Mass Spectrometry Reviews,
Journal Year:
2021,
Volume and Issue:
41(5), P. 842 - 860
Published: March 24, 2021
Abstract
The
lacrimal
film
has
attracted
increasing
interest
in
the
last
decades
as
a
potential
source
of
biomarkers
physiopathological
states,
due
to
its
accessibility,
moderate
complexity,
and
responsiveness
ocular
systemic
diseases.
High‐performance
liquid
chromatography‐mass
spectrometry
(LC‐MS)
led
effective
approaches
tear
proteomics,
despite
intrinsic
limitations
sample
amounts.
This
review
focuses
on
recent
progress
strategy
technology,
with
an
emphasis
for
personalized
medicine.
After
introduction
lacrimal‐film
composition,
examples
applications
biomarker
discovery
are
discussed,
comparing
based
pooled‐sample
single‐tear
analysis.
Then,
most
critical
steps
experimental
pipeline,
that
is,
collection,
fractionation,
LC‐MS
implementation,
discussed
reference
proteome‐coverage
optimization.
Advantages
challenges
alternative
procedures
highlighted.
Despite
still
limited
number
studies,
quantitative
including
investigation,
could
offer
unique
contributions
identification
low‐invasiveness,
sustained‐accessibility
biomarkers,
development
therapy
diagnosis.
Clinical Biochemistry,
Journal Year:
2020,
Volume and Issue:
82, P. 2 - 11
Published: March 15, 2020
Tandem
mass
spectrometry
–
especially
in
combination
with
liquid
chromatography
(LC–MS/MS)
is
applied
a
multitude
of
important
diagnostic
niches
laboratory
medicine.
It
unquestioned
its
routine
use
and
often
unreplaceable
by
alternative
technologies.
This
overview
illustrates
the
development
past
decade
(2009–2019)
intends
to
provide
insight
into
current
standing
future
directions
field.
The
instrumentation
matured
significantly,
applications
are
well
understood,
vitro
diagnostics
(IVD)
industry
shaping
market
providing
assay
kits,
certified
instruments,
first
automated
LC–MS/MS
instruments
as
an
analytical
core.
In
many
settings
application
still
burdensome
locally
lab
developed
test
(LDT)
designs
relying
on
highly
specialized
staff.
cover
wide
range
analytes
therapeutic
drug
monitoring,
endocrinology
including
newborn
screening,
toxicology.
tasks
that
remain
be
mastered
are,
for
example,
quantification
proteins
means
transition
from
targeted
untargeted
omics
approaches
pattern
recognition/pattern
discrimination
key
technology
establishment
decisions.
Briefings in Bioinformatics,
Journal Year:
2021,
Volume and Issue:
23(1)
Published: Oct. 7, 2021
Abstract
High-throughput
next-generation
sequencing
now
makes
it
possible
to
generate
a
vast
amount
of
multi-omics
data
for
various
applications.
These
have
revolutionized
biomedical
research
by
providing
more
comprehensive
understanding
the
biological
systems
and
molecular
mechanisms
disease
development.
Recently,
deep
learning
(DL)
algorithms
become
one
most
promising
methods
in
analysis,
due
their
predictive
performance
capability
capturing
nonlinear
hierarchical
features.
While
integrating
translating
into
useful
functional
insights
remain
biggest
bottleneck,
there
is
clear
trend
towards
incorporating
analysis
help
explain
complex
relationships
between
layers.
Multi-omics
role
improve
prevention,
early
detection
prediction;
monitor
progression;
interpret
patterns
endotyping;
design
personalized
treatments.
In
this
review,
we
outline
roadmap
integration
using
DL
offer
practical
perspective
advantages,
challenges
barriers
implementation
data.
MedComm,
Journal Year:
2023,
Volume and Issue:
4(4)
Published: July 31, 2023
Multi-omics
usually
refers
to
the
crossover
application
of
multiple
high-throughput
screening
technologies
represented
by
genomics,
transcriptomics,
single-cell
proteomics
and
metabolomics,
spatial
so
on,
which
play
a
great
role
in
promoting
study
human
diseases.
Most
current
reviews
focus
on
describing
development
multi-omics
technologies,
data
integration,
particular
disease;
however,
few
them
provide
comprehensive
systematic
introduction
multi-omics.
