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[Music]

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[Applause]

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I think a core problem for many of us in

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origin of life science is figuring out

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what were the first entities capable of

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displaying key lifelike properties such

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as self propagation and adaptive

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evolution but are also simple enough

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that we can imagine them spontaneously

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arising in the absence of a prior

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adaptive process so there are many

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models out there but the one that we

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tend to rally behind is this notion that

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the first entities capable of self

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propagation were cooperating sets of

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chemical species that were spatially

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localized on a mineral surface and could

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grow laterally otto catalytically using

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fluxes of food and energy present in the

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environment and in addition to being a

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being able to self propagate it turns

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out that these slimes as we like to

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refer to them for surface limited

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metabolisms could also be evolvable if

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rare side reactions either alter or

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expand the existing catalytic core and

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add new reaction modules or cores as

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they're referred to and in the context

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of a natural environment where we have

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mineral surfaces bathed in for example

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sea water that's rich in organics and

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other compounds building up by various

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prebiotic synthesis pathways we imagine

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that the burial and continual exposure

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of new mineral surface would tend to

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enrich for systems that are better at

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getting from grain to grain or at least

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can self propagate faster so the goal of

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our research is to test the slime model

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for the origin of life by essentially

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recreating that little seascape I just

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showed you and asking if we can enrich

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for these systems using a protocol that

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we've developed called chemical

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ecosystem selection and the protocol is

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very simple it essentially involves

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combining prebiotic soups containing

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many dissolved organics and other

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compounds in the presence of mineral

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grains allowing for putative slimes to

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emerge and in this figure I've depicted

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several kinds of slimes that maybe

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differ in their colonizing abilities

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denoted by different colors and at the

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end of an incubation period we transfer

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a small subset of colonized grains to

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new reaction vessels containing fresh

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compounds so fresh food and fresh

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uncolonized mineral surface and we do

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this over many

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with the hopes that we would enrich for

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systems that are better at getting from

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grain to grain now the nice thing about

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this framework is that it's chemically

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agnostic meaning that you can test many

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different scenarios based on your

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preference but for the purposes of this

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talk I'm going to give you an example of

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a recipe we've been using extensively

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and have been getting some cool results

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with so the soup that we use is what we

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call an enriched miliary soup so it's

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actually a synthetic soup that we build

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that we make using off-the-shelf

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reagents and we make a number of

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additions to reflect for example what

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you might find in an ocean so salts

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transition metals and we also add

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potential sources of chemical energy and

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the one I'm going to highlight here is

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ATP but I'm also going to say and

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acknowledge that ATP is probably not a

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very pretty but eclis plausible

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phosphate source but we used it anyway

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so I'm going to show you that data as

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for the mineral we've tried a few but

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the one again I'm going to focus on is

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pyrite this iron sulfide mineral which

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we grind up into fine powders and then

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use in our experiments and we combine it

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with our soup in these little reaction

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vessels which are sealed serum vials we

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flush the headspace with nitrogen and

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then we also autoclave them at the end

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of each generation just to ensure

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sterility so that's the recipe and of

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course being able to deploy this this

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protocol implies that would be able to

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detect slimes if they were to emerge and

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the way we do that is by assuming that

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if slimes did emerge and change over

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time we'd be able to see that reflected

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and changes in a sealed reaction vessel

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either in the bulk solution or on the

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mineral surface so that's what we look

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at so here what we have on the y-axis is

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the amount of free phosphate we detect

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in our in our soup in our solutions at

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the end of an incubation period so if

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you remember I mentioned we add ATP so

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we can use simple colorimetric assays to

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measure the amount of free inorganic

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phosphate that's released from the

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hydrolysis of that ATP molecule and

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track how that changes over times as we

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keep selecting so what we see on the y

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axis are different lineages so the gray

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bars are ten independent lineages that

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were set up in the same way with the

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same ingredients but propagated

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independently of each other and that

