EP 97 | Sarah Williams | Bodily Fluids

Join us on February 1, 2024, at 2 PM Eastern for an intriguing Forensics Talks episode, EP 96, with Sarah Williams, Associate Professor at Virginia Commonwealth University. Williams, a leading figure in forensic biology, has pioneered advancements in body fluid identification and DNA analysis. This episode will delve into her groundbreaking research on Raman Spectroscopy and microRNA, her experience as a forensic scientist, and her role in educating the next generation of forensic experts. Don't miss this deep dive into the science of bodily fluids with Sarah Williams!

Originally aired on:  Feb 1, 2024

Transcript

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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

00;13;48;08 - 00;13;51;25
however, many, but like when we think
about forensic evidence, we have,

00;13;51;25 - 00;13;55;03
of course, our two most common right,
which is blood and semen.

00;13;55;03 - 00;13;58;07
And at least those are the two
that we're looking for, the ones that

00;13;58;07 - 00;14;03;23
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.