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[Music]
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foreign
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[Music]
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we are on to our final speaker who is on
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Zoom
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David we are ready for your talk
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whenever you are ready to share your
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slides all right let's do it hi everyone
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wish I could be there wish I was there
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uh next year for sure next oh that's
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great
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I'll hold you up to that promise I've
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got my uh my father visiting from
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Australia he's 83 and
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I think that took precedent but uh next
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year I'll bring him with me that would
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be amazing that would be amazing okay
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well thanks for inviting me let me get
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my
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presentation up and running
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perfect great and I'll set a timer so
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that we're good
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okay all right so um yeah it's it's uh
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it's amazing to be here this conference
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to your credit uh and the other
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organizers um just it's growing to be
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one of the Premier conferences in the
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world in this topic so hats off to you
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and I've really enjoyed the the talks
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uh so just because I don't have much
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time I'll get straight into it
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uh so I've been doing this for a while
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started at MIT working in little yeast
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cells and we discovered that and by we I
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mean a lot of other people as well uh
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the team discovered that uh their
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reaction to genomic instability uh
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particularly repetitive regions uh leads
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to the reorganization of Chromatin which
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leads to changes in gene expression and
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phenotypes of aging and what we work on
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in the lab is that that process that we
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worked on in Lenny grunty's lab in yeast
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in the mid-1990s uh is also true for
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mammals um and that there's a backup
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copy of information to reset the
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epigenome
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uh so what I'll do today is I'll share a
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fair bit of unpublished research it's uh
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it's really a coming out moment here
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um so this is how we think in my lab
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um similar to many others we like to
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understand why we get old
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uh and we think that the Hallmarks are
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part of a whole system and we think that
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the loss of information in particular is
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is very important and information comes
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in two types in in biology mainly it's
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the DNA and the epigenome control
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systems and we have a a lot of evidence
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in the field increasingly so that the
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epigenetic noise as we call it and the
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loss of differentiation is a major
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driver of of the process we call aging
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and illness
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um so I'm going to talk about efforts in
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many organisms including humans to slow
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down aging by targeting epigenetic
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modifiers
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um which include the sirtuins which we
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worked on and continued to do so
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I'm going to talk about the ability to
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reverse aspects of Aging including
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epigenetic age
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and I'm going to talk about what we
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really have talked about a lot at this
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conference and in my lab we are
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fascinated with the
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um the goal of having accurate clocks
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that represent epigenetic aging if not
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other aspects of Aging
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um it's a bit of a complicated slide but
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it does cover what we work on in my lab
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this was from a review back in 2008 when
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we published a paper that showed that
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not just in yeast but in mammals
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chromatin modifiers move around during
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aging and that process can be
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accelerated by extreme cellular damage
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and what we used in this case was the
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double-stranded DNA break or dsb and we
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use an enzyme called people ppo1 to
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accelerate what looked like aging and I
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think you've heard probably me talk
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about this before so I'll go quickly but
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we've used this system to understand the
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process of Aging in mammals and and how
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to reverse it and just some some aspects
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I want to point out
