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Hey everyone, it’s Eugene.

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Welcome to another episode of Forensics
Talks.

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This is going to be episode 97.

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We're getting up.

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Gonna hit that 100 mark soon.

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So today my guest is Dr.

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Sarah Williams
and she's a research associate professor

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in forensic science in Virginia
Commonwealth University, teaching

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several of the forensic biology
track, upper level and graduate courses.

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She started her career in forensic

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molecular biology when she was appointed
to a forensic biology fellowship

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with the Virginia Institute
of Forensic Science and Medicine in 2002.

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She then worked as a forensic scientist

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for the Virginia Department
of Forensic Science until 2007,

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where she performed serological
and ACR DNA analysis on hundreds of cases.

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And since her time at the Virginia
Department of Forensic Science,

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she's worked as a contractor in Iraq,
where she mentored the chemistry and DNA

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sections of the forensic laboratory
and conducted

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technical reviews of cases for defense
purposes.

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Her research interests include body fluid
identification, using both

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standard and novel molecular methods,
including Raman spectroscopy,

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micro-RNA, and many analyzes nanopore
sensing of DNA fragments,

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as well as optimization of DNA extraction
and quantitation methods.

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Now I met Sarah in Saudi Arabia

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during the recent or,
you know, some of my guests here

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came from that from that conference
that was over in Riyadh.

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And I watched her talk about body fluids.

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And it didn't take me long
to realize, hey,

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I think I'm going to have to get around
here to talk about this, too.

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She was very well versed and
pretty passionate about her stuff.

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So let me bring her on in here.

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There she is.

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Hey, Sarah.

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Hey, Jean. Thanks for inviting me.

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Yeah, thank you so much.

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I really appreciate you taking the time
and getting to ask you

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some questions about your work,
which I think would be pretty interesting.

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Yeah.

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I mean, I didn't get a lot to talk to you
in Riyadh, but

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I did see your presentation, and,
yeah, I'm.

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I'm pretty interested
in what you're doing, so.

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But the first thing that I always ask

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is when asked about your background,
kind of lead up to where you are today.

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So, I want to know about little Sarah
when she was running around

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being mischievous and stuff like that.

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So were you always like the science
nerdy kid or were you not like something

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totally different?

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I mean, I was a farm kid,
so, I spent a lot of time,

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like running around on the farm.

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I had horses,
so that was a big thing for me.

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But actually, like I remember

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when I was 12, I told my mom
I wanted to be a geneticist and here I am.

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Wow. Okay.

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So, you knew you were focused
and from when you're.

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Yeah, which is great. Fantastic.

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Now, did you like going through
high school?

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University?

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I mean, university to molecular biology,
right?

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Yeah. So that was a memory.

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And actually, I didn't know
about forensic science at all.

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So, it's really kind of interesting that I,
I accidentally landed in forensic

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science and I love it, but
I started working right out of undergrad

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at the medical College here
at Virginia Commonwealth University in

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and Immunology and Biochemistry laboratory

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and biomedical research is a long term
game.

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It's like ten years and you may
or may not make an impact on the

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the condition or disease
that you're actually doing research on.

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And so, I saw that pretty quickly,
like after doing two years of research,

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that this was pretty frustrating
and I wanted quicker results.

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And so, I started looking around
for a graduate program that where

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I could apply my love of molecular biology
but also get faster results.

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And I stumbled across forensic science.

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Now, like this is 2001, so

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this is a long time ago,
but like I had never seen a CSI.

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I didn't know anything about forensics.

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It wasn't as well publicized as it is now.

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And so, I was like, you know, I'll just
give this a shot and the rest is history.

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What now?

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Was it a specific person,

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like a teacher or like was it somebody
that said friends or just the shows on TV?

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You're like, hey, I want to get into this.

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No, I never watched the show.

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I literally found it on this news website
and said, Oh, that's kind of interesting.

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And then I did my own research.

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But no, I never saw a TV show.

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I didn't talk to anybody.

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I just kind of randomly applied
its strangest way to do it.

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So, you did you did the fellowship right
at the Virginia Institute

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of Forensic Science and Medicine.
So, what was that like?

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So that was really interesting things.

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So back then,

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the Institute of Forensic Science
and Medicine was kind of the training

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and the training institute

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to become a forensic scientist at Virginia
Department of Forensic Science.

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And for a while there, Patricia Cornwell,
you know, the author of the books,

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she was funding the trainees’ salaries.

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And so, we weren't funded
through the state.

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She actually funded my training.

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And I have all of her books signed
because I got to meet her

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and work with her on a couple of things.

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So that was a yearlong training institute.

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And after that we were hired on to the
Virginia Department of Forensic Science.

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Okay.

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And so, yeah, and I was going to
I was going to lead into your role there.

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So, when you were you doing
the same thing

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all throughout the Department
of Forensic Science

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or did your role change
while you were there?

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No, it was pretty much the same
for those four years.

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I was a pretty junior forensic scientist

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when I started, and there were
a lot of people more senior to me.

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So, I didn't take on any leadership
roles there.

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I just primarily worked cases

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and helped out with like

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creating some literature reviews
for the scientists

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every month
so that they were reading papers more.

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I really came from this research
science background and

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I really still felt passionate about that,

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even though I was a practicing
forensic science artist.

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And that's kind of what led to me
being interested in moving on to VCU.

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Okay, nice.

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And so, your what if you had to like,

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sometimes we get students and other people
that are like watching this.

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They're like, hey, you know, this

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this sounds like an interesting career
or something like that.

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But how would you describe,

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like the roles and responsibility

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of somebody that gets into,
you know, biology or molecular biology

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as a forensic scientist?

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Yeah.

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So, most I mean, as I'm sure
many of your interviewers

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have, interviewees have said, you know,
this is nothing like CSI, right?

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So, and the biologists in most crime
laboratories are not going out

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to crime scenes
where receiving the evidence.

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And then we're working it
in the laboratory setting and

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and then we're moving forward into
the analysis and testimony if necessary.

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So, you have to be very comfortable
and happy working in a lab.

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And

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honestly, like I said,
I have a lot of friends

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who are, let's say, detectives
or investigators or FBI agents.

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And, you know, they have a lot
of interactions with victims and suspects.

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And, you know, when you're
working in the lab, it's certainly

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a usually pretty terrible crime
as it's making it to the DNA unit,

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sexual assaults and homicides
and kidnappings and all of that.

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But most of the time, it's pretty easy

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to kind of treat it as evidence and
be unbiased and not really have a like,

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emotional connection to the case
so that you can work it in that

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unbiased manner that you need to be
because you're not interacting with them.

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So that makes it more,
you know, more science

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and less kind of bias,
which is really important to me.

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And I try to make sure
that my students understand that as well.

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Okay. What about

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report writing, testimony, stuff
like that?

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What,
what about that part of the job?

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Yeah.

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So, I was really intimidated by it at first
and I'm not a super extrovert.

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I'm pretty introverted.

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So like, for a while there,
even getting in front of my students

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and lecturing for the first
couple of years was pretty big for me.

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So, testimony was challenging
for me, much more so than the science

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and the way I kind of was evolved
as I got some experience was, you know,

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you really have to treat it
like a game, right?

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Like the defense attorney
and the prosecuting attorney each

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have their own agendas.

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And then you have your agenda,
which is to present the science

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in an unbiased manner and present
your findings as accurately as possible.

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And you have to treat all of this
as a game

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and not a personal attack
like it's never personal, right?

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Yeah, No, that's very, very true.

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That came up actually at the photography
symposium last week.

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We had a talk just on expert witness
testimony and, you know,

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your duties and roles and the speaker
there, Gail Spring, thank you very much.

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But yeah, he talked about some things
where, you know, they get pressured

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on the stand and you know, you get
they get picked on and stuff like that.

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So, it's an uncomfortable situation
for many people,

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but some people actually enjoy it
after a while.

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They've been doing it for a long time.
They get used to it.

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But yeah, that's a very good point.

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So, for people who are listening
or are students who are listening,

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it's,
you know, being on the stand can be put

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you under a significant
amount of pressure for sure.

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I wanted to ask you about the

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so, while you were at the Department
of Forensic Science, you said you

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or I read that you went to Iraq

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and so, you went overseas
and you were helping with like

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were you hoping to set up a laboratory,
like doing training?

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Like what kinds of things
were you doing there?

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What was you.

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Yeah, so I was already at these
you at that point.

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And so, I took kind
of a partial leave of absence.

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I still taught one
class and I went back and forth

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and I was, I was a contractor
with ideal innovations at the time.

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And so, I would go for four weeks and help
and then I would come home for four weeks

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and teach my class.
And I did that for eight months.

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And so

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this was a Department of Defense contract.

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So, Naito had

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put together these forensic laboratories,

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these in the different regions of Iraq,
and equipped them with equipment.

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And so, my role, along with about six
or seven

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other contractors, was to help
these laboratories

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get online, help them develop protocols
that worked in their system,

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and then train them
to the scientific standards

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so that when we left,
they could go forward and,

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you know, run these laboratories
on their own and have good,

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reliable scientific analysis.

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And what was your experience like?

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They're like were they fairly well set up

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in terms of their lab and equipment
and that sort of thing?

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Yeah.

