my home. Drink, drink. I'm working, Johnny, huh? So am I, so am I. This is the way it's done.  Like this. Now wait, the empty bottle. The things inside I can see. Dancers, friends. The people who smile want you to come along. I got no more friends. What's happened, Johnny? No more friends. Look, it'll take them a little while to get used to it. I've seen it happen before. A man acquitted of murder his friends... They think maybe I did it after all. They look at me.  They don't think that. You were acquitted. And Fay is dead. Where she was once is nothing. You never heard a laugh. You talk. And I saw her when... Johnny. What do you want? I saw Larry Moore a little while ago. I got it on the list. I'm gonna see him. Leave him alone. Just to apologize. That's the only reason why I want to see Larry Moore. Apologize because I slugged him. Apologize because Fay is dead. It's a tremendous loss to all of us. I'm here to take you back to the hotel, Mom. You don't know what I've been saying at all, do you? Get your ear out of the mud, friend. I'll say something plain. I'm here because Fay is dead. The twelve good men in Truce say I didn't kill her, and that's good. If I'd killed her, I wouldn't want to live anymore. If I didn't kill her, someone else did. The police will take care of it, Johnny. Surprise, surprise, surprise. Get out of here, friend. Leave me alone. Go on, get out. Leave him alone. Leave him to the life he wanted because you had no reason to intrude. Out on the street again and uptown, stop up for a sandwich, then back to work again, back to headquarters, park the car on the lot across from emergency. Over here, Danny. And the voice that stops you belongs to Detective Muggevin, standing beside an ambulance. What's up, Muggevin? Where have you been? What's the difference, where have I been? What's the matter? You call came as soon as you left. You can leave word where you'd be. I took it. For what? Now, hold it a minute, fellas. Take a look. Oh, no. Larry Moore, Danny. In the morning, he's beat up, and in the evening, he's dead. You see it, Danny? Yeah, I see it, Muggevin. Stabbed to death, Danny. Murdered. You are listening to Broadway's My Beat, written by Morton Fine and David Friedkin, and starring Larry Thor as Detective Danny Glover. Instead of going down, the annual rate of polio cases in this country is going up. Instead of growing panicky with fear in the face of such an unwelcome fact, there is a way in which we all can join the army, which is fighting to check this trend and ultimately defeat infantile paralysis. We can contribute to the march of dimes. Give today so that the 1952 march of dimes will be the biggest ever and a really potent fighting force against polio. When it's January on Broadway, the darkness drains through the scarlet of neon before it's called night. In the dreams that are dreamed where a street corner touches the edge of evening, drift away on the black wind. The whirlpool of color flung skyward by the spectacular's dips, becomes a riot of shadows when it touches the street. It's the once upon a time land wrapped in winter's mist, gray and cold. The laughter's always at the other end of the block. It's night time, crowd time, the lonely time. And consider this night the slaying of a man. Consider facts, dead man Larry Moore. Suspect Johnny Welch, night time, work time. Go back to the bar that Johnny called home. He's not there. Check his hotel, not there. So issue an all-points bulletin again on Johnny. He's not to be found. So next morning go to a friend of his, Ida Gray, the young woman who once helped him. I can't understand why they didn't announce you down at the desk, Mr. Clover. I told them I was a policeman. I told them not to announce me. You were afraid I'd fly the coop? Am I that important? What do you do for a living, Miss Gray? I could have told you that over the house phone. Tell me now. May I be technical? Right ahead. I'm a technician, Mr. Clover. I assist in the preparation of antibiotic cultures. Do I scare you? May I ask you why you went to your vacation? Not at all. Work. I went over to observe techniques in the manufacture of antibiotics in England. Observe, report. Free exchange of scientific methods. That was my job. And you left for England the night of Mrs. Welch's murder and came home during the trial. Fortunate for Johnny, Miss Gray. Had I known of the murder, I would have returned much sooner. Honor bride. Poor Johnny. You feel sorry for him? Bring him to me. Just bring him to me. Just let me get my hands on him. And what? I'd never take him away. Not very scientific talk for a technician like me, is it? He killed a man last night. What? Stabbed him to death. A man named Larry Moore. First Johnny threatened him, then he killed him. Larry Moore? Larry Moore played piano downstairs in the lounge. And Larry killed Johnny's wife, is that it? And who killed Larry? Do you know where Johnny is? If you find out where, take me to him, will you? You'll be here, Miss Gray. As a matter of fact, no. I have a date with a scientific fellow. We're going to discuss variable hydrogen ion concentrations in Oriamias and culture. Do I bore you? Then you might as well go. And something else, Danny? You want something, Geno? There's not a question, do I want something? Let us say rather there's a question, do the gentle lady waiting outside your office want something? They wish to see you, and at the lake to see Larry Moore. Well, bring them in, Geno. They told me... Who cares what people tell me? This way to see Danny Clover. If I am needed, Danny, you know where to reach me. The sergeant said you wanted to see me about Larry Moore. Yeah, I'm Chet Duggar from Tratton. Where are you from, honey? We never did get around to geography. Where are you from? Tell us, honey. Oh, the kid's scared, Mr. Clover. That's why she's climbed up. If you knew what I went through to get her to come down here with... Oh, don't be scared, honey. Why did you come here, Mr. Duggar? Larry and Miss Hamsted and me, Chet Duggar, we were a happy threesome until comes a knock on Larry's hotel room. Larry gets up from the piano to answer it, so... He says to someone, oh, what a pleasant surprise.  