Hi, it's Bridget. Welcome to Sunday Morning Coffee with Bridget, our topic for conversation today is timing. We're going to talk about timing. There's many different aspects of this topic that we could focus on. We could talk about timing as in rhythm, as in connection or intersection points. We could talk about timing as far as miss opportunities. We could also talk about timing in regards to how things fit together. How are they in sync? How do they line up? So I'm going to feel in actually. I think this topic is a good one and it kind of was inspired to me in a conversation I was having with a friend the other day and a reference to timelines like this lifetime or past lifetimes or future lifetimes, that kind of a thing and the sense of time and how it feels different when we're at different points in our lives. So let's talk about timing. I'm going to feel into, oh my awesome spiritual helpers and support team and have them help me to have a conversation with you about timing. The first thing that comes through is actually a thought. Timing is everything. Well, is it? Is timing really everything? Is that true? Is there some grand plan or overlay that covers all aspects of our lives that really impacts whether we do or don't, who we meet or don't meet, what we become or don't become, what we experience or don't experience, how we're saved from tragedy or how we receive victories and triumphs just because of this mystical thing of timing? Is that a universal truth? Is there a map? And if so, why can we not see it? And do we have control or influence over this thing timing? So I sense the energy of Archangel Michael who is one of my lead guides and he brings in for me always a layer of protection. If I ever work with you in a private session, you know you will sense Archangel Michael. He is my right hand. Actually, he's on my left side usually. It's kind of funny. He's on my left side usually and just kind of stand stoic and quiet to help me allow my energy to feel grounded and rooted if I need to or if I feel distracted by outside influences, whether it be my own thoughts, my kids, my human life, or whether it be spiritual, too much chatter in the field, Michael will help to quiet things down and provide a layer of very strong and solid protection for me. So I will feel safe in doing my work, steady, balanced. And when it comes to the vibration of the timing, he reminds me of what a stickler I am. How stubborn I am about time. I am so very stubborn about time at times and yet and other times during other things or other experiences, I am very much, let's just say more laid back. So for example, when I'm on vacation, depending upon my intention or what my goals are for the day or for the week or for the experience, vacation as a whole, timing, my perception of timing can be very different. I can have specific things, exact times, reservations, etc. that I need to places I need to be. Or I can have expectations that I have created goals or intentions that I've set to be able to experience certain things, which then I am having to make sure that I line up with timing based upon those things or experiences, like the hours of operation when they're open, etc. Right. So very real stuff we have to navigate related to time. And yet, that said, time is also this incredible precious commodity. It has so much value because we waste time and it doesn't seem as though we earn time very often. And yet we are constantly trading away our time. Sometimes it's our thoughts, our own thoughts about situation, circumstances or people that steal our time away from us, where we have a loss, a debt of time loss. And once we realize, for example, if you spend too much time on a social media feed, and all of a sudden it's an hour later and you realize you've done nothing but scroll through your social media feed, you will have this sort of angst about it potentially or a grief about the loss of the time, this awareness of that. And so then with that comes this idea or this thought that, well, time can be intentional. We can use it as this incredibly powerful tool to provide a rhythm to our lives, which we do. But we also know that we have to integrate that rhythm into the rhythms of others if we want to have, if we want to have shared experiences. So in that case, the shared experiences and the rhythm of each other with each other, those are where the timing is everything comes in. But it's really not everything because what I'm also seeing is an infinity symbol, an infinity sign, which means that there are multiple possibilities when it comes to timing. So if something doesn't work out, it's not like this romantic gesture of there were like two ships passing in the night that might have made for a fabulous movie back in the day. But the truth is that there is multiple opportunities for rhythm, for cycles, for shifting that allows multitudes of intersection points regarding timing. So it's not just a one-and-done thing, timing is not about all or nothing, it's not. There is not that faded sort of energy, like this is fate, it's all or nothing, the timing works or it doesn't work. It's not an offer on or right or wrong. It is much more fluid. So timing, while it is extremely important, it is not something we control, it is something we move with. It is very fluid, it is very rhythmic. And if we can be rhythmic in our intentions and our goals and allow for the opportunity of the goal setting with the mind and the intention setting with the heart and the spirit to really collaborate and work together, life becomes much more harmonious. And the concept of timing becomes something in our favor, not something we're working against or a structure we dislike or something we just have to deal with, not an overlay, it does become a sort of an outline for us that we can use to our advantage for our greatest good as individuals and collectively in communities, in organizations, in groups, in society. It can be a beautiful harmonizing of energy of multiple patterns and rhythms that work together, that create a broader, more robust experience for all of us. This is what life is about. So yes, while timing is important to be aware of, because we do want to make sure that we recognize the part of it that has such a value, has such a almost like a compensation element and a worthy component that time isn't something to be just wasted or thrown away or trivialized. But it is also not supposed to, it's very, very valuable. It's very precious, but it is also not supposed to be overused to our detriment to control and confine and create stress and create pressure and create compliance. Time is not about compliance. It is about collaboration, coherence, resonance. It's about the rhythms. Recognize time as a fluid piece of energy that is moving about. And we are part of that fluidity of those movements. Very much so. Very, very much so. Does that feel true to you?  Now I have in my life, I have some struggles with time. I feel I have this fear of being late, for example, I don't want to be, I don't want to be late. And that stems from a very specific experience I had when I was literally in kindergarten, where I was scolded for being late to school, which in it had, there was no, it was to no fault of my own, my parents had to drive me to school. So after I was late several times, I was scolded and, you know, called up in front of the class at age five and, you know, scolded about how I needed to be on time. And it was very embarrassing. And I cried and I remember these things. And so time to me became something that was a bit of a stickler, a authority figure that I had to please and to make sure I didn't upset. Because if I did, it will cause me some pain. So this experience with timing or time, specifically with being late for something has really impacted me over the course of my life. And it's something that I've been working on in the last, gosh, eight, 10 years, specifically to not be so worried like, so what if we're late? Big deal. It happens. People are late. Things unexpected things happen. We don't have control over everybody else and all the things like the weather and the car and the traffic and all of the things we don't have control over. So we have to release the expectations. And like for me, my past experiences with time and to be open to the energy of grace when it comes to timing and to recognize that not right now doesn't mean never not right now doesn't mean no. Being late doesn't mean bad. It just means it didn't work out exactly as planned. And sometimes when things don't work out exactly as planned. It's an opportunity for us to have grace to forgive ourselves to recognize that there's so much more to life than just being on time for something like tending to the relationships like that. This is Bridget. Thank you so much for listening to this conversation Sunday morning coffee with Bridget about time. I hope I've inspired your spirit today. Got you thinking a little bit.  This is your life after all. And you got to live it. Just live it. Thanks for listening.


Hello and welcome to the session. In this session we discussed the following question which says two circles touch internally. The sum of their areas is 125 pi cm2 and the distance between their centers is 5 cm. Find the radii of the circles. So we are given that these two circles touch internally and sum of their areas is also given to us. We are also given the distance between their centers and we have to find the radii of these circles. So first of all let's recall the formula for the area of a circle and this is equal to pi r square where this r is the radius of the circle. This is the key idea to be used in this question. Now let's proceed with the solution. Now as you can see these two circles are touching each other internally at a point A. We have one circle with center as O and the other circle that is the internal circle has the center as O dash and we are given that the distance O O dash that is the distance between the centers of the two circles is 5 cm. So this means that O O dash is equal to 5 cm. Now let the radius of the circle with center as O that is the outer circle be equal to r1 and suppose the radius of the circle with center as O dash that is this internal circle be equal to r2 minus the distance between the two centers of the circle that is O O dash is equal to 5 cm. So this would obviously mean that the difference between the radii of the two circles that is r1 minus r2 is equal to 5 cm and this would mean that r1 is equal to r2 plus 5 cm. So if we have that the circle with center as O dash has radius r2 then the radius of the circle with center as O is equal to r1 that is equal to r2 plus 5 cm. So the internal circle that is which has center as O dash has radius r2 and the outer circle with center O has radius r2 plus 5. Now let's calculate the areas of both the circles. So area of the circle with center as O is equal to pi r1 square that is equal to pi r2 plus 5 whole square cm square and the area of the circle with center as O dash is equal to pi r2 square cm square. Now it's given that the sum of the areas of two given circles is equal to 125 pi cm square. This means that pi r2 square plus pi into r2 plus 5 whole square is equal to 125 pi. Further we get pi common here r2 square plus r2 plus 5 whole square is equal to 125 pi. This pi cancels with this pi. So we get r2 square plus r2 square plus 10 r2 plus 25 is equal to 125. This gives us 2 r2 square plus 10 r2 minus 100 is equal to 0 that is we have r2 square plus 5 r2 minus 50 is equal to 0. So now splitting the middle term of this quadratic equation we get r2 square minus 5 r2 plus 10 r2 minus 50 is equal to 0. Now r2 common from the first group so inside we have r2 minus 5 plus 10 common from the second group inside the bracket we have r2 minus 5 is equal to 0. This gives us r2 minus 5 this whole into r2 plus 10 is equal to 0. So this means r2 minus 5 equal to 0 or r2 plus 10 equal to 0 that is r2 equal to 5 or r2 equal to minus 10. Now as r2 is the radius and we know that radius cannot be negative therefore r2 is not equal to minus 10 and thus we have r2 is equal to 5. Thus we say the radius of the circle with center as o dash is equal to 5 centimeters that is r2 and the radius of the circle with center as o is equal to r2 plus 5 centimeters. So this would be equal to 5 plus 5 centimeters that is equal to 10 centimeters. So area of this internal circle is 5 centimeters and the center circle is 10 centimeters. So this is our final answer this completes the session. Hope you have understood the solution of this question.