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So, the equipment was exactly
what we were using over here in the U.S.

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at the time.

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Some of it even state of the art,
not quite here in the U.S. yet.

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So that was really great to see.

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And they were very friendly and trainable

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and eager to get going on
working cases in their regions.

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It was a little challenging.

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I was about 28 years old at the time,
and so being a female

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young scientist
trying to talk to these four-star generals

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because their
leadership was military based and,

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you know, getting across through
a translator what was needed and,

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you know, it couldn't be 99.4% pure argon.

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It had to be 99.997% pure,
and it had to come through Turkey.

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And there were a lot of like logistical
challenges that we had to work through.

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And I learned a lot like it really
it really was a great experience.

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On a related note,
I didn't ask you, but how did you find the

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the conference
in Riyadh at Ninth University?

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Yeah, I loved it.

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So, I went with my colleague and department
chair, Tracy Dawson Green.

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We came together and we really didn't know

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what to expect
and we were really pleasantly surprised.

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There was a lot of good science
being discussed

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and everybody was really friendly.

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The laboratory that we got to tour on, on

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the ground was state of the art
beautiful laboratory.

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I know you got to see it too.

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So, it was amazing.

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Yeah, it was.
I thought it was really, really well done.

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I that was
my first time over that part of the world.

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So, I don't know how to say this,
but they, they did.

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They just went out of their way to make
everybody feels comfortable, I think.

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And welcome. Yeah.

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Yeah.

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It was classic Middle East hospitality.

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Yeah. It was very, very well done. Yeah.

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So, let's talk about your teaching
and some of your research and stuff.

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And I think I always I have to
tell everybody this is not my area.

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So, I do my best
to ask intelligent questions,

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but it's just not my area of expertise.

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So, I'm going to ask them

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some pretty simple questions of you
and hopefully you can help me out.

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But let's talk about when you did

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the presentation in Riyadh,

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talks about body fluids and remember
you are saying that there were five.

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So, tell me about the five. Was it
maybe I'm wrong?

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It was there four or five or more,
but well, there's eight or ten or

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however, many, but like when we think
about forensic evidence, we have,

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of course, our two most common right,
which is blood and semen.

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And at least those are the two
that we're looking for, the ones that

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we probably see even more often are
saliva and vaginal secretions.

00;14;03;26 - 00;14;06;16
And so
those would be kind of your four big ones.

00;14;06;16 - 00;14;09;17
And then menstrual secretions
is also really important

00;14;09;17 - 00;14;13;13
in some cases, for discriminating like,
is this blood because of trauma

00;14;13;21 - 00;14;17;05
or is this
because of a normal menstrual cycle?

00;14;17;08 - 00;14;19;14
And then, of course, you have urine,

00;14;19;14 - 00;14;24;20
feces, perspiration,
and then you can get into all of the

00;14;24;23 - 00;14;28;14
the other kind of biomedical body
fluids that

00;14;28;14 - 00;14;32;22
we sometimes see at a crime lab,
like cerebrospinal fluid,

00;14;32;24 - 00;14;35;24
amniotic fluid, breast milk, tears,

00;14;36;00 - 00;14;38;26
mucus, vomit, that kind of thing.

00;14;38;26 - 00;14;40;02
Okay. So, there's a lot.

00;14;40;02 - 00;14;40;23
Yeah, there is.

00;14;40;23 - 00;14;42;11
So, I wasn't even thinking about that.

00;14;42;11 - 00;14;44;04
Yeah, but there's a whole bunch of others

00;14;44;04 - 00;14;46;11
that I wasn't thinking about,
but I was thinking about the ones,

00;14;46;11 - 00;14;50;10
some of the major ones
that you had mentioned. So

00;14;50;12 - 00;14;53;02
if you had to sort of summarize,
because I'm going to ask you something

00;14;53;02 - 00;14;55;21
specific to your research,
but if it if you had to sort of

00;14;55;21 - 00;14;59;12
summarize
the direction that you're moving in

00;14;59;14 - 00;15;01;05
with body fluids
and that sort of thing, how

00;15;01;05 - 00;15;04;26
would you summarize your area of research
and where you're moving towards?

00;15;04;28 - 00;15;07;13
So, I'm interested in improving

00;15;07;13 - 00;15;11;29
the detection and our confidence
in body fluid identification.

00;15;11;29 - 00;15;16;04
And I've kind of gotten away
from the word identification

00;15;16;06 - 00;15;20;20
and moved more towards classification
because, you know,

00;15;20;20 - 00;15;24;10
any time we're making a body
fluid identification, it's

00;15;24;17 - 00;15;29;12
we want to have some level of,
you know, numerical confidence behind it.

00;15;29;12 - 00;15;33;12
So, we're this body fluid is blood
with a 95%

00;15;33;12 - 00;15;36;21
probability, like we just like
any other forensic field.

00;15;36;21 - 00;15;40;25
We want to be able to ascribe
a quantitative confidence in it.

00;15;40;27 - 00;15;45;10
So, I've kind of moved the classification
instead of just straight identification,

00;15;45;10 - 00;15;48;09
and I'm trying to drag along
along with me.

00;15;48;09 - 00;15;50;18
And there are plenty of people
who agree. So.

00;15;50;18 - 00;15;51;15
Right, right. Okay.

00;15;51;15 - 00;15;53;14
So, trying to make things more objective
right there.

00;15;53;14 - 00;15;54;17
Yeah, absolutely.

00;15;54;17 - 00;15;56;08
Yeah, that makes a lot of sense.

00;15;56;08 - 00;15;59;07
So, let's talk about the one and again,
you have a number of papers.

00;15;59;07 - 00;16;01;20
We'll see how we get through them all.

00;16;01;20 - 00;16;04;20
But there's one on the romance

00;16;04;26 - 00;16;07;29
spectroscopy of blood samples
for forensic applications.

00;16;07;29 - 00;16;08;14
That one.

00;16;08;14 - 00;16;13;08
Okay, So, so talk to me
about just summarizing Raman spectroscopy

00;16;13;08 - 00;16;17;03
in principle, you know, trying to get
some scattered light and stuff.

00;16;17;03 - 00;16;18;26
How does it work?

00;16;18;28 - 00;16;19;26
Oh, you're killing me.

00;16;19;26 - 00;16;22;26
So, I'm biologist, not a physicist.

00;16;22;29 - 00;16;23;21
Okay.

00;16;23;21 - 00;16;28;01
I leaned really heavily
on my collaborators for

00;16;28;04 - 00;16;32;00
many projects
and to be absolutely honest with you,

00;16;32;00 - 00;16;35;05
the only reason I didn't go to medical
school was because I was afraid of taking

00;16;35;05 - 00;16;36;23
physics, so. Oh, really?

00;16;36;23 - 00;16;41;05
What I can tell you
is that when you do raman spectroscopy,

00;16;41;05 - 00;16;44;05
you're looking at in the inelastic
scattering

00;16;44;11 - 00;16;49;14
from specific compound sounds
that are abundant in that body fluid.

00;16;49;14 - 00;16;53;05
And so, we can see a particular signature
that's different

00;16;53;07 - 00;16;58;10
in blood versus
saliva versus urine.

00;16;58;13 - 00;17;01;06
And there this is an older project.

00;17;01;06 - 00;17;04;03
So, we actually haven't worked on this
in about ten years.

00;17;04;03 - 00;17;11;28
But when we were working on it,
there was another tie up in New York,

00;17;12;00 - 00;17;16;03
Eagle redness, and he continues
to work on Raman spectroscopy.

00;17;16;03 - 00;17;20;12
And I think
at this point he's developed an on site

00;17;20;14 - 00;17;21;16
library

00;17;21;16 - 00;17;25;25
for use of Raman at the crime scene
for body fluid ID and there's

00;17;25;25 - 00;17;30;11
some really interesting applications
so, like you can identify body fluids,

00;17;30;11 - 00;17;35;09
but you can also potentially identify
or classify the gender of the person.

00;17;35;11 - 00;17;39;02
Now, you can distinguish species.

00;17;39;05 - 00;17;41;11
So, with Raman

00;17;41;11 - 00;17;45;21
and the kind of the hurdle that we hit
about ten years ago

00;17;45;23 - 00;17;49;22
here at VCU was that fluorescence actually

00;17;49;25 - 00;17;53;02
is overwhelmingly stronger

00;17;53;04 - 00;17;56;23
and overloads the spectrum.

00;17;56;25 - 00;18;00;06
And everybody thought
except for blood fluorescence, right.

00;18;00;09 - 00;18;03;16
So, the lives of fluorescence,
urine, semen, all the big ones

00;18;03;16 - 00;18;08;10
that we're interested in the blood doesn't
like it actually quenches fluorescence.

00;18;08;10 - 00;18;12;10
So, we limited our evaluation to blood.

00;18;12;10 - 00;18;13;14
But Dr.

00;18;13;14 - 00;18;17;27
LUDDEN have done a lot of work
on eliminating or subtracting out

00;18;17;27 - 00;18;21;04
that fluorescence
and having some really great

00;18;21;04 - 00;18;24;10
findings
using Raman for the body fluids as well.

00;18;24;12 - 00;18;26;29
So, you mentioned
and of course, with our technology,

00;18;26;29 - 00;18;29;13
it seems to be getting smaller and better,
whatever.