The knife in his chest makes him more thumbs.  All Miss Hamsted and me want to tell you is, we were there in Larry's hotel room. Because it got gay in the cocktail lounge, didn't it, honey? And Larry invited us up to his cell for more of his piano. And we were getting around to the oldies. Why didn't you come here before? Oh, didn't I tell you? From out of town, the etiquette of what to do when a piano player dies is, well, unknown to us, isn't it, honey? Then comes the dawn and the etiquette is, oh, pardon me, your phone. Danny Clover speaking. Dr. Sinski, Danny, downstairs in the infirmary. He just brought in Ida Gray. You were worried about etiquette, Mr. Duggar. Stick around, we'll try to clear it up for you. Miss Gray's going to recover, Danny. See, you don't have to worry about that. Probably concussion, bruises. What did you find, Dr. Sinski? In an alley, Danny, off West 16. Here, here's the officer's report. No one probably looking at his cell. What did you say? Nothing, I was just reading the report. That's her room, Danny, you want to see? Is she conscious? No. She keeps saying something, though, over and over. Let's go in. What's she saying? Get close to her, Danny. Put your ear close, you'll hear. I know you. Who are you? You understand her? No. They said there wasn't any use. They bring this in here with her? That first? Yeah. Danny, what are you... She'll be a doctor, huh, doctor? This is the way a policeman works. Let's do this. Keys, comb, wallet, bank book. I don't envy you one bit, Danny, to have to pick the little things. To have to pry like that. Sometimes little things, doctor. Would you say this was a little thing? What? This entry in Miss Gray's bank book. So she made a withdrawal and closed her account. Maybe she needed the money. I found myself face-to-face with needing money. But you never had the reason, Miss Gray, dear doctor. Take care of her. Don't let her out of your sight. Markovin, go tag me. Come in. Yeah, sure, sure, Danny. We're coming. You need something, Danny?  Where you been, Markovin? Out and around. That's an answer? Yeah, I consider it an answer. What do you want? Boys, boys, please. Before our lips get pulled any tighter, let's consider that we have all been chums together for a long time now. Donnie Welch has been hammering his way through alleys. Give him a little more time. We'll have more debt on our hands. When are you going to get her out of finding him, Markovin? When I do, you'll be the first to know. I say it in the presence of a witness. When I do... Look, fellas, we are all at nerve's edge here. Our patience exhausted to the raw quick. Our criticism... What about you, Tataglia? How does a police sergeant pass his time? Before you say something for which we will all be ashamed in the morning, Danny, let me tell you what a police sergeant has been doing. He has been heltering and skeltering up the nooks and down the crannies of policing. Doing what? What his good lieutenant has ordered him to do. Checking the bank account of the late deceased Larry Moore against the aforementioned same of Miss Iga Gray, who was lately assailed by person or person's owner. And you're found? What I found is what I hope will make us all friendly once more. In these two bank books is what I found. Do you heads together over at 10 class pans? I'll give them. Yeah, Danny? Take a look. Do anything to you? Yeah. Yesterday, Larry Moore deposited in his bank the exact amount Ida Gray withdrew from hers. That is what it does to me, Danny. Blackmail. Yeah. Dr. Sinski's with a girl named Ida Gray at the emergency hospital. I want that girl booked. Roger, local. You want a book? Hey, look, what's your idea? Tell them who I am, Danny. They should start roughing me for entering without a pass. Marty, you and Freud, Markov and Geno, friend of mine. In case you ever afford a cab, I hack on 43rd and Broadway. Pleased to meet you, fella. What's in your mind, Marty? Hey, remember the blinches my wife said he made for your last holidays? Remember how you enjoyed them? You told me. I did enjoy them, Marty. Well, I got now something you will enjoy even more. And without sour cream. The whereabouts of a fugitive named Johnny Welch. Where? I spotted him sneaking into a fleabag hotel down to the Bowery. Saw the light go on second floor front. Broke a few traffic manifestos getting it to you, Danny. However... Take me there, Marty. Danny? Yeah, what do you want? That girl with Dr. Sinski. What are we booking for? For murder. Come on, Marty, take me to Johnny Welch. So go now to a familiar place. Familiar because it's called the Bowery. Because it's the place where dreams are lost and violence is born. That one, Danny. That one right there. The air is chill with many things. The figure huddled against the night wind. Cold chalk scratched on a brick wall.  And into the derelict hotel and up the steps. And think briefly this is the sound of a winter's grave. Danny? That's right, Johnny. Come on in.  Without meaning, without expression. Wifeless. I've been waiting for you, Danny. Oh? I thought you were hiding. Hiding? After what you did, Johnny. No, no, you got it all wrong. Tell me about it. The reason why I'm here. That's right. I don't know any other place, Danny. There's no other place left for me. Even the people in the bottom of the bottle dance the way. Larry Moore? I had a gray. They're not in your life anymore. Larry? He's dead. I didn't know. How'd he make it? Ida. Ida. Always Ida. I saw her a while ago. She rubbed a cheek against me and said things you'd never believe. And me. She said she'd love me. Did you find her? Uh-huh.  