Once I got into my sorority, it was so cool to just meet all of the different people and kind of go through life at the university together. I've never really expanded my bubble that much. One of the cool opportunities that we had was Homecoming Week when there were so many different competitions and ways to kind of get to meet new people and just expand your community. And one thing that we did was we made a big float for the float competition and the parade on Homecoming. I dressed up like Nick Saban and I got to stand on the float and wave to all the people who we drove past. And it was so fun for me, probably a highlight of freshman year because I not only got to just have some fun on the parade, but I also got to show my outing of football pride.


What's up everybody? Jason here for Jasper's case breaks.com. Excuse me Back from the national guys Tuesday the 2nd of August. I can't believe we're already in August This is a promo break NSCC So some of the promo breaks that we didn't sell at the national will be continuing on here this week And a lot closer than you think eminence and all these other breaks have multiple NSCC spot giveaways So I think we'll probably finish this promo by the end of the week This was one of them that sold out Saturday night when we ran out of time This was 2022 tops tier one baseball 12 box case break pick a change number 17 remember everybody gets an entry into the promo if you buy a team and There we go. This is number 17 number 18 on the website as you can see already down to six Probably break number 18 tonight as well, and I can read all number 19 once that sells out We do have a little break schedule right there from breaks that sold out in the last couple days and Let's rock and roll All right, so there's everybody's name. I Don't even remember who got last Bob Mojo Sold out a couple days ago. So there you go Knife knife the knife's here That's not I'm sure it didn't take my breaking knife over there. Good to go camera was a little off there All right, here we go guys. Good luck. I don't know Tyler. I mean The game has changed a lot when it comes to pitchers now All right, well Juan Soder to start us off freshly traded now a San Diego fathered. How does everybody like that move? I feel like the nationals got a big haul for that guy Adding in Josh Bell in there as well We've got a lot of good prospects coming their way Definitely full rebuild mode And geeky Hernandez the 399 You know this year all that for maybe a wall card spot Maybe not even make the playoffs. I don't know but Obviously that trade is more for the future of the Padres not just for this year but obviously there is still some time to turn it around but I Don't know they're in a pretty deep hole Charlie Barnes Yeah, now you get a hunt some soda next spring. That's right Minnesota and Walker Bueller. I'm just curious. I assume soda is gonna sign a huge contract there, right?  I don't think it was a sign-and-trade type of deal But I assume that he's gonna Sign a big extension there. I don't think they've announced that though, right? Yeah, that's the thing. Well, I assume they wouldn't have done the deal unless Juan Soder was gonna say like no I don't I might might not resign, right? I Mean that's what the Dodgers in a few years back They trade him a shadow for like half a season and then he didn't end up resigning But yeah, I would assume that they did to keep Ryan Hayes But he has to think so this is a little bit different, right? I think he still has another year or two left on his contract So it's not like he has to decide that he wants to stay here But I'm sure that was one of the teams that he was willing to go to Tony Santana Santala Yeah, there you go Jeremy at 2024 so that's like another what year and a half Two years basically this season next season and maybe the year after that and Carlos Delgado Toronto Blue Jays Blake with that one have Garrett Cole Yeah, I think the Padres are obviously confident. He will sign an extension there. There was some good players. They gave up I wonder how our good buddy Brian Feels about solo being traded the Padres. I Wonder if he's I wonder if the true Padres fans are happy or are they kind of upset that they gave up so many good prospects? We have Austin Riley Derrick Lee to 299 and Shane Bass to 10 nice over ink Yeah, that's the big three right there, right? I mean, I'm sure powder fans are happy now It's just if it all works out, right? And then the one thing you would hate to see for the Padres is that it doesn't work out they kind of choke and Then their prospects actually end up being really good because that's the one thing like I said, you know Daughters the last few years giving up a bunch of you know young prospects and players for Mookie and for Scherzer and trade turner and stuff like that a lot of those guys haven't really panned out so it's actually hasn't looked bad and You know, obviously you can't predict which players are gonna pan out which are not but Luke Williams to 10 but like other we're saying online. It's like, you know, the Dodgers trade for solo They're instantly better, right? Because it's not like those players that they're trading are up on up on the Dodgers anyways, but But But If they don't trade for them, they keep all their prospects all their number one prospects Raphael Devers to 149 But it's just it's just like you don't know how what's the percent? Yeah, Mike say what's the percentage? Yeah Yeah, like CJ Abrams and Robert Hassel Boy What do you mean post to Europe? I mean, are you watching from Europe or not? Yeah, I mean all the break videos we we sell we post up the videos But what do you mean by post to Europe? Do we oh, sorry, do you mean do we ship to Europe? Yes, we ship all international I believe there's a charge for everybody if there isn't then You can email us and try to figure out I think we're trying to use ship my cards For international customers Jason Hayward I know the personal side we give you a couple options with like DHL and stuff like that But I don't know about the case breaking side. I think it was a little weird. All right. We have Andrew Vaughan Chicago John doing that one and Manny Machado to 49 a little camel Padres Aaron Miller. There you go, man We're halfway through after this box right here guys so again number 18s on the website It's already down to like five or six you can run that back and I can even post 19 as well Lance McCullers, we have a cow loose Do breakers still do that Joe Pizzle everywhere. It's like if they get traded Instantly they go to the new team even though it has a national's logo on there We have a joy bottle nice one of 50 nice Cincinnati one I just remember breaking before check. Let's be right now, bro He's not on that team anymore. Like why are you still giving it to them? I'm like, bro, the logo's right on the card. Like what do you want me to do? Like it's so controversial. It's like when pelicans became pelicans and we're in the Hornets anymore people are so frickin confused Some people that are not established the rules Paul Goldschmidt Yeah, I find the Yankees made a lot of moves, right? Jake McCarthy. I mean Dodgers even picked up Joey Gallo. I think just took a flyer on that guy, right? If you can do what he did a couple seasons ago And tier one talent Max Muncie Yeah, that's true. They have like under everyone's but you know, it is my people. I've seen people in the recent years, too We're like They've established the rules where like if someone gets traded. They're gonna give it to the new team They're currently on no matter what but I don't know. It just seems so confusing.  Wilson Contreras did not get traded. I'm sure Rex is very happy, right? Maybe they work something out Maybe they trade him in the offseason Signing trade, I don't know Manu Rodriguez that is a Chicago Cup Going to Greg And tier one talent Brooks Robinson to 175 Nice patch. They're Mariano Rivera to 25 It's pretty solid Pretty salad Yankees gonna run Tier one talent Sonny Gray to 299 The hell am I watching on ESPN? What is this the ocho? We have Joe Ryan to 299 Yvonne Rodriguez a little pudge there for Detroit. No, Mike. It was just Too hectic everywhere It was I think we have more entertainment just watching people around walking around Okay, the drawing is once we sell all 75 bricks. We are barely in the 35s By the end of the night, we might be in the 50s though so As I said in the promo Bio is if some breaks didn't sell out during the promo during the national we would be breaking them here Madverling So there's a tab on the schedule that I pinned where you can look at promo breaks and where we're at to see how close we are Aronola nice signature there. All right last two boxes guys nothing super out of the something super crazy, right? I feel like we're do something I did I did a little bit on Friday and on Saturday I did on Friday and Saturday. I didn't really I honestly didn't buy much. I really didn't actually sold a lot of stuff Sold a couple Jalen Hertz rookie autographs from like contenders and mosaic Sold one of my Wayne grats Wayne gratski cup autographs out of ten Sold my Josh Allen RPA that I had I made some good money, so I'm happy Ernie Clement, but the corporate booths were pretty cool. It was just so packed over Glenn Otto to 299 Raleigh fingers Joe's nemesis I'll never forget that day.  I sneezed a couple times Last one here guys. Good luck patch auto Max Kepler thing I don't feel like this case was the best one we've had before Unfortunately, but it's still got some hits for a lot of teams. I know some teams may win hit less, but We do have more tier one I'll do a quick little recap So Raleigh fingers there Glenn Otto Piazza Aaron Nola We've done a lot of these There'll be some cases like this then there'll be some cases like I hit up my trout one-on-one It's just there's far in between.  I was just not the best players All right. Well, there you go guys. That was number 17 18 is on the website and before I go And this video let me jot down everybody's name. So I put it in the promo That way you guys can see that you're in the promo now for this to 100 So you can see this will be break 37 was tier one number 17 and that would be break 37 So we're almost in the 40s guys remember there are a couple breaks like eminence and Tier one three casers that'll have five promo spots the RMB has five That's already ten right there that one has ten. So just between those three breaks right there That'll be another 20 spots.  So from 37. We're gonna jump to 57 So there's that and yeah guys, of course, like I said some product will be here today Some product will be here tomorrow. So just just bear with this guys We'll get that stuff all done by tomorrow that if there is any breaks that sold out today So appreciate you guys next break coming up is NT basketball RMB pack filler. Appreciate you guys