00;18;29;13 - 00;18;33;12
So like, how big of a unit will
I mean, if somebody can just buy a unit

00;18;33;12 - 00;18;34;20
to bring it to a crime scene, like,

00;18;34;20 - 00;18;39;20
do you know, more or less like how big
these pieces of equipment have

00;18;39;23 - 00;18;41;13
been a
couple of years since I've seen them,

00;18;41;13 - 00;18;46;11
but maybe about 12 inches by eight inches

00;18;46;11 - 00;18;50;26
and about two or three inches thick
and maybe like ten or £15.

00;18;50;28 - 00;18;55;24
They're not tiny, but they're not
they're definitely portable.

00;18;55;26 - 00;18;57;10
Right? Right. Oh, it's pretty cool.

00;18;57;10 - 00;19;03;01
And so, you mentioned,
like you can even tell the gender,

00;19;03;03 - 00;19;06;03
you know, so depending on
so, if you have a sample of blood

00;19;06;06 - 00;19;11;02
and you get back some kind of a reading,
how unique is the data that comes back?

00;19;11;02 - 00;19;13;23
Like, is it is it even that?
Can you tell even more?

00;19;13;23 - 00;19;15;24
I mean, you mentioned
you want to just classify it,

00;19;15;24 - 00;19;20;06
but is there even more information there
that can be more information

00;19;20;06 - 00;19;24;00
you can pull or say more about the
there's a whole lot of information.

00;19;24;00 - 00;19;28;09
So, some of his papers
talk about distinguishing gender.

00;19;28;11 - 00;19;33;14
Some of them even suggested
distinguishing ethnicity,

00;19;33;16 - 00;19;35;02
at least in our hands.

00;19;35;02 - 00;19;37;25
We definitely could tell
when we were looking at saliva,

00;19;37;25 - 00;19;41;14
if somebody had had had orange juice
that morning or not.

00;19;41;16 - 00;19;44;28
It's it really the spectra.

00;19;45;05 - 00;19;48;23
There are always very specific

00;19;48;25 - 00;19;52;01
wavelengths that we're looking for
for that particular body fluid.

00;19;52;01 - 00;19;55;01
But you can have some relative uniqueness

00;19;55;02 - 00;19;58;09
between those unique spectra

00;19;58;09 - 00;20;01;09
that we're looking at for that body fluid.

00;20;01;14 - 00;20;04;08
Okay, So this this
this person that you mentioned

00;20;04;08 - 00;20;07;17
is he's looking to develop this technique
further than you.

00;20;07;19 - 00;20;07;27
Yeah.

00;20;07;27 - 00;20;13;00
I mean, it's pretty well developed
and I funded it for 8 to 10 years

00;20;13;00 - 00;20;16;12
and he's got a pattern and I think he's

00;20;16;14 - 00;20;19;12
working with Raman

00;20;19;12 - 00;20;22;01
manufacturers to commercialize it.

00;20;22;01 - 00;20;22;18
Okay. Okay.

00;20;22;18 - 00;20;27;07
So, it's still not maybe
like adopted heavily in forensics.

00;20;27;09 - 00;20;29;06
Okay. Okay. Got it.

00;20;29;06 - 00;20;31;09
So let me ask you about another one.

00;20;31;09 - 00;20;35;02
You have some stuff that you're doing
with micro-RNA

00;20;35;05 - 00;20;39;03
and classifying
different types of body fluids.

00;20;39;03 - 00;20;40;15
So, there was a paper that you did there.

00;20;40;15 - 00;20;42;28
So can you tell me about that one,
what you did there?

00;20;42;28 - 00;20;43;14
Yeah.

00;20;43;14 - 00;20;45;20
So that's been kind of our bread

00;20;45;20 - 00;20;48;15
and butter in my research lab
for about ten years.

00;20;48;15 - 00;20;52;25
I actually got my PhD
on prostate cancer in microRNAs

00;20;52;28 - 00;20;54;28
and then I moved into the body fluid work.

00;20;54;28 - 00;21;02;04
So, microRNAs
are these really small 19 to 22 nucleotide

00;21;02;07 - 00;21;03;29
RNAs and they're

00;21;03;29 - 00;21;08;24
very stable and they're
they're not susceptible to degradation

00;21;08;24 - 00;21;13;16
at the level of regular messenger
RNA or total RNA and even DNA.

00;21;13;16 - 00;21;15;01
They're very stable.

00;21;15;01 - 00;21;18;00
And part of that is because they're always

00;21;18;08 - 00;21;20;26
they always have a body,
so, they're either encapsulated

00;21;20;26 - 00;21;25;26
in a protein complex
or they're enclosed in a lipid vesicle.

00;21;25;29 - 00;21;29;04
And so that gives some protection to them.

00;21;29;07 - 00;21;32;16
So, we initially evaluated microRNAs

00;21;32;16 - 00;21;38;08
in RNA extracts
and using a panel of 6 to 8 microRNAs.

00;21;38;08 - 00;21;43;05
Depending on the study,
we were able to classify the body fluid,

00;21;43;07 - 00;21;46;24
all eight
body fluids that we were interested in,

00;21;46;26 - 00;21;51;03
with 90 to 95% accuracy
depending on the body fluids.

00;21;51;06 - 00;21;51;20
Okay.

00;21;51;20 - 00;21;55;05
But then we decided
to move into DNA extracts.

00;21;55;05 - 00;22;01;01
So, when you have a piece of evidence,
right, you have a blood swab

00;22;01;04 - 00;22;04;28
and you're going to extract
your extracting DNA.

00;22;04;29 - 00;22;09;11
And when you extract DNA,
you usually get rid of all of the RNA.

00;22;09;13 - 00;22;13;17
So, there was another small report
in the literature where they demonstrated

00;22;13;17 - 00;22;17;08
that microRNAs were also in DNA extracts.

00;22;17;15 - 00;22;20;21
And so, we evaluated that, and we found that
that was the case.

00;22;20;22 - 00;22;27;05
And so, we expanded our project
to use microRNAs that were taken from

00;22;27;05 - 00;22;32;19
DNA extracts and see if we could classify
body fluids to the same accuracy.

00;22;32;19 - 00;22;33;20
And we could.

00;22;33;20 - 00;22;38;02
So, we did a big study
where we looked at about 600 samples

00;22;38;05 - 00;22;41;09
and we were able
to classify all of the body fluids that

00;22;41;09 - 00;22;42;04
we were interested in.

00;22;42;04 - 00;22;47;15
It was about six
at that point with 92% accuracy.

00;22;47;17 - 00;22;48;02
Okay.

00;22;48;02 - 00;22;54;11
So that's really important because you
don't have to do a separate extraction.

00;22;54;13 - 00;22;57;06
RNA extractions are expensive.

00;22;57;06 - 00;22;59;16
They take more time than DNA extractions.

00;22;59;16 - 00;23;04;08
They're not as easily automatable
and you have less sample consumption.

00;23;04;11 - 00;23;09;01
And so, if you already have a DNA extract
because you're doing human identity,

00;23;09;03 - 00;23;14;18
it would be easy for you to also do body
fluid identification using that extract.

00;23;14;20 - 00;23;15;06
Okay.

00;23;15;06 - 00;23;19;14
Now, when you say, you know,
it's like 92% or 95% accurate, whatever.

00;23;19;17 - 00;23;22;13
So, what is the complication
with the other 5%?

00;23;22;13 - 00;23;25;08
8% like what?
What's happening there. Yeah.

00;23;25;08 - 00;23;28;12
So sometimes they misclassify
as other body fluids

00;23;28;12 - 00;23;32;12
like we don't have that problem
with regular venous blood

00;23;32;14 - 00;23;35;28
where some of the complications
are in the female intimate.

00;23;35;29 - 00;23;39;14
So vaginal secretions
will commonly misclassify

00;23;39;14 - 00;23;42;20
as menstrual secretions and vice versa.

00;23;42;23 - 00;23;46;14
Sometimes female urine
will misclassify as secretions,

00;23;46;14 - 00;23;50;07
and they're all coming
from the same general area, right?

00;23;50;09 - 00;23;53;27
And so that's not surprising.

00;23;54;00 - 00;23;56;10
Sometimes semen and male

00;23;56;10 - 00;23;59;16
urine will classify similarly.

00;23;59;19 - 00;24;02;16
And so those related fluids

00;24;02;16 - 00;24;05;24
kind of reduce the overall classification
rate.

00;24;05;26 - 00;24;06;15
Okay.

00;24;06;15 - 00;24;11;23
Now what about the factors like the
the age of the sample?

00;24;11;23 - 00;24;14;03
Like if it's something
that's been sitting for,

00;24;14;03 - 00;24;16;22
you know, two weeks in the heat
or something like that

00;24;16;22 - 00;24;19;22
versus something that's fresh,
that does the age make a difference?

00;24;19;26 - 00;24;21;06
It depends on the body fluid.

00;24;21;06 - 00;24;22;12
So that's a great question.

00;24;22;12 - 00;24;26;08
And whether it depends on the body fluid,
whether we're looking at RNA extracts

00;24;26;08 - 00;24;31;11
or DNA extracts, it's kind of consistent
across the type of extraction

00;24;31;14 - 00;24;35;15
that blood and urine
tend to be quite stable

00;24;35;17 - 00;24;40;16
and we can trash them
with bleach or acetic acid.