She didn't tell me. Maybe it didn't give her a chance. I gave her all the time she needed. She talked and talked. The things she told me. Did she tell you how she perjured herself for you? How you were never with her the night of your wife's murder? She told me. And you almost killed Ida for it. I told you something once, Danny. I told you if I killed my wife, I didn't want to live anymore. I meant it.  You can't touch me for it because I was acquitted. Double jeopardy. The state can't try a man twice for the same crime. That's right, Johnny. We can't hold you for assault with intent to kill for a long time. Intent? Didn't I make it? No. What's gonna happen to Ida? You know she'd be tried for murder. Why'd she kill him? Very more must have known she was lying on the stand at your trial. He worked at the hotel he saw. Ida lived for the boat by herself, not with you. So he was blackmailing her. Twisting? Yeah. And all she wanted was you. That's why she perjured herself, got you off. I asked you before, Johnny. Why'd you beat her up?  I told you I don't want to live now that I know what I did. You'll live. Present, Johnny. You can stall it for a while, Danny. And then I'll come back here. Look at this place. Then go over to the window and look outside. Got her from top to bottom, all of it. Hold me as long as you want. Then I'm coming back to it. Why? Why? What's being dead got that this hasn't got. It's the place that dares you. And one way or another, it'll rock you to sleep. It's Broadway, the gaudiest, the most violent, the lonesomest mile in the world. Broadway. My Beat.  Folks who haven't met Mr. Boyington, education-slinging Eve's bashful boyfriend, and the rest of our Miss Brooke's laughmates, shouldn't let another Sunday pass without enjoying this refreshing CBS laugh spreader. Bill Anders speaking. And remember those lovable rascals Amos and Andy are here every Sunday on the CBS radio network.


Godfrey Mitubazi, Executive Director of Uganda Communications Commission, welcome to Geneva, welcome to WSIS Plus 10 high-level event. You've been involved in the high-level talks. Have they been productive? Have they been useful? Yes, they have been very useful in the sense that we get lots of different ideas coming up, the progress from different countries, challenges, so on and so forth. So it's been very useful. Now today is the conclusion of the talks and the conclusion is expected to be the endorsement by application of two key documents, as you know, the statement on implementation of outcomes and the WSIS Beyond 2015 vision. Do you think these documents are important? Yes, they are very much important, you know, inevitably we are seeing a lot of change. Our countries are moving towards semi-direction, digital revolution has taken over, spread of information on different platforms has really moved tremendously. So it's very important that these documents are endorsed and we move forward. And what difference do you think they'll make? Well, there are some countries, especially in Africa, that are slow, they are not moving at required pace. I think this is a wake-up call that really we must move on, we must wake up and start moving faster in regulation, implementation and other areas that require the development of information in developing countries. In Uganda, what are your priorities? You know the action lines from the outcome documents. Is it infrastructure, is it capacity, is it or a combination of all? It's a combination of all. We have infrastructure challenges, of course we have just established a national backbone and it connects most of the border posts, for example we connect with Kenya, with the Rwanda and soon with Tanzania and we have Sudan and we have the Congo to go. It's very important, the infrastructure itself needs to be stabilized, it's not very stable, it's very expensive. We are a landlocked country, we need the national backbone. Traditionally our borders depend on satellite, but satellite is so expensive. So we are really trying to develop the national backbone. Now at this point as we speak, there is what we call Northern corridor in East Africa, Kenya, Uganda and Rwanda and Southern Sudan are coming up with an infrastructure so that we can ease the flow of information, also bring the cost down. So there are a lot of things we are doing and of course we have also got challenges in the content which is not available, it's very expensive. The same applies to terminal equipment, hand pieces are very expensive, smartphones are very expensive, mindset just going to rural areas and start spreading all this technology is not easy. So those are the challenges we are facing. You mentioned surrounding countries, does taking part in the Worcesters process help you with that kind of collaboration, networking? Yes, yes, we have very able and dynamic countries, we have Rwanda, we have Kenya and Tanzania, we are very, very up one moving. If you look at the regulatory organization of those countries, they are a formal organization, it's very dynamic, we are working together in every area. We are trying to develop, as I said, infrastructure together and see how we can move. So the policies, we are trying to harmonize the policies to see how we can work together and make this industry much more, you know, development or dynamic as you would say. So yes, we have all these three countries, four countries together moving towards that goal. Okay, well thank you very much for being with us today, it's lovely to talk to you. Thank you so much, nice talking to you. Thank you.