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NAD is a cofactor co-substrate as you
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know so Twins and we found that up
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regulating cert one gene expression as
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well as NAD levels in the cell can slow
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down this reorganization of the
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epigenome and prevent loss of gene
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expression patterns and we did this in a
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mouse back in 2008 in in neurons in the
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brain but we've gone a long way since
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then
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come a long way oh we also I want to
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report a little bit about mib626 which
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is an NAD
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precursor uh it's a polymorph of
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nicotinamide mononucleotide that is GMP
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pure it's been in humans and I'll update
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you on that and how that seems to work
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and our goal there is to have a drug
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that will treat
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um not just aging but diseases of aging
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and they're about I think right now
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we've got five clinical trials up and
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running and I'll share some results of
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that
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um so what about the clocks uh we have a
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paper that's up online it's not yet
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published this is work by Patrick
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Griffin and Jen Lee in my lab two
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students who came up with the idea that
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you can greatly reduce the the cost of
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sequencing by uh transposon tagging DNA
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samples and we can pull 500 or more
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people or dogs or mice and we've built
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some and Patrick and Jenna built some
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really accurate clocks for Mouse tissues
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and in humans you can see down below
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wherever I can I give you directions to
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go follow up on this news
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um these are hot off the press human
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clocks from Patrick they're really great
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they've got um
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all the attributes that you'd want this
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is from human blood we have brought in
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over a thousand human samples from
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people a variety of Ages and you can see
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that the the uh our values are really
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great and uh the uh midday of 3.5 uses
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it's not bad for a first start uh and
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this is again just half the presses uh
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the mouse ones look really good too I
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would also phenotypic age clocks which
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we've published on if you're interested
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you could check that out
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uh how about slowing aging well we've
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worked on activators of sirtuins for a
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long time Resveratrol was the one back
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20 years ago we've developed some
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synthetic ones and some NAD precursors
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uh mib626 is as I mentioned an oral
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formulation of a polymorph of mh66 that
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stabilized crystalline and it's gone
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through a lot of safety studies over the
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last few years headed by this lab are
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shally basin's group at Brigham and
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Women's Hospital and David Livingston
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runs the group at Metro biotech which is
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a massachusetts-based company that's
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been making NAD precursors both
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synthetic and natural for the last
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decade
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uh and that and full disclosure this was
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spun out of my lab and others including
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Sheena Mai and Raj after
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uh how do you measure uh what the effect
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might be well one of the ways that
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Shelley's lab did it was to look at
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endurance and strength uh within an MRI
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and so this is uh an example of the
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machine that they built to insert the
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patients into the machine and measure
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their endurance strength and things like
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uh ATP NAD oxygenation
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um and some of the data that hasn't
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probably been published yet but we're
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starting to talk about it and this is
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their group's data not mine uh is that
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uh
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a number of things happen when you take
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uh 1 000 milligrams from roughly a month
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of this uh substance orally
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and you can see here an example of some
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of the data uh the repetitions the
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failure of that leg exercise uh
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significantly greater after taking
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mib636 this is similar or at least
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reminiscent to the mouse data that we
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published in 2018 on endurance in mice
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due to increased vascularization of the