00;24;40;16 - 00;24;44;24
We can stick them in a 95 degree
incubator.

00;24;44;27 - 00;24;49;14
We can we use the FBI's
environmental chamber record

00;24;49;17 - 00;24;50;26
week period,

00;24;50;26 - 00;24;54;17
mimicking a Virginia summer day.

00;24;54;20 - 00;24;56;13
And blood and urine

00;24;56;13 - 00;25;00;07
were consistently robust, right?

00;25;00;09 - 00;25;05;03
Semen and saliva tended to fail

00;25;05;06 - 00;25;09;23
with in terms of
they wouldn't classify correctly.

00;25;09;26 - 00;25;11;04
But not only would they

00;25;11;04 - 00;25;15;09
not classify correctly,
we just wouldn't detect the microRNAs.

00;25;15;11 - 00;25;17;26
So, at the same time, you're not detecting

00;25;17;26 - 00;25;21;16
messenger RNA
and sometimes the DNA was trashed as well.

00;25;21;18 - 00;25;25;18
So, we're kind of on par there in somebody

00;25;25;18 - 00;25;28;29
fluids with the other body fluid

00;25;29;01 - 00;25;32;12
identification techniques.

00;25;32;15 - 00;25;35;14
But blood and urine were quite robust.

00;25;35;14 - 00;25;35;29
Okay.

00;25;35;29 - 00;25;39;05
Now, what happens if in a situation
where there's like a mix?

00;25;39;05 - 00;25;42;24
So, you got,
I don't know, blood with vaginal fluid

00;25;42;24 - 00;25;46;06
or something like that, Does
it does it still work?

00;25;46;08 - 00;25;50;04
So that is the challenge with microRNAs

00;25;50;07 - 00;25;54;16
and that's kind of where
we're kind of stuck out right

00;25;54;16 - 00;25;59;29
now, is being able to classify
a mixed body fluids sample.

00;26;00;04 - 00;26;02;11
Am I going to say it's impossible now?

00;26;02;11 - 00;26;08;16
Do I need a different classification
method that allows for the possibility

00;26;08;16 - 00;26;13;11
of two or three body
fluids to be mixed together? Yes.

00;26;13;13 - 00;26;18;07
So currently, like the machine learning
method that we developed

00;26;18;10 - 00;26;21;03
is only looking for one answer, right?

00;26;21;03 - 00;26;25;02
And so, we would need to train it
and have a way

00;26;25;02 - 00;26;28;24
for it to also classify
multiple bodies fluids.

00;26;28;26 - 00;26;32;06
So, we'd have to have a training set
and the machine learning

00;26;32;06 - 00;26;35;21
method would have to be different
to allow for that multiple option.

00;26;35;24 - 00;26;39;15
Okay, so is that so that method
that you said that the machine learning,

00;26;39;15 - 00;26;41;24
is that the quadratic discriminant
analysis?

00;26;41;24 - 00;26;42;21
Mm hmm. Yeah.

00;26;42;21 - 00;26;43;13
Is that what that is?

00;26;43;13 - 00;26;46;19
Can you describe a little bit
about what it's doing at a high level?

00;26;46;22 - 00;26;49;08
Because I just like,
is it just like a static?

00;26;49;08 - 00;26;51;25
Is it a statistic,
the statistical technique?

00;26;51;25 - 00;26;53;10
Is that what it is? Yeah.

00;26;53;10 - 00;26;55;14
So, it's a statistical technique.

00;26;55;14 - 00;26;59;10
So, we trained it with

00;26;59;12 - 00;27;02;03
50 to 200 samples of each body

00;27;02;03 - 00;27;06;00
fluid from,
you know, 50 to 200 different donors.

00;27;06;00 - 00;27;09;06
And we said, okay, this is semen, right?

00;27;09;06 - 00;27;11;06
This is 50 different samples of semen.

00;27;11;06 - 00;27;14;03
This is 50 different samples
of venous blood.

00;27;14;03 - 00;27;16;13
And then we would hit it.

00;27;16;13 - 00;27;20;04
So, once it's trained
and it knows the microRNA expression

00;27;20;04 - 00;27;23;06
patterns for each body

00;27;23;06 - 00;27;26;17
fluid across a population of donors,

00;27;26;20 - 00;27;29;15
then when we show it an unknown sample,

00;27;29;15 - 00;27;33;12
it works to match that expression.

00;27;33;12 - 00;27;36;15
What is the closest expression matrix

00;27;36;15 - 00;27;40;21
and it classifies
the body fluid based on that.

00;27;40;23 - 00;27;41;23
Okay. Yeah.

00;27;41;23 - 00;27;45;07
Let me ask you about the
another study here.

00;27;45;10 - 00;27;48;29
And I'm not exactly sure what this is,
but I have an idea.

00;27;49;00 - 00;27;52;25
But it says droplet based optical
trapping for cell separation in

00;27;52;25 - 00;27;55;15
mock forensic samples.

00;27;55;17 - 00;27;58;27
Tell me about what the heck is droplet
based optical trapping.

00;27;58;27 - 00;28;01;29
It sounds to me
like you're shining a laser like lasers.

00;28;02;06 - 00;28;05;06
You're shining a laser
through a sample or something, and then

00;28;05;11 - 00;28;08;10
you're looking at the fraction of light
or something like this.

00;28;08;10 - 00;28;10;13
Yes, you're exactly right.

00;28;10;13 - 00;28;14;18
So, we can take a cell suspension,

00;28;14;21 - 00;28;19;13
like we can take a dried swab
that's a post-coital swab

00;28;19;15 - 00;28;21;13
and just reconstitute with water

00;28;21;13 - 00;28;24;13
in about 10 minutes and put it on a slide

00;28;24;13 - 00;28;28;01
and place it on our optical
trapping instrument.

00;28;28;01 - 00;28;29;19
Again, this is a collaboration

00;28;29;19 - 00;28;33;12
with Joe Reiner
in our department of Physics here at VCU,

00;28;33;14 - 00;28;34;15
and he's the physicist.

00;28;34;15 - 00;28;37;14
He does the laser work,

00;28;37;17 - 00;28;40;03
but the cell,

00;28;40;03 - 00;28;46;00
it becomes trapped within that laser
because of the dipole interactions.

00;28;46;03 - 00;28;49;06
And when you move the stage, the cell

00;28;49;06 - 00;28;53;09
remains in in the laser trap.

00;28;53;12 - 00;28;55;28
I actually
have a video pulled up from YouTube.

00;28;55;28 - 00;28;58;07
I don't know if you want me to show it,
but you know what?

00;28;58;07 - 00;29;02;01
Where I can provide a link in the comments
if you'd like it.

00;29;02;01 - 00;29;02;18
Or you know what?

00;29;02;18 - 00;29;05;14
If you dropped the link
and what I'll do is I'll,

00;29;05;14 - 00;29;08;00
I'll, I'll even played here
and bring it up

00;29;08;00 - 00;29;10;13
so that we can talk about it,
because this is it's pretty fascinating.

00;29;10;13 - 00;29;12;08
I'm not sure

00;29;12;08 - 00;29;14;04
exactly what it is, but let's see here.

00;29;14;04 - 00;29;16;24
I just put it in the private chat. Okay.

00;29;16;24 - 00;29;17;09
Thank you.

00;29;17;09 - 00;29;23;00
I'll bring that up here in a second
so, we can very quickly trap these cells.

00;29;23;00 - 00;29;24;21
We can choose which cell that we want.

00;29;24;21 - 00;29;27;04
This is all based on morphology
at this point.

00;29;27;04 - 00;29;30;21
So, the cells have to morphologically
look different.

00;29;30;21 - 00;29;33;20
So epithelial cells versus sperm cells,

00;29;33;26 - 00;29;37;17
white blood cells versus epithelial cells,

00;29;37;19 - 00;29;40;15
but we can trap them and collect them

00;29;40;15 - 00;29;45;13
and then isolate the fractions away
from the mixture.

00;29;45;13 - 00;29;48;16
I'm sorry, my light just went off. I'll go

00;29;48;18 - 00;29;52;08
Problem.

00;29;52;11 - 00;29;53;04
All right.

00;29;53;04 - 00;29;57;10
So, the video you're looking at
has two sperm cells trapped,

00;29;57;13 - 00;29;59;14
and so, they've pulled the trap.

00;29;59;14 - 00;30;01;10
These are two simultaneous traps.

00;30;01;10 - 00;30;04;24
And you can see, you know,
the little tail is moving behind it.

00;30;04;24 - 00;30;09;03
And the yellow circles denote the trap,
and it just picked up another sperm cell.

00;30;09;05 - 00;30;11;28
And he's moving around

00;30;11;28 - 00;30;15;09
vaginal epithelial cells to take them

00;30;15;11 - 00;30;19;28
to another position on the microchip
where we've got two separate fractions.

00;30;19;28 - 00;30;23;11
We've got our sperm fraction
and our epithelial cell fraction.

00;30;23;13 - 00;30;26;19
And what we found by using this method

00;30;26;19 - 00;30;31;03
is that we need about 40 cells,
40 sperm cells

00;30;31;03 - 00;30;34;26
to because they're haploid, they only have
one copy of the genetic material.