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orange bar is the average of a control

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pool that's

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using the same reagents at the same time

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but only exposed to one history of

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transfers and what you can see from this

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plot hopefully pretty clearly is that as

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a number of generations increases we

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have a progressive decline in the amount

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of phosphate we detect and so we infer

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that to mean pretty simply that a

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history of transfer matters and then

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another thing that we that we measure is

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basically how much light is absorbed by

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that bulk solution at the end of a

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generation as a proxy for how many light

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absorbing compounds including some of

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the organics that we have in our

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solution remain after such incubations

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and what we find is that vials or

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reaction vessels that have a long

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history of transferring in this case 18

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have significantly lower absorbance than

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our control set and we and for that to

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mean that some of light absorbing

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compounds including the organics have

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been depleted from the solution in some

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way

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so this coincident reduction in both the

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amount of free phosphate and light

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absorbing compounds and organics and our

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bulk solution led us to inspect the

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surfaces of our pyrite grains to see if

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we could observe any systematic

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differences and we used electron

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microscopy to do this so here's a

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representative micrograph of grains

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taken from a control vial so again this

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was one that only had one transfer in

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its history and this is what we see when

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we look at experimental grain so this

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one had 18 rounds of transfer in its

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history and what you can see hopefully

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yes you can see them pretty clearly are

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these really distinctive fractal

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structures now to make a long story

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short about what our best guess as to

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what these things are is so we don't

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actually think these are the putative

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slime or the phosphate or organic

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consuming structures we think that there

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are salt crystals that are fouled with

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organics or growing on a layer of

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organics that are on the pyrite surface

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and that gives them this distinctive

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fractal or seaweed dendrite shape so

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what these results in mind we decided to

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repeat the experiment this time we

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carried it out for longer and we also

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took measurements at the end of each

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generation this time and this was what

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we saw in the free orthophosphate

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concentration so this time I've pulled

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it to reflect the average of our ten

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independent experimental lineages and

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you can see pretty clearly this

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pretty distinctive oscillatory pattern

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where we have an initial what we call a

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boom phase that is this linear decline

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in the amount of free phosphate and then

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a sudden reversal in that trend where we

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go back to our initial phosphate levels

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if not overshooting it a little bit so

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we have a few hypotheses to explain this

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behavior one is that that initial

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decline in free phosphate which is now a

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repeatable instance although you'll

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notice the timing is a little bit

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different this time and we think that

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that's because we use slightly different

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batches of our enriched miliary soup

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that might vary a little bit we think

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that that's reflective of the

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self-propagating state taking hold and

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growing on the mineral surface now the

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bust phase can be explained in a number

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of ways the one that we like to to

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consider is kind of an ecological

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perspective where you essentially have

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resource depletion this the system gets

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to stay where it consumes its resources

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and then collapses and the process

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starts all over again

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I also want to point out that we've

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looked at the fractal coverage at

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different points here and we have some

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qualitative arm wavy estimates of how

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they correlate with the phosphate

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pattern so turns out that we get the

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highest incidence of fractals when the

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phosphate it is also at its minimum so

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we think that this provides

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circumstantial evidence for what we

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think these critters are they're not

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actually the slimes they are a proxy for

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them essentially but one thing I mean is

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pretty clear from from this graph alone

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is that it seems like we've enriched for

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some kind of nonlinear chemical system

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which is good news and that I view long

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linearity as being a self a prerequisite

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for self propagation and evolution so in

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that front were good but I want to get

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at the source of this non-linearity a

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little bit more specifically and so what

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we did for that is we actually looked at

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what happened intra generationally so

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what happens when you set up your Miller

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Urey soup with your pyrite you autoclave

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it and then you track how these

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different proxy traits change over time

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and what we saw in the phosphate at

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least is this really again pronounced

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oscillatory pattern that looks to be

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damped

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and notably it also looks like there's a

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lot of potential for non-linearity even