auditory pathway starts from hair cells which are present in cochlea. These hair cells are of two types that is the outer hair cells and there are inner hair cells and both of them receive the afferent and efferent. However, major afferents come from inner hair cells and the major efferents go to the outer hair cells but both have the efferents and the efferents. Now the afferents from these outer and inner hair cells form the auditory component of the vestibulo cochlea nerve and these are basically the dendrites of the bipolar neurons which are present in the spiral ganglion. These are bipolar neurons because they have a long dendrite process and then there is axon which goes to the medulla. So these afferents form the auditory component of the vestibulo cochlea nerve. Now this spiral ganglion is also present in the cochlea where it is present it is present in the modulus of cochlea. Fine. Now at medulla they actually synapse all the fibers of this axon synapse and they synapse in nuclei in the medulla known as ventral and dorsal cochlea nuclei. Ventral and dorsal cochlea nuclei so first synapse is occurring in the cochlea nuclei. From ventral and dorsal cochlea nuclei there is diversion of the pathways and the auditory pathway goes in four direction. So this is the ventral and dorsal cochlea nuclei. From here most of the pathways actually go and synapse on the nuclei present in the medulla and this is the superior olivary nuclei. Again superior olivary nuclei are two there is medial and lateral superior olivary nuclei. So most of the fibers go synapse on the opposite side. So suppose this is the midline okay and I am drawing pathway of only one side remember. So there will be ventral and dorsal cochlea nuclei this side also. For simplicity I am drawing only one side. So remember most of the pathways travel on the contralateral side going to the superior olivary nuclei. Then some fibers also go to the ipsilateral superior olivary nuclei so that is the second pathway. Third from here some of the fibers directly go to the nucleus of the lateral leminescus nucleus of the lateral leminescus and here it forms the the bundle of fibers forms a lateral leminescus. So that is the third pathway and also some of the fibers go to the reticular formation reticular formation in the pons. So all these group of fibers have different processing going on remember that is why there is so much diversion of the pathways. We will see what is the processing little bit later. Let us move on further with the auditory pathway. So from superior olivary nuclei then again the fibers ascend and they reach to another nucleus of the midbrain that is the inferior colliculus. Again from here they reach to the inferior colliculus okay and here also nucleus the fibers which have synapse in the lateral leminescus they also reach to the inferior colliculus. So these fibers which reach to the inferior colliculus they are third order neurons okay. First order neuron synapsed in the ventral and dorsal cochlear nuclei second order neuron mostly the synapses is occurring in the superior olivary nucleus and from there the third order neuron it is reaching to the inferior colliculus. From inferior colliculus these fibers reach to the thalamus and there is nucleus medial geniculate body. So there again there is synapsing of the neurons and from medial geniculate body there are auditory radiations okay auditory radiations and then from there they reach to the auditory cortex and where is this auditory cortex present? It is present in the superior temporal gyrus. Okay with this now let us see what is going on at different levels in the auditory pathway. You see in the cochlea what is going on in the inner hair cells there is basically discrimination between the pitch and loudness okay. So in the cochlea along the length of the cochlea there is basically the fibers which respond to different pitch at the base of the cochlea the fibers respond to higher pitch and at the apex of the cochlea the fibers respond to lower pitch. So at the level of the cochlea itself there is coding going on for the pitch of the sound and loudness of the sound for this I have made another video that is theories of hearing for pitch discrimination you can have a look on that. So from the cochlea that discrimination between the pitch has started and the loudness is also coded. So this information reaches to the ventral and dorsal cochlear nuclei. Now from the ventral and dorsal cochlear nuclei the fineness between this pitch discrimination starts. So here itself there is something known as lateral inhibition okay. So all the fibers are reaching there but you might be aware that in sensory system lateral inhibition is one concept which is important for increasing the contrast between the different sensations coming from different areas basically. So information from one area inhibits the information from just a nearby area so that is lateral inhibition that fineness of information starts in ventral dorsal cochlea nuclei especially for pitch discrimination and why it is traveling to so many different areas you see the information of pitch directly travels to the lateral discrimination. So here whatever fineness of information has happened that goes directly to the lateral lemniscus but the information also goes to the superior olivary nucleus where now the second level processing starts that is for the localization of the sound localization of the sound. So what happens you see that this superior olivary nucleus receives information from both sides okay. So from this side also the information will cross and reach to the opposite superior olivary nucleus. Now depending on from where the sound is coming say suppose the sound is coming from the center both of these superior olivary nuclei will receive the information together. However if the sound is coming from say somewhat left side what will happen that left ear superior olivary nucleus will receive same information little bit earlier while right superior olivary nucleus will receive same information little bit later and we are saying that the information is going to the opposite side also. So from left ear this superior olivary nucleus will receive the information first and from right ear same superior olivary nucleus will receive the same information little bit later. So there is something known as time lag okay and there is also intensity lag okay because the sound has to travel little bit more distance so little bit less intensity happens from the information which is reaching from the ear of the opposite side. So this information that is the difference in the time lag and difference in the intensity lag reaching to the superior olivary nucleus helps in localization of the sound. Again a detailed video on this localization of the sound I have already made you can have look on that as well. Then moving on further I said that information is also going to the reticular formation and what is reticular formation responsible for? Reticular formation is important for activation of the nervous system because from here information goes up also and there is generalized information which is going to activate the nervous system and goes down into the spinal cord as well. So your awake state alert state it is caused by activation of the reticular formation. So our responses to loud sound which make us alert to the sound. Suppose if we are sleeping and there is some loud sound suddenly we wake up that is being caused by the information which is going to the reticular formation fine. Next going into the inferior colliculus that is the tectum what is happening here.  So our head and eye movements which occur towards the loud sound for that the reflex movement for that this tectal information is important. Then the information goes to the medial geniculate body and relays here and you know that thalamus is the relay center because lot of information is being communicated within the thalamus itself and lot of processing is going on here and why is it important thalamic relay center? Because it is the gateway of the information the information how much information is going to the auditory cortex and how much information is also coming from the other sensory systems or what is the state of the cortex that all decides that how much auditory information is going to the cortex say suppose for example you are sleeping in that case you see the responses to loud sound are intact because the information is going to the lower centers as well but how much you are able to appreciate the intensity of the sound while sleeping it will be very difficult so initially maybe you might become aware of the sound you will become awake and there will be postural movement but actual discrimination of the sound you cannot make because the information has not gone to the auditory cortex that well because our gateway has little bit to stop that information some processing has happened there so that is the mean thalamic nuclei function then the information goes to the auditory cortex now in auditory cortex there are tonotopic maps what are these tonotopic maps as we know that in other sensation also there are maps which are basically for the localization of the sensation from different areas so in auditory system there are tonotopic maps that is the maps which are based on pitch okay and mostly the maps which are for low frequency they are basically arranged laterally and laterally actually and then as we move posterior medially the maps are for high frequency so there is arrangement like this for the maps and why i'm saying maps are not a single map because actually there are six maps in the auditory system six maps and why do we need six maps well there are different maps for different characteristics of the sound for example we need to find about the pitch okay then we need to localize the sound then we need to find out how complex the sound is so all that we have six different maps in the auditory cortex then from this auditory cortex which is basically the primary auditory cortex which is the area number 41 and 42 the information also goes to association area association auditory cortex and all the association areas of the cortex basically receive information from other sensory areas and that is very important for interpreting any information because from the environment we interpret information in a holistic way we don't separate all the information okay this is the sound this is the vision when we are supposed watching a movie everything we interpret in a holistic way so that is going on in the association area and very important in case of audition is the verni case area which is important for interpreting the meaning of the sound so that is the fundamental of the auditory pathway which goes from bottom to the top but there are some top-down pathways as well so before going into that little bit just we will summarize this so what is happening from outer hair cells and inner hair cells there is the auditory component of the vestibulo cochlear nerve which is the bipolar cells located in the spiral ganglion in the cochlea then information goes to the ventral and dorsal cochlear nuclei which is present in the medulla then there is crossing over lot of crossing over most of the fibers cross over to the superior olivary nuclei of the other side again present in the medulla some fibers go to the superior olivary nucleus of the same side from here information is going to the inferior colliculus which is present in the mid-brain okay and that is via the later leminescus pathway that is the some fibers here also go to the nucleus of the later leminescus some are basically synapsing and here is the later leminescus then from inferior colliculus the fibers go to the medial geniculate body okay so that is medial geniculate body that is located in the thalamus and then from here the fibers are going to the auditory cortex so this is a simplified auditory pathway and what is the mnemonic to remember it i remember it like collic m a collic m n what is this there is cochlear nuclei c o is cochlear nuclei o l is olivary nucleus superior olivary nucleus before it because it is coming first so i remember it as a superior superior olivary nucleus then there is later leminescus l l then there is inferior colliculus and m is the medial geniculate body a is the auditory cortex so that is a mnemonic to remember the auditory pathway let's go into some more details about the auditory pathway that is the top down pathway some information is also