00;30;34;26 - 00;30;38;03
So, there's our little clump of sperm
cells.

00;30;38;05 - 00;30;44;11
We need 40 cells to develop a full DNA
profile, but we only need 6 to 10

00;30;44;13 - 00;30;45;25
epithelial cells to

00;30;45;25 - 00;30;49;05
generate a full DNA profile.

00;30;49;07 - 00;30;53;13
And so, this is cell
sorting on a micro scale.

00;30;53;16 - 00;30;56;25
But for the purposes of forensic analysis,

00;30;56;25 - 00;31;01;11
we don't need a lot of cells at this point
to develop a full DNA profile.

00;31;01;13 - 00;31;05;08
And these profiles are clean
like it is not a mixture in any way.

00;31;05;08 - 00;31;10;18
They are clean fractions,
which is really, really a great thing.

00;31;10;20 - 00;31;14;07
That is amazing that you're just doing
that with a little laser in your hand.

00;31;14;08 - 00;31;16;03
You're just you're able to sort of drag

00;31;16;03 - 00;31;18;14
these guys along
and bring them to the pile.

00;31;18;14 - 00;31;20;02
Yeah, that's awesome.

00;31;20;02 - 00;31;24;19
And so, then you just collect the parts
of the samples that you need, right?

00;31;24;22 - 00;31;25;03
Yeah.

00;31;25;03 - 00;31;28;26
So, we've moved this on to a micro device
and that's the paper

00;31;28;26 - 00;31;30;25
that we're working on finishing up
right now.

00;31;30;25 - 00;31;35;05
So, look for it like later this summer,
hopefully in one of the big forensic

00;31;35;05 - 00;31;35;29
science journalists.

00;31;35;29 - 00;31;40;11
So is this a in terms of

00;31;40;13 - 00;31;43;27
like in forensic cases or whatever,
is this something where, you know,

00;31;43;27 - 00;31;48;25
you just have just a few sample
or you have very small,

00;31;48;27 - 00;31;50;29
you know, Yeah, like a small sample
or something like that.

00;31;50;29 - 00;31;53;11
It just helps you to concentrate

00;31;53;11 - 00;31;56;11
the number of samples that you
a good sample that you get out of it.

00;31;56;18 - 00;31;59;26
So, we kind of see it as a future
potential tool.

00;31;59;26 - 00;32;03;26
Like am I worried so much
about separating out sperm versus

00;32;03;26 - 00;32;07;29
non sperm when we can do it really well
with the differential extraction?

00;32;07;29 - 00;32;12;23
No, but could it be used
for separating cells of different

00;32;12;23 - 00;32;17;10
morphologies out of a mixture
and preventing that mixture?

00;32;17;10 - 00;32;23;04
Deconvolution of the DNA analysis stage
and the probabilistic genotyping

00;32;23;04 - 00;32;27;01
and all of those like preventing
the mixture in the first place

00;32;27;03 - 00;32;31;06
would be a great place to start. Yeah.

00;32;31;08 - 00;32;34;23
What about the
types of cells that you can use this for?

00;32;34;26 - 00;32;38;16
Like the size of the cell matters
is limited in that regard.

00;32;38;16 - 00;32;41;23
You know, not so much
with the laser that we have now.

00;32;41;23 - 00;32;46;22
So, this laser can capture
and hold epithelial cells.

00;32;46;22 - 00;32;50;01
The earlier laser we were using out
was kind of limited to sperm

00;32;50;01 - 00;32;51;09
cells and epithelial cells.

00;32;51;09 - 00;32;54;24
So, the power of the laser definitely has

00;32;54;27 - 00;32;57;26
an effect on the types of cells
that you can trap.

00;32;58;03 - 00;33;02;09
But the cells that we're trapping
now, like we can grab an epithelial cell

00;33;02;12 - 00;33;04;00
and drag it over.

00;33;04;00 - 00;33;08;01
But actually, what we're finding
is that your vaginal and your oral

00;33;08;01 - 00;33;10;05
epithelial cells are never by themselves.

00;33;10;05 - 00;33;13;24
So, we're actually dragging
a clump of multiple cells,

00;33;13;27 - 00;33;17;24
and that's indicated by the DNA plant
that we're seeing because we know

00;33;17;24 - 00;33;21;12
how many cells we think we trapped
and we're getting DNA yields

00;33;21;12 - 00;33;25;03
triple and quadruple that,
which can only indicate

00;33;25;07 - 00;33;29;07
that it was a clump of cells,
not individual cells, is amazing.

00;33;29;07 - 00;33;33;12
So, what was what was so
what was the most surprising find for you

00;33;33;18 - 00;33;36;11
during this particular project?

00;33;36;14 - 00;33;38;01
This is a long project, too.

00;33;38;01 - 00;33;39;11
Like everything.

00;33;39;11 - 00;33;41;03
Everything takes a long time.

00;33;41;03 - 00;33;45;17
So that's been a really interesting
finding.

00;33;45;19 - 00;33;49;22
Something that we had happened early on
is that we were trapping

00;33;49;25 - 00;33;53;06
and then depositing the cells onto a glass

00;33;53;06 - 00;33;56;18
cover slip
and then extracting off of that.

00;33;56;21 - 00;33;58;28
And it worked really great for sperm
cells.

00;33;58;28 - 00;34;01;04
You know, sperm cells are really tough
little guys.

00;34;01;04 - 00;34;05;01
They've got a really tough outer
coating to protect the head as it moves

00;34;05;01 - 00;34;10;00
through the vaginal tract,
through the cervix and up into the uterus.

00;34;10;03 - 00;34;11;13
But other cells are not.

00;34;11;13 - 00;34;17;06
And so, when we initially moved on
to our next cell type, which was

00;34;17;09 - 00;34;21;19
leukocytes or white blood cells,
we were getting no DNA yields

00;34;21;19 - 00;34;25;29
and we didn't understand what was going on
until we realized that the

00;34;26;01 - 00;34;28;10
the minute we padded

00;34;28;10 - 00;34;31;10
the cells onto the glass cover slip,

00;34;31;15 - 00;34;36;18
they dried and lice
and the DNA was sticking to the glass.

00;34;36;18 - 00;34;42;16
So, one of the most commonly used methods
of DNA extraction

00;34;42;16 - 00;34;46;14
that the whole forensic community uses
are these silica column extraction.

00;34;46;18 - 00;34;47;06
Right.

00;34;47;06 - 00;34;53;24
And under certain chemical conditions,
DNA adheres to silica and glass is silica.

00;34;53;26 - 00;34;54;28
So that was a big

00;34;54;28 - 00;34;58;03
learning opportunity for all of us.

00;34;58;03 - 00;34;59;26
And we had to switch

00;34;59;26 - 00;35;02;26
kind of totally switch what we did
and move to a droplet

00;35;02;26 - 00;35;06;02
where we are pipetting it directly into a tube
and we solved that problem.

00;35;06;02 - 00;35;09;04
But it was an interesting conundrum
for a while, figuring out

00;35;09;04 - 00;35;13;01
where our cells had gone
and using now all your research and stuff.

00;35;13;01 - 00;35;15;02
I mean, you,

00;35;15;02 - 00;35;18;02
you part of your duties
there is you handle a lot of the research,

00;35;18;08 - 00;35;22;26
is the graduate research
that you're mostly working on.

00;35;22;29 - 00;35;24;18
So, most of my research

00;35;24;18 - 00;35;27;18
is working with Masters

00;35;27;25 - 00;35;30;25
students, but
I have a couple of undergraduate students.

00;35;31;01 - 00;35;36;11
I usually have somewhere between five
and eight students in my lab from.

00;35;36;11 - 00;35;41;07
I've even had a high school student
all the way up to PhD students,

00;35;41;09 - 00;35;44;04
and I also run
the graduate program here at VCU.

00;35;44;04 - 00;35;48;21
So, we have 48 students currently, 24

00;35;48;21 - 00;35;53;28
first year master's students
and 24 second year Masters student.

00;35;54;00 - 00;35;56;00
And it's a spec accredited program.

00;35;56;00 - 00;35;58;06
So, we have a lot of accreditations
requirements

00;35;58;06 - 00;36;01;22
that I have to manage every year,
but I've really enjoyed it.

00;36;01;22 - 00;36;02;27
It's been a really,

00;36;02;27 - 00;36;06;10
really great opportunity
for the past five years now

00;36;06;10 - 00;36;07;23
as VCU pretty much specialized.

00;36;07;23 - 00;36;11;13
I mean, it sounds like you're doing
a lot of stuff, obviously in biology,

00;36;11;20 - 00;36;13;03
molecular biology and stuff like that.

00;36;13;03 - 00;36;17;04
But in the forensic science program,
is that your strength really at VCU?

00;36;17;06 - 00;36;19;07
So, I would say we have dual strengths.

00;36;19;07 - 00;36;22;25
So, our forensic biology program is very

00;36;22;27 - 00;36;26;11
but our drugs and toxicology
program is just as strong.

00;36;26;11 - 00;36;32;15
So, we have research faculty
that are working on kind of pharmacologic

00;36;32;21 - 00;36;37;19
and forensic impact
of different drugs, of abuse on people.