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action on endothelial cells
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um and others nice bit of data I would
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admit it was a surprise a nice surprise
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is that Shelley's group showed that um
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lipids and cholesterol uh went in the
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right direction for improved Health uh
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as you can see here
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uh HDL was not affected which was also
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reassuring
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uh what about acceleration of Aging now
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we do this for two reasons one is to
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understand why we age because if we can
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cause it then we have some idea that
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we're on the right track but we also
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want to know if we can have a model of
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Aging that's much quicker because
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typical longevity experiment takes way
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too long and in organoids organoids are
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way too young when you build an organide
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from a stem cell an ipsc they're age
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zero which is not that useful and so
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we've used this system which you may
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know about it's close to getting
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8:52
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accepted we hope uh last last stages of
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this uh 12-year Journey
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8:59
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um actually I started this project with
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9:00
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Philip oberdorf when I was 39 so I've
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9:03
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aged a little uh this project is uh the
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combination of 20 labs around the world
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to see if we can displace chromatin
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modifiers in a way that mimics aging and
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we've done that and that's this work
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which we call the ice system and we have
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cell based systems and mouse systems to
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do that
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and we'll use it in a minute I'll show
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you later but we can drive aging
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forwards as far as we can tell
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epigenetically and the other Hallmarks
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of Aging accelerate as well for the most
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part
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the reversal this is a very hot topic as
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you all know we use uh typically we use
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a combination of three of the yamanaka
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factors rather than four we leave out
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cmic and we're using other methods
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chemicals now as well we published this
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um in 2020 so I'm not going to repeat
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that data but we did use it to
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rejuvenate neurons in mice and restore
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Vision in mice that had damaged or old
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retinas by targeting the neurons
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um and we find that we need all three of
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those factors O S and K shown down here
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in this Vector that we can control with
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Doxycycline Teton and Ted off system if
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you would like to try it this isn't uh
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injections in the eye which was in the
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the nature paper this one's the whole
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brain and we're using a variety of aavs
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now to infect different tissues and the
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whole body in the in efforts to not just
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accelerate aging but take those mice and
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wild type and reverse them and see what
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happens and this is work that I'm
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showing you from Xiao Tian uh primarily
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and jeun jeunyang and their goal is to
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reverse the age of the brain and see
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what happens
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and uh well this was the paper I just
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wanted to remind you and we had a lot of
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10:47
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help from people in the field some of
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10:48
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who are at this conference uh Morgan's
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10:50
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here uh that in was great help Steve
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10:53
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Horvath there's a long list you can see
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10:55
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here I couldn't have done any of this
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without their Labs as well what was
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amazing about this was that we showed
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that there's a repository of youthful
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information that can reset a cell's
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11:06
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epigenome we measure gene expression on
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the right you can see it's nicely reset
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proportionally to how this genes were
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expressed when they were young this is
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RNA and on the left I think even
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11:16
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just as impressive is the methylation
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patterns were largely restored as well
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um and the clock uh which uh Morgan and
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11:24