Yeah, hi everybody as I think we discussed earlier during the introduction. I think there's some new people. So I'm Gary Bader. I'm a faculty at University of Toronto and I'm going to give an introduction to what we're going to work on and learn about during this course. So as a reminder, Nia mentioned that all of the content here is freely shareable, so you're welcome to reuse it. And even if you want to run your own workshops, so and also modify it and improve it. Okay, so why are we here? Most of us are interested in genes and what they do, their function, and this is not so hard to study. If you're interested in one gene, but if you have many genes to work on, whether they're from, you know, a screen or a cross evolutionary space, or from any kind of big genomics experiment, we're usually stuck with figuring out what they all do. And this is sort of typically a problem in genomics, any kind of genomics where we collect data on many genes. And generally we're interested in trying to understand what's interesting about these genes, what do the genes have in common, what do they do, how are they related to a disease or phenotype that I'm studying. So, and frequently the sort of starting point for analyzing genomics data is you might rank the genes by some score that you have, like a gene expression score, or you might cluster it to find genes that work similarly or have similar patterns to each other because of genes have similar patterns, maybe they're working together in some way. And but then, you know, what happens next. And in this course we're going to talk about what happens next. One way that people have found is extremely useful to answer the question what's interesting about these genes is to find out if they're related to known biology known pathways complexes and functions. And we'd like to automate that because if you want to do that manually, let's say you had 1000 genes and you wanted to find out what pathways they were involved in if you didn't have any other resources and you're just looking at the literature. It would take a long time to go through those genes. So, pathway and network analysis is the area of computational biology or bioinformatics that tries to automate this type of activity. And with the goal of helping to gain a mechanistic insight into big gene lists and frequently genomics data. The difference between gene list and genomics data is the genomics data often has measurements available with the genes. So it's not just a list of genes it's also gene expression values or other things like that. And we might like to identify a master regulator, or drug targets or characterize pathways that are active in a sample just to better understand the biology that's occurring in the context that we're studying. And in the context of this course, any type of analysis that involves pathway or network information is we're calling pathway analysis. So the most popular type is pathway enrichment analysis which we'll talk a lot about today but there are many others that are available and useful, and so we'll cover some of those as well. In the next few slides, I'm just going to give you some success stories of pathway and network analysis that we've used in our research that have that's mostly collaborative that has led to interesting insights into and discoveries. So the first analysis example I wanted to mention is work that we did with a lab that studies autism spectrum disorder. The lab is Steve Sharer's lab at the University of Sick Children, the hospital for sick children nearby here. And they've studied the genetics of this, this disorder. You might know that autism spectrum disorder is sort of a kind of spectrum of phenotypes that includes a number of different aspects. Trouble with social situations all the way down to really severe developmental delays and intellectual disability. And it is known to have a genetic component previous to the study that I'll tell you about it sort of knew that we knew that there were some rare genetic single gene disorders and chromosomal rearrangements that caused autism spectrum disorder. And people had previously before this study was published this was in 2010 so it's a while ago but before this people had a general understanding that copy number variants that were de novo or not inherited from the parents might be involved in explaining say 5 to 10% of ASD cases. So, and but in general, not much was known about the genetics of this disease at the time. So, the share lab was very interested in this new at the time finding that copy number variants, especially de novo copy number variants were important. So they measured copy number variants in about 1000 cases and controls cases are, you know, individuals that had severe autism and controls were cases that didn't or individuals that didn't. And they used a snip array to measure snips across the genome and then converted those to copy number variants. You have a deleted region of a genome, there's no snip measurements in a region and so you can say okay that's a deletion and similarly you can call gains. And then they were interested in de novo ones that in particular that were rare, which again they thought sort of had a hypothesis that they were involved in the genetics. So they selected copy number variants from that list that were less that were rare less than 1% frequency. And they found that in general, ASD individuals had more to know those CNVs than than expected. And, but they didn't find a lot of genes that were associated repeatedly in the 1000 case roughly 1000 cases. So only about 10 genes were associated from this analysis. So we thought we can look for, we can do a pathway analysis of all the genes that were associated with all the copy number variants. Interestingly, we found a rich set of pathways that were seem to be involved in this disease so all of the circles and we'll learn how to make maps like this later. This is called an enrichment map, and it's a method that our lab developed, Ruth is one of the original developers actually of this software that made this. All the circles represent pathways, the size of the circle represents the number of genes in the pathway, and the lines that connect them also called edges represent crosstalk or overlap between the pathways so pathways share the same genes they get a strong green line that connects them. And then, so, and then the white to red color represents how strong the genes on that pathway are linked to autism