00;36;37;21 - 00;36;39;04
We have Dr.

00;36;39;04 - 00;36;42;27
Michelle Pease,
who is working on vaping and the Texas

00;36;43;00 - 00;36;46;07
vaping and diverted drugs

00;36;46;07 - 00;36;50;05
in vape pens and how those impacts

00;36;50;07 - 00;36;52;15
let how it impacts the person.

00;36;52;15 - 00;36;56;18
But also, you know,
working with state legislators

00;36;56;18 - 00;37;03;02
and federal legislators for how to
how to manage this type of drug use.

00;37;03;04 - 00;37;06;29
And we have faculty
in the physical evidence.

00;37;06;29 - 00;37;10;03
We have a faculty member that's doing
a lot of research on firearms.

00;37;10;03 - 00;37;12;14
We have trace evidence
in an anthropology.

00;37;12;14 - 00;37;15;09
So, we have a lot a lot of things going on.

00;37;15;09 - 00;37;17;28
It's a really exciting program
to be a part of.

00;37;17;28 - 00;37;18;06
Yeah.

00;37;18;06 - 00;37;21;13
I mean, you know, you get a lot of stuff
going on, that's for sure.

00;37;21;15 - 00;37;24;19
Let me ask you about the
another paper here.

00;37;24;19 - 00;37;26;16
You got a lot of stuff here.

00;37;26;16 - 00;37;31;17
It says A combined molecular approach
utilizing microbial DNA and microarrays

00;37;31;17 - 00;37;34;22
in a Q PCR multiplex
for the classification of five

00;37;34;22 - 00;37;36;24
forensically relevant body fluids.

00;37;36;24 - 00;37;39;14
So, what was that one about?

00;37;39;14 - 00;37;44;25
That was like the perfect combination
of two of my previous projects.

00;37;44;25 - 00;37;47;24
So, I told you about the
My MICROLEARNING project.

00;37;47;24 - 00;37;52;13
We also had a at the same time
I had a collaboration with Dr.

00;37;52;13 - 00;37;58;06
Bannon sourcing here at VCU, who's
a microbial and next gen sequencing guru.

00;37;58;06 - 00;38;03;16
And so, we also under and I support

00;38;03;18 - 00;38;10;22
evaluated 1800 people for their microbial,

00;38;10;24 - 00;38;12;13
the microbial

00;38;12;13 - 00;38;16;24
microbiomes of each of their body fluids,
forensically relevant body fluids.

00;38;16;26 - 00;38;19;25
And so, we also,
while I was doing the MICROLEARNING work,

00;38;19;25 - 00;38;23;19
we developed methods
for classifying body fluids,

00;38;23;19 - 00;38;26;19
using bacterial signatures.

00;38;26;24 - 00;38;30;17
And what we found was really interesting,
it was that, you know,

00;38;30;19 - 00;38;34;21
more sterile body
fluids like blood and semen don't classify

00;38;34;21 - 00;38;38;10
well with microbial signatures,
but they classify really well

00;38;38;10 - 00;38;42;04
with microRNAs and vice versa, things that

00;38;42;07 - 00;38;45;06
vaginal secretions, saliva

00;38;45;06 - 00;38;49;11
don't classify
well as well as I'd like was microRNAs

00;38;49;11 - 00;38;52;09
that they classify really well
with microbial signatures

00;38;52;09 - 00;38;56;05
because there are a lot of bacteria
naturally occurring in those areas.

00;38;56;07 - 00;38;57;12
And so, my Ph.D.

00;38;57;12 - 00;39;02;27
student, Carolyn Lewis,
she pulled those two together

00;39;02;27 - 00;39;07;25
and developed an RTP CRC
that combined the strengths of each

00;39;07;25 - 00;39;11;28
to classify
those body fluids with a pretty high rate.

00;39;12;00 - 00;39;13;01
So, you're doing both

00;39;13;01 - 00;39;16;01
and then running some stats,
the statistics and then trying to.

00;39;16;08 - 00;39;20;14
Yeah, I mean, she got it
all on one plate and two wells.

00;39;20;17 - 00;39;23;03
And so, it's a quick

00;39;23;05 - 00;39;26;14
one hour, two PCR analysis

00;39;26;14 - 00;39;30;17
that can classify as body fluids
with a pretty high degree of accuracy.

00;39;30;19 - 00;39;32;17
So, the microbial stuff.

00;39;32;17 - 00;39;37;13
So, I mean how,
how so is that just as unique,

00;39;37;16 - 00;39;41;15
you know, are very specific
to different individuals.

00;39;41;17 - 00;39;44;13
Yes. Is similarly to the Raman
spectroscopy.

00;39;44;13 - 00;39;50;15
Microbial signatures can go from
very high level to very low level.

00;39;50;15 - 00;39;50;25
Right.

00;39;50;25 - 00;39;55;06
You can classify
just the body fluid, right.

00;39;55;09 - 00;39;58;01
But you can also dive deeper.

00;39;58;01 - 00;40;03;19
And we know from the literature
that people who cohabits together,

00;40;03;19 - 00;40;06;01
whether they're family or roommates,

00;40;06;01 - 00;40;09;18
tend to share a lot
of their microbial signatures.

00;40;09;18 - 00;40;15;02
And so, you can even get to a point
of where these people cohabiting

00;40;15;04 - 00;40;19;04
or, you know,
was this person in this location.

00;40;19;04 - 00;40;22;06
I'm not sure that the research is
quite there yet, but there are

00;40;22;06 - 00;40;25;16
some things that are trending there
that's super interesting.

00;40;25;16 - 00;40;31;24
So, yeah, so if people in a home, even
though they may have different types of

00;40;31;27 - 00;40;35;18
microbes, microbes, bacteria or whatever,
yeah, sure.

00;40;35;18 - 00;40;36;23
Then yeah.

00;40;36;23 - 00;40;40;28
So, if they share two or three,
that may be very common to just to them,

00;40;40;28 - 00;40;44;11
then maybe it'll say something
about the relationship between people too.

00;40;44;13 - 00;40;45;10
Yeah.

00;40;45;10 - 00;40;46;08
Okay.

00;40;46;08 - 00;40;49;04
Yeah. That, that's very, very interesting.

00;40;49;04 - 00;40;52;12
So, I mean, ultimately, like all these,
all these, you know,

00;40;52;12 - 00;40;56;08
identifying the fluids and stuff, I mean,
are you looking to do something like

00;40;56;08 - 00;41;00;09
where you're trying to just try
to bring new procedures, new techniques

00;41;00;11 - 00;41;03;27
to the forensic science discipline,
or are you looking to commercialize

00;41;03;27 - 00;41;05;13
anything on your own as well?

00;41;05;13 - 00;41;08;09
Look at the university.

00;41;08;09 - 00;41;10;21
So, it's a great question.

00;41;10;21 - 00;41;14;05
So as a researcher,

00;41;14;05 - 00;41;17;20
like I feel like science
should be public and free, right?

00;41;17;26 - 00;41;22;08
And so, everything that we've done
has is publicly available

00;41;22;08 - 00;41;27;27
like we've published or protocols
we've published the prediction

00;41;27;29 - 00;41;32;08
algorithms for both the microbial
and all of the microphone assays.

00;41;32;08 - 00;41;36;11
Like you can go on to one of our papers
and we've got a link, and you could

00;41;36;11 - 00;41;40;18
run the assay and use our algorithm
to predict the body fluid

00;41;40;20 - 00;41;45;18
and ultimately anything
that's going to be used in the forensic

00;41;45;20 - 00;41;49;07
community is going to be commercialized,
right?

00;41;49;09 - 00;41;50;03
I do.

00;41;50;03 - 00;41;53;18
I have aspirations
of like making $1,000,000.

00;41;53;18 - 00;41;59;26
Now, do I want my tools to hopefully help
the community? Yes.

00;41;59;28 - 00;42;00;12
Yeah.

00;42;00;12 - 00;42;04;19
So, I mean, I try to make things
as open access as possible with the hope

00;42;04;19 - 00;42;08;20
that a commercial manufacturer
will find it useful and pick it up.

00;42;08;23 - 00;42;11;07
Yeah, it makes sense, I think. So.

00;42;11;07 - 00;42;15;24
How important is working with people So,

00;42;15;27 - 00;42;20;06
you know, people outside of your field
in research today?

00;42;20;08 - 00;42;21;21
Oh, I think it's essential.

00;42;21;21 - 00;42;26;24
Like I've said before,
like I lean on my physicist collaborators

00;42;26;24 - 00;42;31;14
for their expertise in the project
and they lean on me.

00;42;31;17 - 00;42;37;24
I'm working currently with somebody in
the Department of Kinesiology here at ICU

00;42;37;27 - 00;42;39;23
because we were just funded,

00;42;39;23 - 00;42;42;28
just awarded a grant
from the National Institute of Justice

00;42;42;28 - 00;42;48;14
to look at body weight classification
or prediction using microRNAs

00;42;48;17 - 00;42;50;19
as part of a phenotypic panel.

00;42;50;19 - 00;42;51;01
Right.

00;42;51;01 - 00;42;54;28
So, we already can
predict hair color, skin color, eye color,

00;42;55;00 - 00;42;57;29
age to a pretty narrow range.