This
review
outlines
existing
technical
categories
multi-omics,
cautions
for
experimental
design,
focuses
integrated
analysis
methods
especially
approach
machine
learning
deep
integration
corresponding
tools,
medical
researches
(e.g.,
cancer,
neurodegenerative
diseases,
aging,
drug
target
discovery)
as
well
open-source
tools
databases,
finally,
discusses
challenges
future
directions
precision
medicine.
With
algorithms,
important
disease
research,
also
provided
detailed
introduction.
will
guidance
researchers,
who
are
just
entering
into
research.
Scientific Reports,
Journal Year:
2021,
Volume and Issue:
11(1)
Published: June 29, 2021
Abstract
The
age
of
precision
medicine
demands
powerful
computational
techniques
to
handle
high-dimensional
patient
data.
We
present
MultiSurv,
a
multimodal
deep
learning
method
for
long-term
pan-cancer
survival
prediction.
MultiSurv
uses
dedicated
submodels
establish
feature
representations
clinical,
imaging,
and
different
omics
data
modalities.
A
fusion
layer
aggregates
the
representations,
prediction
submodel
generates
conditional
probabilities
follow-up
time
intervals
spanning
several
decades.
is
first
non-linear
non-proportional
that
leverages
In
addition,
can
missing
data,
including
single
values
complete
was
applied
from
33
cancer
types
yields
accurate
curves.
quantitative
comparison
with
previous
methods
showed
Multisurv
achieves
best
results
according
time-dependent
metrics.
also
generated
visualizations
learned
representation
which
revealed
insights
on
characteristics
heterogeneity.
Computational and Structural Biotechnology Journal,
Journal Year:
2022,
Volume and Issue:
21, P. 134 - 149
Published: Dec. 1, 2022
The
emerging
high-throughput
technologies
have
led
to
the
shift
in
design
of
translational
medicine
projects
towards
collecting
multi-omics
patient
samples
and,
consequently,
their
integrated
analysis.
However,
complexity
integrating
these
datasets
has
triggered
new
questions
regarding
appropriateness
available
computational
methods.
Currently,
there
is
no
clear
consensus
on
best
combination
omics
include
and
data
integration
methodologies
required
for
This
article
aims
guide
studies
field
types
method
choose.
We
review
articles
that
perform
multiple
measurements
from
samples.
identify
five
objectives
applications:
(i)
detect
disease-associated
molecular
patterns,
(ii)
subtype
identification,
(iii)
diagnosis/prognosis,
(iv)
drug
response
prediction,
(v)
understand
regulatory
processes.
describe
common
trends
selection
omic
combined
different
diseases.
To
choice
tools,
we
group
them
into
scientific
they
aim
address.
main
methods
adopted
achieve
present
examples
tools.
compare
tools
based
how
deal
with
challenges
comment
against
predefined
objective-specific
evaluation
criteria.
Finally,
discuss
downstream
analysis
further
extraction
novel
insights
datasets.
Chemical Reviews,
Journal Year:
2023,
Volume and Issue:
123(13), P. 8297 - 8346
Published: June 15, 2023
Omics
technologies
have
rapidly
evolved
with
the
unprecedented
potential
to
shape
precision
medicine.
Novel
omics
approaches
are
imperative
toallow
rapid
and
accurate
data
collection
integration
clinical
information
enable
a
new
era
of
healthcare.
In
this
comprehensive
review,
we
highlight
utility
Raman
spectroscopy
(RS)
as
an
emerging
technology
for
clinically
relevant
applications
using
significant
samples
models.
We
discuss
use
RS
both
label-free
approach
probing
intrinsic
metabolites
biological
materials,
labeled
where
signal
from
reporters
conjugated
nanoparticles
(NPs)
serve
indirect
measure
tracking
protein
biomarkers
Biosensors and Bioelectronics,
Journal Year:
2023,
Volume and Issue:
235, P. 115387 - 115387
Published: May 11, 2023
Advances
in
consumer
electronics,
alongside
the
fields
of
microfluidics
and
nanotechnology
have
brought
to
fore
low-cost
wearable/portable
smart
devices.
Although
numerous
devices
that
track
digital
biomarkers
been
successfully
translated
from
bench-to-bedside,
only
a
few
follow
same
fate
when
it
comes
traditional
biomarkers.