spectrum disorder cases versus controls. And so we found lots of interesting pathways, self projection motility, different types of CNS or brain related pathways like neuron cell, well, that were involved in basically neuronal neuronal processes like CNS development brain development. So now that was interesting. However, and kind of expected given that autism affects the brain. And however, we didn't. A lot of the pathways were new. And so one of the questions that was asked by the, our collaborators was how does this relate to known genes that we know affect autism and intellectual disability which is a related phenotype. So, we took all the, let's say 100 genes, intellectual disability genes and 100 autism genes, and we plotted those and their pathways that were enriched in those gene lists on this map. And that's what these other symbols are so triangles or intellectual disability and parallelograms are autism spectrum disorder, and, and we plotted those in relationship to all the copy number variant and rich pathways and there was a bunch of overlap which is interesting, as I was showing here. But the interesting, what one in particular interesting thing to me was how we found so much more by all biology from doing pathway analysis compared to looking at individual genes. And when we looked at some of these individual pathways, we found that. Yes, there were more autism spectrum disorder patient or individuals that were that had genes in those pathways and we expected, but it wasn't the same genes each time. It was different genes in different individuals, but it was always the same pathway. So, when we looked at the gene level we couldn't see repeated patterns, we just saw everybody had different genes that were affected. And when we map those genes to pathways, we found it was the same pathways over over time so just that mapping of genes to pathways just the bringing in the additional information about prior knowledge about pathways made a huge difference in the study, and being able to find the patterns that we think are important in the biology of this disease. And I'll come back to that and again a few times that general concept. The second pathway analysis example that is my favorite was work that we did with Michael Taylor who's a neurosurgeon, a pediatric neurosurgeon also at the hospital for sick children. He studies his lab studies at PENOMA. PENOMA is a cancer of the appendix, which is the lining of the central nervous system. And it's the most. It's the third most common brain cancer in children, fortunately not brain cancer is not very common in children but among brain cancers and children so third most common, and people had known for a long time that, depending on where the brain cancer occurs anatomically. It has different outcomes, and in particular, the most common and morbid location in childhood is in the posterior fossa which is the back of the brain. It contains the brain stem and the cerebellum. Gene expression analysis that we've done also Ruth was involved in analyzing this data identified that there were two classes of this disease. Previously, anatomically they all everybody thought if it's in the back of the brain it's bad.  One that affect the affected the youngest individuals and had a terrible outcome and another one that affected the oldest individuals, still children but had a excellent outcome. And that was determined just by gene expression clustering. So we wanted to find out more about the genetics and you know in cancer, typically we expect mutations to be important. So we searched for mutations with whole exome and whole genome sequencing, but there were no mutations basically basically like, you know, very surprising to me but it turns out pediatric cancers actually have a much lower mutation burden than expected, or then we expect from adult cancers. And so that was not actually that surprising given the context of the pediatric condition. Moving on to another genomics data layer DNA methylation we found that the, the, the PF posterior faucet type a that affects the youngest individuals was more transcriptionally silenced with CPG methylation compared to the B type that affects that has a better outcome. And there were about 2000 genes that were differentially methylated, and it was not very easy to kind of figure out what those genes had in common. If you just looked at them standard kind of looking through is hard to kind of know. So we looked at enriched pathway enrichment analysis with a large database that we collected from many different other databases. And what we found was that there was one pathway that was really strongly enriched in the 2000 in the 2000 genes that were differentially methylated, and that was a pathway that we collected from the GSA MSIC DB database that was had collected a set of genes related to the PRC2 complex. So PRC2 is a complex that methylates histones and then DNA gets methylated. The targets of that complex have been mapped. And this bar here represents that gene set and then also they'd also mapped the targets of subunits of the complex whose 12 and ED are proteins that are part of the PRC2 complex. And the bar plot here represents the significance kind of measured as a number that converts the p-value into a number by taking the negative logarithm of that number. So the higher, the longer the bar, the more significant the pathway is enriched in the list of 2000 genes than expected. And that's interesting. So we'll tell you all about how to do those statistics later today. But the interesting thing biologically was that basically no mechanism had been known to be important in a pendemoma. There were no drugs or therapy other than surgery or radiation. And so this PRC2 complex represents at the first time that a molecular mechanism had been identified in this disease, in particular the serious type A of the posterior fossa pendemoma. And not only that, people have been studying this PRC2 complex for a while and had identified various chemical inhibitors to it. And those were tested in cell lines and mouse models and they killed, preferentially killed, or specifically killed the appendemoma cells. And so that was very interesting. And then it was actually basically validated as a mechanism through those experiments. And then clinicians on the team searched for drugs that might be already on the market that target similar processes and they found a drug called the DASA or 5-Azicididine that inhibits DNA