00;42;57;29 - 00;43;01;05
Height is getting there, but nobody's

00;43;01;05 - 00;43;05;01
even tackled kind of body weight,
which is important.

00;43;05;01 - 00;43;05;12
Right.

00;43;05;12 - 00;43;09;16
So, it's another part of the picture
of what the assailant

00;43;09;16 - 00;43;11;12
or the victim might look like.

00;43;11;12 - 00;43;14;25
And so, I'm working with a colleague

00;43;14;25 - 00;43;17;25
over in kinesiology
because this is totally new to me.

00;43;18;02 - 00;43;20;24
And she's already brought in
some really great ideas

00;43;20;24 - 00;43;24;16
and some tools that we can use
to assess body composition

00;43;24;19 - 00;43;27;19
that will make our analysis of the data

00;43;27;19 - 00;43;30;29
more informative and more accurate.

00;43;31;01 - 00;43;34;10
So, nobody's done any preliminary work
in this particular area

00;43;34;10 - 00;43;35;20
or published anything really.

00;43;35;20 - 00;43;37;13
No, really?

00;43;37;13 - 00;43;39;25
Yeah, I'm really excited.

00;43;39;25 - 00;43;43;02
We have some really
good preliminary data, but

00;43;43;04 - 00;43;43;29
yeah, nobody's.

00;43;43;29 - 00;43;45;13
Nobody's done anything.

00;43;45;13 - 00;43;48;03
Well,
what about the fact that weight changes so

00;43;48;03 - 00;43;51;03
everything's changing with you
like it's a reckoning.

00;43;51;05 - 00;43;53;22
And that's the beauty of using RNA.

00;43;53;22 - 00;43;57;16
So, DNA is relatively static
over a person's lifetime.

00;43;57;16 - 00;44;02;20
But as somebody gains fitness or loses
fitness and gains

00;44;02;20 - 00;44;05;28
weight, there are any compression
is going to change.

00;44;06;01 - 00;44;08;25
And again, because we can detect microRNAs

00;44;08;25 - 00;44;11;25
in DNA extracts,
we don't need additional sample.

00;44;11;29 - 00;44;13;16
You know, we can use the DNA

00;44;13;16 - 00;44;18;00
that's already being used
for a phenotypic profile in human identity

00;44;18;02 - 00;44;20;26
to hopefully classify or give an idea of

00;44;20;26 - 00;44;24;03
if the person is lean or muscular

00;44;24;05 - 00;44;27;23
and underweight,
average, overweight or obese.

00;44;27;25 - 00;44;31;24
I actually want to go I want to talk about
phenotyping at some point.

00;44;31;24 - 00;44;33;21
It's sort of on its own
as a separate subject.

00;44;33;21 - 00;44;37;18
But I'm just curious,
but can you give me a sense of where

00;44;37;20 - 00;44;40;15
sort of
at what level is phenotyping at today?

00;44;40;15 - 00;44;44;14
Is it sort of still in the inception stage
or is it well, is it well understood?

00;44;44;14 - 00;44;47;04
Is it well on its way?

00;44;47;06 - 00;44;47;15
Well,

00;44;47;15 - 00;44;50;26
there's so I'm definitely not
the expert of this.

00;44;50;26 - 00;44;53;29
You should reach out to, for example,
student Susan

00;44;53;29 - 00;44;57;07
Walsh, IAP Walsh at IUPUI.

00;44;57;09 - 00;45;01;03
She's been really crucial in the U.S.

00;45;01;05 - 00;45;04;13
and she's she worked under member Kaiser,
who's kind of the pioneer

00;45;04;13 - 00;45;06;22
for this in forensic analysis.

00;45;06;22 - 00;45;08;10
What I can say is, you know,

00;45;08;10 - 00;45;12;00
there are a lot of things
we don't understand in certain traits,

00;45;12;00 - 00;45;14;12
but there are a lot of things
that we do understand.

00;45;14;12 - 00;45;19;27
And many of the single nucleotide
polymorphisms or snips

00;45;19;27 - 00;45;24;15
that have been characterizing hair
color, skin color, eye color

00;45;24;17 - 00;45;29;17
are already in commercial panels
and are being used

00;45;29;19 - 00;45;33;25
for prediction
of phenotypic characteristics.

00;45;33;27 - 00;45;34;18
Yeah, interesting.

00;45;34;18 - 00;45;35;16
I think that's a

00;45;35;16 - 00;45;39;04
that would be a very interesting thing
if we can start really starting to define

00;45;39;06 - 00;45;41;01
what a suspect is going to look like, too.

00;45;41;01 - 00;45;43;29
I think that's very futuristic.

00;45;44;02 - 00;45;47;25
And talking about futuristic things,
I mean, how important is

00;45;47;28 - 00;45;50;17
Yeah, you mentioned you
mentioned machine learning.

00;45;50;17 - 00;45;54;07
You know, you're using machine learning
algorithms and stuff like that, but

00;45;54;09 - 00;45;56;22
have you had discussions
about artificial intelligence

00;45;56;22 - 00;46;00;26
and all this other stuff that, you know,
people have been talking about these days?

00;46;00;28 - 00;46;03;01
Not yet. Yeah.

00;46;03;01 - 00;46;04;11
Yeah, I'm.

00;46;04;11 - 00;46;05;28
I'm sorry, but not yet.

00;46;05;28 - 00;46;09;25
I, I mean,
I definitely think there's a place for it.

00;46;09;28 - 00;46;13;03
We have so much research data

00;46;13;03 - 00;46;17;05
that really no one
person can kind of see all of that

00;46;17;05 - 00;46;21;09
in their head and come up with,
you know, potential linkages.

00;46;21;09 - 00;46;25;00
I think that AI is going to be a really
important tool to help us with that.

00;46;25;00 - 00;46;26;05
And we're already seeing that

00;46;26;05 - 00;46;32;18
some in the biomedical community
I just read a paper last week about

00;46;32;20 - 00;46;37;23
using AI, I believe, to identify

00;46;37;26 - 00;46;41;29
a marker that shows that

00;46;42;02 - 00;46;44;23
if the woman has that she has a 22%

00;46;44;23 - 00;46;47;22
higher potential for miscarriage like.

00;46;47;26 - 00;46;50;29
And so, I definitely think the

00;46;51;06 - 00;46;54;22
AI is going to help us make those linkages
out of huge datasets.

00;46;54;22 - 00;46;56;08
But am I there yet?

00;46;56;08 - 00;46;59;16
I'm not confident,
so, I need to do some additional.

00;46;59;19 - 00;47;00;17
Yeah, okay.

00;47;00;17 - 00;47;02;20
But I imagine like with the machine
learning, you have,

00;47;02;20 - 00;47;06;22
you have a people that you lean on
maybe in computer science or whatever.

00;47;06;25 - 00;47;07;17
Yeah.

00;47;07;17 - 00;47;09;01
Well yeah, right. Yeah.

00;47;09;01 - 00;47;10;29
Well, I think that's
the reality of today is just you

00;47;10;29 - 00;47;12;17
can't be an expert in every single area.

00;47;12;17 - 00;47;15;17
So, you have to have to pick
and choose your battles, that's for sure.

00;47;15;22 - 00;47;16;10
Yeah.

00;47;16;10 - 00;47;21;03
So where, so what is next
for like all of this research

00;47;21;03 - 00;47;25;05
now that you've done a bunch of different
things like identifying different body

00;47;25;05 - 00;47;29;04
fluids and stuff, so is there
are there like one or two or three things

00;47;29;04 - 00;47;31;25
that you're really going
to be pushing forward on?

00;47;31;27 - 00;47;32;05
Yeah.

00;47;32;05 - 00;47;36;00
So currently we're still working
pretty hard on the optical trapping

00;47;36;00 - 00;47;39;29
and the body weight
classification is just getting started.

00;47;39;29 - 00;47;43;09
So that's going to be a big focus for me
over the next couple of years.

00;47;43;09 - 00;47;48;02
And I think hopefully further
as it continues to be successful,

00;47;48;04 - 00;47;51;20
I'd really like
to get the combined microbial

00;47;51;20 - 00;47;55;07
and my current body fluid

00;47;55;09 - 00;47;58;29
classification panel on to a next

00;47;58;29 - 00;48;02;16
gen sequencing human identity panel.

00;48;02;19 - 00;48;06;20
I propose that and I, I hope that

00;48;06;22 - 00;48;10;26
I can improve that proposal
and maybe get it funded this year.

00;48;10;29 - 00;48;14;09
It's going to require some partnership
with commercial manufacturers.

00;48;14;09 - 00;48;18;21
But I think that, you know,
that would be the easiest transition

00;48;18;21 - 00;48;22;01
to getting a molecular method
for body fluid identification

00;48;22;01 - 00;48;25;12
into the hands of practitioners
is we make it easy for them.

00;48;25;15 - 00;48;28;08
They don't have to do any additional work.

00;48;28;08 - 00;48;31;03
They get their human identity
and they also get a prediction

00;48;31;03 - 00;48;34;03
of what body fluids were present
in that in that sample.

00;48;34;07 - 00;48;37;05
Okay, I just looking here in the comments,
but it's somebody

00;48;37;05 - 00;48;40;16
somebody seems to be interested
in applications for grad school.