coming from top to down and why it is important again i'll give you the example of focusing suppose you are focusing on something watching movie or reading what happens during that time our sensitivity to other sounds diminishes so you can try this basically sit in an environment where fan is on you will hear the environmental sounds as well so try to focus on the environmental sounds now try to focus somewhere else where you start reading say suppose and you will notice that the other sounds basically have disappeared now you are not able to even listen to that sound so how it is happening that is because of some thalamic processing yes and also because of some top down pathway which is causing the information to change which is coming from i h c n o h c so this outer hair cell basically there is change in the length of this outer hair cell and because of this change in the length of the outer hair cell the sensitivity of the basilar membrane of the cochlea to respond to sound changes then also the efferents which are going to the inner hair cell from here it basically it impinges on these afferents only and this decreases the response of this afference to the stimulus so this is top down pathway very important for sensitivity to various sounds in our environment we are basically living in a noisy world so we need to choose where we focus and which sounds we should hear however any dangerous sound i said that any dangerous loud sound even then your cortex can respond because of the activation of the reticular formation fine now we will end the session with some lesions if you have understood the auditory pathway you will understand that if there are lesions at various places what can be the problems so suppose there is lesion of this hair cells what will happen see not all the hair cells will die immediately there will be progressive loss of the hair cells and that happens in old age or when there is consistent exposure to loud sounds so in that case also there is hair cell damage so there will be progressive hearing loss progressive hearing loss okay so that is one then what will happen if there is damage to the ventral and dorsal cochlear nuclei in the medulla the information will not go further isn't it so there will be hearing loss okay then what will happen if there is damage to the superior olivary what is the function of superior olivary nuclei the processing for the localization it starts here right so this superior olivary nuclei if that is damaged we will have problem with the localization of the sound but can but can we determine the pitch and loudness of the sound yes we can determine because this is another pathway which is going via the lateral leminescus and synapsing in the nucleus of the lateral leminescus and reaching to the inferior colliculus so yes we can determine the pitch and loudness but we will not be able to localize the sound properly because the localization pathway travels from here to the auditory cortex and has a different map so that is not happening then what will happen if there is a damage to the auditory cortex will we able to hear yes if there is damage to auditory cortex or one side only you see we are telling that most of the fibers cross and reach to the auditory cortex so we will be able to hear properly only little bit hearing loss might be there but otherwise not much problem happens because auditory information travels bilaterally understanding however we will not be able to localize the sound properly there will be some problem in determining the complexity of the sound differentiating very fine differentiation of the pitch that may be problem yes somewhat crude differentiation we will be able to do the responses to the sound will be intact the reflex responses to the sound will be intact so hearing loss full hearing loss will not occur when there is damage to the auditory cortex and what will happen if there is damage to the varni case area that is then interpretation of the speech problem for that again I have made another video please have a look on that as well so that was all about the fundamentals of the auditory pathway thanks for watching the video if you liked it do press the like button please share the video with others and don't forget to subscribe to the channel physiology open thank you


Kaj je inštačno, da smo počkali? Zdaj, kaj je inštačno počkali? Dobro, sem glasba, kaj je. Zdaj sem vseh P.H.D. studentov na EFOM, v Milanu. Zdaj je izvršenja, ki je vzivno skončil na kanserice. Vzivno, ki se dobro vseh, da imamo model, ki možemo ještječne zvršenje dajselebe. V mene, kaj sem izvršenja, da je vzivno skončil na grojt. Zdaj, zelo vseh, da vzivem, da vzivem, da vedem, da je vziv, da je vziv vziv, da se vzivem, ki je vziv. When a cell is exponentially growing, the state of the proton composition is tightly related to the growth rate. For the proton we refer to the whole group of proteins that are expressed by a cell in a certain condition. In triple smo je pravdi, in je to upbeeping in je je, da je naspežen, in je to pravdučezne. In je tje, da je, je dološen klasifikacije, da vam je zelo vse dolačen. kapožena je otvarjana do zelo, učil je ještje obježenje obježena. Tako chill do zelo, da je stranje z delovмет, da je na sel milit producez čest, se pričo se priče, je tko, da pletuje cel zelo, da je tkaj preč postel, ker bude zelo, da je počet, in zelo, da je ta otroj sektor ubil, That's what we usually call phosphor. The relation arises because of the problem in research. Cell needs to be clears, so a time that synthesizes the cell so we can build up mass. But in order to do that, cell needs aminoacid and other precursor in prišli in godzimi zelo, tako gre, da reprežite zelo vse, ne zelo se, da ležite, batteri nismo, tudi nekih, tako, da lahli, ki so ta nisi na večelo, ki se rečijo, k Clo, ki je nekaj vse, nič si je, da so nekaj, praying vse, da jo se ko opreživajo, Kaj je izgleda iz teori, kaj je izgleda izgleda iz regulatoriji, kaj je izgleda iz regulatoriji strategij. V Bakteriju je zelo, že PPGPP je izgleda, kaj je izgleda izgleda iz izgleda iz izgleda iz izgleda izgleda, in odpičen je državnjo, ker PPGPP je odmah, če je izgleda, kaj je izgleda izgleda izgovoril je zelo. Paj zelo izgleda zelo, da izgleda izgleda izgleda, zelo izgleda se z vrča posložnoj, kaj je izgleda izgleda izgleda izgleda izgleda. In razliš page n integration of these two issues. So I'm going to introduce now our framework, which is composed of four main parts. So the first ingredient are the regulatory functions of the pros and sectors, which is basically the function that tells how the... s nekaj človpoundovčke, tudi nekaj človrbi človrbi, s veči človrbi, in sljup in v koristice, kar je, da je, da je, kot jo, izgledaj, to, da je, da je, ko, da je, in, in, neko, dahe, pomagaj medicines nekaj čel in zelo pa, da je svoje rezačne, skupno nekaj trvalovač nekaj se možete kratilo dopelju končnosti, več, da je minimija protem, zelo je sektor, kaj nekaj je propr Performance mass, in tudi je nekaj idej za akumulacij Tačnojga. Na predrha, In z nekaj načajo ga se značila, da je skonjunga prijeljna biomaska, je tudi skonjunga biosynthesima vriste, k če nekaj je vrtele neko je skonjunga vrste spesivnje sektoris, je toz bilj nači vrtele vrtele tudi s Kaj. Se to je kanal u vrtele vrste. Tako je tudi sektor misljenja dešne spesificije. in zelo se počutno počutiti, kako se izvajalo, da počutno počutim začet večen, je veliki na večenom zelo. Na večenom, kako se načale, nekaj da se začet na večen, je veliko na večen. OK. The next ingredient is to understand how the value of the regulatory function arises. Because we want to know how the ribosome can know how many ribosome they have to produce, how many housekeeping protein and constitutive protein. The fact is that the ribosome do not know those particular ratio that they have to produce the protein. They just randomly attach to the mRNA and start transcribing for whatever is code in them. Therefore, we think that we propose that the regulatory function, their value, arise strictly tied to the composition of the mRNA pool. And we define the regulatory function as the fraction for the sector i as the fraction of the transcript for that gene i divided by the total transcript. So in order to understand the dynamics of the regulatory function, we need to look into the transcript dynamics, which is given by a production term beta p, where p is the RNA polymerases, and the degradation term. This for the total transcript, while if we look at the transcript for a particular sector, in this case, it's written for the ribosomal one, we have that the production term is multiplied by a function omega, which is really similar to the regulatory function for the proton synthesis. Here, omega is telling us how many RNA polymerases are transcribing for ribosomal gene, in this case. So putting together the two equation for the transcript dynamic and the definition of kylet was in the other slide, we found this equation for the dynamic of the regulatory function. And also from here, we can see from this equation, and the one before, we see that a steady state requirement is that omega equal ky equal pi for any given sector. So in bacteria, we know that the PPGPP is the one that sets how many ribosomal transcript I'm going to produce, because it interferes with the binding of the RNA-P on the ribosomal promoter. Therefore, omega R will be a function of the PPGPP level, and we set this function by the fitting of steady state data. OK, the next ingredient is to understand how the level of PPGPP is fixed. And in this case, we choose to adhere to the last paper by Teriwa's lab, where they basically found an empirical relation between the PPGPP level and the elongation rate, the transition elongation rate. In general, the PPGPP level will be determined by a term that represents the synthesis of the PPGPP and a term that represents the degradation. And the co-authors in their paper, they propose that the synthesis term is proportional to the dwelling time, which is the time that the ribosom, after the elongation is the time that the ribosom waits to get another charge tRNA, while the degradation, and this time is, of course, also related to the abundance of tRNA, of amino acid, and other elongation factor. While the degradation of PPGPP, they propose that it is instead proportional to the time of translocation, so to the time that it takes for amino acid to get incorporated into the protein and for the ribosom to move to the next code. Put in together this equation with the definition of the translation rate, where the inverse of the translation rate is given by the sum of these two times, we get to the empirical relation between the PPGPP level and the elongation rate. Epsilon tilde is the maximum elongation rate. So basically, when the elongation rate is maximum, we get that the PPGPP level is zero, while when my ribosom is lower, I build up the PPGPP. OK. So the last ingredient that we need is to understand what is the dynamic for the amino acid. And here is relatively simple, because the dynamic is just given by the influx of amino acid mediated by the constitutive sector, where nu is the nutrient quality of the external nutrients, and the outflux, which is given by the biomass flux, because the ribosom that are using the amino acid in order to build the protein, while the minus lambda psi is a dilution term given by the growth of the cell. OK. So I finished presenting my model. I do a quick recap here. So basically, we have that the size of the sector is decided by the regulatory function. The regulatory function are tied to the composition of the mRNA pool, which is given by the PPGPP mediated ribosomal