methylation, a related pathway. And so they were actually able to, because this safe drug is on the market, they were actually able to test this in an individual. This is a child who came in with a posterior fossa type A that the patient reached the end stage of their treatment where the tumor had metastasized to the lung. And this is a picture of the tumor in the lung. And over two months, the tumor had doubled in size. So at that point, there's no more treatments left for this patient. They're just going to be in hospital and for the rest of their life. So they tried on compassionate grounds to give this patient a course of treatment of this drug on the market drug. And it stopped the tumor growing and the patient gained their energy and was actually able to leave the hospital. And that lasted for 15 months before the tumor start growing again. But it was enough information to start a couple of clinical trials and those are ongoing and still and lots of patients are now taking this therapy, which is definitely helping them. So this is a great story for us because in a short period of time, just a couple of years, we went from knowing very little about the mechanism of the disease to identifying a mechanism and then a drug and then actually treating the patient basically within two years. And it's a great success story, I think for genomics and pathway analysis and we were also able to find kind of, you know, because there was only one pathway that came up, we were able to conclusively say that if it wasn't for pathway analysis we wouldn't have been able to it wasn't for collecting all the data in our database and identifying that pathway we wouldn't have made that link. And we wouldn't have had, we wouldn't have found that important mechanism. Okay, so a couple more examples I'm going to tell you about that are more quick. The third example is studying these ependymoma tumors more broadly. It turns out that there's not just posterior or phosphotype AMB ependymoma occurs all over the central nervous system. And we had lots of different data gene expression data for these. And we wanted to find out if there were any differences between the known clusters of this disease from gene expression data. So previous work had found at this point, a few years after the ependymoma story that I mentioned that there were nine types of this ependymoma by gene expression clustering. And we did a pathway analysis like similar to the one I showed you before and visualized it as this enrichment map view where the circles represent the circles represent pathways and the size of the circle is the number of genes in the pathway. And you can see links between pathways that are similar. And then we group them into bubbles that we label as kind of major categories of pathways. And then we colored them based on how prevalent these pathways were in each subtype. And you can see that a really nice view of the biology of all the different subtypes. There are certain pathways that are specific to specific subtypes there are other pathways that are present in multiple subtypes. And so this summary just provides a really nice overview of the biology of the whole disease. And the last example I'm going to tell you about is more recent looking at single cell transcriptomics data of five healthy livers that we worked on with the liver team here in Toronto that initially revealed 20 different cell types. You might have seen these plots if you definitely familiar with them if you work with single cell genomics data, each little dot is a cell and they're placed in space so that cells that have similar transcriptional profiles are close to each other. So when you look do that you see that there's groups of cells that are have similar transcriptional profiles and it turns out those are major cell types like hepatocytes or different types of immune cell types. And, and so we've labeled those all here. We, one of the interesting things that we noticed that there was a whole bunch of different clusters that we called hepatocytes. And so we did a pathway analysis on this, it's maybe hard to see all the little, little dots here, but we, we also had some information about where the cell types occur anatomically in the liver. And so the, we ordered the, so we made these little enrichment maps per cell type. There's different clusters here cluster 5146 these represent these clusters here, like 4216 here. We ordered ordered them along an access of like an anatomical access from Peri portal to Peri central, which is, you know, part kind of defines helps to find where blood flows through liver sinusoid and lobules. So I, I'm not really explaining how that works. I'm not showing you how that works exactly, but just to the take home messages that this is a prior way that we knew to order things. And then we, we visualize the pathways in kind of an anatomical view, and we found that there was an interesting division of labor among the different hepatocytes cell types. So if you zoom in on these pathways, you can see that there's a lot of drug metabolism pathways, which is under an important function of hepatocytes, but different hepatocytes of different parts of the anatomy do different things. And so that was interesting, you know, description basically of the, the data that helps us kind of identify where certain functions occur anatomically. So far about any things I mentioned. Okay, so I'm going to go through a little bit more general background now. Those are just examples, a few examples from our own work that we're excited, we are, you know, excited about and it's just hopefully motivating to kind of see, okay, these are real world examples where pathway analysis was important. You can view it and we, you know, to answer different questions and we'll teach you during this workshop how to do those analyses and other ones that might be related to your work. Okay, so coming back to a point that I made about the autism spectrum disorder. I mentioned that the genes that we identified as being important were not identified repeatedly across individuals, but the pathways that were in were were identified repeatedly across individuals. So I want to give you some kind of theoretical background or just an example of a few sort of theoretical or conceptual view of how that works. So exactly statistically why you get signal with this prior knowledge that we have when you didn't have signal in your data before. So let's imagine we're doing a genome wide