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Steve and that even helped us show uh
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was as well and one of the
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interesting things in this paper is we
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found that damage to neurons accelerates
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epigenetic aging as well so it's not
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just DNA cutting
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11:37
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um or time it's extreme cell stress like
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11:40
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a nerve Crush that can do it as well
|
11:43
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uh this has been commercialized or is
|
11:46
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being commercialized by life biosciences
|
11:48
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a boston-based company also spun out of
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11:50
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my lab you can check it out
|
11:53
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um and you'll probably get the website
|
11:54
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if you spell The Sciences correctly
|
11:57
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there's an e in there
|
11:59
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um Blackberry Sciences was started in
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12:01
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2017 uh Bruce Cassandra at Mass Eye and
|
12:04
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Ear has done a lot of the pre-clinical
|
12:06
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work and safety work we've now got a
|
12:08
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fair amount of data and we're now in
|
12:10
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non-human primates with a goal uh of
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12:12
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some time in uh the next whole to 24
|
12:15
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months of uh starting uh work towards an
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12:18
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IND and getting into humans if all goes
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12:20
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well and our goal is to reverse
|
12:22
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blindness in a variety of different
|
12:24
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disorders in humans
|
12:26
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but it is remarkable if you reverse the
|
12:28
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age of neurons in the retina you can
|
12:30
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restore vision and gene expression this
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12:32
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way
|
12:33
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um of course I'm standing on the back of
|
12:34
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some very big names uh in this field who
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12:37
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uh showed pointed the way uh this is new
|
12:41
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data unpublished I was allowed to share
|
12:43
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this from Bruce Cassandra's lab
|
12:45
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uh he and I are infecting not the
|
12:47
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neurons here but the retinal pigment and
|
12:49
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pythelium cells rpe and these give rise
|
12:52
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to uh the photoreceptors and these
|
12:54
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degrade over time particularly in
|
12:56
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macular degeneration and what Bruce has
|
12:58
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found is that he can actually restore
|
13:00
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the morphology and the function of these
|
13:02
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cells and restore eyesight back to a
|
13:04
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young State similar to what happens when
|
13:06
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you rejuvenate neurons in the eye as
|
13:08
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well
|
13:09
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the system uh in the lab now that we're
|
13:11
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doing is more human we have inducible
|
13:13
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human neurons uh where we can
|
13:16
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differentiate them both into flat
|
13:17
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cultures and three-dimensional and we do
|
13:20
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pro-aging with ice and reversal with osk
|
13:22
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typically okay I'll give you some
|
13:25
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examples of what we do
|
13:27
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and this is work mainly by Xiao and Jay
|
13:29
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in the lab we grow the nerves on these
|
13:31
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little culture dishes that can sense
|
13:33
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electrical signals uh when we have a
|
13:35
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control induction of no osk there's not
|
13:40
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very good electrical firing but when we
|
13:42
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rejuvenate them
|
13:44
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uh with uh the osk treatment uh just for
|
13:48
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a short amount of time this just takes a
|
13:50
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little over a week we see that there's a
|
13:54
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great induction of function
|
13:57
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um and it continues out the longer we go
|
13:59
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this is day 50 that you're seeing on the
|
14:01
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right so that's just neurons that's
|
14:03
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human neurons we've got Alzheimer's
|
14:04
|
patient neurons as well we can make
|
14:07
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these into little brain organoids you
|
14:09
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can see here that we can turn on all of
|
14:11
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the three yamanaka factors that we like
|
14:13
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in these organoids which have a similar
|
14:15
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brain structure to ours great models
|
14:19
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um for human aging we can age these
|
14:21
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forward and get them to take on
|
14:23
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inflammatory and senescent signatures
|
14:26
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which I think will be a useful model
|
14:28
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in terms of reversal uh we've done this
|
14:30
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in mice as well we can now deliver the
|
14:33
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osk system into various places in the
|
14:37
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brain whole brain or in this case on the
|
14:39
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right the excitatory neurons and in both