transcript dynamics. The PPGPP level is determined by the speed of the ribosomal elongating. And at the end of the amino acid level is just set by the equilibrium of the different fluxes. So now I will show you the theoretical result that we get with this model. So firstly, we wanted to make sure that our model predicted for a stable fixed point, because otherwise any kind of perturbation would just draw the system of this trail. And we found that the fixed point of the model are stable, and they also reproduce the first growth law, which this is an important prediction, because as you have seen before, we did not use the first growth law as a definition for our model. So this is indeed a genuine prediction of the model. And another thing we can predict is the growth law for the size of the amino acid pool. And we can do that, because in our model we explicitly describe this quantity. And the prediction is that also for the size of the amino acid pool, we get a linear relation, which is increasing in the growth rate. OK, then we wanted to understand the nature of the relaxation toward the new steady state after a perturbation in the nutrients. And what we find is that the relaxation is characterized by damp oscillation. And in particular, you can see that in particular, we have seen that all the important quantities in the model are showing this dynamic, even the size of the sector, which are the quantities that change with the slower time scale. Because in order to change them, you need in the cell need to make new biomass and to dilute the inner composition. OK, then we wanted to study why this particular behavior arise. And what we found is that this behavior can arise under a very wide set of conditions. And it's not mandatory that the regulatory circuit the equation that we show before. The really important things is that between the ribosome and the amino acid pool, it's important that there is this inquiry feedback between them. So we have the ribosome presence, hini bit, the presence of amino acid, because the ribosome use the amino acid in order to make protein. So the more ribosome I have, the less amino acid I will have. And for the other interaction, we have the presence of amino acid in answer the presence of ribosome. Because if the cells sense that they have more amino acid than required, it means that the considerably sector is a bit too big for that external environmental condition. Therefore, it will enhance the production of protein in order to go back to the desired proteome composition. And yes, as long as this feedback between these two quantities is maintained, we get the stable fixed point and the oscillatory. Yes. Yes. String them together. But what is the mechanism to get at the bottom? OK. Basically, we have that when the amino acid build up, the elongation speed of the ribosome. I mean, the ribosome will start to go faster, because they have more substrate to use to make the protein. If the elongation goes up, the PPG. That depends on tRNA pools, not directly on amino acids. Yes, it also depends on the tRNA pools. In our model, that's right. But the first signal that the environment is changing is not on the tRNA pools, that tRNAs are still something that you need to synthesize. So it cannot be the first signal of the environment changing. But the first thing that the cell sends is that there are more carbon precursor and amino acid around. And this will speed up the elongation rate, even if at the very start of the shift, the tRNA pool has not changed yet. So why are they speeding up? How do the ribosomes know they have to go faster? Because the tRNA pool, in general, is not changing. But when I have more amino acid, the percent of charge tRNA is going up, because I have more amino acid around. I mean, I don't just need that. So the amino acid concentration increase leads to a shift of the tRNA pools towards more charged tRNAs and more charged tRNA speed up elongation. Exactly. And OK, next, we wanted to make sure that this was really the reason we see oscillation. And that the present oscillation do not hinge on some microscopic parameter that is not under control. So what we do is to compare two different systems, one with the transcriptional delays, which is the one that I showed you before. So where the dynamic of the regulatory function is given by the dynamic of the tRNAs. Sorry, of the mRNAs. We can see here in the first plot that we get the oscillation. And during the shift, the value of the regulatory function does not follow the steady state relation with the value of the elongation rate. Where the steady state relation is the dash line. But during the shift, it doesn't follow it. And what we found is that even if we force the regulatory function to adjust immediately with the change in the elongation rate, so it adjusts immediately and it follows the steady state relation, we still get the oscillatory relaxation. Even if, of course, the amount of oscillation is different. The growth rate is shown here on the y-axis. So the double time, I think, will be maybe 20 minutes for the post shift and see it better here. Yes, yes, because three hours is yes. OK. Yeah, all the results that I showed you are also supported by analytical calculation, where we treated our framework as a dynamical system. So we studied in values, the stable fixed point, et cetera, et cetera. OK, now, as a conclusion, I wanted to show some experimental evidence of the oscillation, which we do not collect, but we have a search in the literature if someone has seen this behavior. And in the first plot that I show you, here are two different work. And in the first one, we can see some really rapid oscillation of the regulatory function of the ribosome after an upshift. While in the second plot, we can see the adjusting dynamic of the growth rate for bulk shift in between different carbon sources. And in the second plot, the oscillation are not so clear, like in the first one, but we think that we cannot exclude the fact that maybe they are there. And lastly, I wanted to show those experiment, which our partner lab in Cambridge have performed this experiment, where they shift from anemic fluidic device from a medium with glucose to a medium with glucose plus amino acid. And you can see that both the growth rate and the ribosomal sector, as they would have an overshoot before relaxing to the finite state. And in this case, our model can reproduce this trend if we adjust a little the parameter that connect the amino acid pool to the speed of the elongation rate. Unfortunately, in our lab, we cannot do experiment. And this phenomenon is not really well studied. I mean, not that I know. So here, we are doing what we can. We did it that we have. So this is growth rate as a function of time. Yes. It's four hours. But sort of in the mother machine glucose, it's 80-minute doubling or something.  So I want to, this is like a population average growth rate that you're looking at? Yes.  But what I'm showing here is the population average. But you expect the oscillations to be only at the single cell level and not necessarily be in phase with each other. No? Yeah, that's true. But nevertheless, we see them also at the population level. People, please. Oh, no. I mean, you give a clear impulse at this specific time for all the cells at the same time, right? So if there are some intensive time scale then. That's true. That's true. But I think that, OK, you are giving a specific input. But at the single cell level, there are multiple factors that are important. For example, the phase of the cell cycle where the cell is at that specific moment. So I mean, that's true that the signal should coordinate them. But there are also other mechanisms that can play a role. OK, so to conclude, basically we have a framework that put together the growth load theory with a more mechanistic description of the PPGPP sensing regulation. And the main theoretical result that we have is that we expect an oscillatory dynamic for the relaxation toward the new steady state. As a consequence of this, I mean, this result means that basically if you put in the model the whole chain between, from the take of the amino acid to the protein synthesis, oscillation is what you would expect. And if this is not seen in the experiment, there is probably meaning that the cell is putting some other mechanism in order to avoid, to have this behavior. So last day, I want to thank my group for the support they gave me and all of you for their attention. Thank you. I just a comment. So an overshoot in the response could have a functional role in speeding up the response time for protein changes. Yes, yes. So I was wondering if you compare situations with the overshoot and others without the overshoot. And look at the response time of the new proteins being produced if you can see this. This could be a reason for this overshoot to exist. Yeah, we did not compare that. But yeah, we know that, I mean, there are some paper by Alon's lab. And also other paper that says that the oscillatory relaxation is probably the one that optimizes the timing of the response. But no, we didn't compare the two versions of the model. Also because really, if you put together the amino acid consumption and the ribosomal production, you will get oscillation. So we can compare different model, but my version of the model has oscillation. We cannot get rid of them. Sorry, can you just show that last plot again from the one you fit against? This one. It seems like the ribosomal mass fraction does a less of an overshoot. Is that something you expect? Or is it just, if you normalize it, is it sort of self-similar eventually? Even in your model, it seems like there's. I mean, I think that also in the model, this example here, the ribosomal fraction is not oscillating as fast as the other. And I will say also the amplitude is a bit different. Because as I say before, in order to change the protein composition, you need to produce new mass. And to dilute the inherent composition that you had before. So for sure, the time scale and also the amplitude of the oscillation of the sectors is reduced, respect to, for example, the one of the elongation rate. I don't know if I answered. Sorry, does your model give any indication of that lag time, like a mechanistic understanding of that phase shift between ribosomal fraction and growth rate, or could it? I mean, we did not study that specifically. But just by looking at the equation of the model, I mean, the way we modelize the shift is that the nutrient quality, nu, basically goes with a jump. And what happens is that the derivative of the amino acid is discontinuous. And so is the one of the elongation rate. But then, in order to arrive from this to the production of new biomass, you have first to change, to adjust the mRNA pool with the time scale tau, which is 10 minutes, around 10 minutes. And then, you have to adjust the size of the sector, where the time scale here is lambda. So the faster the saliva is growing, the quicker it will be here. But still, you have two steps from the shift to the adjustment of the size of the sector. That's why, I mean, you have different time scales. One more question. Last one for the talk. So the last data that you show for FIAR, are the promoter. I mean, it's the GFP data. Yes, it's the GFP signal. OK, so do you consider also the maturation time of the GFP?  Here they use fast maturing GFP. So the maturation time was around 10 minutes, which, I mean, it's a time scale that exists. But you see that the oscillation is like two hours. So it's not really impacting the result. Right. Let's thanks the speaker again. And now we have our last talk, I think.