association study, where we have cases and controls, and we measure snips or mutations for all the individuals. These are five cases, these are five individual people and five controls and other five individual people, and we measure a bunch of snips a to f here. And if the individual has a snip in one form it's called one, otherwise it's zero. And the ideal situation for GWAS study a genome wide association study is to identify a repeated pattern that's present in all the cases and none of the controls. So A in this case is present in all the cases and none of the controls. And there's another snip D that's present in all the controls and none of the cases. So if we saw a pattern like that it would be a very strong signal to get a very good p value and using GWAS statistics. And we might conclude or predict that that snip might be causal for the phenotype that we're studying. So in the statistics situation whenever you do these studies and whenever we look at genomics data it's very messy, much more realistically would you'll have like, you know, each individual here has a different snip. And there's no repeated snips. So now you're on the other side of the, you know, the worst case scenario I showed you the best case scenario where the pattern is repeated it's obvious it's easy to see here. And that's easy to see other than everybody has a different snip that's like the pattern and you can't really do much with that. So, however, if we map the genes to pathways and let's say all the snips that we identified were part of apoptosis pathway, we can collapse all of those, those single numbers down to make our perfect pattern again. So now we have a pattern where we've collected all the ones from all the gene measurements are all snip measurements. We know that the snip measurements are on the pathway. We rewrite this table so that instead of looking at snips we're looking at pathways and we're looking to see if there's a snip in the pathway, given pathway and cases versus controls. And now, and so we recover that signal. So the increased statistical power that we get comes from two things basically one is aggregating the counts. So we take all of these counts now that we're all spread out and we didn't see any relationship between them, and we merge them together and now we see a strong relationship. And that's the probably the most important type of method of basically the most important statistical technique that we gain from using prior information about how genes or snips are related to each other. The other thing that I'm not showing you very much here is and we'll talk about more later today is it reduces multiple testing correction problems. And so if you have multiple association tests like we're testing if snip a is related to cases and then we're testing this and B is related to cases, etc. Let's say we have millions of snips. There's a chance we just test if we're just repeating the test over and over again there's a chance that we'll get a significant p value randomly. And so we need to correct when we're making many tests we need to correct for that and there's a standard statistical method for do there are standard statistical methods for doing that. It's multiple testing correction so we'll talk about it later, but it reduces if you especially if you have lots of data it reduces your ability to identify significant signal signals. In this case of pathway analysis by reducing the number of tests that we're doing from, you know, all the snips and merging them together into a smaller number of pathways. We reduce the number of tasks that we do and increase our ability to identify signal without getting confounded by random significance results. Then the third interesting thing conceptually is that the pathway analysis gives us some mechanistic insight, ideally into what we're studying so we're just looking at a bunch of snips they're like okay the snip a is effect is you know associated with cases. But now with pathway analysis we say apoptosis is related with cases, and that is a lot easier for us to follow up on. So those are basically the, you know, the, the key fundamentals between behind everything that we're going to be doing in the course, and anytime you see an opportunity to do this.  Okay, so, you know, just one one additional example. I didn't have a good publication example of this but you know, in terms of mechanistic understanding. An example of master regulator analysis, and this is, you know, another way of explaining about gaining mechanistic insight is that we want to explain the data in some way so let's say we have a bunch of samples each column here is a is a sample and each row here is genes and all the colors are measurements of the genes, we have a bunch of expression data with red being high and blue being low. And we've grouped all of these genes we've identified, say hundreds or thousands of genes that are following some kind of pattern here and we're we can identify the pattern very clearly in our data, but we don't have a mechanistic explanation for it. One of the things we might be able to do just as an example is find out that the all the genes that are have a similar pattern are all regulated by the same transcription factor. And if that known set of transcription factor targets are enriched, they're present in this list of genes more than we expect by chance. So this transcription factor is might be controlling these genes and maybe that explains this big pattern that we see. And this is what we did with a PRC to complex example in a in a way. Okay, so, and we'll talk about that as well. Okay, so just to summarize and I'll go through a couple more slides. So this is what we're doing, what we'll do for the rest of the class, the benefits, the rest of the workshop, the benefits of pathway analysis versus analyzing individual snaps or transcripts is that generally the results of pathway analysis are hopefully easier to interpret because they use familiar concepts. We identify possible causal mechanisms like the transcription factor example I mentioned. So we might be able to use it to predict new roles for genes I didn't talk about that very much but we'll talk about gene function prediction. Later, it improves statistical power and the way that I mentioned, and one way that I didn't mention is that it can be more reproducible across cohorts or studies, because, you know, you can imagine if you did a GWAS study like the one I mentioned with A to F. And, you