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after our typical transfer period which

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is two days I'm know if I mentioned that

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yet

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we also looked at the total absorbance

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and how that changed over our time

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course and you can see that it has its

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own dynamics it doesn't necessarily

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completely overlap with what we see in

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the phosphate but it does seem to

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indicate what we would expect to see

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with the fractals so again this is very

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qualitative we don't really have a good

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way to quantify the extent of fractal

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coverage yet but what it looks like is

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that the fractal frequency increases

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over the first 72 hours which is

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coincident with this trough in the

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uv-vis data after which we no longer

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observe them and they never seem to come

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back as far as we can tell at least over

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the period we looked at so is it a slime

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well we're not sure yet but I do think

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that these results are really

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interesting and I think they kind of

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give us an idea of what kinds of

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chemistry and what kinds of dynamics we

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can expect to find using this protocol

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but what we would really need to

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convince ourselves that this has the

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potential to be a slime as we've defined

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it is to demonstrate that it can self

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propagate and although we think it's

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likely that there is a self propagating

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a stage we would really need to

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demonstrate that the non-linearity is

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actually confined to the mineral surface

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and that's part of ongoing work that

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also includes clarifying the chemistry

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of the slime I'm sure you are dying to

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know as much as I am what this thing

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looks like what it's made up of

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chemically and we just have no idea at

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this point and we also to that end want

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to test complementary conditions and do

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things like swap out ATP for a more

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realistic source of phosphate and

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finally I just want to end and comment

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on this question of is it evolvable I

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think that's ultimately what we want to

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know and what would make us really

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excited to find and so we're moving in

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that direction right now and we're

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basically looking to see if we can find

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changes in the rate of propagation over

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time in response to our protocol and

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that figure down there it's just

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hypothetical data just to show you that

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we have some notion of what that should

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look like even if we have kind of

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different modes of evolution and then

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finally I think a long-term goal or kind

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of idealistic one would be to create

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environment specific strains if you will

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that are adapted to slightly different

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conditions like pH temperature dissolved

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oxygen and have them be fitter or more

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efficient in their own respective

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environments so with that I just like to

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quickly acknowledge the long list of

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people that makes us possible and I

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actually do these experiments so of

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course my PI David Bohm our co-author

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and collaborator Jim Cleves our funding

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sources that come out of the NASA NSF

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ideas labs I'd like to thank our

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collaborators as part of that of course

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our amazing research group and then

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finally just a quick shout out to the

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artist of some of the illustrations that

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you saw in my talk that actually comes

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from a comic we co-wrote about how you

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can use science to solve seemingly

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intractable questions like the origin of

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life so thank you very much we have time

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for a couple of questions while our next

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speaker comes up here Yeah right there

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in the center so I'm very curious you

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have these fractals that are interacting

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with the the pyrite crystal correct and

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they go away with this you know during

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the cycling but I'm wondering if at the

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end of your experiment if you look very

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carefully at the pyrite crystals is

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there some evidence that that was there

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was some interaction that that was there

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are they leaving a record of themselves

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if you will so the short answer is we're

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not sure yet so we're just getting in

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the realm of in-depth surface analysis

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that's something that's been quite

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difficult to do using the grain format

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that we're using so we just don't know

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so it's possible that because we don't

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see them come back that it's not that

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they're gone

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per se but they might have diffused to

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the point where we don't actually see

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them kind of localized and these really

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cool fractal structures so that's one

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possibility but we just simply don't

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know at this point what was your control

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with with no pyrite or did you show that

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so in the selection experiments we have

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controls that are set up strategically

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alongside the generations we measure out

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so that they only have one generation in

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their history so we'll compare samples

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that have identical conditions except

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that will have say 20 generations of

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transfers versus just one but you

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haven't done it with no pyrite oh we've

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done the time series experiments with no

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pyrite and convinced ourselves that the

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at least the intergenerational dynamics