|
14:43
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cases we get an improvement in learning
|
14:45
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in these old mice which is what I think
|
14:49
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might have we might find out as a field
|
14:51
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is that diseases of old age particularly
|
14:53
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in the brain I'm thinking of like
|
14:55
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Alzheimer's if you make the the brain
|
14:57
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young then the diseases just go away
|
14:59
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because most of these diseases of Aging
|
15:01
|
are caused by edging I mean it's obvious
|
15:03
|
to a lot of us but to the rest of the
|
15:05
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world it's not
|
15:07
|
um so I want to thank the people who
|
15:09
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made this possible uh there's a large
|
15:11
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group The the clinical trial group is at
|
15:14
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Brigham and Women's Hospital there are
|
15:16
|
four other clinical trials that are
|
15:18
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ongoing there's one actually for
|
15:20
|
Alzheimer's disease that's starting to
|
15:21
|
recruit there's one um well I won't say
|
15:25
|
the whole lot but they're interesting
|
15:26
|
ones
|
15:28
|
um you can see that we've got
|
15:29
|
collaborators both for exercise
|
15:31
|
physiology the hormones and this is um
|
15:34
|
the mib636 group at Metro biotech
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15:38
|
uh here we have uh the people in my lab
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15:40
|
that helped or did major contributions I
|
15:43
|
want to point out the work of Jay who
|
15:45
|
did the Ice Mouse
|
15:47
|
um and matoshi I want to thank everyone
|
15:49
|
really but I want to focus on I
|
15:52
|
mentioned Xiao Jian
|
15:55
|
um for the osk work uh Yuan Chang Liu
|
15:58
|
who left the lab after he published
|
16:00
|
rightly so uh he's uh not listed but he
|
16:03
|
was the first author on that nature
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16:05
|
paper and I also want to point out Chris
|
16:07
|
who's doing reversal of senescence uh
|
16:10
|
Gerald who's working on a lot of the
|
16:13
|
mouse projects I could go on I won't uh
|
16:15
|
do that but I do want to thank Patrick
|
16:17
|
who I probably didn't mention enough he
|
16:19
|
was the one that came up with this idea
|
16:21
|
to do the time seek clock
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16:23
|
um so many collaborators it's impossible
|
16:25
|
to thank everybody these are the
|
16:26
|
highlights and I am so grateful for
|
16:29
|
their uh advice uh reagents and uh and
|
16:32
|
friendship over the years and the people
|
16:34
|
who uh supported the work financially
|
16:36
|
have been amazing too
|
16:38
|
um so I'll stop there and take any
|
16:39
|
questions thank you for having me
|
16:47
|
thank you so much David we have a
|
16:50
|
question here in the front from one of
|
16:52
|
our Inspire ambassadors
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16:54
|
they're the high school students that
|
16:56
|
are involved in the erdd organization
|
17:00
|
hi my name is Andrea
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17:02
|
um I was just wondering so you you said
|
17:05
|
that you used three of the Fourier
|
17:06
|
Monica factors when looking at eyesight
|
17:09
|
Rejuvenation have you tested any other
|
17:11
|
combinations of these yamanaka factors
|
17:15
|
we tested all combinations
|
17:18
|
um and
|
17:19
|
we needed three uh four uh worked as
|
17:23
|
well but we were concerned about the
|
17:26
|
loss of cellular identity so we left c
|
17:28
|
MC out and those three are necessary if
|
17:31
|
we just do one or two combinations uh it
|
17:34
|
did not work and if we gave them
|
17:36
|
individually in different viruses it
|
17:39
|
still didn't work so it seems like we
|
17:40
|
need to package them into the same AV
|
17:41
|
three of them put them in a polycystron
|
17:44
|
and get those in were there slight
|
17:46
|
changes maybe but the the big difference
|
17:49
|
was when when we put in all three now we
|
17:52
|
were trying for years different factors
|
17:53
|
so we tried nanog and that didn't work
|
17:55
|
very well it was pretty toxic
|
17:58
|
um and I think I mean it sounds like we
|
18:00
|
just tried something and it worked but
|
18:01
|
it was actually many years of one
|
18:03
|
Chang's efforts to find this particular
|
18:05
|
combination
|
18:08
|
great thank you so much uh it's quite
|
18:11
|
late here and we have we have a couple
|
18:13
|
questions Paul sorry it's late for me I
|
18:15
|
guess it's a couple of questions in the
|
18:17
|
back there
|
18:19
|
hi I was wondering if you also tested
|
18:21
|
the data that you showed in rpe cells in
|
18:24
|
pathological conditions either genetic
|
18:26
|
or chemical
|
18:29
|
oh uh yeah so it's been done in a uh a
|
18:32
|
mouse model of macular degeneration
|
18:37
|
um with the the iodide model if you're
|
18:39
|
familiar with it and it uh it works well
|
18:42
|
in that situation okay cool cool thanks
|
18:46
|
there's another one from Lawrence
|
18:48
|
hi David uh I don't know if you can see
|
18:50
|
me it's Lauren Zion from vitadel I am
|
18:53
|
wondering about the the time sake if you
|
18:55
|
can talk a bit about the implications
|
18:57
|
there uh how would it look like for the
|
19:00
|
consumer what does this enable what are
|
19:03
|
the uh downsides as well
|
19:07
|
uh yeah I don't know of any true
|
19:10
|
downsides uh
|
19:12
|
the cost is the main thing so what we do
|
19:14
|
is we we barcode each each person's
|
19:17
|
sample and we run them through the same
|
19:19
|
sequencing reaction there's also an
|
19:21
|
enrichment step that I didn't mention uh
|
19:23
|
and so it currently costs us
|
19:25
|
less than a you know basically a few
|
19:27
|
dollars less than five dollars per
|
19:29
|
sample and that's just on the bench here
|
19:30
|
not high throughput not optimized so we
|
19:33
|
think we can get the test down to really
|
19:35
|
low amounts and for the consumer that's
|
19:37
|
of course a benefit
|
19:40
|
um it this technology is licensed to a
|
19:42
|
company that next year will if all goes
|
19:45
|
well provide a product to Consumers
|
19:48
|
um to try this out but I wouldn't
|
19:50
|
release that until we've shown that it
|
19:52
|
works well we've done I think a couple
|
19:53
|
of thousand people so far we have 10 000
|
19:56
|
samples waiting to be tested and about
|
19:58
|
250 000 people on the waitlist so we
|
20:01
|
will use those numbers to aim to get a
|
20:03
|
really good clock and not put it out
|
20:04
|
there at all if it doesn't work I'm
|
20:07
|
assuming the costs doesn't include the
|
20:09
|
the logistics right so it would only
|
20:10
|
make sense in in batches with shipping
|
20:13
|
or something like that
|
20:14
|
yeah you know the shipping will be more
|
20:17
|
expensive than the cost of the test
|
20:18
|
eventually but yeah that that's just the
|
20:21
|
cost of the reagents and the the
|
20:23
|
sequencing yeah
|
20:25
|
great one more uh hello David uh so my
|
20:29
|
question is have you ever tried to uh
|
20:31
|
combine also fasting and color reduction
|
20:34
|
as a synergistic effect in your
|
20:36
|
reprogramming with the harmonica factors
|
20:38
|
uh we have not we have not we
|
20:42
|
have tried a few chemicals in
|
20:43
|
combination and we're still working on
|
20:45
|
that but no I think it's a good idea
|
20:48
|
um
|
20:49
|
it may be that some of the genes that I
|
20:52
|
talked about today could be involved
|
20:54
|
we'll try it
|
20:56
|
thank you
|
20:57
|
all right very cool thank you so much
|
20:59
|
David that was a fantastic and inspiring
|
21:02
|
talk we're looking forward
|
21:08
|
and we're living we're looking forward
|
21:10
|
to seeing you here next year so thank
|
21:13
|
you so much and everybody will
|
21:16
|
reconvene in 13 hours maybe we'll see
|
21:19
|
each other in the bar thank you so much
|
21:21
|
for today and see you later
|
21:29
|
[Applause]
|
21:33
|
[Music]
|