In this video, we are going to look at the most common list methods and let's do so with an example. So let's create a new file and call it list methods. And let's continue with a new example. Let's call it name. So we are going to create a list holding names. And the first name is going to be Carl with a C. And the second name is for now going to be Peter. So let's execute that and let's look at names and names is indeed a list with two names. So in our memory, what that looks like will be as follows. We create a list object like that and here I will make it a bit bigger because we will have to make some changes throughout the video. And yeah, so let's also write here list data type. And now for the first element, we simply have the name Carl and I will abbreviate that with simply a C, Carl with a C and the second name is going to be Peter with a P. So let's simply write here P. So these objects are actually string objects. I'm not going to write that here, but it's going to be string objects, Carl and Peter. And the variable name is also going to be named simply and it's going to reference this object. That is what we have created so far. And now what you're going to see is why for all the times now in this course where I drew a list in memory diagram, I always had those excess spaces, those excess fields here where I never put something in there. And I always told you that the reason why Python creates basically list objects a little bit too big is so that we have some flexibility to later on add some further objects into this list. And this is what we will do using list methods. And also not all methods, of course, do that, but list methods help us do that, of course. So let's look at the first method. The first method is very common. It is called the append method. So we say names.append. And to repeat that, a method is simply a function that is attached to an object, in this case a list object. So we are going to say the names list object, and then we're going to write the dot operator to access the attribute called append. So the append function, if you so will, that is attached to the names object. But any function that is attached to an object is what we refer to as a method. And we will see in chapter 11 when we talk about object orientation of how we can define our own methods and what methods really are. But for now, we simply call them functions attached to an object. So the append method takes one argument, and that is actually not entirely true. It visibly takes only one argument, but actually takes two. So the argument here, as an example, is going to be, let's say, the German name Eckhardt, I think, with a DT. And yeah, I think the age is wrong, so let's put it like that. So German name, some name starting with an E. And what the append method is going to do, it is going to take the object, in this case the string object Eckhardt, and it's going to append it to the list at the last position. So if I execute that, you see one minor thing, some minor detail that I want to make you aware of. Below the cell that I just executed, there is no output. So whenever a method has no output, there is a pretty high chance that something must have had a side effect. And we will see that in the memory diagram. The side effect is the following. We simply create a new string object, the name Eckhardt, put the E here, and we'll simply go ahead and put another reference into the list. So the side effect here is that the list now has one more reference than before, and it happens to reference the letter E here. And so why is that important that we don't see any output here? So there are mutable data types like lists, but there are also immutable data types. And in chapter 6, we talked extensively about the string data type to model textual data, and we said that the string data type is an immutable data type. So once you create a string object, you cannot make any changes to it. So with a list object, things are different. The list objects are mutable. And we just saw that we can put a new element at the end of a list that is called appending. And what does that have to do with method calls? Well, in the chapter 6 on strings, when we called, or when I showed the methods, most of them actually returned a string. So there was a string given, and we called some method.  However, that is something that is generic, so to say, for many immutable data types. So whenever you have an immutable data type like a string and you call a method on an object of this data type, and the method actually changes the value, then it does not change the value of the actual object in which we call the method, but it rather goes ahead and creates a new object with the changed value. That is why that is so significant here. So for data types like the list data type that are mutable, we don't get a return value, but to indicate that something has changed in place. So we have made a change to an already existing object. So that is what you can see when a method has, or what you can guess, when a method has a no return value here. It's not true for all methods, but for methods that should change, conceptually speaking, the value of an object, that is the difference between a mutable and an immutable object. So let's look at names, and indeed the name echo is at the end, just as I showed you in the memory diagram. So that's the append method. So let's take that one step further. Let's assume you don't want to simply append one object at the end of the list, but you want to append several objects. There are two ways you can do that. The first one is to write a for loop, for example, and in the body of the for loop call the append method, and then one by one append a new object at the end of the list. However, you can also use the so-called extend method, and the extend method also takes one argument, and the one argument it takes is a list object, in this case an iterable, something we can loop over, and this iterable contains the elements that are appended. So for example, I will append the name Carl with a K, and the name Oliver with an O. I activate the code cell, and we see that we don't have any return value. That is an indication that the method extend changed something in place. So let's look at names, and indeed names has been changed. So let's look at the memory diagram, and simply what the method did is it simply appended a further object right here, which is Carl with a K, and one more, which would be Oliver, and we show that with an O right here. So extending is really just appending in a loop, so to say. Repeated appending. Okay, so let's take that further. So let's assume you want to put something in the list, but you don't want to append it at the end of the list, but let's say at some other spot. So for example, let's assume I want to insert some element at the very first position. How can I do that? Well, we are going to call the insert method, and the insert method now takes two arguments, the first one being the index of the position where we want to insert. So I said at the beginning, and the beginning is index zero. And then the second argument is going to be the object that we want to insert, and let's say I want to insert Bairthold. Let's execute that. We see there is no return value under the code cell that indicates that a mutation happened. So the object, the names object was mutated in place. Let's look at names, and we will see that Bairthold is at the beginning of the list. So what has happened in memory? So in memory, what's going on is the following. Once the insert method is executed, it basically, and in this case we inserted with index zero, that basically means we have to make space here to put something in. And the way how Python does that is it simply goes ahead and it takes all the references that are already in the list and moves them one to the right. So we will get rid of that reference, just like that. This reference, this reference, and this reference here. And also last but not least, the very first reference. And now we have made space. And what are we going to do here? Well, obviously we are going to insert Bairthold, which would be the B, and we will go and put a reference right here. So now there is a consequence of that. So whenever Python has to move references, in this case it has to move all the references by one, this takes longer. A pending is very easy because there is already an empty spot at the end. We can just put in a reference, that's it. It's a so-called constant time operation. However, inserting at the beginning of the list means that we first have to move all the references by one to the right. And that is what happens in so-called linear time. Linear meaning it takes time that is proportional to the number of references we have. So if we have like here, I think it was five references, it takes five computational steps to move five things one to the right. If we had five million references here, it would take five million steps, computational steps to move everything to the right by one. That is what we refer to as linear time. Linear time is still okay, but it's lower than constant time. So inserting at the beginning of the list is a slower operation than appending at the end of the list. Something to know if you want to work with big data. So let's continue the example. And the next step is instead of inserting at the beginning of a list, what we could also have done is we could have gone away and inserted at any other position. So if I went ahead and let's say, I put let's say index one or two in here, we would insert the object at the corresponding position. And then only the reference to the right of it have to be moved, of course, but still it is still a so-called linear operation, linear time operation. So that is inserting. So now we have a list here. And obviously the names are not in alphabetical orders. So maybe let's do now, let's talk about how to sort a list. You know, list, usually list remain or list remember the order in which we appended or enter or put objects into the list. And now we want to change the order. We want to sort it. We want to sort, for example, in alphabetical order. So one way of doing that is to use the built-in function called sorted. So let's look at the documentation of the sorted function. Let's go to the library reference, the built-in functions, and where is it? The sorted function here. And now sorted takes a couple of parameters as we see here. And the first one is an interval and then the other ones all have a default value here. So we only give it one argument, which is an interval. And then it says return a new sorted list from the elements, from the items in the interval, okay? So let's go ahead and do that. So I call the sorted function and I pass names as the only argument and I get back a list object where all the names are in alphabetical orders. The reason why they are in alphabetical orders is because the sorting with a list works like that. Python simply dispatches the or delegates, that is the technical term, the sorting to the involved object. So in other words, Python will go to the Behrthold object and the Carl object and will ask them, hey, can you please sort yourself by using the lower than operator? And we saw in the chapter six when we talked about string comparison, when we compare words, how they are compared. And we remember that all the uppercase letters come before all the lowercase letters and things like that. So sorting is not as trivial as it seems, but it's not case insensitive. But here all the names come in title case, so the first character is uppercase, the rest is lowercase and also there is no first letter used twice here. So it's therefore the sorting is very much straightforward here. And we see that we get back a sorted list. However, and that is now the important thing to notice, if I look at names, it is still as we see unsorted, okay? And if we look at the documentation, it also says return a new sorted list, okay? In other words, it takes any iterable, the sorted built in function takes any iterable, for example, a list and it returns a new list. So now we have two lists here, the names list as before that we still have in memory, but also a new list. And I'm not going to draw the new list in the memory diagram to save ourselves some time and space, but this would be a new list, which referring the previous video has a shallow copy of all the elements in there, right? So maybe I showed to you in this diagram, but what this would do is it will create a new list object and all the references here, they are basically copied over in sorted order into the new list object, but the object themselves, so the string objects themselves, they are not copied. It would be a shallow copy. So in the earlier video, and there is also one of the reasons why I included the video, shallow versus steep copies, is in Python, oftentimes shallow copies are created without you explicitly knowing about it. And when you use the sorted build and you get a new list, which basically is a shallow copy of the old list and the references are in a different order, in a sorted order, of course, but at the end of the day, both the new list that comes as the return value from the sorted function and also the old list names here have references going to the same string object. So they share the same data in between them. So implicitly, we are creating shallow copies all the time when we do sorting. Okay, so let's continue with methods. So you may wonder, why am I showing you the sorted function here? Sorted here is not a method, it is a function that takes, for example, lists as an input. However, the list data type also has a sorted method. So let's see what the difference is. I say names.sort, so it's a sort method. And if I call that, I don't see a return value. So how is that? Well, the reason for that is because something happened in place. So something was mutated and of course the names object was mutated. So now names and what we see above here, the outcome or the output of the sorted function are now the same. But now we have made the changes in place. So the difference is sorted creates a new list object with a shallow copy of all the references in sorted order. The sort method, however, sorts a list in this case in place without creating a new list. So what the sort method really does, it simply goes ahead and it first removes all the references, all the orange ones here. And now it goes ahead and using red here, I think B is the first letter. So let's make B reference that. C is the second letter. So this goes