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we see require the presence of pyrite

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but we have not yet done selection

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experiments in the absence of pyrite and

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we plan on doing that alright one more

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over here so you saw fun dynamics with

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within a single vial but without

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transfers right so I was wondering is

379
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there anything do you know if there's

380
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anything different that happens if you

381
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transfer out of that vial at different

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time points like does it starve and stop

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being able to propagate or does it

384
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propagate differently if you pull it out

385
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at different moments like that might

386
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tell you if it's depending on non

387
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equilibrium chemistry yes that's a great

388
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question the only real data that I have

389
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to that from experiments like the ones

390
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you've just suggested are very

391
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preliminary we did them just once

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actually in parallel with the time

393
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course I just showed you and we found

394
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basically did a one-day transfer and a

395
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two-day transfer and we kept those

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lineages separately so basically one had

397
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a two-day generation time the other had

398
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a 1-day generation time and we did find

399
00:14:43,950 --> 00:14:41,890
that the boom-bust patterning that you

400
00:14:45,480 --> 00:14:43,960
got in those two or it was quite

401
00:14:46,920 --> 00:14:45,490
different the timing was quite different

402
00:14:50,300 --> 00:14:46,930
which suggests that when you do that

403
00:14:52,260 --> 00:14:50,310
initial transfer where you are in that

404
00:14:54,150 --> 00:14:52,270
oscillation that you get

405
00:14:57,030 --> 00:14:54,160
intergenerationally matters but that's

406
00:14:58,860 --> 00:14:57,040
all very preliminary and we are going to

407
00:15:00,860 --> 00:14:58,870
do experiments much more extensively and

408
00:15:03,990 --> 00:15:00,870
try to use that intergenerational

409
00:15:06,630 --> 00:15:04,000
dynamic pattern to strategically select

410
00:15:07,830 --> 00:15:06,640
different generation times but yeah

411
00:15:09,920 --> 00:15:07,840
that's a great question we're thinking

412
00:15:12,330 --> 00:15:09,930
along those lines very much so okay and

413
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one more quick question in the center a

414
00:15:17,640 --> 00:15:15,880
quick question it seems to me that one

415
00:15:19,380 --> 00:15:17,650
of the sort of important assumptions

416
00:15:22,350 --> 00:15:19,390
that goes into the slime model is you

417
00:15:24,090 --> 00:15:22,360
have a relatively slow chaos for these

418
00:15:25,770 --> 00:15:24,100
like organics on its surfaces and it

419
00:15:26,940 --> 00:15:25,780
seems like that's actually a pretty like

420
00:15:28,560 --> 00:15:26,950
at least compared to what you've done

421
00:15:30,360 --> 00:15:28,570
like a pretty simple experiment you

422
00:15:31,980 --> 00:15:30,370
could do to sort of limit or constrain

423
00:15:32,620 --> 00:15:31,990
what types of species you're interested

424
00:15:36,670 --> 00:15:32,630
in

425
00:15:39,040 --> 00:15:36,680
yeah yes and I am by note I'm not an

426
00:15:42,340 --> 00:15:39,050
expert in nonlinear dynamics so I am not

427
00:15:43,960 --> 00:15:42,350
I don't know what to say it your to your

428
00:15:45,249 --> 00:15:43,970
point about yes have you guys tried to

429
00:15:47,379 --> 00:15:45,259
do in the experiment you take a single

430
00:15:49,720 --> 00:15:47,389
component add it to pyrite and just see

431
00:15:52,030 --> 00:15:49,730
what's how what's the kinetics of it

432
00:15:54,100 --> 00:15:52,040
sticking on to pyrite we have not but we

433
00:15:56,230 --> 00:15:54,110
plan on doing kind of reduction

434
00:15:57,819 --> 00:15:56,240
experiments where we leave out whole

435
00:15:59,439 --> 00:15:57,829
groups of compounds and maybe I don't