know, every individual has a different snip if I look at 100 individuals in all of different snips, and then I go do that in another population will probably have another, you know, everyone's affected by different snips but the pathway information is hopefully if it explains the biology, it's likely going to be more reproducible across those studies. And it can facilitate integration of multiple data types, like if you have different genomics layers, gene expression and protein expression and proteomics other types of proteomics data. Okay, so finally just the last little bit of information I want to give to you is a preview of the pathway analysis workflow that we're going to be covering in the course. The general idea is that we have some genomics data or experimental data that generates a lot of information about genes. We normalize and score it using standard methods, which we're not going to cover here but we can answer questions about. And that gives us a list of genes potentially available with scores. And then we learn about the underlying cellular mechanism with pathway and network analysis that's the ideal. And that would be, you know, involve visualizing and identifying interesting pathways, trying to find one that's interesting like it's novel, and then we drill down on that and we look into more detail about it and we might be able to publish that that specific thing. Blowing this out into more detail we have lots of different types of genomics data up here different types of normalization methods. They all generate a gene list. And then we have ways of finding interesting pathways interesting networks and doing this mechanistic drill down each of these little boxes is a type of analysis and each highlighted yellow box is a tool. We'll be talking about almost all of me probably almost almost all of these tools in the workshop. So we'll come back to this. Okay, so that's it the workshop outline. As I mentioned just to summarize it is that we'll be working on pathway enrichment analysis where we can summarize and compare. So that's network analysis can help us predict gene function, find new pathway members identify new pathways. We'll be also talking about regulatory network analysis and which helps us find and analyze master regulators. And that's it for the intro so right now we're on a 30 minute coffee break and networking session so we can chat amongst ourselves.


Governor Mark Dayton has signed most of a bill authorizing almost $1.5 billion in public construction across Minnesota. Dayton signed the so-called Bonding Bill Wednesday, but used his line item veto pen on just one project. Dayton said $1 million for additional reviews of state water regulations would have added a needless bureaucracy. The Democratic governor said the bill was too skimpy, especially for upkeep on college and university campuses, and he objected to a provision that uses money from an environmental fund, but Dayton wrote that he still signed the bill because Minnesota communities need the projects and jobs. The Bonding Bill provides $35 million in funding for two large Bemidji projects. $12.5 million will go towards funding for a veteran's home to be built in Bemidji. At a press conference earlier today, legislators and advocates for the facility celebrated near the site of the new home. The veterans home project has been in the works over the past 10 years. Through bonding, veterans homes will be built in three cities, Bemidji, Montevideo and Preston. The homes carried bipartisan support, along with strong community support as well. This has really been a community effort over 10 years in the making without the support of the commissioner's court and without the support of Sanford and without the support of numerous veterans and other people in the community, this would not have happened. Now that the state has put money towards the project, it is up to the federal government to make the final decision. Those involved are optimistic that the veterans home will become a reality. If you're watching what the president has done along with the VA, they've put a lot of money into getting care into the community. And part of that is through the residential facilities and having places to take care of veterans. So I'm real optimistic. I'm very optimistic with the federal government doing the right thing. If the federal government approves the project, the veterans home would likely be built in 2022. $22.5 million in bonding funds will go towards building projects at Bemidji State University. Most of those funds will be dedicated to the demolition and construction of a new Hag Sauer Hall on the school's campus. Over the past five years, BSU has worked to get these bonding dollars for the project. The new Hag Sauer Hall will feature energy improvements, interactive technology and flexible learning spaces that will create a better learning environment for its students. Combined with the work that we've been doing in recent years, almost all of our academic learning spaces will be upgraded, improved, renovated. I think it's going to create a real fresh experience and environment for our students. Renovations on existing buildings will begin this fall with the completion of the new Hag Sauer Hall scheduled to be completed by the fall of 2020. Now the Bonnie Bill also includes $14 million for the Red Lake School District for renovations and updates as well as the design and construction of a connection structure between the Red Lake Early Childhood Center and the Red Lake Elementary School. In addition, funds will go to address school facilities at the Northwest Angle Inlets One Room Schoolhouse. If you enjoyed this segment of Lakeland News, please consider making a tax-deductible contribution to Lakeland PBS.


Lifespan.io has recently launched a new crowdfunding campaign to support longevity research. The new campaign will be funding a large human trial, the Participatory Evaluation of Aging with Rapamycin for Longevity Study or PERL. Rapamycin is a drug well known for its longevity benefits and mice and this trial aims at finding out whether there's similar benefits in humans. The trial will follow up to 200 participants over 12 months testing four different rapamycin dosing regimens. It will be double-blind, randomized, placebo-controlled, and registered with clinicaltrials.gov. Follow the link in the description below to learn more and make a donation. See the full video at youtube.com backslash x10show