here. Then comes E. So this will go to E here. This one will go, I guess, to K. Then we will go to the O. And the last reference, let's make it a bit more obvious, we'll go to the P here. So that is what the sort method does. It basically reorders the references, right? So that's basically what it does. It changes the list in place by rearranging the references. Big difference here. So now you may wonder if we can sort by, let's say, alphabetical order here. So why do we do that? Well, the reason why we are doing alphabetical sort is because this is how two names would compare to each other. So in other words, if I have, let's say, in the unsorted version, let's say I have Peter that comes before Eckhardt. Let's assume, let me simply copy-paste that. And let's copy-paste that in a cell. And let's compare that using the comparison operator. Falls here indicates that Peter should go after Eckhardt. And the true would indicate that the two objects are already in order. So this is how Python does the sorting behind the scenes. And now you may wonder how can you adapt the sorting? And you can do that using a key, so-called key function. So what is a key function? A key function is a function that takes one argument which are the objects to be sorted one by one. And it returns some other object, for example, a number that is then used to sort the actual objects, okay? So let's do an example. And that is, it sounds more complicated than it really is. So let's assume I want to sort the names here, not by alphabetical order, but let's say by the number of characters. So I want to have the short words first and the long words later. So how can we do that? So what we are going to do is, first I'm going to use the sorted function to illustrate that, I give it names. And if I call that, I get back the sorted names by alphabetical order, but what I can do is, I can pass it a second argument, the key function, and as the key function, I simply pass it a reference to the lend function, to the built in lend function. So in other words, what this does is, it will pass each of these words here one by one to the lend function, and then the lend function will return the number of characters in the word, and then this number is used to sort all the words. So let's do that. And we see that we have the short words first and the longer words last, okay? Now you may wonder what happens as a type breaker. So we see Carl with a C and Carl with a K, both have four characters. So there is an easy type breaker. The type breaker is, if two objects compare equal, then whatever object came first before the sorting also comes first after the sorting. That is called the so-called stable property of sorting algorithms. On other words, a sorting algorithm is stable if it has this property that whenever two objects compare equal, whatever came first before the sorting must come first after the sorting, okay? And now we can also do that if we look at names, we see that names are still in the alphabetical sort order. But now what we could do is, we could also go ahead and simply say, let's call the sort method now to make the change, the sorting changes on the names object. And we can also pass this method a key argument. And let's also pass it a length here. And if I now look at names, now we see that we have the same sorting order also for the named object, right? So again, sorted creates a new list with the corresponding sorting order and the sort method makes the sorting in place on the actual already existing object. One more thing, let's say you want to sort in reverse for example, alphabetical order, but you could also do is, we could go ahead and we could simply call the sort method on the names list again. And instead of providing a key argument, we can simply provide a reverse flag. So I'm simply going to say reverse equals true. That is what we call a flag. So any argument that is simply a true or false argument, a Boolean argument, is what we as programmers casually refer to as a flag. So by passing a reverse flag, a reverse true flag, what is going to happen is, we now get back a reverse alphabetical order. Why alphabetical? Well, if I don't pass a key function, then again, the objects are compared as strings and strings by default are compared using alphabetical sort. So that is why we have alphabetical sort here and the reverse equals true makes the sort algorithm go backwards basically. So now, what have we seen so far? So we have seen how we can create a list and how we can add new objects into the list by appending, extending, inserting. Then we made changes to the order of the list. And now what still remains is the following. We want to remove stuff from the list, of course. So how can we do that? So first of all, what I'm going to do is, I'm going to say names.sort again, mainly because now the names list here in the Jupyter Lab is now alphabetically sorted. And if I go into the memory diagram, we also have the same sorting, okay? So now the example in the Jupyter Lab and the memory diagram are in line, so to say. And now what we could do is we, let's talk about how to remove some objects from a list. One of the very common methods to do so is the pop method. So let's say names.pop and what the pop method does is, it simply pops off the last element by default and it returns it. So in other words, what we are going to see, let's say removed, let's assign that to a variable called removed. What we see is, removed is now Peter because Peter was the last element. And if we look now at names, names that the name Peter is gone in names or so. So pop, the pop method does really two things. The first one is it removes a reference and the second one is it returns the reference, right? We will also see another way where we can just remove the reference without returning it. So what happened in memory? So in memory, what happened is, this reference here, the last one is going to be removed from the list object and here we have P and the reference to P is given back as the return value and we called it the removed variable. So removed now points to be, okay? And so P is now, so Peter is now not in the list anymore, okay? The reference is gone. So what the pop method can also do is, and I'm not going to show that here, but what we could do is the pop method also accepts an index as an argument. So for example, index zero and then it would simply pop off the first element and then what we have to understand is, again as before, let's say if I pop off the B here, the first element, then the first slot here becomes empty and that will lead to all the references here being moved one to the left, okay? So therefore what we learn from that is, using pop with an index of negative one or maybe or simply without an index, pops off the last element, popping off the last element in the list is a very cheap operation, a very fast operation because it happens in constant time. However, if I'm going to pop off any element other than the last one, then what's going to happen is, after we pop it off, there are all the references to the right of it have to be moved one to the left. Therefore, popping off any element other than the last one is a linear time operation, right? So we have to be careful. So if we build algorithms where speed matters, using the pop method with anything other than no argument is probably not such a good idea but we are not going to do that here. So what else do we have? So what else we can do is we can use, we can remove objects by value and we do that with another method which we call simply the remove method. So the remove method takes a value, it takes some input, an object and it compares by value the value we pass in as the argument to all the values that are inside the list and the first one it finds that is equal, that compares equal is the one that's going to be removed. So let's say, if I go ahead and I want to remove, let's say, who do I want to remove? Let's say I want to remove, let's say, Carl with a K. Let's do that. I don't get a return value here that is different to the pop method. Why do I not get a return value? Well, assuming I'm already passing in an object of a certain value, I already have access to this value, so to say. So therefore it doesn't make sense to also return it. So now if I look at names, Carl with a K is now gone. What happened in memory? Well, quite simple. Carl with a K, which is this Carl here, which is this reference here, is now being removed. And because there's no further reference, the Carl is also removed. And also this red reference here is also moved one to the right. Maybe I can do that by simply drawing it like this so that you see that this O now moved one to the left, actually. Okay, so let's continue. If I call this method again a second time and the value is not in the list anymore, I get a value error, that is a nice thing because then we know, okay, we basically looked for the value in the entire list and it was not there. So I personally like those so-called loud error messages because this way you often find errors before they become, yeah, before you find errors simply before you put a program into a real life scenario, right? And so therefore that is just what the remove method does. It simply complains if the value is not in the, or if no object with the same value is inside the list object here. Okay, so what else is there? So this is removing and technically, what we could do, I showed you there or I told you that I can remove stuff from a list without getting a return value back. So we could use the del statement, for example. This is now not a method to be strict, but I could go ahead and say del names and I give it negative one as the index. And now I don't have a return value, but now what happens is, oliva, which happens to be the last element is now also gone. So now the only thing that happened here is I now remove the last reference without returning it and therefore the O is also now removed from memory. Okay, so, but again, the del method, the del statement, sorry, is not a method. So in this chapter here, this video is mainly on list method. So what are further list methods? Well, there are a couple of others that are quite useful sometimes. So for example, there's a method called index and the index method, we saw that earlier also with the string data type. It takes one argument, let's say call with a C and it gives us back the index of the first object that compares equal to this argument here, quite simple. And then a close relative to that, which you also saw in the context of strings is the, sorry, once type string here, I should type count here, it's the count method. So if I count how often do I see call in here, I also get back one. And if I use, let's say, call with a K, I would of course get back zero because we removed call with a K. Okay, so these are methods that we saw before with the string data type and you may wonder why does the list data type also have them? Well, remember that both the string data type and the list data type are both sequences in abstract terms, right? And because they're both in abstract terms similar to each other in behavior, many methods make sense for both, the string and the list data type. Okay, so let's finish that video with the methods with one more method, which is simply the copy method. So if you say names.copy, what you get back is a new list object where all the objects in it are just copied. Now you may wonder, is it a shallow copy or is it a deep copy? And the answer is, of course, it is a shallow copy. How can you find out? So you could find out by, yeah, going ahead. And first of all, maybe you want to compare the copy to names itself, you get back false. So this way this confirms to us that we get back a new list object actually. And now if you want to know, is the new list object shallow or deep? One quick check we could do is we could make a copy and we could assign it to, let's say, names copy. And let's go ahead and maybe go to names copy and simply pop off the last element, which is Eckhardt here. Let's look at names copy. Now Eckhardt is gone. But now let's also look at names, the original names. And we see Eckhardt, oh, it's still there. But the reason why, so we see that as a copy, but the important thing is, and that is something, it's actually quite good that I can show it to you like this. The Carl here and the Carl here and the Bertolt here and the Bertolt here, they're actually the same object. So now note because we only have immutable objects inside the list object and we only have strings here, strings are immutable. Working with shallow copies is actually nothing that can cause confusion because if you only work with data that cannot be changed, that is immutable, then making changes to objects that have more than one reference going to it just as we did in the nested example in the previous video, this cannot go wrong here because we cannot change the objects anyway because they are immutable. However, it's still a shallow copy. So the Bertolt and this Bertolt is the same object and this Carl and this Carl is also the same object. Okay, so that is also a list method. But now you may wonder, should you use the copy method here or should you use instead names and take a full slice? Probably this depends on your taste but these are actually exactly the same operation here. So both of them lead to the exact same result. Both of them lead to a shallow copy of the already existing list object. Usually you would say that using the copy method is more explicit but it says copy, doesn't say shallow copy. So also more explicit is maybe not really okay to say here and some beginners may be confused before what this notation here means but as we learned in a previous video, this simply means to take the full slice and the full slice is nothing but a copy, right? Okay, so this concludes this video talking about methods. So the copy method is actually not that important. The important methods for you to understand going forward are the append, extend and insert method and also the pop method and sorting is also a topic on its own so these are the things that you should take out of this video. The index and count method sometimes are usable for some algorithm you want to come up with but I personally don't use them quite often. So probably everything until the remove method here are the more important methods that you will encounter in day to day life. Okay, so I will see you in the next video when we talk about list operation. So using lists together with operators and I will see you then.