Current
practices
still
involve
laboratory-based
tests,
followed
by
blood
collection,
conducted
clinical
setting
as
they
require
trained
personnel
specialized
equipment.
In
fact,
real-time,
passive/active
robust
sensing
physiological
behavioural
data
patients
can
feed
artificial
intelligence
(AI)-based
models
significantly
improve
decision-making,
diagnosis
treatment
at
point-of-procedure,
circumventing
conventional
methods
sampling,
person
investigation
expert
pathologists,
who
are
scarce
developing
countries.
This
review
brings
together
biomarker
through
portable
autonomous
miniaturized
We
first
summarise
technological
advances
each
field
vs
current
we
conclude
merging
two
worlds
AI/ML
technologies
patient
treatment.
The
fundamental
role,
limitations
prospects
AI
realizing
this
potential
enhancing
existing
facilitate
development
translation
"point-of-care"
(POC)
diagnostics
is
finally
showcased.
Cureus,
Journal Year:
2023,
Volume and Issue:
unknown
Published: Sept. 4, 2023
Artificial
intelligence
(AI)
has
opened
new
medical
avenues
and
revolutionized
diagnostic
therapeutic
practices,
allowing
healthcare
providers
to
overcome
significant
challenges
associated
with
cost,
disease
management,
accessibility,
treatment
optimization.
Prominent
AI
technologies
such
as
machine
learning
(ML)
deep
(DL)
have
immensely
influenced
diagnostics,
patient
monitoring,
novel
pharmaceutical
discoveries,
drug
development,
telemedicine.
Significant
innovations
improvements
in
identification
early
intervention
been
made
using
AI-generated
algorithms
for
clinical
decision
support
systems
prediction
models.
remarkably
impacted
trials
by
amplifying
research
into
efficacy,
adverse
events,
candidate
molecular
design.
AI's
precision
analysis
regarding
patients'
genetic,
environmental,
lifestyle
factors
led
individualized
strategies.
During
the
COVID-19
pandemic,
AI-assisted
telemedicine
set
a
precedent
remote
delivery
follow-up.
Moreover,
applications
wearable
devices
allowed
ambulatory
monitoring
of
vital
signs.
However,
apart
from
being
transformative,
contribution
is
subject
ethical
regulatory
concerns.
AI-backed
data
protection
algorithm
transparency
should
be
strictly
adherent
principles.
Vigorous
governance
frameworks
place
before
incorporating
mental
health
interventions
through
AI-operated
chatbots,
education
enhancements,
virtual
reality-based
training.
The
role
decision-making
certain
limitations,
necessitating
importance
hands-on
experience.
Therefore,
reaching
an
optimal
balance
between
capabilities
considerations
ensure
impartial
neutral
performance
crucial.
This
narrative
review
focuses
on
impact
balanced
incorporation
make
use
its
full
potential.
Pain,
Journal Year:
2023,
Volume and Issue:
164(9), P. 1912 - 1926
Published: June 15, 2023
Abstract
Chronic
pain
affects
more
than
50
million
Americans.
Treatments
remain
inadequate,
in
large
part,
because
the
pathophysiological
mechanisms
underlying
development
of
chronic
poorly
understood.
Pain
biomarkers
could
potentially
identify
and
measure
biological
pathways
phenotypical
expressions
that
are
altered
by
pain,
provide
insight
into
treatment
targets,
help
at-risk
patients
who
might
benefit
from
early
intervention.
Biomarkers
used
to
diagnose,
track,
treat
other
diseases,
but
no
validated
clinical
exist
yet
for
pain.
To
address
this
problem,
National
Institutes
Health
Common
Fund
launched
Acute
Signatures
(A2CPS)
program
evaluate
candidate
biomarkers,
develop
them
biosignatures,
discover
novel
chronification
after
surgery.
This
article
discusses
identified
A2CPS
evaluation,
including
genomic,
proteomic,
metabolomic,
lipidomic,
neuroimaging,
psychophysical,
psychological,
behavioral
measures.
will
most
comprehensive
investigation
transition
postsurgical
undertaken
date.
Data
analytic
resources
generatedby
be
shared
with
scientific
community
hopes
investigators
extract
valuable
insights
beyond
A2CPS's
initial
findings.
review
rationale
them,
current
state
science
on
acute
gaps
literature,
how
these
gaps.