00;48;40;16 - 00;48;43;04
So, tell me
tell me about the program there and like

00;48;43;04 - 00;48;46;16
maybe how people can get started
or get involved. Yeah,

00;48;46;19 - 00;48;50;10
we really focus on hands on experience.

00;48;50;10 - 00;48;54;15
We have every instrument
that is used in a current

00;48;54;16 - 00;48;58;17
forensic laboratory or and or
that will be used in the next ten years.

00;48;58;17 - 00;49;02;15
All of our graduate classes
have laboratories

00;49;02;15 - 00;49;06;23
associated with them
with small under 12 student sections.

00;49;06;26 - 00;49;11;01
Um, and we're actually really excited
that we not only have our,

00;49;11;03 - 00;49;15;04
our biology or DNA concentration,
our drugs talks,

00;49;15;07 - 00;49;19;02
our trace concentration
and our physical evidence concentration.

00;49;19;02 - 00;49;23;06
But we as long as we get approval
from our state board, we should have

00;49;23;06 - 00;49;27;00
a digital forensics undergraduate
and graduate program starting this fall.

00;49;27;06 - 00;49;30;03
So, we're really excited about that too.

00;49;30;03 - 00;49;30;21
Yeah. Amazing.

00;49;30;21 - 00;49;33;22
So, you already have
some good people doing that, I think.

00;49;33;22 - 00;49;35;26
Yeah, yeah, yeah.

00;49;35;26 - 00;49;40;28
I hope to be able to accept applications
for the digital by June.

00;49;41;00 - 00;49;43;00
We're already taking applications

00;49;43;00 - 00;49;47;28
for the Graduate program
and evaluating those for all good starts.

00;49;48;00 - 00;49;49;08
Amazing. Yeah.

00;49;49;08 - 00;49;49;16
Yeah.

00;49;49;16 - 00;49;51;09
So, what's next for you?

00;49;51;09 - 00;49;54;06
What's next on the list here?

00;49;54;06 - 00;49;58;03
You've you said you've got the weight
thing, you've got

00;49;58;05 - 00;49;59;07
some of the stuff going on.

00;49;59;07 - 00;50;02;13
But if you're looking ahead in five years,
what are you going to be doing

00;50;02;13 - 00;50;05;13
in five years from now?

00;50;05;14 - 00;50;07;17
Oh, that's a great question.

00;50;07;17 - 00;50;10;22
I'm not old enough to retire.

00;50;10;25 - 00;50;11;21
I love research.

00;50;11;21 - 00;50;15;20
So, I mean, I my assumption
is that I'll continue

00;50;15;20 - 00;50;19;10
on some of these projects
and developing new ones

00;50;19;13 - 00;50;21;20
where we also do a lot.

00;50;21;20 - 00;50;26;03
We work with some practitioners
on some interesting, like immediately

00;50;26;03 - 00;50;29;12
relevant things, like I've got a student
who's been working on

00;50;29;12 - 00;50;31;07
there's a laboratory,
a couple of laboratories

00;50;31;07 - 00;50;34;13
that use acetone on their swabs
to collect biological samples.

00;50;34;17 - 00;50;38;25
So, we've been evaluating that
as a potential diluent.

00;50;38;27 - 00;50;43;04
We've looked at kind of the best methods
for extract acting sperm

00;50;43;04 - 00;50;48;08
cells out of things like diapers
and sanitary napkins and tampons.

00;50;48;08 - 00;50;49;26
And that's a terrible thing to work on.

00;50;49;26 - 00;50;51;09
But it happens, right?

00;50;51;09 - 00;50;53;03
And there's challenges to that.

00;50;53;03 - 00;50;55;16
And now the period panties, right.

00;50;55;16 - 00;50;58;03
So where are the sperm going?

00;50;58;03 - 00;50;59;14
Are we able to get them out?

00;50;59;14 - 00;51;01;11
Are they still there after you wash?

00;51;01;11 - 00;51;04;24
These are like really important questions
for working practitioners.

00;51;04;24 - 00;51;09;25
And so, I really like including
those projects in my research as well.

00;51;09;28 - 00;51;14;01
Hey, do you mind if I put up your the VQ

00;51;14;04 - 00;51;14;21
thing here?

00;51;14;21 - 00;51;16;09
I just want to put this up here
because there may be

00;51;16;09 - 00;51;19;18
someone that just wants to reach out,
get a hold there, whether it's for

00;51;19;20 - 00;51;23;05
grad school or whether it's for research
related items or something like this.

00;51;23;11 - 00;51;24;08
Yeah, absolutely.

00;51;24;08 - 00;51;28;08
And if you ever have cool ideas
in the forensic biology

00;51;28;11 - 00;51;32;10
realm, in your case,
your laboratory is too busy to do them.

00;51;32;11 - 00;51;34;02
Reach out to me, will collaborate.

00;51;34;02 - 00;51;35;11
I'll put you on a grand committee.

00;51;35;11 - 00;51;37;19
We'll get you on a paper
if the results are good.

00;51;37;19 - 00;51;40;11
I love working with practitioners,
so, reach out.

00;51;40;11 - 00;51;41;25
Are you doing are you doing any training?

00;51;41;25 - 00;51;42;19
Like do you do any

00;51;42;19 - 00;51;47;21
like for other agencies
or do you get out and do workshops or DNA?

00;51;47;21 - 00;51;51;14
We don't have training right now,
but we have been talking about doing

00;51;51;14 - 00;51;55;14
some DNA
training for attorneys and judges,

00;51;55;16 - 00;51;58;28
but we do currently have a firearms

00;51;58;28 - 00;52;03;17
training program
that we've just started up that would be,

00;52;03;19 - 00;52;06;15
I believe it's 16 months

00;52;06;15 - 00;52;10;27
of an intensive half year at VCU
have back at home.

00;52;10;29 - 00;52;14;10
But you would come out of it
certified as a firearms examiner.

00;52;14;10 - 00;52;17;06
So, we're really good about that, too.
Yeah, that's cool.

00;52;17;06 - 00;52;18;11
Yeah. So, you're doing

00;52;18;11 - 00;52;21;25
like ballistics and examinations
on cartridges, aces and bullets.

00;52;21;28 - 00;52;25;13
Oh, wow.
I never heard of that. That's fantastic.

00;52;25;15 - 00;52;27;19
Are you being
you are getting out to any of the conferences

00;52;27;19 - 00;52;30;22
coming up, like the American Academy
or other things that are coming up?

00;52;30;22 - 00;52;32;11
You doing any presentations?

00;52;32;11 - 00;52;34;27
Yeah.
Yeah, I'll be at the academy meeting.

00;52;34;27 - 00;52;38;17
I'll be there Sunday for feedback
all the way through to Friday.

00;52;38;17 - 00;52;39;19
We have students presenting.

00;52;39;19 - 00;52;42;19
I'm on a workshop to workshops.

00;52;42;20 - 00;52;45;21
I'll be presenting a body to workshop
at the mid-Atlantic

00;52;45;21 - 00;52;49;14
Association of Forensic Sciences
meeting in Pittsburgh in May.

00;52;49;17 - 00;52;52;16
I'm going to Green Mountain Conference in

00;52;52;16 - 00;52;56;12
July and then I'll be at Icfi
in Spain in September.

00;52;56;12 - 00;52;58;18
So, I'm excited about that.

00;52;58;18 - 00;52;59;29
You're going to be busy bouncing around.

00;52;59;29 - 00;53;01;07
I think.

00;53;01;07 - 00;53;04;06
Yeah, I know
2024 is going to be a busy year for sure.

00;53;04;06 - 00;53;04;23
For sure.

00;53;04;23 - 00;53;05;29
Yeah. Amazing.

00;53;05;29 - 00;53;07;26
Well, look, thank you so much.

00;53;07;26 - 00;53;11;03
I really appreciate your time
and helping us figure out

00;53;11;10 - 00;53;13;12
the kind of work that you're doing
and all this cool stuff.

00;53;13;12 - 00;53;16;15
And VCU sounds like a great place,
a great option for a lot of students,

00;53;16;19 - 00;53;18;12
forensic science students.

00;53;18;12 - 00;53;19;22
You know, you can read Dr.

00;53;19;22 - 00;53;23;15
Williams and get into some really cool
research and firearms now, too,

00;53;23;15 - 00;53;25;12
which is really interesting
and the digital.

00;53;25;12 - 00;53;27;17
So, all the digital stuff
that's coming up as well.

00;53;27;17 - 00;53;29;24
So, look, thank you so much.
I really appreciate your time.

00;53;29;24 - 00;53;32;24
And do me a favor,
hang back and we'll chat a second.

00;53;33;00 - 00;53;35;01
Thank you for having me.
I really enjoyed it.

00;53;35;01 - 00;53;36;05
My pleasure.

00;53;36;05 - 00;53;38;03
Okay, folks, that does it for this one.

00;53;38;03 - 00;53;40;01
But, hey, look,
I want to say thanks to everybody.

00;53;40;01 - 00;53;43;28
I really appreciate all your time
and have a good Thursday afternoon

00;53;43;28 - 00;53;45;20
and we'll see
you soon. Take care. Bye bye.