On February 7, the occupying Russian army launched rocket attacks on the capital of Ukraine, Kiev. The Ukrainian press reported on this. The strikes were launched from Russian territory by 295 MS bombers and X-101-slash-X-55-slash-X-55 cruise missiles were used. One of the rockets hit a multi-story residential building, resulting in a fire. The city's technical service station was also hit by a missile. The city's electricity grid has been damaged, and there are victims. Kiev Mayor Vitaly Klitschko said that as a result of the rocket attack, six people were injured in the city, five of them were hospitalized, note that this is the third such attack on Kiev in 2024.


Okay, so I guess I'll introduce myself, everybody else, the people I work with are at the NANAS conference. So I'm flying solo. Anyway, my name is Victor Wong and I'm a DUI4 Uralge resident and I'm here to briefly tell you about a case of really bad optic rights. So this was a case that was seen by Dr. Warner in 2008, or starting in 2008, is a 23-year-old patient that presented with payments patient loss in her left eye over two months prior to her first presentation. On exam, her visual acuity was 2100 in her left eye and 2030 in her right eye. She had no APD, her optic nerve was normal, and she had a normal OCT. So as I visited her visual fields in her left eye, she had a superior left quadrant effect in her right eye. Her retinal nerve fiber layer was normal, and then over the course of a month, her right eye felt worse and blurriness, so she was diagnosed with bilateral sequential optic arthritis. They did an MRI that showed bilateral optic nerve enhancement on T2 with no evidence of myelitis. So they started treatment with IMU for this long per O&T protocol, and she got a little better. One month later, further histories, her mother came in and said that her grandmother would have an OCT. So that's where some genetic analysis and they found in 11778 mutations was one of the labor's mutations. But she was started on coenzyme to be 10 at that point. Overall, she improved on IV and PO steroids. We lapsed at one year and then responded again to steroid treatment. At her follow-up at one year, they got a no-ray MRI, showed no further enhancement of her optic nerves, but showed new periventricular legions concerning formal sclerosis. This meant the endowment criteria for diagnosis, so she was started on MS treatment, and then also continued on IV-pulse steroids, depending on her fluctuating region changes. She responded pretty well at the time. This is the MRI from that visit. So on the axiocut on the left side, you can see a couple new regions, periventricular and then on the right side, a little even on the axiocut. So that made this question whether there's a link between labor's or LHON and MS. It's far too described and mostly in case studies appears to be higher than chance the coexistence of these two. But it's hard to study since LHON is relatively rare. But opal sclerosis is pretty common. It's the most common demyelinating disease in the CNS, caraparite by multiple areas of demyelination with loss of all of the dendrocyte and master wheel scarring. There's some clinical features for MS. It's not specific. But MS is using a relapsing or bidding pattern. Age of onset is 15 to 50. Other symptoms include apicneuritis, ILO, herniasine, the utopsis, and so on. As far as the diagnosis of MS, the most, well, relatively most recent is the McDonald criteria that I kind of mentioned earlier. This came out in 2010. And that's probably very much the dissemination in space and time. The dissemination of space is basically defined as one or more key to readings on two of the MS typical regions. These are the peregrine tricular infantorial spinal cord and juxtaportable regions. And dissemination of time means simultaneous enhancing lesions and non-enhancing lesions or a new vision on a follow-up MRI or a development of a second clinical attack. Just recently, the Magnum's group, which is a magnetic resonance imaging MS a couple of months ago, came out with stricter criteria for the diagnosis in the dissemination of space, which is because we get, as MRI imaging improves, we can try to pull in on diagnosis better. And so, again, there's a 2010 McDonald criteria, which I just mentioned. But in 2016, they added a couple things. And there's two of the following. There's three or more peregrine tricular lesions. Again, the infantorial lesion, spinal cord lesion. And then they added an optic nerve lesion as part of criteria as well. And then, of course, the juxtaportable regions. There's just an example of a more typical MRI. And I've also experienced patients on the left again actually cut with several lesions. And then on the right is the cellular cut with... So, these... These come off the ventricle, probably the term, the dozen's fingers. And so that's typical MS. As far as labors, or LHON, there are 300 DNA mutations at positions 11, 7, 7, 8, 14, 44, and 34, 60. These are mis-sense mutations in these sub-UNGs for electron transport chain. They can cause profound impairment in the complex one dependent on ATP synthesis. And clinically, LHON is an eternally inherited form of blindness. They're derived by loss of retinal gait in themselves, an optic nerve generation. Prognosis is poor. The onset's usually between 10 and 30 degrees. It's usually pretty severe bilateral vision loss. And the visual defect usually starts with the central or super-central scutoma. It's a predominantly male and rare one, and it's usually 50,000. So why would we care? So there's a lot of similarities between the two LHON MS, including the AIDS onset, vision involvement, central vision loss with the neuronal fundage. But there are a lot of differences in that LHON is more common in men, whereas MS is more women affected by MS. LHON patients usually have only two visual events that are, and both eyes separated within six months, to use a painless improvement in MS where they have several visual events. It affects the optic nerves, and sometimes painful. And then finally, it's complicated to use. There's the combination element LHON MS, which has recently been described. Harding was the first one to describe it. So it's a men's heart disease. This is the concurrent LHON and MS. One study looked at all the LHON diagnoses in the UK and found five cases of concurrent diagnoses. So in that paper, considering that normal MS prevalence in the UK is one in a thousand, they conclude that the co-occurrence is 50 times greater than chance. Just FYI, the Utah MS rate is a lot higher, and it has to be about one year. So for patients with the combination LHON and MS, it's usually women. Some of them have one to two visual events, and usually there's a long interval between both eyes being affected from one and a half years to 17 years. So that raises a lot of questions in the literature. Several of them. Does MS inflammatory stress provoke women to show symptoms of LHON? Is this a coincidence? Is there an interaction between mitochondrial dysfunction and immunologic mechanism? And finally, is LHON and MS a different entity from LHON and more MS by themselves? So as far as treatment, you probably will know that LHON doesn't really have established treatment, but there is a period of benefit of any absence. In DevDome or CoQ10, it's been prescribed. There is a new intrabutrile injection study done by Massimo Colman. So that's all there is for LHON. For MS, there's several treatments now for attacks. We usually use steroids and platelet braces, and there's a lot of disease-modified therapies, including beta-intolerance and the tumor. And then finally, for the combination, there's still this question of whether it exists or not, and there's only one case report with a description on treatment, specifically for this, where they found that in this patient who had optic neuropathy, she didn't respond to IVL for this long, but she did have spastic paraphernesis, which is more of an opus sclerosis symptom, which improved in DevDome, worsened without, and improved again when restarted. So again, the question is, maybe is this an MS-like syndrome, improved by a mitochondrial default? So for follow-up of that patient that I talked about, she was diagnosed with both MS and LHON. She's tried a variety of MS drugs in addition to steroids, stabilized versus stabilized version. In 2010, she had a new lead, and so at that point, we started to tie the IV with IV steroids in combination with MS treatment. And she kind of continued this course, stabilized, and was seen last month, now on Gelena, which is a P.O. MS drug. At that visit, her visual acuity was 2,300 in her right eye and 2,100 left eye, and she's still on P.O.Q. 10. Her visual fields are stable, a little worse, but in the same pattern, and written on fiber layer, which shows things in both eyes. So that's it. So I need therapy in here. It's G therapy. That's what I was going to comment. Most of the therapies that are in current clinical trials are all T therapy, but I don't remember which treatment I looked at. ND4. Okay, thanks.